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19,000 | Please write an abstract with title: A Two-Stage Isolated Resonant DC-DC Converter for Wide Voltage Range Operation, and key words: Power system measurements, Prototypes, Modulation, Europe, Switches, DC-DC power converters, Zero voltage switching. Abstract: This paper proposes a high-efficiency two-stage isolated dc-dc converter for applications with wide variations of output voltages. It employs a first, pre-regulation stage and a second stage based on an LLC converter, integrated with the first. The second stage is always operated at resonance, ensuring maximum efficiency. The first pre-regulation stage is in charge of i) achieving the desired overall conversion ratio and of ii) always achieving soft-switching operation of all the switches, even in presence of wide output voltage variations. This allows to tackle the typical challenge of keeping conversion loss low even with input or output port voltages that may vary in a wide range. In this paper, the considered conversion structure is shown considering a preliminary experimental prototype that interfaces a 750-V dc-link with an output bus of nominal voltage in the range 250 V to 500 V, which is common in electric vehicle battery-charging applications. The considered preliminary prototype is rated 5 kW and achieves a peak efficiency of 97.5% at 3 kW output power. |
19,001 | Please write an abstract with title: Contribution of GIS, GIS-Cloud and Remote Sensing In Agricultural Sustainability Using Smart Biosolutions in Coastal Chaouia, Morocco, and key words: Economics, Pollution, Salinity (geophysical), Sea measurements, Markov processes, Solids, Sensors. Abstract: This paper presents the Biosolutions proposed to combat salinity and agricultural pollution in Coastal Chaouia. The integration of methods (Markov, CA Markov, AHP, MCDA, IDW) to GIS and remote sensing allowed to detect economic and socio-environmental problems in the study area. The results proved that the Coastal Chaouia is facing major salinity problems as well as agricultural pollution. In order to mitigate the gravity of these problems, the introduction of Avicennia Marina is an effective solution to combat desertification in saline coastal areas. PGPR offers interesting applications for improving agricultural productivity. Anaerobic digestion process will allow to valorize solid wastes from agricultural activity and animal production. The proposed BioSolutions as well as the elaborated maps can be shared with stakeholders and farmers via the GIS-Cloud to ensure the preservation of the potentialities in the Coastal Chaouia. |
19,002 | Please write an abstract with title: New UV and visible laser oscillations in chlorine, oxygen, nitrogen, and titanium, and key words: Nitrogen, Titanium, Pump lasers, Gas lasers, Coils, Laser excitation, Laser transitions, Joining processes, Inductance, Coatings. Abstract: Eight new UV laser lines and 12 new visible laser lines of chlorine, oxygen, nitrogen, and titanium have been obtained by connecting or not connecting inductance coils with the discharge circuit to control the peak discharge current so as to stimulate the laser actions of the lower multiple ion or the higher multiple ion. As the laser duration is much longer than the discharge duration, the lasers are excited in the afterglow, that is, these are recombination lasers in the UV and the visible regions. |
19,003 | Please write an abstract with title: Exergetic analysis of a turbojet engine in off design conditions, and key words: Engines. Abstract: The exergetic analysis of the behavior of industrial systems and plants is employed quite frequently in enter to uncover critical points of the system itself. In the field of aircraft propulsion the applications are still very few and usually confined to analyses in design conditions. This even if the recourse to the exergetic analysis allows, also in the field of aircraft propulsion, to achieve a deeper analysis of the behavior of each component, together with its interactions. The present paper deals with an analysis applied to the exergetic behavior of a simple turbojet, outside its design conditions. First of all, some parameters to be employed are discussed in order to define the exergetic efficiency for each component and for the turbojet as a whole, with reference also to the classic definition for the efficiency usually adopted in conventional analyses. It is then accomplished, in order to make available a situation to be used as a reference, die exergetic analysis of a turbojet at design conditions. A study is now performed, still from an exergetic point of view, of the turbojet behavior in some typical situations of off design (change of: Mach number, flight conditions, altitude, cycle max temperature, etc). Both global and single component behaviors are taken into consideration, to emphasize the critical points in different operative conditions. This allows to make an evaluation about the optimization of the available exergy with reference also to the assigned kind of mission. The analysis presented allows however to emphasize how moving from design to off design conditions some consistent differentiations emerge for the behavior of many components. With reference to this result, it becomes therefore possible to conduct a much deeper evaluation of the off design behavior of the turbojet, in order also to make a full optimization of its performances. |
19,004 | Please write an abstract with title: Research on EBG structure consisting of bianisotropic media, and key words: Periodic structures, Metamaterials, Photonic band gap, Permeability, Electromagnetic scattering, Anisotropic magnetoresistance, Laboratories, Lattices, Permittivity, Photonic crystals. Abstract: The paper reviews a computational model developed for the analysis of EBG structures consisting of bianisotropic media. It is based on the plane wave expansion (PWE) method. A typical EBG structure, made of a triangular lattice of air cylinders embedded in a uni-axial chiral medium, is considered. Simulation results show that the structure with a uni-axial chiral host (whose permittivity and/or chirality are/is uni-axial) possesses a wider band-gap than that with a traditional biisotropic chiral host. However, the permeability, whether with uni-axial anisotropy or not, always plays a negative role on the width of the band-gap. Further studies show that other forms of permittivity, permeability and chirality, such as in the biaxial crystal with principle axes coinciding with the universal coordinates or not, the gyrotropic crystal, contribute nothing to the width of the band-gap. |
19,005 | Please write an abstract with title: Design and initial testing of an outer rotating segmented rotor switched reluctance machine for an aero-engine shaft-line-embedded starter/generator, and key words: Testing, Rotors, Reluctance machines, Reluctance generators, Topology, Aircraft, Turbines, Temperature, Reluctance motors, Prototypes. Abstract: This paper describes research aimed at producing a shaft-line-embedded starter/generator for an aircraft gas turbine. This machine needs to run in a very high ambient temperature of around 350 degC, whilst at the same time having a very high specific output. A review is made of possible designs that highlights potential mechanical and thermal problems and which eliminates the use of some machine topologies. The paper suggests that an outer rotating segmented rotor switched reluctance motor topology could satisfy all the thermal, mechanical and electromagnetic requirements. An initial prototype has been constructed to allow verification of the design and the design methods used. Preliminary results indicate that the performance, size and thermal requirements can be achieved using a fully developed version of this machine |
19,006 | Please write an abstract with title: Dual Transfer Learning for Event-based End-task Prediction via Pluggable Event to Image Translation, and key words: Representation learning, Electrical impedance tomography, Visualization, Image segmentation, Motion segmentation, Transfer learning, Semantics. Abstract: Event cameras are novel sensors that perceive the perpixel intensity changes and output asynchronous event streams with high dynamic range and less motion blur. It has been shown that events alone can be used for end-task learning, e.g., semantic segmentation, based on encoder-decoder-like networks. However, as events are sparse and mostly reflect edge information, it is difficult to recover original details merely relying on the decoder. Moreover, most methods resort to the pixel-wise loss alone for supervision, which might be insufficient to fully exploit the visual details from sparse events, thus leading to less optimal performance. In this paper, we propose a simple yet flexible two-stream framework named Dual Transfer Learning (DTL) to effectively enhance the performance on the end-tasks without adding extra inference cost. The proposed approach consists of three parts: event to end-task learning (EEL) branch, event to image translation (EIT) branch, and transfer learning (TL) module that simultaneously explores the feature-level affinity information and pixel-level knowledge from the EIT branch to improve the EEL branch. This simple yet novel method leads to strong representation learning from events and is evidenced by the significant performance boost on the end-tasks such as semantic segmentation and depth estimation. |
19,007 | Please write an abstract with title: Prediction of Body Constitutions through Life-Style for Health Guidance, and key words: Training, Machine learning algorithms, Sociology, Medical services, Prediction algorithms, Statistics, IEEE Constitution. Abstract: The body constitutions (BCs) of traditional Chinese medical theory are predicted through machine learning algorithms in this work. On the basis of the original questionnaire including 258 life-style features, the least absolute shrinkage and selection operator (LASSO) algorithm is employed for predicting the BCs over the population of 851 persons. Moreover, the principle features (PFs) of life-style are identified to recover the biased BCs into the gentle constitutions as the health guidance. Compared to the state-of-art works, the prediction accuracy is improved by 29% and the amount of identified PFs is reduced to 66.7%. |
19,008 | Please write an abstract with title: Spiking Neural Networks Using Backpropagation, and key words: Backpropagation, Training, Neuromorphics, Artificial neural networks, Transforms, Hardware, Task analysis. Abstract: Brain-inspired Spiking Neural Networks (SNNs) occur with well-known neuromorphic hardware that delivers extra energy compared to conventional artificial neural networks (ANNs). Nevertheless, exploiting the same network layers as conventional ANNs to persevere a task appears unsuitable. Previous works employ similar architectures as Artificial Neural Networks and transform them into Spiking Neural Networks to attain the most exemplary performance as conventional ANNs. Nevertheless, this conversion technique needs greater timesteps for training spiking neural networks (SNNs). In this work, rather than using the ANN to SNN conversion method, we exploit the SNNs training directly using spike-based backpropagation. Since utilizing SNNs with the spike-based backpropagation requires fewer timesteps compared to ANN to SNN transformation approach. This work evaluates the classification performance on public and private (MNIST, Fashion MNIST, and KITTI) datasets. |
19,009 | Please write an abstract with title: The Controller Design of the Bi-directional Three Level Converter, and key words: Renewable energy sources, Systematics, Design methodology, Transfer functions, Bidirectional control, Integrated circuit modeling, Tuning. Abstract: The unified modeling method and double loop controller design of the bi-directional three-level converters are proposed in this paper. The drawbacks of the conventional system are the complex controller configurations due to the different current paths at the duty boundary of 0.5. It makes hard to design double loop controller at previous researches. The unified modeling method which can applicable to full duty ratio is proposed in this paper. The systematic analysis method enables double loop controller design very easily. The controller gains are obtained by the MATLAB automated gain tuning and verified by the PSIM circuit-based program. It can be seen that the waveforms are exactly matched to the design specifications and thus the designed controller can be applicable to the commercial systems. |
19,010 | Please write an abstract with title: Effect of Bromine in Molding Compounds on Gold - Aluminum Bonds, and key words: Gold, Aluminum, Electrical resistance measurement, Wire, Degradation, Bonding, Temperature, Semiconductor device measurement, Kelvin, Pins. Abstract: Degradation rates of gold wire ball bonds on aluminum bonding pads were studied in two molding compounds as a function of bromine concentration, temperature, and time at temperature. The measure of degradation was the resistance increase of the aluminum-gold contact. The rate of degradation was observed to increase with increasing bromine content and temperature for both molding compounds. However, the bromine content dependence of the activation free energy of the degradation reaction indicates a different degradation mechanism for each molding compound. |
19,011 | Please write an abstract with title: Exploring Dynamic Partial Reconfiguration in a Tightly-coupled Coprocessor Attached to a RISC-V Soft-processor on a FPGA, and key words: Runtime, Linux, Software algorithms, Reconfigurable logic, Intellectual property, Logic gates, Software. Abstract: Dynamic reconfigurable processors take advantage of the flexibility of general-purpose processors architectures to execute instruction programs, and the flexibility of reconfigurable logic, implementing specialized hardware designs with better performance and energy-efficiency. During runtime, the reconfigurable logic is modified to fit calculations of the application. Prior works propose new reconfigurable architectures that lack of a software ecosystem or architectures based in intellectual property instruction sets. In the present work, partial dynamic reconfiguration is implemented to a tightly coupled coprocessor attached to a RISC-V soft-core that executes Linux. The complete system is tested on the Nexys 4-DDR development board with the AES and DES encryption algorithms. The results show a speedup of up to 249.91 times faster execution and an average reconfiguration time of 151 ms. |
19,012 | Please write an abstract with title: Forward-backward iterative method for scattering by dielectric fractal surfaces, and key words: Iterative methods, Dielectrics, Fractals, Sea surface, Rough surfaces, Surface roughness, Electromagnetic scattering, Soil, Polarization, Linear systems. Abstract: The iterative forward-backward (FB) method is an efficient technique for numerical evaluation of scattering from perfectly conducting 1D rough surfaces. The method has been recently generalised to analyse scattering from dielectric 1D rough surfaces. In this paper the FB method for dielectric surfaces is framed within the theory of iterative methods for the solution of linear systems. In addition, application of the FB method to dielectric band-limited fractional Brownian motion (fBm) fractal surfaces is addressed. |
19,013 | Please write an abstract with title: Research on Laser Jamming Model of Infrared Imaging System, and key words: simulation modeling, laser jamming model, high confidence, full link. Abstract: With the application of laser jamming technology in the field of infrared imaging guidance weapons, the research on laser jamming performance and anti-jamming technology are paid more and more attention, and they are related to laser jamming model research closely. In order to construct a high confidence laser jamming model. Firstly, we analyzed the physical model of the laser jamming and the characteristics of full link transmission, and established a theoretical model of laser jamming. At the same time, we analyzed the influence law of different wavelength lasers in atmospheric transmission and the variation law of irradiance of different divergence angles with distance. Finally, by comparing the results of laser irradiation infrared camera experiment and digital simulation, we verified the coherence between the laser jamming model and the laser jamming image generated by experiment. |
19,014 | Please write an abstract with title: Research on Aircraft Type Recognition from Remote Sensing Images in Complex Scenes, and key words: Information science, Image recognition, Image resolution, Target recognition, Feature extraction, Classification algorithms, Aircraft. Abstract: Aircraft targets in remote sensing images are important research objects. Accurately identifying different types of aircraft will bring the greatest value of intelligence into play. In this paper, we combine the YOLOv5 detection algorithm and the MMAL-Net classification algorithm to detect the aircraft target and identify the aircraft type in the remote sensing image. Firstly, we use the YOLOv5 algorithm to determine the area where the aircraft target is located in the complex scene. Then the MMAL-Net algorithm is used to classify the aircraft in the area at the fine-grained level, and the type of aircraft target is identified. Through the experiment, the method proposed in this paper can accurately detect the aircraft target and identify the aircraft type, and the accuracy is 73. 2%. |
19,015 | Please write an abstract with title: Power and Resource Allocation in Sensor Network Using Harmony Search Algorithm, and key words: Routing, Wireless sensor networks, Optimization, Energy efficiency, Resource management, Linear programming, Heuristic algorithms. Abstract: For the communication of information over sensor networks, power consumption, and spectrum usage play a significant role. As the number of sensors increases tremendously, it’s vital to optimize power and spectrum usage. The HSA has already been implemented for repetitive subcarrier and power allocation in smart downlink multicarrier systems to accurately implement power and subcarrier allocation. This work maximizes energy efficiency through routing optimization in a senor communication network using a harmony search algorithm. Simulation results describe the significant improvement in a network life time and residual energy of nodes. |
19,016 | Please write an abstract with title: Islanding Detection Methods Based on Self-oscillation of Particular Frequency in DC Distribution Systems, and key words: Analytical models, Islanding, Voltage fluctuations, Fluctuations, Power quality, Voltage control, Time-domain analysis. Abstract: Detecting the DC-based island is essential for safe operation of DC distribution system. State-of-the-art of islanding detection methods in DC systems mainly utilize the positive feedback principle to shift the voltage amplitude out of the normal range and then trigger over/under voltage protection. However, this has the negative consequences of deteriorating of power quality and causing blackouts in the islanding event. This paper proposes the methods of oscillation of particular frequency as an indicator to detect islanding conditions quickly with less deterioration of power quality and no blackouts. Firstly, the paper establishes the model of the DC distribution system for the purpose of analyzing DC-based islanding mechanism. This paper then introduces two islanding-detection methods that implement the voltage oscillation at particular frequency as an indication of islanding conditions. Finally, the proposed methods are validated through time-domain nonlinear simulations and experimental results from a laboratory-scale DC distribution system. |
19,017 | Please write an abstract with title: Cooperative Jamming Cancellation Under Nonlinearity and Imperfect Time-Frequency Alignments for Physical-Layer Security, and key words: Time-frequency analysis, Conferences, Linearity, Power amplifiers, Receivers, Stability analysis, Numerical models. Abstract: Cooperative jamming (CJ) is considered as one of the crucial means in physical-layer security (PLS) for defending against eavesdropping. With the aid of the CJ signal from a friendly jammer, the eavesdropper's channel quality will be intentionally degraded. Unfortunately, the CJ signal also propagates into the legitimate receiver (RX) as the jamming-interference (JI), which should be estimated, rebuilt, and cancelled accordingly. In this paper, we first model the JI after considering practical imperfections existed in the transmit-receive link that incorporates the power amplifier nonlinearity, the carrier frequency offset, and imperfect time-frequency alignments. Then, we formulate an advanced time-frequency misalignments tolerant memory polynomial (TFMT-MP) model to rebuild and cancel the received JI in the legitimate RX. Numerical simulations show that the proposed solution provides the excellent JI cancellation performance and exhibits the strong tolerance of imperfect time-frequency alignments, over the existing MP model solution. |
19,018 | Please write an abstract with title: Generalized Image Reconstruction over T-Algebra, and key words: Dimensionality reduction, Visualization, Information science, Image coding, Algebra, Shape, Compounds. Abstract: Principal Component Analysis (PCA) is well known for its capability of dimension reduction and data compression. However, when using PCA for compressing/reconstructing images, images need to be recast to vectors. The vectorization of images makes some correlation constraints of neighboring pixels and spatial information lost. To deal with the drawbacks of the vectorizations adopted by PCA, we used small neighborhoods of each pixel to form compoun pixels and use a tensorial version of PCA, called TPCA (Tensorial Principal Component Analysis), to compress and reconstruct a compound image of compound pixels. Our experiments on public data show that TPCA compares favorably with PCA in compressing and reconstructing images. We also show in our experiments that the performance of TPCA increases when the order of compound pixels increases. |
19,019 | Please write an abstract with title: Leaning processes by mobile technologies in a Product Development Sample Shop, and key words: Waste reduction, Prototypes, Companies, Production, Product development, Mobile applications, Manufacturing. Abstract: Lean Thinking is a well-known management philosophy pulling continuous improvement in all organizations processes. By doing this, solutions are designed to add value to the product by reducing wastes in the processes. The wastes could be identified by Value Stream Design for indirect Areas (VSDiA) tool. This tool increase company awareness of each complete process and allows improvement opportunities. Such improvements, many times related to better material and information flow, lead to a reduction of product lead-time. Technology is fundamental to support such improvements. In this article, a multidisciplinary team carried out a project in a company aiming to reduce the lead time in the product prototype development process using the VSDiA and technological solutions via a mobile application. This article presents the ongoing work towards an interface for digitizing information flow using a mobile application that is being submitted to the user's test. |
19,020 | Please write an abstract with title: Abstraction and flow analysis for model checking open asynchronous systems, and key words: Chaotic communication, Explosions, Software engineering, Software systems, Open systems, Data analysis, Mathematics, Computer science, Mathematical model, Automatic control. Abstract: Formal methods, especially model checking, are an indispensable part of the software engineering process. With large software systems currently beyond the range of fully automatic verification, however, a combination of decomposition and abstraction techniques is needed. To model check components of a system, a standard approach is to close the component with an abstraction of its environment. To make it useful in practice, the closing of the component should be automatic, both for data and for control abstraction. Specifically for model checking asynchronous open systems, external input queues should be removed, as they are a potential source of a combinatorial state explosion. In this paper we close a component synchronously by embedding the external environment directly into the system to avoid the external queues, while for the data, we use a two-valued abstraction, namely data influenced from the outside or not. This gives a more precise analysis than that investigated by Ioustinova et al. (2002). To further combat the state explosion problem, we combine this data abstraction with a static analysis to remove superfluous code fragments. The static analysis we use is reminiscent of that presented by Ioustinova et al., but we use a combination of a may and a must-analysis instead of a may-analysis. |
19,021 | Please write an abstract with title: On a New SNR Estimation Approach With Polar Codes, and key words: Maximum likelihood estimation, Conferences, Modulation, Channel estimation, Numerical simulation, Information management, Reliability. Abstract: A maximum likelihood polar code-aided (ML-PCA) SNR estimation algorithm is proposed in this paper. In the ML-PCA algorithm, the posterior soft information of polar BP decoding is adopted to help the SNR estimation process. Benefiting from the excellent performance of polar code, the ML-PCA algorithm is able to acquire more reliable decoding information and further improve the SNR estimation quality. By detailed derivation, the SNR estimator and Cramér-Rao Lower Bound (CRLB) of the proposed algorithm are achieved. Numerical simulations demonstrate that the ML-PCA algorithm considerably outperforms the conventional M2M4 and ML-NDA algorithms. |
19,022 | Please write an abstract with title: DiGS : Divergence guided shape implicit neural representation for unoriented point clouds, and key words: Point cloud compression, Representation learning, Surface reconstruction, Solid modeling, Three-dimensional displays, Design automation, Smoothing methods. Abstract: Shape implicit neural representations (INRs) have recently shown to be effective in shape analysis and reconstruction tasks. Existing INRs require point coordinates to learn the implicit level sets of the shape. When a normal vector is available for each point, a higher fidelity representation can be learned, however normal vectors are often not provided as raw data. Furthermore, the method's initialization has been shown to play a crucial role for surface reconstruction. In this paper, we propose a divergence guided shape representation learning approach that does not require normal vectors as input. We show that incorporating a soft constraint on the divergence of the distance function favours smooth solutions that reliably orients gradients to match the unknown normal at each point, in some cases even better than approaches that use ground truth normal vectors directly. Additionally, we introduce a novel geometric initialization method for sinusoidal INRs that further improves convergence to the desired solution. We evaluate the effectiveness of our approach on the task of surface reconstruction and shape space learning and show SOTA performance compared to other unoriented methods. Code and model parameters available at our project page https://chumbyte.github.io/DiGS-Site/ |
19,023 | Please write an abstract with title: Economic Considerations for Communication Systems, and key words: Costs, Communications technology, Design engineering, Systems engineering and theory, Contracts, Management training, Quality of service, Engineering management, Communication equipment, Road transportation. Abstract: Developments in communications techniques and equipment provide the user with a wide choice of means and systems to obtain the desired quantity and quality of service. At the same time, increasing requirements for communications and the need for transmitting different kinds of information with higher speeds and reliability, a high degree of invulnerability and increased capacity have increased the complexity of systems and the quantity and types of equipment used in them. These factors, sometimes conflicting, have had an impact on communication system costs. The cost of different kinds of systems and equipment will be analyzed and general rules provided for cost estimating with due consideration of the above items. |
19,024 | Please write an abstract with title: Maturity Oriented Description Model for Innovation Ideas of Technical Systems, and key words: Technological innovation, Companies. Abstract: Today, innovation is more crucial for companies than ever. The prerequisite for every innovation is an innovation idea (referred to as “idea” within this paper). Especially the implementation of ideas for technical systems requires financial and capacitive resources. Due to resource constraints, companies only pursue the most promising ideas. The understanding of a promising idea may differ from company to company. Therefore, an evaluation process, including company specific evaluation criteria, is applied in order to identify those promising ideas. The basis of this evaluation process is the idea description, presenting all relevant aspects of an idea in a structured manner. Today’s existing models for the description of ideas require a specific type and format of information (the so called “specification format”). However, these specification formats remain unchanged over the course of the idea development process. Consequently, the same type and format of information are used to describe any idea of any development status. This regularly leads to a distorted idea description, ultimately resulting in an erroneous basis for the idea evaluation. To prevent this, the idea description model has to be oriented at the idea’s current development status. Therefore, this paper aims at the development of a model for the maturity oriented description of ideas for technical systems assuring both a meaningful as well as efficient idea description. |
19,025 | Please write an abstract with title: Performance Comparison Between Single Layer and Several Configurations of Bilayer P(VDF-TrFE) Transducers in Pulse-Echo Measurements, and key words: Piezoelectric films, Fabrication, Transducers, Sensitivity, Pulse measurements, Resonant frequency, Bandwidth. Abstract: Piezoelectric copolymers such as P(VDF-TrFE) have been used over the years for the fabrication of high-frequency transducers, and particularly for medical imaging. With the aim of optimizing the sensitivity/bandwidth trade-off of this type of transducer, several manufactured bilayer P(VDF-TrFE) transducer configurations were obtained and the corresponding electroacoustic properties were compared with those of a reference single-layer transducer. In a first step, based on a previous study, performances of bilayer P(VDF-TrFE) transducers with both layers acting in emission and reception were compared with performances of a single-layer transducer. Electrical connections (parallel) and polarization direction (opposite) between piezoelectric layers were chosen. For this study, the piezoelectric layers consistently had the same thickness leading to different transducer center frequencies (a ration of 2). The bilayer configuration showed an increased sensitivity (+ 5.2 dB). In a second step, different configurations were studied, in which both piezoelectric layers acted in emission and both or only one of the layers acted in reception. Performances were compared with a reference single-layer transducer at the same frequency (10 MHz). The results showed that regardless of the bilayer configuration of our fabricated transducers, the single-layer structure had to be preferred in terms of sensitivity (+ 5 dB) at the expense of the relative bandwidth (−60 %) for imaging applications. |
19,026 | Please write an abstract with title: Investigating Facebook Advertising Feature Through Performance Expectancy on Customer Purchase Intention, and key words: Social networking (online), Advertising, Statistics, Sociology, Business, Companies, Rectifiers. Abstract: Over time, many Facebook users use Facebook not only for sharing photos but also used as a means for advertising and promoting. Promotion in the form of advertising on social media is believed to be more effective because it does not require much time, cost, and effort for the company, and makes it easy for consumers to find out information. Facebook ads or paid advertisements from Facebook are features offered by Facebook to promote or advertise a business product or service with different reach and can be arranged by the advertiser. Ads from Facebook can reach more people than just posting both fan pages and personal accounts. The aims of this research are to determine the influence of hedonic motivation, interactivity, informativeness, and perceived relevance of consumer purchase intentions through performance expectancy on advertising on Facebook's social media. The research method used is quantitative with SEM (Structural Equation Model) analysis technique. The results showed that hedonic motivation, interactivity, informativeness, and perceived relevance have a direct effect to purchase intention and indirect effect through performance expectancy. There were empirical findings on this study that hedonic motivation and perceived relevance built higher influence to purchase intention than other variables. |
19,027 | Please write an abstract with title: Frequency dependence of scintillation at K and Ka-band, and key words: Frequency dependence, Extraterrestrial measurements, Communications technology, Artificial satellites, Rain, Predictive models, Weather forecasting, Temperature, Clouds, Fluctuations. Abstract: This paper addresses the frequency dependence of tropospheric scintillation by comparing the scintillation of both frequencies at the seven sites. Theoretically, tropospheric scintillation increases as the frequency increases with respect to a power function, f. The goal of this paper is to determine values for a, and study site, climate and elevation angle, dependence of a, with respect to rain and clear-sky conditions. |
19,028 | Please write an abstract with title: Boat Monitoring and Classification System utilizing infrared and visual data streams for port safety enhancement, and key words: Machine learning, classification, thermal imaging, convolutional networks. Abstract: This paper presents a prototype monitoring and classification system designed to enhance safety in port areas. The system utilizes infrared and visual data streams from four cameras to detect and classify incoming and outgoing boats, even in adverse weather conditions. Deep neural networks, specifically region-based Convolutional Neural Networks (CNNs) and the You Only Look Once (YOLO) network, are employed for boat detection and classification. The experimental hardware setup, including camera specifications and positioning, is described. The paper discusses different architectures for object detection and compares their performance. A discussion on future developments and the potential for extending the application of the developed system to other ports. |
19,029 | Please write an abstract with title: Compositional models of distributed and asynchronous dynamical systems, and key words: Algorithm design and analysis, Explosions, State estimation, Discrete event systems, Clocks, Concurrent computing, Telecommunication computing, Add-drop multiplexers, Maximum likelihood estimation, Stochastic systems. Abstract: Proposes a framework to describe and handle distributed systems as an interaction graph of elementary components. Components are discrete event systems operating on several state variables, and defining local dynamics on these variables. Components are interconnected by sharing variables, which defines the interaction graph of the compound system. They evolve asynchronously, with their own clock, so there is no notion of global time. This behavior is captured by the so-called true concurrency semantics on trajectories of the system. Just like the global system factorizes as a product of components, we prove that its trajectories also "factorize." As a consequence, the global system can be handled by parts, for example for state estimation; the global state of the system is never computed. This is a key to deal with large systems. This framework has been applied to design distributed diagnosis algorithms for telecommunication networks. |
19,030 | Please write an abstract with title: BoostSole: Design and Realization of a Smart Insole for Automatic Human Gait Classification, and key words: Legged locomotion, Wireless communication, Pain, Instruments, Medical services, Classification algorithms, Time factors. Abstract: This paper presents BoostSole; a smart insole based system for automatic human gait recognition. It consists of a smart instrumented insole connected to the cloud via the patient’s smartphone using low-power wireless communication. First, the design of BoostSole is introduced with discussions of sensors choice, placement, calibration, and data communication. Next, an adaptive multi-boost classification algorithm is deployed to accurately identify different gait patterns. The algorithm is fast and lightweight and can be implemented in ordinary smartphones with a small footprint in terms of computational requirements, energy consumption, and communication usage. Raw and on-device classified data can be securely uploaded to a distant cloud server for continuous monitoring and analysis. Indeed, they can be visualized and exploited by doctors to identify/correct walking habits and assess the risks of chronic pain associated with an abnormal walk. The system has been evaluated on a dataset containing three gait patterns, namely: shuffle walk; toe walking; and normal gait. Obtained results are promising with more than 97% classification accuracy accompanied by low response time and computational demands. |
19,031 | Please write an abstract with title: Stabilizing linear systems with saturation through optimal control, and key words: Linear systems, Optimal control, State feedback, Open loop systems, Nonlinear dynamical systems, Eigenvalues and eigenfunctions, Control systems, Cost function, Lyapunov method, Hydraulic actuators. Abstract: We construct a continuous feedback for a saturated system x/spl dot/(t) = Ax(t) + B/spl sigma/(u(t)). The feedback renders the system asymptotically stable on the whole set of states that can be driven to 0 with an open-loop control. Trajectories of the resulting closed-loop system are optimal for an auxiliary optimal control problem with a convex cost and linear dynamics. The value function for the auxiliary problem, which we show to be differentiable, serves as a Lyapunov function for the saturated system. Relating the saturated system, which is nonlinear, to an optimal control problem with linear dynamics is possible thanks to the monotone structure of saturation. |
19,032 | Please write an abstract with title: Real Time Rainfall Prediction for Hyderabad Region using Machine learning Approach, and key words: Technological innovation, Machine learning algorithms, Urban areas, Monsoons, Predictive models, Prediction algorithms, Real-time systems. Abstract: A novel technique for the Prediction of Monsoon Rainfall using Hybrid Machine Learning Algorithms and their ensembles, operated on Real time Hyderabad Rainfall data is Proposed. Over the years many models have been developed for the prediction of rainfall, An Accurate Prediction of Monsoon Rainfall for farmers is necessary for centuries together. As regression algorithms fail to generalize the outcomes with the mean of rainfall being near 0(no rainfall). We have come up with a Hybrid Technique that uses the classification of rainfall into Binary Data, there upon which applies the Regression Algorithm, which significantly improved the result. Out of the many tests conducted on various algorithms, the Hybrid Model of Random Forest Classifier with Multi-Layer Perceptron Regressor has given the best outcome with a practical Accuracy of 0.92537 and with a Mean Absolute error of 1.063540 tested over a period of 3 months. Furthermore, we have elaborated different Hybrid Model compositions used in ensemble learning for the improvement of small scale outputs. These results are tested on Real time data obtained on Hyderabad rainfall data and compared with real time. |
19,033 | Please write an abstract with title: A Hybrid MMC with Low FBSM Ratio for DC Fault, and key words: Multilevel converters, Costs, Circuit breakers, Bridge circuits, Voltage, Power system stability, Hybrid power systems. Abstract: Flexible DC transmission system using modular multilevel converters (MMC) is facing the problem of DC fault clearance. The existing sub-module hybrid MMC uses full bridge sub-modules (FBSM) to achieve non-blocking fault ride-through (FRT), but the ratio of FBSM needs to reach 50% or more, the cost and operating loss are more than half higher than that of the half bridge MMC. This paper proposes a low ratio hybrid MMC suitable for DC fault clearance. When the ratio of FBSM is less than 50%, the DC output voltage is reduced to zero by reducing the value of the arm voltage proportionally to isolate the faulty line. This paper analyzes the fault isolation sequence and controller structure of the scheme. Finally, a simulation model is built in PSCAD/EMTDC to verify the effectiveness of the scheme. |
19,034 | Please write an abstract with title: A Robust Heading Estimation Solution for Smartphone Multisensor-Integrated Indoor Positioning, and key words: Magnetometers, Buildings, Gyroscopes, Estimation, Interference, Magnetic separation, Magnetic field measurement. Abstract: As a part of Internet-of-Things applications, various smartphone-based indoor location services have considerable commercial value. It is largely agreed that the integration of multiple sensors is the preferable solution for improving the performance of smartphone indoor positioning, thanks to the diversity of built-in sensors. However, heading error remains a challenge for smartphone indoor positioning, especially in complex indoor scenes. This article, therefore, proposes a heading estimation solution to enhance the accuracy and reliability of smartphone indoor positioning. The extended Kalman filter (EKF)-based solution fuses smartphone built-in motion sensors, magnetometers, building map knowledge, and fingerprinting coarse positions from Wi-Fi or Bluetooth. First, the context of pedestrian mobility and scene knowledge is inferred by combining these data. Then, a scene augmentation strategy and magnetic interference online detection method are applied to calibrate the gyro accumulation error and improve the heading estimation accuracy. Additionally, quasistatic and low-dynamic judgments and online calibration are used to mitigate gyro drift. The proposed solution is implemented on a smartphone device and validated in several experiments under natural pedestrian mobility and complex indoor scenarios. Experiments show that the accuracy of heading estimation is improved from 13.1° to 2.0°. The improved heading estimation enhances the accuracy of smartphone indoor positioning from 3.57 to 0.90 m. The proposed solution is applicable to real location-based service scenarios. |
19,035 | Please write an abstract with title: CAST: A Cross-Article Structure Theory for Multi-Article Summarization, and key words: Task analysis, Bibliographies, Periodic structures, Redundancy, Computer science, Coherence. Abstract: Over the last decade, discourse relations, also referred to as rhetorical or coherence relations, have been used to improve a range of natural language processing applications. Researchers have devised several theories, including rhetorical structure theory and cross-document structure theory, to examine relations between generic text units in single and multiple documents, respectively. In this paper, we propose a cross-article structure theory (CAST), that extends the benefit of discourse relations to multi-scientific article applications. It is based on the rhetorical structure theory (RST) and the cross-document structure theory (CST). The insight that underpins CAST is to consider both intra-section and cross-section relations. At the outset, these relations are classified based on the structural features of the article (that is, their appearance within each section type) and then the relations between text portions across multiple articles are classified. The practicality of the theory is showcased by solving a problem that consists to identify the types of relations which exist between each pair of sentences in related sections of different articles. A CAST bank was created and the k-nearest neighbors algorithm was used to develop two classifiers based on CAST and CST, respectively. The performance results obtained markedly demonstrate the role of the specific relations to scientific articles in CAST. Other applications of CAST could address the redundancy and readability problems, which represent main issues for different tasks, such as the summarization of multiple articles. |
19,036 | Please write an abstract with title: Hybrid Density-based Adaptive Clustering using Gaussian Kernel and Grid Search, and key words: Adaptive systems, Clustering algorithms, Spatial databases, Kernel. Abstract: Density-based spatial clustering of data with noise (DBSCAN) is a popular clustering algorithm that groups data points which are close together using two parameters eps - which is the radius of each cluster, and Minpts, which is the minimum number of points in each cluster. However, the performance of DBSCAN reduces for the datasets with varying density clusters. This paper proposes the implementation of a distributed and adaptive DBSCAN algorithm on the HPCC Systems platform. The proposed approach uses techniques such as grid search and Gaussian kernel to search optimized values for the threshold density of clusters, thus eliminating the requirement for users to specify the parameters. Further, the experimental investigation suggests that proposed ADBSAN performs better compared to existing ADBSCAN implementations using k-dist and Gaussian kernels. |
19,037 | Please write an abstract with title: Mixed Intrusion Events Recognition Based on Group Convolutional Neural Networks in DAS System, and key words: Sensors, Feature extraction, Optical fiber amplifiers, Optical fiber couplers, Optical fiber sensors, Optical fiber networks, Rayleigh scattering. Abstract: The mixed intrusion events recognition is still a challenging problem in optical fiber perimeter security with distributed acoustic sensing (DAS), because the vibration signals will be mixed when multiple events occur at the same time and in close proximity. In order to identify mixed events consisting of two single events, we propose a recognition scheme based on deep group neural networks algorithm. The 100 groups convolutional neural networks (100G-Net) model is designed to make the best of vibration information of samples for feature extraction and classification. The experiments show that not only average training recognition accuracy of the proposed algorithm can reach 99.6%, but also the generalization ability of the proposed algorithm is better than typical CNN models. |
19,038 | Please write an abstract with title: A motion based object detection method, and key words: Convolution, Computational modeling, Neural networks, Object detection, Computer applications, Motion detection, Security. Abstract: To improve the performance of motion detection and object detection in security monitor, a motion based object detection method is proposed. Combining motion detection, target detection is proposed. This method first improved the accuracy of motion detection, then combined the result of motion detection and object detection. The experimental results show that proposed method can effectively improve the detection of small targets, reduce the false detection and negative detection rate, and decrease the computing cost. |
19,039 | Please write an abstract with title: Continuous plasma separation from whole blood using microchannel geometry, and key words: Blood, Microchannel, Geometry, Microfluidics, Plasma applications, Plasma properties, Immune system, Reservoirs, Plasma measurements, Glass. Abstract: Plasma separation from whole blood using microfluidics was investigated. We suggested modified channel geometry called "corner-edge" to enhance plasma skimming effect at branching channel. To evaluate separation efficiency, microfluidic chip was fabricated with silicone elastomer and glass. The efficiency of separation was above 99% comparing with whole blood hematocrit. This microfluidic unit could be integrated with microchannel network for lab-on-a-chip applications such as immunoassay. |
19,040 | Please write an abstract with title: Evaluation of DFIG Wind Turbine Generator and Transformer Conditions with Electrical Signature Analysis, and key words: Wind speed, Rotors, Doubly fed induction generators, Wind power generation, Wind farms, Fatigue, Generators. Abstract: During field studies of Doubly-Fed Induction Generators (DFIG) and Singly-Fed Induction Generators (SFIG) transformer and generator failures several unusual conditions were detected. A combination of sub-synchronous control interaction, sub-synchronous torsional interaction, and starting resonances were detected with electrical signature analysis in specific operating conditions of the machines. A review of historical operating conditions, wind, thermal and power distribution system design indicate that low-level sub-synchronous resonances are present that result in unusual transformer heating/aging, generator rotor component electrical and mechanical fatigue, and gearbox wear after years of service. The severity of the condition results from a combination of average loading and distance from customer loads and wind farm configuration. In this paper we will discuss the discovery and progress in the research with potential in-service solutions to be presented. |
19,041 | Please write an abstract with title: Prediction of Mortality and Length of Stay with Deep Learning, and key words: MIMICs, Bit error rate, Electronic medical records, Deep learning, Translational research, Task analysis, Signal processing. Abstract: Predicting the mortality and the length of stay of patients during ICU stay is important for better acute care and planning of ICU resources. The recent advancements in deep learning and with the Electronic Health Record data becoming available for researchers, there has been an increasing interest in the healthcare domain. While patient's structural data are frequently used, most of the studies in the literature do not use the clinical notes due to the complex nature. In this study, we use the clinical notes besides time-series features to improve our predictions. The results have shown that the proposed deep learning based multimodal approach outperforms on all clinical tasks over baseline models. |
19,042 | Please write an abstract with title: Interpretability of Knowledge Graph-based Explainable Process Analysis, and key words: Knowledge engineering, Stochastic processes, Machine learning, Decision trees, Hybrid intelligent systems, Business. Abstract: The last decade produced rapid developments and powerful new technologies that are creating a huge upsurge in artificial intelligence research. However, for critical operational decisions (e.g., consulting services), the need for explanations and interpretable results are becoming a necessity. The integration of knowledge graphs that provide relevant background knowledge in machine-readable form, and machine learning methods represents a new form of hybrid intelligent systems that benefit from each other's strengths. Our research aims at an explainable system with a specific knowledge graph architecture that can generate human-understandable results even when no suitable domain experts are available. Against this background, the interpretability of a knowledge graph-based explainable artificial intelligence approach for business process analysis is focused. We design a framework of interpretation, and show how interpretable models are generated. Result paths on weaknesses and improvement measures related to a business process are used to produce stochastic decision trees, which improve the interpretability of results. This can lead to interesting consulting self-services for clients or be applied as a device for accelerating classical consulting projects. |
19,043 | Please write an abstract with title: Highly Efficient Layered Syndrome-based Double Error Correction Utilizing Current Summing in RRAM Cells to Simplify Decoder, and key words: Error Correcting Codes(ECC), Double Error Correcting codes (DEC), resistive RAM (RRAM), Orthogonal Latin Square (OLS), syndromes, soft errors. Abstract: Applications involving machine learning and neural networks have become increasingly essential in the AI revolution. Emerging trends in Resistive RAM technologies provide high-speed, low-cost, scalable solutions for such applications. These RRAM cells provide efficient and sophisticated memory hardware structures for machine-learning applications. However, it is difficult to achieve reliable multilevel cell storage capacity in these memory technologies due to the occurrence of soft and hard errors. As these memories can store multi-bits per cell, exploring limited magnitude symbols(multi-bit) error correction in RRAM is important. This paper proposes a new syndrome-based double error correcting code that divides the syndromes into groups and, uses addition and XOR operations to correct double limited magnitude errors in the RRAM cells. The key idea is to use the built-in current summing capability of RRAM cells to perform the addition operations that are used for the error correction thereby greatly reducing the overhead of the decoding logic needed to implement the ECC. This effectively avoids the need for explicit adder hardware in the decoding logic making it smaller and faster than conventional ECC codes with similar error-correcting capability. Experimental results show that the proposed code reduces the number of check symbols and significantly reduces the decoder area and power by using the RRAM cells to perform the addition. |
19,044 | Please write an abstract with title: Low-Latency Live Streaming Over HTTP in Bandwidth-Limited Networks, and key words: Streaming media, Bandwidth, Throughput, Video recording, Quality assessment, Bit rate. Abstract: HTTP adaptive streaming (HAS) can achieve low latency for live streaming with the Common Media Application Format. However, the legacy mechanisms inaccurately measure the available bandwidth because the download time is affected by not only the network but also idle times between chunks at the live encoder side. These wrong measurements may condemn users to a low quality-of-experience (QoE). This letter presents a HAS client with a novel bandwidth measurement heuristic. Our experiments show that it provides a better QoE with fewer video freezes and higher video quality while achieving a live latency down to one second in bandwidth-limited networks. |
19,045 | Please write an abstract with title: Novel Affine Power Flow Method for Improving Accuracy of Interval Power Flow Data in Cyber Physical Systems of Active Distribution Networks, and key words: Load flow, Uncertainty, Computational efficiency, Voltage, Distributed databases, Active distribution networks, Programming. Abstract: A large number of load power and power output of distributed generation in an active distribution network (ADN) are uncertain, which causes the classical affine power flow method to encounter problems of interval expansion and low efficiency when applied to an AND. This then leads to errors of interval power flow data sources in the cyber physical system (CPS) of an ADN. In order to improve the accuracy of interval power flow data in the CPS of an ADN, an affine power flow method of an ADN for restraining interval expansion is proposed. Aiming at the expansion of interval results caused by the approximation error of non-affine operations in an affine power flow method, the approximation method of the new noise source coefficient is improved, and it is proved that the improved method is superior to the classical method in restraining interval expansion. To overcome the decrease of computational efficiency caused by new noise sources, a novel merging method of new noise sources in an iterative process is designed. Simulation tests are conducted on an IEEE 33-bus, PG&E 69-bus and an actual 1180-bus system, which proves the validity of the proposed affine power flow method and its advantages in terms of computational efficiency and restraining interval expansion. |
19,046 | Please write an abstract with title: Photon-Starved Scene Inference using Single Photon Cameras, and key words: Training, Sensitivity, Lighting, Cameras, Robustness, Sensors, Task analysis. Abstract: Scene understanding under low-light conditions is a challenging problem. This is due to the small number of photons captured by the camera and the resulting low signal-to-noise ratio (SNR). Single-photon cameras (SPCs) are an emerging sensing modality that are capable of capturing images with high sensitivity. Despite having minimal read-noise, images captured by SPCs in photon-starved conditions still suffer from strong shot noise, preventing reliable scene inference. We propose photon scale-space – a collection of high-SNR images spanning a wide range of photons-per-pixel (PPP) levels (but same scene content) as guides to train inference model on low photon flux images. We develop training techniques that push images with different illumination levels closer to each other in feature representation space. The key idea is that having a spectrum of different brightness levels during training enables effective guidance, and increases robustness to shot noise even in extreme noise cases. Based on the proposed approach, we demonstrate, via simulations and real experiments with a SPAD camera, high-performance on various inference tasks such as image classification and monocular depth estimation under ultra low-light, down to < 1 PPP. Project Page: https://wisionlab.cs.wisc.edu/project/photon-net |
19,047 | Please write an abstract with title: Development of an Electronic Stethoscope Using Raspberry, and key words: Heart, Headphones, Noise reduction, Lung, Stethoscope, Noise cancellation, Magnetic heads. Abstract: In this study, Raspberry Pi 3B was used to develop an electronic stethoscope by embedding a condenser microphone in the traditional stethoscope head to collect heart and lung sounds. The collected signals pass through amplification and filter circuits, and then the processed signals are transmitted to the Raspberry Pi through audio cables. In addition, a recording system for heart and lung sounds was developed in the graphic user interface on the Raspberry Pi. After recording, the audio file can be directly stored in Raspberry Pi, played on headphones or a small speaker connected to the Raspberry Pi, or transmitted via Bluetooth or Filezilla to a computer for further analyses. The functions of recording audio sounds and playing recorded sounds can help doctors to relieve the pain caused by the long-term use of the traditional stethoscope in the ear. They also improve the inability of recording the heart and lung sounds when using the traditional stethoscope. In this study, we also explored the use of dual microphones for noise reduction. Five kinds of stethoscope heads were developed, and the corresponding audio signals were observed using Fast Fourier Transform (FFT) to analyze their effects on noise reduction. The designed circuit has two modes for collecting sounds depending on the audio source: the heart sound mode or the lung sound mode, and it also has anti-noise mode. After testing, the effect on active noise cancelling proposed in this study is not as good as expected. The frequency of the noise sound changes after passing through the material that the stethoscope surface touches. Various materials cause different variations on frequency received by the microphone, causing incomplete frequency cancellation on noise sound. Based on the testing for passive noise cancelling, the best one, among all the stethoscope heads including one commercial electronic stethoscope, is that the microphone is placed in the stethoscope head and the periphery of the stethoscope head is covered by cork. |
19,048 | Please write an abstract with title: Self-Concept and Social Networking of Students at Polytechnic College, and key words: Social network services, Internet, Psychology, Visualization, Engineering education, Linguistics. Abstract: The paper presents results that reveal interactions between indicators of self-concept and peculiarities of networking of students at the polytechnic college. It has been concluded that recreational and communication motives are main ones to turn to social networking for college students. It is shown that self-concept plays an essential role in identifying a pattern of social networking. Self-confidence, self-worth mediate a level of communication and creative self-realization in social media, whereas self-blame and motivation of social acceptance define self-disclosure, self-presentation in social media. |
19,049 | Please write an abstract with title: Investigation of Induced EFT Transient Noise and Effect on Chip and Package Level, and key words: Analytical models, Capacitors, Immunity testing, Generators, Finite element analysis, Transient analysis, Integrated circuit modeling. Abstract: This paper investigates the noise induced from EFT Burst transient IEC61000-4-4 on the chip and package levels and analyzes its degradation effect. We first introduce the EFT Burst transient generator model previously established published with ANSYS Designer, which has later been adopted into ANSYS Electronics Desktop serving for immunity effect and protection measure analysis. We then describe how electromagnetic simulations can provide chip-level immunity analysis for IEC 62215-3. The analysis of EFT pulse propagation can be extended to package level with its impact on clock waveforms of different frequencies. With the help of established model, the residual transient noise energy due to normally found decoupling capacitor will be observed to show its effectiveness on noise filtering and the significant benefits to EMS protection. This study intends to provide an efficient simulation model to help IC and package designers enhancing their design capability against EFT disturbance. |
19,050 | Please write an abstract with title: Characterization of THz-induced bias voltage modulation in an STM, and key words: Geometry, Surface waves, Microscopy, Modulation, Tunneling, Junctions, Transient analysis. Abstract: To understand and characterize the transient bias voltage induced by single-cycle terahertz (THz) pulses coupled to a scanning tunneling microscope (STM), the Bardeen tunneling model is applied to a 3-dimensional geometry of the STM junction. The simulated THz-induced tunneling current at the junction agrees well with that observed by THz-STM on a Cu(111) surface, providing a benchmark to quantify the THz-induced bias voltage at the tip-sample interface. |
19,051 | Please write an abstract with title: What Drives Global E-Governance? An Exploratory Study at a Macro Level, and key words: Electronic government, Moon, Information technology, Paper technology, Technology social factors, Current measurement. Abstract: Global e-government is being tracked using a variety of different measures, none of which have been systematically validated. Little research compares and contrasts these measures and little work has sought to frame and identify potential independent drivers of e-government at the national level. This paper systematically compares and contrasts the dependent variables and the relationships between the e-government variables and independent drivers. Using data from a variety of institutional sources, we find low correlations among e-government measures and low to moderate consistency in the relationships between established independent variables and e-government measures. Findings indicate a significant measurement validity problem and conclusions recommend consideration of a different approach. |
19,052 | Please write an abstract with title: Skunk — A Blockchain and Zero Trust Security Enabled Federated Learning Platform for 5G/6G Network Slicing, and key words: Data privacy, Federated learning, Network slicing, Security management, Privacy breach, Complexity theory, Blockchains. Abstract: The network slicing in 5G/6G mobile networks enables billions of connected devices to transmit data at higher rates than ever before. The high number of devices and the huge data rates result in configuration complexities and complex security management. Machine learning techniques could play a key role in managing these system complexities. While feder-ated learning (FL) has recently been proposed as an emerging paradigm to build privacy-preserving machine learning models, many of the existing systems involve centralized coordinators which are known to be vulnerable to attacks and privacy breaches. In addition, current FL models have weak support for transparency and provenance mechanisms. In this paper, we propose a Blockchain-based, Zero-trust Security-enabled Federated Learning system “Skunk” to address privacy and data provenance requirements. The proposed federated learning system also supports the requirements of 5G/6G networks. The sharding-based architecture in the blockchain enables the deployment of Skunk in 5G/6G network slice environments. As a use case of Skunk, we have considered a scenario with IoT device attacks in a 5G/6G network. The proposed FL models detect such attacks in the 5G/6G network sliced environment. |
19,053 | Please write an abstract with title: A hybrid genetic algorithm with chemical reaction optimization for multiple sequence alignment, and key words: Simulation, Hidden Markov models, Genetics, Classification algorithms, Task analysis, Information technology, Optimization. Abstract: Multiple Sequence alignment is the ultimate challenging tasks of biological science. It is used for comparison or difference or similarities in these sequences of data. Here, we applied a pragmatic Genetic Algorithm (GA) & Chemical Reaction Optimization (CRO) apparently the most suitable and familiar expansion technique and influenced by the natural genetic structure. Inquiring the magnificent alignment of a biological sequence set is classified as an NP-hard optimization problem for that, GA-CRO algorithms are capable to drive this complication. To find good results, we are going to show the benchmark dataset, the suggested approach is compared with those of the current tools like the SB-PIMA, SAGA, RBT-GA and GAPAM, HMMT. The simulation results recommend that our method be a viable solution with the other methods in terms of efficiency with the appropriate selection of parameters. |
19,054 | Please write an abstract with title: A Functional Verification Study of Quantum Key Distribute Networks and Services with a Trusted Node applied in KOREN, and key words: Communication equipment, Couplings, Information and communication technology, Quantum cryptography, Interoperability, Standards, Guidelines. Abstract: The development of quantum cryptographic communication technology and the establishment of quantum cryptographic communication infrastructure and services have been presented in the public and private business sectors. In this paper, quantum cryptography communication equipment from various vendors is established in the Korea Advanced Research Network (KOREN) operated by the National Information Society Agency(NIA), and functions and interoperability are verified in the test network. So far, basic verification standards and operation guidelines for quantum cryptography communication equipment have not been established. In this paper, we would like to examine the basic functions, linkage functions, and long-term driving requirements of each device that provides quantum cryptography communication services. |
19,055 | Please write an abstract with title: Optimized Design of Worm Gear and Worm Drive of a Certain Shipborne Antiriot Launcher Based on MATLAB, and key words: Systematics, Gears, Metals, Production, Grippers, Optimization, Matlab. Abstract: Worm gear and worm drive mechanism is widely used in mechanical drive. In traditional design, the valuation trial method is generally used, and then the design scheme is checked to verify whether the design parameters are within the performance range for the given conditions. In a sense, the design parameter values obtained by this method are not the most reasonable and economical. Under the premise of systematic study of the possible failure forms and design criteria of worm gear and worm drive, design criteria and use of materials, we determine the optimization design objectives, design variables and constraints, and use the MATLAB optimization toolbox to complete the optimized design of worm gear and worm drive. We finally obtain the optimization results and compare them with the original design data. The optimization results show that MATLAB can significantly improve the analysis efficiency and quality of worm drive design, which will reduce the cost. |
19,056 | Please write an abstract with title: Corner reflectarray for indoor wireless applications, and key words: REFLECTARRAYS, FSS, WIRELESS PROPAGATION. Abstract: Two reflectarray surfaces (RAS) placed on opposing walls in a corner demonstrate steering of wireless signals at 90°, suitable for propagation around a corner in a corridor. A prototype using square patch RASs was evaluated achieving comparable performance to an inclined metal reflector at 5.5 GHz. The RASs were constructed using a foam spacer with the arrays printed onto a thin polyester film leading to a low cost solution. This also provided sufficient bandwidth to meet the requirement of the 5 GHz Wi-Fi band (12%). |
19,057 | Please write an abstract with title: A Study of real-Time 4K drone images visualization to rescue for missing people base on web, and key words: Law enforcement, Data visualization, Streaming media, Real-time systems, Web servers, Rivers, Artificial intelligence. Abstract: Recently, interest in the use of drones has increased, and drones are being actively introduced in various fields. We are trying to develop and use drones in various fields such as national defense, logistics, life safety, facility safety management, forest protection and monitoring, but there are still restrictions on the use of drones. The biggest limitation is the use of drones on land such as mountains and rivers. For example, if the police are searching for a missing person in an area with mountains, bushes, and a large river, multiple police personnel must visually check the drone footage on site every day. And then there's the problem of finding a missing person or lost article of a missing person and having to re-search where it was found. Therefore, the visualization technology proposed in this paper is a technology that visualizes real-time spatial mapping of drone images taken in real time onto a web-based 2D map. In cooperation with the missing person search AI inference function, the AI analysis result video is mapped on a web-based 2D map in real time. AI analysis results are visualized in real time on a web map using spatial information among the meta information in the video. |
19,058 | Please write an abstract with title: Effect of Different Deconvolution Methods on Structure Function Calculation, and key words: Integrated circuits, Deconvolution, Filtering, Frequency-domain analysis, Conferences, Filtering algorithms, Bayes methods. Abstract: For the calculation of correct structure function, getting the correct time constant spectrum is an important prerequisite. The time-constant spectrum is the result of the deconvolution of the derivative of the unit step response and weight function. However, deconvolution is an ill-posed problem which needs utmost care. The literature on the problem of structure function proposes two prominent solutions for the deconvolution step, namely Inverse Filtering and Bayesian deconvolution. This research work implements both deconvolution methods in the algorithm for structure function algorithm and compares the obtained structure function with the analytical solution. On the one hand, inverse filtering requires a filter function which does not change the low-frequency components but strongly attenuates high-frequency components in the frequency domain and on the other hand Bayesian deconvolution is an iterative process and might be time-consuming in case of high iteration. The comparison of structure functions for test structures procured from both deconvolution method shows that the structure function derived from Bayesian deconvolution have a better match with that of analytical structure functions. |
19,059 | Please write an abstract with title: A 0.41W 34Gb/s 300GHz CMOS Wireless Transceiver, and key words: Wireless communication, Radio frequency, Design automation, Asia, Transceivers, Topology, Mixers. Abstract: A 300GHz CMOS-only wireless transceiver that achieves a maximum data rate of 34Gb/s while consuming a total power of 0.41W from a 1V supply is introduced. A subharmonic mixer with low conversion loss is proposed to compensate the absence of the RF amplifiers in TX and RX as a mixer-last-mixer-first topology is adopted. The TRX covers 19 IEEE802.15.3d channels (13-23, 39-43, 52-53, 59). |
19,060 | Please write an abstract with title: Experimental Testing of a Nonredundant Spherical Spiral NFFF Transformation for Offset Mounted Quasi-planar AUTs, and key words: Spirals, Noise measurement, Springs, Interpolation, Antenna measurements, Probes, Electromagnetics. Abstract: This communication deals with the experimental validation of an accurate nearfield-far-field (NFFF) transformation technique with spherical spiral scanning for offset mounted quasi-planar antennas, which, unlike the classical spherical one, requires a number of NF data minimum and coincident with that needed in the onset mounting case. This last feature makes such a NFFF transformation very attractive, since, when a centred mounting of antenna under test (AUT) is not possible, the number of NF data required by the classical spherical NFFF transformation considerably increases. Such a NFFF transformation exploits the nonredundant sampling representations of electromagnetic fields and has been attained by considering a quasi-planar antenna as enclosed in an oblate ellipsoid and applying the unified theory of spiral scan-nings for nonspherical AUTs. An optimal sampling interpolation formula allows the fast and precise recovery of the NF data required by the classical spherical NFFF transformation from the collected nonredundant ones. Some experimental results, which assess the efficacy of the developed technique, are shown, thus confirming its validity also from the practical viewpoint. |
19,061 | Please write an abstract with title: Signaling and Architecture for Unified Simultaneous Wireless Information and Power Transfer, and key words: System performance, Conferences, Prototypes, Receivers, Hardware, Internet of Things, Resource management. Abstract: In this paper, we propose a unified simultaneous wireless information and power transfer (SWIPT) signal and its architecture design in order to take advantage of both single tone and multi-tone signaling by adjusting only the power allocation ratio of a unified signal. For this, we design a novel unified and integrated receiver architecture for the proposed unified SWIPT signaling, which consumes low power with an envelope detection. We demonstrate that the proposed unified SWIPT system improves the achievable rate under the self-powering condition for low-power Internet-of-Things (IoT) devices. This will facilitate effective deployment of low-power IoT networks that concurrently supply both information and energy wirelessly to the devices by using the proposed unified SWIPT signaling and architecture. |
19,062 | Please write an abstract with title: D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features, and key words: Three-dimensional displays, Feature extraction, Detectors, Convolution, Kernel, Two dimensional displays, Training. Abstract: A successful point cloud registration often lies on robust establishment of sparse matches through discriminative 3D local features. Despite the fast evolution of learning-based 3D feature descriptors, little attention has been drawn to the learning of 3D feature detectors, even less for a joint learning of the two tasks. In this paper, we leverage a 3D fully convolutional network for 3D point clouds, and propose a novel and practical learning mechanism that densely predicts both a detection score and a description feature for each 3D point. In particular, we propose a keypoint selection strategy that overcomes the inherent density variations of 3D point clouds, and further propose a self-supervised detector loss guided by the on-the-fly feature matching results during training. Finally, our method achieves state-of-the-art results in both indoor and outdoor scenarios, evaluated on 3DMatch and KITTI datasets, and shows its strong generalization ability on the ETH dataset. Towards practical use, we show that by adopting a reliable feature detector, sampling a smaller number of features is sufficient to achieve accurate and fast point cloud alignment. |
19,063 | Please write an abstract with title: Research on intelligent recommendation system model supported by data mining and algorithm optimization, and key words: Analytical models, Companies, Big Data, Real-time systems, Data models, Internet, Electronic commerce. Abstract: With the rapid development of China's mobile Internet and the advent of 5g era, employees from all walks of life will basically use websites to buy all kinds of goods needed in life. As we all know, big data has become a key direction in the work of various Internet companies and the recommendation system can be said to be one of the best landing applications of big data. The benefits it brings to Internet companies are real and visible. Especially for e-commerce, intelligent recommendation system can directly affect the sales performance of an e-commerce enterprise[1]. How to store these massive data and efficiently mine valuable user information is the real challenge of big data technology[2]. In this paper, based on the modified Chinese Amazon e-commerce data set well-known in the field of recommendation system construction, and based on the real business data architecture of an e-commerce website, the project constructs an integrated e-commerce recommendation system, offline recommendation service and real-time recommendation service provide a variety of methods to achieve mixed recommendation effect. It provides a variety of off-line analysis methods and clever and accurate real-time recommendation model to realize data mining. |
19,064 | Please write an abstract with title: Enhanced MPC for Omnidirectional Robot Motion Tracking Using Laguerre Functions and Non-Iterative Linearization, and key words: Prediction algorithms, Optimization, Trajectory, Robots, Heuristic algorithms, Mobile robots, Computational modeling, Stochastic processes, Trajectory tracking. Abstract: To cope with the computational complexity of the traditional model predictive control, and to reduce the error of the linearization and prediction processes, this paper presents an improved model predictive control algorithm, based on Laguerre functions, for the motion tracking of an omnidirectional mobile robot with non-iterative linearization. To design the controller, the kinematic modeling of the three-wheeled omnidirectional robot was first performed. Next, the model predictive algorithm was developed using Laguerre functions to parametrize the control signals. At each sampling instant of the online optimization, a linearization along the predicted trajectory, based on the duality principle between optimal control and stochastic filtering, was carried out to deal with the nonlinearities of the system. This non-iterative linearization provides better approximation of the nonlinear behavior which improves the prediction process and the tracking performance, with lower computational burden due to the use of the Laguerre functions. The new controller is applied to solve the trajectory-tracking problem of an omnidirectional robot. A comparative study between the proposed controller, the conventional model predictive control, and the nonlinear model predictive approach is made. Simulation results confirm that the new controller outperform the latter ones regarding tracking accuracy with considerably low computational effort. The feasibility of the controller is demonstrated by real-time experiment on the Robotino-Festo omnidirectional mobile robot. |
19,065 | Please write an abstract with title: Strategies for Improving the New Media Literacy Education for University Students, and key words: Media, Education, Logic gates, Artificial intelligence. Abstract: With the development of new media technology, university students have been exposed to the extensive communication environment of new media information. The new media literacy of university students is the key to effectively dealing with the massive amount of new media information. However, the new media literacy ability of university students directly depends on the level of their new media literacy education. This paper analyzes and finds out that there are still some problems in the new media literacy education for university students, such as the lack of education environment for social new media literacy, the backward curriculum of new media literacy education in universities, and the lack of learning awareness of new media literacy for university students, and moreover, relevant strategies are proposed in this paper from the social, university and university student levels. |
19,066 | Please write an abstract with title: Coarse-to-Fine Joint Distribution Alignment for Cross-Domain Hyperspectral Image Classification, and key words: Feature extraction, Task analysis, Adaptation models, Hyperspectral imaging, Training data, Semantics, Image classification. Abstract: Domain adaptation (DA) aims to enhance the feature transferability of a model across different domains with feature distribution differences, which has been widely explored in many computer vision tasks such as semantic segmentation and object detection, but has not been fully studied in hyperspectral image (HSI) classification task. Compared with the natural image-based DA, HSI-based DA still faces two main challenges: First, due to the strong spectral variability of HSIs, it is difficult to extract discriminative and domain-invariant features from different domains, resulting in the misalignment of cross-domain features; Second, class-wise (or fine-grained) spectral feature inconsistency between domains also inevitably degrades the classification accuracy. To address these issues, in this article, we propose a novel coarse-to-fine joint distribution alignment (JDA) framework for cross-domain classification of HSIs. Specifically, the training samples from source and target domains are first fed into a coupled variational autoencoders (VAE) module, which is composed of two well-designed VAEs equipped with mutual information metric to learn high-level domain-invariant representations in a shared latent space, so that the network can learn a coarse-grained source-target feature consistency. Furthermore, to alleviate the class-wise inter-domain feature inconsistency, a JDA module is constructed to perform a fine-grained cross-domain alignment by matching the joint probability distributions between the source and target domains through adversarial learning. Extensive experiments on both simulated and real hyperspectral datasets demonstrate the superiority of the proposed method in comparison with several conventional and state-of-the-art methods. |
19,067 | Please write an abstract with title: Cooperative Scheduling for Directional Wireless Charging With Spatial Occupation, and key words: Costs, Inductive charging, Robot sensing systems, Wireless sensor networks, Wireless communication, Radio frequency, Pricing. Abstract: Wireless Power Transfer (WPT) technology has been developed rapidly in recent years. The cooperative charging model and corresponding scheduling methods have been proposed to save the charging cost in paid charging service. However, the state-of-the-art methods ignore the spatial occupation issue of rechargeable devices. Moreover, the cooperative charging scheduling in directional wireless charging has not been studied yet. This paper studies the cooperative scheduling for directional wireless charging with spatial occupation. We formulate the Cooperative Charging Scheduling with Spatial occupation (CCSS) problem of Mobile Rechargeable Sensor Devices (MRSDs) for optimizing the total cost of whole charging system. We first investigate the properties of optimal arrangement of MRSDs in charging group and calculate the tight intervals of charging angles of MRSDs. We show that it is sufficient to bound the error by conducting angle discretization for only two MRSDs in each charging group. Then, a $(\ln n+1)(1+\varepsilon)$-approximation algorithm of the CCSS problem is proposed based on greedy approach, where $n$ is the number of MRSDs, and $\varepsilon$ is the discretization error. The results of extensive simulations and field experiments demonstrate that our algorithm can reduce at most 42.5% total cost comparing with the benchmark algorithms. |
19,068 | Please write an abstract with title: CW atomic oxygen laser at 4.56 µ, and key words: Atomic beams, Atom lasers, Atomic measurements, Gas lasers, Laser tuning, Laser transitions, Electron tubes, Fault location, Laser excitation, Pump lasers. Abstract: CW laser oscillation at 4.56 μ was observed in atomic oxygen produced in a magnetic induction discharge located at the upstream end of a fast flow system. The laser transition has been identified and an inversion scheme is proposed. |
19,069 | Please write an abstract with title: Direction of Arrival Positioning Requirements for Location-Aware Beamforming in 5G mmWave UDN, and key words: Direction-of-arrival estimation, 5G mobile communication, Simulation, Receiving antennas, Estimation, Interference, Classification algorithms. Abstract: The rapid growth in the number of simultaneously operating transceivers in deployed radio access networks of the fifth and subsequent generations leads to the problem of an unacceptably high level of intra-system interference, provided they are densified to one device per square meter. Adaptive Location-Aware Beamforming (LAB) can potentially compensate for high interference levels by maximizing the antenna pattern to the source / receiver of the desired signal and minimizing the antenna pattern to the source / receiver of the interfering signal. The prerequisite for LAB is precise Direction of Arrival (DOA) positioning of neighbor user equipment (UE). This study analyzes the algorithm of multiple classification of UE signals from the gNodeB (gNB) point of view in the F2 millimeter wave (mmWave) frequency range. The content of this investigation can be divided into two parts. In the first part mathematical model of the DOA algorithm is given. In the second part simulation results for DOA scenarios in 5G mmWave Ultra-Dense Networks (UDN) are described. The contribution of this investigation is the 2D-MUSIC resolution estimation in 5G UDN scenarios, which reveals the dependence of the resolution threshold for 2D-MUSIC algorithm on the number of elements in the antenna array and Signal-to-Noise-and-Interference Ratio (SINR). Simulation results reveal, that the resolution of the 2D-MUSIC algorithm is achieved with two degrees angular separation of devices, the number of antenna array elements more than 64 and SINR more than 30 dB. |
19,070 | Please write an abstract with title: Design and Investigation of Funnel for Acoustic Wave, and key words: Acoustic waveguides, Ultrasonic imaging, Transducers, Waveguide components, Simulation, Waveguide theory, Reliability theory. Abstract: Ultrasound sources of an appropriate size and controllable power are crucial for extensive investigations and applications, especially in exploratory experiments needing precise ultrasound stimulations. We designed an acoustic wave funnel (AWF) that changes the ultrasound source to a suitable size and acts as a small ultrasound source suited for widespread experiments and applications. The AWF consists of three parts—two cladded waveguides of different radii connected by a hollow cone. The larger waveguide has the same radius as the transducer, whereas the radius of the smaller waveguide is set for application requirements. Using the cone, the AWF squeezes the acoustic wave from the large transducer into the small output port and produces a small intense acoustic source. Both theoretical analyses and numerical simulations show that AWF works efficiently and exhibits a pretty amplification factor. The AWF is effective and practical in providing a miniaturized acoustic wave source with high intensity. These results indicate that, when requiring a miniaturized ultrasound source in experiments and applications, the AWF is a practical and reliable device. |
19,071 | Please write an abstract with title: Annealing for Distributed Global Optimization, and key words: Optimization, Symmetric matrices, Distributed algorithms, Annealing, Convergence, Technological innovation, Linear programming. Abstract: The paper proves convergence to global optima for a class of distributed algorithms for nonconvex optimization in network-based multi-agent settings. Agents are permitted to communicate over a time-varying undirected graph. Each agent is assumed to possess a local objective function (assumed to be smooth, but possibly nonconvex). The paper considers algorithms for optimizing the sum function. A distributed algorithm of the consensus + innovations type is proposed which relies on first-order information at the agent level. Under appropriate conditions on network connectivity and the cost objective, convergence to the set of global optima is achieved by an annealing-type approach, with decaying Gaussian noise independently added into each agent's update step. It is shown that the proposed algorithm converges in probability to the set of global minima of the sum function. |
19,072 | Please write an abstract with title: Person Re-Identification Using Additive Distance Constraint With Similar Labels Loss, and key words: Training, Task analysis, Additives, Face recognition, Machine learning, Measurement. Abstract: Despite the promising progress made in recent years, person re-identification (Re-ID) remains a challenging task due to the intra-class variations. Most of the current studies used the traditional Softmax loss for solutions, but its discriminative capability encounters a bottleneck. Therefore, how to improve person Re-ID performance is still a challenging task. To address this problem, we proposed a novel loss function, namely additive distance constraint with similar labels loss (ADCSLL). Specifically, we reformulated the Softmax loss by adding a distance constraint to the ground truth label, based on which similar labels were introduced to enhance the learned features to be much more stable and centralized. Experimental evaluations were conducted on two popular datasets (Market-1501 and DukeMTMC-reID) to examine the effectiveness of our proposed method. The results showed that our proposed ADCSLL was more discriminative than most of the other compared state-of-the-art methods. The rank-1 accuracy and the mAP on Market-1501 were 95.0% and 87.0%, respectively. The numbers were 88.6% and 77.2% on DukeMTMC-reID, respectively. |
19,073 | Please write an abstract with title: Colored Petri Net Reusing for Service Function Chaining Validation, and key words: Service function chaining, Computational modeling, Conferences, Petri nets, Network security, Software, Libraries. Abstract: With the development of software defined network and network function virtualization, network operators can flexibly deploy service function chains (SFC) to provide network security services more than before according to the network security requirements of business systems. At present, most research on verifying the correctness of SFC is based on whether the logical sequence between service functions (SF) in SFC is correct before deployment, and there is less research on verifying the correctness after SFC deployment. Therefore, this paper proposes a method of using Colored Petri Net (CPN) to establish a verification model offline and verify whether each SF deployment in SFC is correct after online deployment. After the SFC deployment is completed, the information is obtained online and input into the established model for verification. The experimental results show that the SFC correctness verification method proposed in this paper can effectively verify whether each SF in the deployed SFC is deployed correctly. In this process, the correctness of SF model is verified by using SF model in the model library, and the model reuse technology is preliminarily discussed. |
19,074 | Please write an abstract with title: Overcurrent and Short-circuit Capability Experimental Investigation for GaN HEMT at Cryogenic Temperature, and key words: Resistance, Temperature, Switching loss, Cryogenics, Switches, HEMTs, Threshold voltage. Abstract: Recent research reveals that gallium nitride (GaN) devices achieve significantly reduced on-state resistance and faster switching speed operating at cryogenic temperature. These characteristics enable GaN-based power converter to achieve higher efficiency and power density and make GaN device an excellent candidate for cryogenic power electronics applications. However, overcurrent and short-circuit capability of GaN device at cryogenic temperature have not been evaluated. This paper characterizes a 650V-30A enhancement-mode GaN high-electron mobility transistor (HEMT) and experimentally evaluated the overcurrent and short-circuit capability at cryogenic temperature. Testing results show that this GaN HEMT achieves >5X conduction loss reduction and 30% switching loss reduction at cryogenic temperature. Moreover, GaN HEMT is capable of operating at around 4X of rated current at cryogenic temperature. The short-circuit capability at cryogenic temperature is similar to that at room temperature. Both the device failure threshold dc voltage and short-circuit withstand time are almost unchanged at cryogenic temperature. |
19,075 | Please write an abstract with title: Synergies between electric vehicles and distributed renewable generation?, and key words: ELECTRIC VEHICLES, GEOGRAPHIC INFORMATION SYSTEMS, MUTUAL INFORMATION, PHOTOVOLTAICS, DIFFUSION THEORY. Abstract: Prosumers represent an important building block under the paradigm of a decentralized energy landscape such as outlined in the EU Clean Energy Package. However, the synergetic use of distributed resources such as electric vehicles (EV) or residential roof-integrated photovoltaics (PV) on household or neighbourhood level requires their diffusion patterns being temporally and spatially synchronized. This paper is dedicated to the joint analysis of their adoption patterns, using spatial analysis interfaced with mutual information and criteria ranking analysis. Surprisingly, outcomes for Portugal suggest that residential photovoltaics and electric vehicles are adopted by different population layers, as their occurrence is linked to diverging sets of socio-demographic criteria. Furthermore, an analysis of these criteria sets shows that their internal composition (the driving factors behind EV and PV adoption) varies among regions which has important implications on electricity network planning. |
19,076 | Please write an abstract with title: The Energy Management Strategies of Residential Integrated Energy System Considering Integrated Demand Response, and key words: Heating systems, Electric potential, Energy resources, Simulation, Switches, Demand response, Power grids. Abstract: In this paper, a novel residential integrated demand response model is proposed, which enables residential consumers to participate in demand response programs not only by shifting appliances, but also through changing energy types they consumed. The integrated demand response is modeled from three levels, namely the interactions with utility grids, the flexibilities of power, cooling and heating demands and the optimal operation of smart energy hub. In order to demonstrate the effectives and advantages of integrated demand response, four contrastive cases are studied, and simulation results show that the integrated demand response can bring better economic and environmental benefits. Furthermore, a new evaluation index: electricity substitute ratio is also proposed to evaluate the integrated demand response capacity and potential. |
19,077 | Please write an abstract with title: Electric current classification with tiny machine learning for home appliances, and key words: Deep learning, Support vector machines, Home appliances, Voltage measurement, Microcontrollers, Computational modeling, Current measurement. Abstract: Non-intrusive electric load monitoring methods analyze changes in voltage and current measured at the household's power plug connection point. This helps to disaggregate the total power consumption into individual appliances contributions. The idea is to use their unique fingerprint to identify and classify the active appliances. In this paper the mel power spectrogram of the current measurement was used as an input transformed data for both convolutional neural network and more traditional machine learning models. The primary goal was to achieve high accuracy classification. Moreover, the memory and computational complexity of these models were compared against the challenging constraints set by limited resource embedded systems and during the development. The work was concerned on developing machine learning models targeting software execution and deploying those models into a future intelligent meter. Microcontrollers were considered as the primary execution targets in order to evaluate the models' ground truth performance. As a result, the classification accuracy of the appliances measured on the WHITED dataset for the convolutional neural network was 98.6%. While the accuracy with the COOLL dataset achieved 95%. By carefully analyzing both convolutional neural network and off the shelf machine learning models, only the former achieved a tiny memory suitable for the microcontroller deployment. |
19,078 | Please write an abstract with title: Integrating Electrical Engineering Fundamentals with Instrumentation and Data Acquisition in an Undergraduate Mechanical Engineering Curriculum, and key words: Data acquisition, Heat transfer, Strain measurement, Springs, Microcontrollers, Digital filters, Instruments. Abstract: The Anonymous University Mechanical Engineering department was awarded a grant from the National Science Foundation to revolutionize its undergraduate program. The goal of the grant is to implement department wide changes that create a focus on doing engineering with engineers and fosters stronger engineering identities in students and faculty. One area of change is the program’s curriculum. This paper describes how the Electrical Engineering Fundamentals course was integrated into the Mechanical Engineering Instrumentation and Data Acquisition (DAQ) course with the goal of creating connections between electrical engineering concepts and applications in mechanical engineering. Design and implementation of this course sequence are presented. Assessment and evaluation methods are also discussed. |
19,079 | Please write an abstract with title: Performance Evaluation on Various Resistively Loaded Wrapped Bowtie Antenna, and key words: Performance evaluation, Loading, Meetings, Reflector antennas, Loaded antennas. Abstract: The pulse radiating performance of variously loaded wrapped antennas is simulated. The loading profile with the inclusion factor is presented and the evaluation factor is introduced. Based on the performance evaluation for variously loaded wrapped antennas, the lower inclusion case is better than the conventional profile. |
19,080 | Please write an abstract with title: Prioritized Replay Dueling DDQN Based Grid-Edge Control of Community Energy Storage System, and key words: Uncertainty, State of charge, Convergence, Real-time systems, Load modeling, Energy storage, Microgrids. Abstract: This paper develops a new prioritized replay dueling DDQN (PRD-DDQN) method for grid-edge control of community energy storage system with good robustness to uncertainties and fast convergence speed while achieving good control performance. The control problem is first formulated as a Markov decision process (MDP) considering the current time interval, state of charge of the CESS, the price signals, and the pre-trading power between MG and CESS/utility grid. Unlike the double deep Q-network-based method to solve this MDP, the proposed PRD-DDQN endows the agent with a powerful capability of learning by interacting with a more complex environment. This is due to the collaboration of the dueling structure and prioritized replay policy based on the sum-tree. As a result, the control accuracy, model robustness, and algorithm convergence speed are significantly enhanced. Besides, the proposed algorithm supports minute-level and multi-agent parallel control. Comparison results with a deterministic model-based method and other deep reinforcement learning-based methods demonstrate the effectiveness and superiority of the proposed approach. |
19,081 | Please write an abstract with title: Performance Evaluation of Traffic Congestion Detection Algorithms in Real-Life Scenarios, and key words: Performance evaluation, Economics, Roads, Urban areas, Transportation, Feature extraction, Real-time systems. Abstract: Traffic congestion in urban cities has substantial economic and social effects. Roads in urban cities have become more and more crowded. However, it is challenging to upgrade the cities' infrastructure and open new roads for traffic. There-fore, Intelligent Transportation Systems (ITS) introduce Artificial Intelligence (AI) based solutions to help keep the traffic flow in a free state. Identifying the traffic congestions in real-time is critical in ITS solutions as it can provide time to prevent the congestions' transitions through the city road network. In our previous work, we have proposed three novel algorithms to detect the congestions in real-time [1], [2]. The algorithms were verified using synthetic traffic data. In this paper, their performance evaluation using real-life data from the state of California [3] is introduced. The experimental results show that the algorithms are capable to be utilized in real-life scenarios. Our algorithms overperformed the other methods from the literature in terms of detection rate and false alarm rate. Moreover, they have achieved the best performance in terms of detection time by identifying the congestions faster than the other algorithms, which is crucial for the city traffic operators to intervene on time to avoid the transition of the congestion to other roads' sections. |
19,082 | Please write an abstract with title: Blue Noise Sampling and Nystrom Extension for Graph Based Change Detection, and key words: Measurement, Statistical analysis, Signal processing algorithms, Tools, Signal processing, Sampling methods, Radar polarimetry. Abstract: In this paper, we address the problem of sampling on graphs for change detection in large multi-spectral (MS) and synthetic aperture radar (SAR) images by proposing a graph-based data-driven framework. The main steps of the proposed approach are: (i) the segmentation of regions that enclose the change; (ii) the use of smoothness prior for learning a graph of the regions; (iii) the integration of blue-noise sampling (BN) in the change detection scheme. We validate our approach in 14 real cases of remote sensing according to quantitative analyses. The results confirm that using a structured sampling such as BN outperforms recent state-of-the-art methods in change detection for multimodal data. |
19,083 | Please write an abstract with title: The architecture of high-speed matched filter for searching synchronization in DSSS receiver, and key words: Matched filters, Spread spectrum communication, Hardware design languages, Parallel processing, Pipelines, Adders, Table lookup, Signal analysis, Performance analysis, Digital signal processors. Abstract: A high-speed matched filter for searching synchronization in direct sequence spread spectrum (DSSS) receiver is studied. A model to implement the matched filter by hardware description languages (HDL) is proposed. The proposed model is based on parallel processing and pipeline architecture including circular buffer, multiplier, adder, and code look-up table. The proposed model is analyzed with respect to the performance and compared with a conventional digital signal processor (DSP) implementation. |
19,084 | Please write an abstract with title: Impact of spread of information communications technology on lifestyle change, and key words: Information technology, Technology social factors, Teleworking, Energy conservation, Behavioral science. Abstract: In this study the impact of information communications technology (ICT) on lifestyle changes are analysed between the years 2000 and 2010 from three view points namely energy efficiency, increased leisure time and cost reduction. The impact of ICT on lifestyle changes and its effect on energy consumption are analyzed using a microscopic model. It was clarified that lifestyle change, including introduction of teleworking and e-commerce could result in lower energy consumption under a given model. |
19,085 | Please write an abstract with title: Cluster Head Selection Algorithm For Wireless Sensor Networks Using Machine Learning, and key words: Performance evaluation, Wireless sensor networks, Machine learning algorithms, Heuristic algorithms, Wireless networks, Clustering algorithms, Machine learning. Abstract: A Wireless Sensor Network (WSN) is a group of hardware sensors linked together over a wireless network. The sensors are segregated into clusters where every cluster has a cluster head whose job is to collect and transmit data back to the sink node (base station). A sensor node performs activities like data capturing, processing and transfer, which consumes energy. Since these nodes are usually deployed in areas not easily accessible by humans, battery life is one of the key aspects to work on in WSNs. Choosing the appropriate node as a cluster head improves the energy efficiency of the network. This paper proposes a K-Means Energy Efficient Cluster Head Selection Algorithm (KE-CHSA) for WSN where machine learning is applied to form clusters and elect cluster heads. We propose an equation which dynamically changes the number of clusters every round, based on the number of sensor nodes alive and a density parameter. Our algorithm elects the best-suited node as the cluster head considering the energy remaining and its distance from the other nodes. KE-CHSA outperforms the traditional LEACH [21] and C-LEACH [22] by improving the lifetime of WSNs. |
19,086 | Please write an abstract with title: Infrared lasing from Cr/sup 2+/ doped CdTe & optical properties of Cr/sup 2+/ doped ternary II-VI's, and key words: Chromium, Pump lasers, Absorption, Biomedical optical imaging, Optical pumping, Optical sensors, Laser excitation, Optimized production technology, Laser theory, Semiconductor lasers. Abstract: Summary form only given. In this paper we present an evaluation of Cr doped CdTe for solid-state laser applications. We discuss the material preparation, spectroscopic properties, and the laser performance at room temperature. In addition, we present an overview and comparison of the optical properties of several Cr/sup 2+/ doped binary and ternary II-VI materials. |
19,087 | Please write an abstract with title: A Novel Sentence Embedding Based Topic Detection Method for Microblogs, and key words: Bridges, Social networking (online), Computational modeling, Blogs, Neural networks, Clustering algorithms, Task analysis. Abstract: Topic detection is a difficult challenging task, especially when the exact number of topics is unknown. In this article, we present a novel topic detection approach based on neural computing to detect topics in a microblogging dataset. We use an unsupervised neural sentence embedding model to map blogs to an embedding space. The proposed model is a weighted power mean sentence embedding model in which weights are calculated by a targeted attention mechanism. The experimental results show that our embedding model performs better than baseline in sentence clustering. In addition, we propose a clustering algorithm, referred to as Relationship-Aware DBSCAN (RADBSCAN), to discover topics from a microblogging dataset in which the number of topics is automatically determined by the characteristics of the dataset. Moreover, to provide parameter insensibility, we use the forwarding relationship in the blogs as a bridge of two independent clusters. Finally, we validate the proposed method on a dataset from the Sina microblog. The results show that our approach can detect all topics successfully and can extract the keywords of each topic. |
19,088 | Please write an abstract with title: Case study: Adaptive load shedding in critical industrial facilities, and key words: LOAD SHEDDING, IEC 61850 GOOSE, IEEE C37.118 SYNCHROPHASORS, IEC 61131, ISLANDED AND NON-ISLANDED SYSTEMS. Abstract: Industrial plant activities involve critical processes, especially those that include the use of toxic gases. In the event of a loss of electricity supply, such processes can fail and cause lethal health risks to those near the plants. In industrial plants that rely on their own power generation and are interconnected to an electric utility for energy backup, both the power system topology and the importance and criticality of the electrical loads across these plants change dynamically as processes and operations are initiated or stopped. In the event of a fault, an effective load-shedding scheme that adapts automatically to changes in system topology, such as islanded and non-islanded conditions, is key to compensate for lost generation, maintain power system stability, and avoid blackouts. This paper describes the design, implementation, and operational results of an in-service load-shedding scheme for a large chemical industrial complex in Mexico. The proposed load-shedding scheme uses high-speed IEC 61850 Generic Object-Oriented Substation Event (GOOSE) messages and synchrophasors, which provide apparatus monitoring and control, remote load shedding, and monitoring of power measurements for onsite generators and the interconnection with the electric utility system. |
19,089 | Please write an abstract with title: Segregated Linear Decision Rules for Inverter Watt-VAr Control, and key words: Optimization, Inverters, Reactive power, Uncertainty, Photovoltaic systems. Abstract: The modern photovoltaic inverter has an active power-reactive power (Watt-VAr) control curve that is part of its management modes. The Watt-VAr curve, whose settings can be remotely modified, regulates the inverter reactive power output in function of its active power. This paper proposes the optimization of inverter segregated linear decision rules (LDRs), starting from the legacy Volt-VAr optimization in distribution networks. As opposed to classical LDRs that are interfaced with Volt-VAr optimization, the segregated LDRs are piecewise linear continuous curves that directly satisfy the reactive power capability of inverters, and their multiple segments can capture the correlation in solar power variability. The paper presents linear programming formulations for optimizing the segregated linear decision rules using stochastic optimization, robust optimization, and distributionally robust optimization. The optimization schemes are demonstrated on both meshed and radial networks, and their performance is validated via Monte-Carlo simulation. |
19,090 | Please write an abstract with title: Sentiment Analysis From Bengali Social Media Posts Using Hybridized Feature Extraction Approach, and key words: Support vector machines, Deep learning, Sentiment analysis, Machine learning algorithms, Social networking (online), Blogs, Data preprocessing. Abstract: Now-a-days, Social media platforms like Facebook, Twitter etc. are becoming more and more popular to express feelings and thoughts. People not only share their happy moments on these platforms but also share their feelings when they are extremely depressed. Analyzing these social media posts, one’s mental condition can be detected whether he/she is happy, sad or angry at a particular time using sentiment analysis in natural language processing. Most of the research in this field is based on English language and the accuracy of sentiment analysis from Bengali language is not very high. So, our purpose is to work on this field using Bengali dataset collected from different social media posts and make the sentiment detection more accurate so that this work can be used to build a system that can be used in the mental health sector of our country. In this research, we have first collected social media data. After applying different data preprocessing techniques, we have made a number of feature selection and extraction combinations. We have applied some basic and advanced machine learning and deep learning algorithms on each of these to find the best combination and algorithm by monitoring the highest achieved accuracy. |
19,091 | Please write an abstract with title: Development Prospects of the ERA-GLONASS System, and key words: Space vehicles, GSM, Roads, Modulation, Medical services, Radio links, Orbits. Abstract: Often, a victim during a road traffic accident does not have the opportunity to independently call the rescue services and dies from the lack of medical care. Saving such lives is the primary goal of the ERA-GLONASS system. This article is overview one of the ways to development prospects of the ERA-GLONASS system in areas with complete or partial lack of mobile network coverage. In particular the usage of highly elliptical spacecraft instead of already familiar ways. The radio link budget calculation uses the GSM standard with allowable modulation methods and possible line losses, as well as the characteristics of known systems in a highly elliptical orbit. Opportunities are proved by a series of graphs. |
19,092 | Please write an abstract with title: FO-PI Controller for Regulating DC Link Voltage in UPQC Integrated HES System for Power Quality Improvement, and key words: Wind energy, Power quality, Power system stability, Active filters, Harmonic analysis, Hybrid power systems, Stability analysis. Abstract: This paper emphasis on an optimized Fractional order PI controller (FOPI) for enhancing the power quality of three phase hybrid energy storage (HES) system integrated unified power quality conditioner (UPQC). In order to offer uninterrupted electricity, renewable energy sources regarding wind energy, solar PV, and battery energy storage systems (BESS) are also explored. Whenever the windmill as well as PV array is not supplying electricity, the BESS could improve the stability of the power distribution system, meet entire load requirements. Grid power quality harmonics as well as concerns induced via non-linear loads are addressed by the UPQC type with shunt and series active filter compensators. To ease the grid’s power quality issues and the harmonics introduced by non-linear loads there subsist the UPQC model with active filter shunt and series compensator. The FOPI controller is used for improving the power quality of a 3-phase hybrid energy storage device with an integrated UPQC. RES such as PV arrays, BESS, as well as wind energy are analyzed in order to deliver continuous electricity. Whenever the PV array as well as windmill is not supplying power, the BESS could provide entire load demand, which increases the stability of the power system distribution. The UPQC model including series and shunt active filter compensators exists to alleviate grid power quality problems as well as harmonics introduced by non-linear loads. The UPQC shunt compensator collects power from hybrid energy systems, while the load is protected from grid-related power quality issues by the series compensator. The FOPI controller is built with iso-damping characteristics to control the voltage of the DC connection at a desirable level. The gain of the FOPI controller (Kp, Ki, $\lambda$,) is optimally tuned by a Enhanced Seagull with Rooster Update (ES-RU) Algorithm, which merge the concepts of the Seagull Optimization Algorithm (SOA) as well as the Chicken Swarm Optimization Algorithm (CSO). |
19,093 | Please write an abstract with title: Machine Learning Based Protocol Classification in Unlicensed 5 GHz Bands, and key words: Wireless communication, Training, Protocols, Recurrent neural networks, Conferences, Simulation, RF signals. Abstract: To monitor RF activity and efficiently coordinate channel access for heterogeneous wireless systems over a shared channel, it is important to be able to classify observed transmissions accurately without decoding them. In this paper, we propose novel recurrent neural network (RNN) architectures for signal classification, considering as a use case on interleaving-based spectrum sharing model for Wi-Fi, LTE-LAA, and 5G-NRU over the unlicensed 5 GHz bands. Several classifiers are presented, which take raw in-phase/quadrature (I/Q) samples as input. First, we examine Simple RNNs, Long Short-term Memory (LSTM) networks, and Gated Recurrent Units (GRU) networks for protocol classification. These RNNs are used to capture the unique features in observed signals. To further improve the classification accuracy, we extend the RNN designs into a bidirectional structure, allowing an RNN cell to learn the temporal dependence in the waveform in both forward and backward directions. Bidirectionality can effectively increase the amount of information and the context available to the neural network. We then extend our designs to multi-layer RNNs, which allow the classifier to capture temporal correlations at multiple time scales, hence increasing the network's computational capacity. Finally, we propose further enhancements to reduce the over-fitting problem in RNN training, including regularization, recurrent weight constraints, and rate halving. Our simulation results show that the multi-layer and bidirectional designs can effectively improve the accuracy of the RNN-based RF signal classifier. Combining the two features, an RNN structure can achieve more than 92% accuracy in our protocol classification problem. |
19,094 | Please write an abstract with title: Image Art Innovation based on Extended Reality Technology, and key words: Technological innovation, Art, Extended reality, Space technology, Production, Media, Data science. Abstract: Image art creation based on XR technology has developed rapidly in the past years. Relevant technologies have been continuously improved, so that corresponding works have also received extensive attention in different media. This paper first discusses the creative characteristics of image art based on XR technology. In terms of production process, technical modules and artistic language, XR images fully reflect the artistic characteristics which integrate virtual and real. It is embodied in the combination of multi technology modules, multi space narration, interactive, real-time, on-site creation, Pre-post production, etc. Secondly, from the perspective of art and technology integration and innovation, XR image art is a new form of narrative art creation. It is a new stage of the development of traditional image narrative art, which embodies the characteristics of real-time, virtual, interactive and so on. It can better adapt to the demands of social and cultural development. Finally, the paper considers and analyzes the practice of XR image in the inheritance and development of traditional culture and art. Explore the innovative significance of XR image art in the current era in terms of social cultural demands and aesthetic thoughts. |
19,095 | Please write an abstract with title: Geometry-Aware Segmentation of Remote Sensing Images via Joint Height Estimation, and key words: Semantics, Data models, Image segmentation, Labeling, Decoding, Estimation, Convolution. Abstract: Recent studies have shown the benefits of using additional elevation data [e.g., digital surface model (DSM) or normalized DSM (nDSM)] for enhancing the performance of the semantic labeling of aerial images. However, previous methods mostly adopt 3-D elevation information as additional inputs, while, in many real-world applications, one does not have the corresponding DSM images at hand, and the spatial resolution of acquired DSM images usually does not match the aerial images. To alleviate this data constraint and also take advantage of 3-D elevation information, in this letter, a geometry-aware segmentation model is introduced to achieve accurate semantic labeling of aerial images via joint height estimation. Instead of using a single-stream encoder–decoder network for semantic labeling, we design a separate decoder branch to predict the height map and use the DSM images as side supervision to train this newly designed decoder branch. With the newly designed decoder branch, our model can distill the 3-D geometric features from 2-D appearance features under the supervision of ground-truth DSM images. Moreover, we develop a new geometry-aware convolution module that fuses the 3-D geometric features from the height decoder branch and the 2-D contextual features from the semantic segmentation branch. The fused feature embeddings can produce geometry-aware segmentation maps with enhanced performance. Our model is trained with DSM images as side supervision, while, in the inference stage, it does not require DSM data and directly predicts the semantic labels. Experiments on International Society for Photogrammetry and Remote Sensing (ISPRS) Vaihingen and Potsdam data sets demonstrate the effectiveness of the proposed method for the semantic segmentation of aerial images. |
19,096 | Please write an abstract with title: A Velocity Filtering Method for Track - Before- Detect with Multiple Sensors, and key words: Sensors, Target tracking, Radar tracking, Coordinate measuring machines, Object detection, Noise measurement, Trajectory. Abstract: Detecting and tracking weak targets with multiple sensors performs superiorly to that with a single sensor. In this paper, a multi-sensor velocity filter based track-before-detect (MS-VF-TBD) method in mixed coordinates is proposed for weak target detection. First, the predicted position in the global Cartesian coordinates of each cell of each sensor is achieved in terms of the assumed velocity and the position in Cartesian coordinates which is converted by the cell in sensor coordinates. Then the measurement of the cell is added onto the cell closest to the predicted position converting back to the global sensor coordinates to realize the process of target energy integration within multiple sensors. The energy accumulation procedure of multiple sensors is derived in detail. Simulation results demonstrate the superiority of the proposed method compared with other MS- TBD methods in terms of detection probability and estimation accuracy. |
19,097 | Please write an abstract with title: Enhancement of Partial Discharge Resistant Characteristics of XLPE Nanocomposites Using Plasma Treatment Technique, and key words: Nanoparticles, Nanocomposites, Plasmas, Discharges (electric), Surface discharges, Chemicals, Surface treatment. Abstract: Polymer nanocomposites are well-known for their superior insulation properties over the existing polymer insulating material due to the existence of nanoparticles. However, the agglomeration of the nanoparticles within the polymer matrix is the main factor that restricts the enhancement of insulation characteristics because the nonuniform dispersion of nanoparticles reduces the interfacial area and creates weak polymer-nanofiller interfacial bonds. Thus, the main contribution of this work is conducting a comprehensive technique of nanoparticle surface modification using atmospheric pressure plasma (APP) to improve the surface compatibility between nanoparticles and polymer matrix, consequently enhancing insulation properties. In this study, the APP with the homogeneous and stable discharge was used in treating the surface of silicon dioxide (SiO2) nanoparticles to enhance its compatibility with cross-linked polyethylene (XLPE) matrices. In comparison with unfilled XLPE, the most effective formulation of XLPE nanocomposites was shown by the sample with 3 wt% of plasma-treated SiO2 nanoparticles with a reduction of partial discharge (PD) magnitude up to 62.85% and the reduction of PD numbers up to 26.70%. Plasma has proven to be a comprehensive technique to improve the PD resistance of XLPE nanocomposites by exciting the formation of more substantial interfacial regions through forming interfacial bonds and reducing the size and number of agglomerated clusters. |
19,098 | Please write an abstract with title: Depthwise Separable Residual Network Based on UNet for PolSAR Images Classification, and key words: Support vector machines, Convolution, Geoscience and remote sensing, Network architecture, Feature extraction, Spatial databases, Polarimetric synthetic aperture radar. Abstract: According to the small sample characteristics of polarimetric synthetic aperture radar (PolSAR) data and its unique data attributes, a new network architecture for PolSAR images classification based on Unet is proposed in this paper. Fully considering the characteristics of PolSAR data, the spatial features and channel features of the input data are extracted respectively by the depthwise separable convolution and avoid extracting redundant features. In order to improve the classification accuracy, the residual structure is used to increase the depth of the network and fully transmit the characteristics information of PolSAR data. The experimental results clearly demonstrate that the architecture we proposed can achieve better classification accuracy than other PolSAR images classification methods. |
19,099 | Please write an abstract with title: Oscilloscope influence on the calibration uncertainty of the pulse rise time of ESD simulators, and key words: Oscilloscopes, Calibration, Uncertainty, Electrostatic discharge, Current measurement, Time measurement, Voltage, Low pass filters, Impedance, Pulse measurements. Abstract: In the paper an approach to contribution of the oscilloscope in uncertainty estimation of the rise time by measurement of the ESD discharge current is performed. Correlation between input signal and the displayed voltage at the oscilloscope called here transmittance is measured and approximated with the second order low pass filter along with the Gauss filters. Voltage at the oscilloscope input is calculated as the product of the analytically expressed current and measured input impedance of the oscilloscope. Moreover measurement uncertainty of input impedance and oscilloscope transmittance are built in the uncertainty estimation. The approach is compared with the two rules concerning conservative estimation of the rise time of oscilloscopes as stated in C. Mittermayer and A. Steiniger (for original article see IEEE Trans. on instrumentation and measurement Vol. 48, No. 6, p. 1103-7, December 1999). Presented calculations of the uncertainty of the rise time for pulses with different rise time shows advantages and better suitability of the novel method by measurement of the ESD discharge current |
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