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14,100 | Please write an abstract with title: Instrumentation problems related to determining geotechnical properties of ocean sediments, and key words: Instruments, Oceans, Sediments, Acoustical engineering, Environmental economics, Acoustic measurements, Sea measurements, Seismic measurements, Sampling methods, Acoustic testing. Abstract: The extraction of most oceanic resources including the methods and economics is influenced by the nature and type of the ocean floor as well as the extent to which the geotechnical properties of the ocean bed can be confidently evaluated. In the near-shore and inner continental shelf zones, methods for such evaluation are mostly extensions and modifications of the conventional procedures used onshore. With the expansion of offshore activities into deeper zones, new techniques are needed for preliminary and detailed evaluation of ocean bed characteristics if operations in these deeper regions are to be viable. In recent years, there has been a proliferation in the instrumentation for offshore environments. Geotechnical engineers generally have limited exposure to sophisticated instrumentation techniques, nor are the instrumentation engineers fully conversant with details of geotechnical measurements and their application. This paper reviews the methods currently used for evaluating geotechnical properties of the ocean floor including sampling (corers, etc.), in situ testing (shear vanes, penetrometers, etc.), and indirect (seismic, acoustic, etc.) techniques. The type of data that a geotechnical engineer generally wishes to obtain, the problems in obtaining them, and the application of the data in practice are briefly reviewed. |
14,101 | Please write an abstract with title: 40-Gb/s Optical receiver achieving 13 dB dynamic range without optical preamplifier, and key words: Optical receivers, Dynamic range, Preamplifiers, Optical distortion, Optical sensors, Optical crosstalk, Gaussian noise, Bit error rate, Stimulated emission, Optical noise. Abstract: We have developed 40-Gb/s optical receiver consisting of a limiting amplifier and a transimpedance amplifier. Using NRZ-format, back-to-back receiver sensitivity of -8 dBm and input dynamic range of 13 dB were achieved without an optical preamplifier. |
14,102 | Please write an abstract with title: An IoT-based Smart Campus Monitoring System, and key words: Education, Information sharing, Air pollution, Real-time systems, Internet of Things, Information technology, Monitoring. Abstract: Education has gotten a lot of attention in recent years. Combining rapidly developing information technology with education can provide students with an accessible learning environment, while also enhancing information sharing between schools and guardians. This paper proposes a smart campus monitoring system based on the Internet of Things (IoT). The system collects real-time campus data as well as students’ physical data through different IoT devices. This paper explains how teachers analyze students’ learning status based on the monitoring data and take effective strategies to improve their learning status. The experimental results show that the proposed system can make prompts in time and teachers can adjust lesson plans based on the monitoring data. |
14,103 | Please write an abstract with title: IP multicast architectures over next-generation GEO satellites, and key words: Satellite broadcasting, Digital video broadcasting, Encapsulation, Artificial satellites, Streaming media, Next generation networking, Payloads, Internet, Delay, Broadcast technology. Abstract: The article proposes a new approach for IP multicast networks using a geostationary satellite. An overview of the current use of satellites for the Internet is presented. It describes the interaction between the network and link layers and underlines the limits of current solutions, i.e., the use of a transparent payload and multi protocol encapsulation (MPE). Then, solutions are proposed, presenting the use of an on-board intelligence and of a more interactive standard than DVB-S, namely DVB-RCS (DVB-return-channel-for-satellite). The paper sets out to study a system conveying multicast streams over an on-board-switching GEO satellite. We study the implementation of both an encapsulation and a signalisation protocol adapted to the system, focusing on the on-board-switching. Eventually, as food for thought, the adaptation of terrestrial protocols in this framework is brought up. |
14,104 | Please write an abstract with title: Analyzing of segregation in mixtures of 3-methylpyridine and heavy water by dynamic neutron radiography (II), and key words: Neutrons, Radiography, Temperature, Polynomials, Image analysis, Inductors, Mathematical model, Pixel, Histograms, Separation processes. Abstract: In 3-methylpyridine-heavy water mixture, the segregation in the closed-loop phase diagram in relation to the temperature and heavy water concentration was studied by dynamic neutron radiography (DNR) at the 10 MW VVR-SM Research Reactor in Budapest, Hungary. On the pixel properties of the DNR images, taken from the phase separation process by Iman 2/spl beta/ v. image analyzing program, polynomial fitting, 3-D intensity histograms were applied. For modeling the segregation process, a two-variable segregation model: S=f(T,D) was set up. From the partial differentiation of the function f with respect to the temperature it was established that the highest rate changes in the segregation take place in the region of 50-55/spl deg/C and are modified by 3-methylpyridine concentration. The increase in the segregation process progresses up to 93-96/spl deg/C, then declines. |
14,105 | Please write an abstract with title: Prediction Method of Real-time System Task Flow of Aviation Equipment Based on Wavelet Neural Network, and key words: Scheduling algorithms, Conferences, Neural networks, Predictive models, Real-time systems, Task analysis, Information technology. Abstract: In view of the difficulties in scheduling aperiodic real-time tasks in the real-time aviation equipment system, task flow prediction method for this system was studied in this paper. According to the characteristics of the real-time aviation equipment system and based on the wavelet neural network (WNN), a task flow prediction model was built, and a forecast simulation experiment was performed by using the model. The experimental results show that task flow in a real-time system can be effectively predicted by the task flow prediction system established based on WNN. |
14,106 | Please write an abstract with title: Evolutionary Large-Scale Dynamic Optimization Using Bilevel Variable Grouping, and key words: Optimization, Statistics, Sociology, Resource management, Heuristic algorithms, Dynamic scheduling, Vehicle dynamics. Abstract: Variable grouping provides an efficient approach to large-scale optimization, and multipopulation strategies are effective for both large-scale optimization and dynamic optimization. However, variable grouping is not well studied in large-scale dynamic optimization when cooperating with multipopulation strategies. Specifically, when the numbers/sizes of the variable subcomponents are large, the performance of the algorithms will be substantially degraded. To address this issue, we propose a bilevel variable grouping (BLVG)-based framework. First, the primary grouping applies a state-of-the-art variable grouping method based on variable interaction analysis to group the variables into subcomponents. Second, the secondary grouping further groups the subcomponents into variable cells, that is, combination variable cells and decomposition variable cells. We then tailor a multipopulation strategy to process the two types of variable cells efficiently in a cooperative coevolutionary (CC) way. As indicated by the empirical study on large-scale dynamic optimization problems (DOPs) of up to 300 dimensions, the proposed framework outperforms several state-of-the-art frameworks for large-scale dynamic optimization. |
14,107 | Please write an abstract with title: Understanding the Use and Abuse of Social Media: Generalized Fake News Detection With a Multichannel Deep Neural Network, and key words: Fake news, Social networking (online), Kernel, Feature extraction, COVID-19, Deep learning, Convolutional neural networks. Abstract: Fake news has spread across social media platforms and with the ease of access, negative consequences have come with it on individuals and society. This issue has become a focus of interest among various research communities, including artificial intelligence (AI) researchers. Existing AI-based fake news detection techniques primarily make use of a 1-D convolutional neural network (1D-CNN) with unidirectional word embedding. We propose a multichannel deep convolutional neural network (CNN) with different kernel sizes and filters as an AI technique. Multiple embedding of the same dimension with different kernel sizes technically allows the news article to be processed at different resolutions of different n-grams at the same time. Different kernel sizes increase the learning ability of the proposed classification model. The proposed model determines how to integrate these interpretations (different n-grams) most suitably. Three real-world fake news datasets were used in experiments to validate the classification performance. The classification results showed that the proposed model has high accuracy in detecting fake news. Regardless of the dataset, the proposed model can be used for fake news detection in binary classification problems. |
14,108 | Please write an abstract with title: Universal adversarial perturbation for remote sensing images, and key words: Training, Deep learning, Perturbation methods, Conferences, Signal processing, Stability analysis, Data models. Abstract: Recently, with the application of deep learning in the remote sensing image (RSI) field, the classification accuracy of the RSI has been dramatically improved compared with traditional technology. However, even the state-of-the-art object recognition convolutional neural networks are fooled by the universal adversarial perturbation (UAP). The research on UAP is mostly limited to ordinary images, and RSIs have not been studied. To explore the basic characteristics of UAPs of RSIs, this paper proposes a novel method combining an encoder-decoder network with an attention mechanism to generate the UAP of RSIs. Firstly, the former is used to generate the UAP, which can learn the distribution of perturbations better, and then the latter is used to find the sensitive regions concerned by the RSI classification model. Finally, the generated regions are used to fine-tune the perturbation making the model misclassified with fewer perturbations. The experimental results show that the UAP can make the classification model misclassify, and the attack success rate of our proposed method on the RSI data set is as high as 97.09%. |
14,109 | Please write an abstract with title: The part of statistical considerations in the separation of a signal masked by a noise, and key words: Filtering, Integral equations, Filters, Probability, Signal analysis, Information theory, Upper bound, Polynomials, Tin, Stochastic resonance. Abstract: The object of this paper is to demonstrate that the stochastic considerations presently involved in signal detections are purely descriptive and are not sufficiently developed to reach the proposed aim. |
14,110 | Please write an abstract with title: What Are PVDF-Based Backsheets Made Of?, and key words: Degradation, Photovoltaic systems, Uncertainty, Films, Aging, Polymers, Stress. Abstract: It is important to have a deep knowledge of a material's formulation to understand the degradation mechanisms taking place when the materials are exposed to external stresses. In the last years, cracking of backsheets with polyvinylidene fluoride (PVDF) has become an issue. PVDF based backsheets are widely used, but there is still quite some uncertainty regarding their exact formulation and the mechanisms behind the degradation. In this study seven PVDF films were investigated to get a deeper knowledge regarding their formulations and their principal properties. |
14,111 | Please write an abstract with title: Shallow Donors in Transmutation-Doped GaAs in High Magnetic Field, and key words: Germanium, Silicon, Magnetic fields, Temperature measurement, Neutrons, Magnetic field measurement, Gallium arsenide. Abstract: Germanium and selenium donors have been created in n-GaAs by neutron capture. Line shapes and positions of shallow hydrogenic 1s to 2p (m= -1) donor transitions are studied by Fourier transform spectroscopy and are identified. |
14,112 | Please write an abstract with title: Research on learning vocabulary test system under computer big data technology, and key words: Resistance, Vocabulary, Education, Memory management, Learning (artificial intelligence), Big Data, Market research. Abstract: The application of computer big data technology in education is an inevitable technology trend leading to educational reform. The wide application of big data technology has brought new development opportunities to English learning, and big data technology has enriched the ways and means of English professional vocabulary learning. Therefore, the English vocabulary test system driven by big data has become one of the essential topics in the current education reform and the cultivation of high-quality professionals. English learning and vocabulary testing have always been the bottleneck in English learning. We must use the big data platform to provide timely and accurate data and an accurate teaching system to break this bottleneck. This paper has some enlightenment effects on English Vocabulary learning from the background of the times, vocabulary learning mode and practice, application conditions of a test system, theory, and test items. |
14,113 | Please write an abstract with title: Deep Image Sensing and Retrieval Using Suppression, Scale Spacing and Division, Interpolation and Spatial Color Coordinates With Bag of Words for Large and Complex Datasets, and key words: Feature extraction, Image color analysis, Detectors, Visualization, Shape, Image retrieval. Abstract: Intelligent and efficient image retrieval from versatile image datasets is an inevitable requirement of the current era. Primitive image signatures are vital to reflect the visual attributes for content based image retrieval (CBIR). Algorithmically descriptive and well identified visual contents form the image signatures to correctly index and retrieve similar results. Hence feature vectors should contain ample image information with color, shape, objects, spatial information perspectives to distinguish image category as a qualifying candidate. This contribution presents a novel features detector by locating the interest points by applying non-maximum suppression to productive sum of derivative of pixels computed from differential of corner scores. The interest points are described by applying scale space interpolation to scale space division produced from Hessian blob detector resulted after Gaussian smoothing. The computed shape and object information is fused with color features extracted from the spatially arranged L2 normalized coefficients. High variance coefficients are selected for object based feature vectors to reduce the massive data which in fuse form transformed to bag-of-words (BoW) for efficient retrieval and ranking. To check the competitiveness of the presented approach it is experimented on nine well-known image datasets Caltech-101, ImageNet, Corel-10000, 17-Flowers, Columbia object image library (COIL), Corel-1000, Caltech-256, tropical fruits and Amsterdam library of textures (ALOT) belong to shape, color, texture, and spatial & complex objects categories. Extensive experimentation is conducted for seven benchmark descriptors including maximally stable extremal region (MSER), speeded up robust features (SURF), difference of Gaussian (DoG), red green blue local binary pattern (RGBLBP), histogram of oriented gradients (HOG), scale invariant feature transform (SIFT), and local binary pattern (LBP). Remarkable outcomes reported that the presented technique has significant precision rates, recall rates, average retrieval precision & recall, mean average precision & recall rates for many image semantic groups of the challenging datasets. Results comparison is presented with research techniques and reported improved results. |
14,114 | Please write an abstract with title: Zero-error rule induction using a memetic algorithm, and key words: Memetics, Machine learning, Task analysis, Semantics, Standards, Optimization, Heuristic algorithms. Abstract: Rule induction in traditional machine learning (ML) concentrates on finding rules that minimize error to produce high accuracy through a trade-off between sensitivity and specificity. But what if the machine learning task is to produce minimal length rules with zero error (the error-free ML optimization problem)? In its most basic form, the problem can be recast as reverse-engineering the syntactically-minimal well-formed formula (wff) that correctly covers all rows of a given Boolean truth table. The main problem for evolutionary approaches to zeroerror rule induction is the design of a suitable fitness function to cope with a search landscape that is not amenable to hillclimbing. In this paper we demonstrate how using the ratio of true to false rows in the truth table can be used as a heuristic to guide a memetic algorithm for exploring and exploiting the search for zero-error, syntactically minimal wffs in randomly generated truth tables for up to 12 variabes. The search depth of candidate solutions is determined by the number of variables in the data and the size of a solution is allowed to increase as long as its coverage improves. Significant differences in solution size were found depending on the ratio of true to false values in the data. The results provide a basis for further formalization and development of zero-error rule induction if ML is to be used confidently in safety critical situations where no error in induced rules is permissible. |
14,115 | Please write an abstract with title: A Novel Home Energy Management System Environmental-based with LCA Minimization, and key words: Energy management, Batteries, Carbon dioxide, Linear programming, Electrical engineering, Meteorology, Greenhouse effect, Climate change. Abstract: This paper presents a novel environmental-based home energy management system that focuses on the environmental impact caused by residential electricity consumption. It is aimed to reduce the carbon footprint by minimizing the kg of carbon dioxide equivalent, considering all the stages of the life cycle of the generation sources utilized, from cradle-to-grave. The global warming potential indicator is chosen to decide if it is more sustainable to purchase electricity from the grid or to use flexible generation sources at homes, such as batteries or photovoltaic generation. The environmental-base energy management system endeavors to give the end-user a more influential role in the climate change solution, giving up the reduction of the electricity bill in exchange for causing a low environmental impact by minimizing its greenhouse gas (GHG) emissions. The results prove that in periods of significant penetration of renewable sources in the energy mix, it is more sustainable to buy electricity from the grid than discharging batteries or using the photovoltaic surplus energy to charge them. The proposed environmental-based energy management system reduces the GHG emissions by 38% compared with the price-based program, which prioritizes the minimization of energy costs. |
14,116 | Please write an abstract with title: Automatic Sleep Stage Scoring on Raw Single-Channel EEG : A comparative analysis of CNN Architectures, and key words: Sleep, Pipelines, Computer architecture, Benchmark testing, Brain modeling, Electroencephalography, Sleep apnea. Abstract: The significance of sleep in sustaining mental and physiological equilibrium, as well as the relationship between sleep disturbance and disease and death, has long been accepted in medicine. Deep Learning methods have provided State Of The Art performance in tackling numerous challenges in the medical arena since the advent of the domain of HealthTech. Polysomnography is a type of sleep study that uses electroen-cephalogram (EEG) measurements, among other parameters, to get a better picture of a patient’s sleep patterns. Various brain activity correspond to different stages of sleep. Monitoring and interpreting EEG signals and the body’s reactions to the changes in these cycles can help identify disruptions in sleep patterns. Successfully classified sleep patterns can in turn help medical professionals with the prognosis of several pervasive sleep related diseases like sleep apnea and seizures. To address the pitfalls associated with the traditional manual review of EEG signals that help classify sleep stages, in this work, several Convolutional Neural Networks were trained and analysed to classify the five phases od sleep (Wake, N1, N2, N3, N4 and REM by AASM’s standard) using data from raw, single channel EEG signals. With PhysioNet’s Sleep-EDF dataset, this comparative analysis of the performance of popular convolutional neural network architectures can serve as a benchmark to the problem of utilizing EEG data to classify sleep stages. The analysis shows that CNN based methods are adept at extracting and generalizing temporal information, making it suitable for classifying EEG based data. |
14,117 | Please write an abstract with title: Design of Path Tracking Control for Wheeled Mobile Robots Based on Model Predictive Control, and key words: Autonomous systems, Roads, Friction, Force, Kinematics, Predictive models, Robustness. Abstract: The path tracking control is investigated in this paper using a four-wheeled robot kinematical model and tube-based model predictive control. Simultaneously, in order to improve the robustness, the steering angle calculated by the model predictive controller is converted into the corresponding expected yaw rate through the vehicle kinematical model, owing to the better control effect of the cascade control. To track the expected yaw rate, we use a basic PID controller. By combining the PID controller and the model predictive controller, the path tracking controller bridges the gap between theoretical results and their applications for four-wheeled robot tracking control. |
14,118 | Please write an abstract with title: Real-Time Parameter Estimation of a Fuel Cell for Remaining Useful Life Assessment, and key words: Real-time systems, Estimation, Integrated circuit modeling, Stability analysis, Computational modeling, Thermal stability, Convergence. Abstract: This article presents a real-time parameter estimation of a proton exchange membrane fuel cell (PEMFC). The proposed strategy estimates online the PEMFC's resistance, since it is directly correlated to its remaining useful life assessment. The estimation of the PEMFC's parameters is a difficult task to undertake due to various uncertainties, like temperature and aging, that lead to a drift in parameters and limit the performance of the overall energy system. Therefore, online system identification is essential to track online the PEMFC's time-varying parameters. Unlike other identification techniques, the proposed strategy is based on a simple yet accurate PEMFC's model and adjusts its parameters in real-time using a Lyapunov-based adaptation law, which yields guaranteed stability. Experiments are conducted on a 500-W Horizon PEMFC and results along with a comparison against the well-known Kalman filter highlight the effectiveness of the proposed approach, which is instrumental for its numerous applications, such as the energy management of hybrid fuel cell vehicles. |
14,119 | Please write an abstract with title: A New Stegano-Cryptographic Approach for Enhancing Text Data Communication Security, and key words: Computers, Steganography, Portable computers, Media, Robustness, Internet, Encryption. Abstract: As the use of smartphones, laptops, and computers grows, these devices have become indispensable in our daily lives. We are exchanging a great deal of data via the Internet. Many of this data are very confidential, which include banking credentials, national secrets, and defence strategy, among other things. Steganography and cryptography are two fundamental areas of security that deal with delivering information or data via media like the Internet. Steganography is known as concealing information in a message, while cryptography is the method of encrypting the message. They are both utilized to keep things safe. However, none of them can easily meet the basic security requirements, such as robustness, undetectability etc. As a result, a new technology known as Stegano-Cryptography is being developed, which combines steganography with cryptography to overcome each other's shortcomings and make it harder for attackers to assault or steal important information. This paper proposes a new method where a text is first turned into a stego object using a suitable steganographic technique, and then the stego object is encrypted using the AES encryption algorithm. Thus, this approach can enhance the security of text data communication. |
14,120 | Please write an abstract with title: A Lightweight Model with Separable CNN and LSTM for Video Prediction, and key words: Deep learning, Performance evaluation, Solid modeling, Three-dimensional displays, Uncertainty, Computational modeling, Predictive models. Abstract: Future frame prediction is an emerging, yet challenging task in the deep learning field due to its inherent uncertainty and complex spatiotemporal dynamics. The state-of-the-art methods achieve significant accuracy at the expense of complex, computationally intensive deep neural networks, which makes it difficult to deploy in mobile devices. In the light of recent wide popularity of Green AI which aims for efficient environment friendly solutions alongside accuracy, we propose a lightweight model using 3D separable convolutions, which can predict future video frames with reduced model size and reasonable accuracy-complexity tradeoffs as compared to the state-of-the-art methods. |
14,121 | Please write an abstract with title: Towards a Data-Driven Fuzzy-Geospatial Pandemic Modelling, and key words: Data models, Pandemics, Uncertainty, Predictive models, COVID-19, Fuzzy systems, Fuzzy logic. Abstract: The current Covid-19 worldwide outbreak has many lessons to be learned for the future. One area is the need for more powerful computational models that can support making better decisions in controlling future possible outbreaks, particularly when being made under uncertainties and imperfections. Motivated by the rich data being daily generated during the pandemic, our focus is on developing a data-driven model, not primarily relying on the mathematical epidemiology techniques. By investigating the implications of the current pandemic data, we propose a fuzzy-geospatial modelling approach, in which uncertainties and linguistic descriptions of data, some of which being geo-referenced, are handled by non-singleton fuzzy logic systems. In this paper, we outlining a conceptual model designed to be trained by the available pandemic worldwide data, and to be used to simulate the effect of an enforced controlling measure on the geographical extent of the infection. This can be considered as an uncertain decision support systems (UDSS) in controlling the pandemic in the future outbreaks. |
14,122 | Please write an abstract with title: Development and Verification of a 3 - DOF Trailer Model for Truck Vehicles, and key words: Mathematical model, Tires, Roads, Acceleration, Differential equations, Software, Wheels. Abstract: This paper presents the development of 3-DOF trailer model connected to Calspan tyre model. The mathematical models are simulated in that MATLAB-SIMULINK software. The hitch model is derived using differential equation based on the truck responses in longitudinal, lateral and yaw directions. The trailer model is tested in simulation for single lane and double lane change tests at two different speeds 60 km/h and 80 km/h, and followed by verification process using TruckSim software. Verification results showed a good response with acceptable error in simulated model. |
14,123 | Please write an abstract with title: Design and Experimental Validation of an Augmented Reality System With Wireless Integration for Context Aware Enhanced Show Experience in Auditoriums, and key words: Wireless communication, Wireless sensor networks, Visualization, Auditory system, Wireless fidelity, Three-dimensional displays, User experience. Abstract: The development of multiple cultural and social related activities, such as shows related with the performing arts, conferences or presentations rely on facilities such as auditoriums, theatres and conference sites, which are progressively including multiple technological features in order to enhance user experience. There are still however situations in which user experience is limited owing to lack of environment adaption, such as people with disabilities. In this sense, the adoption of Context Aware paradigms within auditoriums can provide adequate functionalities in order to comply with specific needs. This work is aimed at demonstrating the feasibility in enhancing user experience (e.g., improving the autonomy of disabled people) within auditorium and theatre environments, by means of an Augmented Reality (AR) device (HoloLens smart glasses) with wireless system integration. To carry out the demonstration, different elements to build AR applications are described and tested. First, an intensive measurement campaign was performed in a real auditorium in the city of Pamplona (Baluarte Congress Center) in order to evaluate the feasibility of using Wi-Fi enabled AR devices in a complex wireless propagation scenario. The results show that these environments exhibit high levels of interference, owing to the co-existence and non-coordinated operation of multiple wireless communication systems, such as on site and temporary Wi-Fi access points, wireless microphones or communications systems used by performers, staff and users. Deterministic wireless channel estimation based in volumetric 3D Ray Launching have been obtained for the complete scenario volume, in order to assess quality of service metrics. For illustration purposes, a user-friendly application to help hearing impaired people was developed and its main features were tested in the auditorium. Such an application provides users with a 3D virtual space to visualize useful multimedia content like subtitles or additional information about the show, as well as an integrated call button. |
14,124 | Please write an abstract with title: Hierarchical segmentation of cervical and lumbar vertebrae using a customized generalized Hough transform and extensions to active appearance models, and key words: Spine, Image edge detection, Active appearance model, Image segmentation, X-ray imaging, Biomedical imaging, Shape, Robustness, Radiography, Image analysis. Abstract: The paper describes a semi-automatic segmentation method for application to cervical and lumbar X-ray images. The method consists of a three stage, coarse to fine, segmentation process utilizing the generalised Hough transform for one stage, and active appearance models for two stages. Customizations to these algorithms are introduced, and segmentation results for 273 cervical X-ray images and 262 lumbar X-ray images are presented. |
14,125 | Please write an abstract with title: Constrained RF Level Interpolation for Normalized Cross Correlation Based Speckle Tracking, and key words: Radio frequency, Interpolation, Correlation, Estimation, Speckle, Frequency estimation, Strain. Abstract: Speckle tracking by normalized cross correlation (NCC) requires subsample accuracy for effective strain estimation. Without this, low displacement causes quantized images that result in unusable strain maps. Doppler methods work well on small displacement, however they operate very poorly on large displacement data where they are prone to aliasing. When manually palpating the medium, it is difficult to maintain a constant deformation rate and pressure, resulting in a mixture of large and small displacement data throughout a total data set. This paper presents the Constrained Radio Frequency method (CRF) of speckle tracking. This method uses the correlation gradients at the sample level to constrain the subsample search region such that the RF data can be interpolated to accurately estimate displacement with subsample precision. Simulated and experimental data sets are used to estimate displacement and strain to compare the CRF method to NCC speckle tracking and the Loupas algorithm doppler technique. The CRF is the most accurate method at estimating displacement and generates strain estimates with higher contrast to noise ratios (CNR) compared to the other methods tested. |
14,126 | Please write an abstract with title: High-performance InGaP power HBT technologies for wireless applications, and key words: Heterojunction bipolar transistors, Power amplifiers, High power amplifiers, Fingers, MMICs, Feedback circuits, Linearity, Electrodes, Power generation, Wide area networks. Abstract: We review the technological features of our InGaP power HBTs for 5GHz wireless application. The features include self-aligned base-contact and base-mesa formation process, small-sized via holes located between multi-finger transistors, and bias and feedback circuits for the reduction of distortion. These technologies improve both gain and linearity, producing higher power added efficiency (PAE) in power amplifiers. |
14,127 | Please write an abstract with title: A Multi-Robot Coverage Path Planning Algorithm for the Environment With Multiple Land Cover Types, and key words: Robot kinematics, Task analysis, Approximation algorithms, Visualization, Classification algorithms, Clustering algorithms. Abstract: Many scholars have proposed different single-robot coverage path planning (SCPP) and multi-robot coverage path planning (MCPP) algorithms to solve the coverage path planning (CPP) problem of robots in specific areas. However, in outdoor environments, especially in emergency search and rescue tasks, complex geographic environments reduce the task execution efficiency of robots. Existing CPP algorithms have hardly considered environmental complexity. This article proposed an MCPP algorithm considering the complex land cover types in outdoor environments to solve the related problems. The algorithm first describes the visual fields of the robots in different land cover types by constructing a hierarchical quadtree and builds the adjacent topological relations among the cells in the same and different layers in the hierarchical quadtree by defining shared neighbor direction based on Binary System. The algorithm then performs an approximately balanced task assignment to the robots considering the moving speeds in different land cover types using the azimuth trend method we proposed to ensure the convergence of the task assignment process. Finally, the algorithm improves Spanning Tree Covering (STC) algorithm to complete the CPP in the area where each robot belongs. This study used a classification image of the real outdoor environment to the verification of the algorithm. Results show that the coverage paths planned by the algorithm are reasonable and efficient and its performance has obvious advantages compare with the current mainstream MCPP algorithm. |
14,128 | Please write an abstract with title: Downsampling of EEG Signals for Deep Learning-Based Epilepsy Detection, and key words: Sensor signal processing, convolutional neural network (CNN), deep learning, downsampling, epilepsy. Abstract: Deep learning-based methods have achieved state-of-the-art accuracy in epileptic seizure detection. However, the high computational demands of deep neural networks pose a significant challenge for implementing epilepsy detection in wearable sensing devices. Existing approaches primarily focus on model lightweighting to reduce the computational burden. This letter, on the other hand, approaches the reduction of inference complexity of deep learning models from a fresh perspective: downsampling of electroencephalogram (EEG) signals. Three types of downsampling methods are presented: direct downsampling, compressed downsampling, and convolutional downsampling. The downsampled EEG signals are directly fed to the deep neural network for seizure detection. Experimental results using the CHB-MIT scalp EEG dataset show that the proposed downsampling methods greatly reduce the computational complexity without sacrificing the detection accuracy. The reduction of computational complexity is nearly proportional to the downsampling factor. In the cases with small to medium downsampling factors, most of the proposed downsampling methods can even improve the seizure detection accuracy. |
14,129 | Please write an abstract with title: A 72GS/s, 8-bit DAC-based Wireline Transmitter in 4nm FinFET CMOS for 200+Gb/s Serial Links, and key words: Transmitters, OFDM, Modulation, Linearity, Bandwidth, Very large scale integration, FinFETs. Abstract: A DAC-based SST transmitter for wireline applications is reported in a 4nm FinFET technology. 8b resolution and high analog output bandwidth (BW) are achieved by employing a segmented architecture along with a single-ended LSB. Hybrid analog/digital tuning is used in the DAC LSB segments, resulting in well-matched MSB/LSB segments with -0.63/0.67 LSB INL and -0.16/0.43 LSB DNL. 216Gb/s PAM8 and 212Gb/s QAM64 OFDM operation are demonstrated at 288mW from a 0.95V supply. |
14,130 | Please write an abstract with title: Research On Ferromagnetic Resonance Overvoltage Based On Station Service Voltage Transformers, and key words: Inductance, Ferromagnetic resonance, Circuit faults, Windings, Capacitance, RLC circuits, Integrated circuit modeling. Abstract: Station Service Voltage Transformers (SSVT) combines the operating characteristics of power transformers and the design characteristics of measuring voltage transformers. Due to its lower initial cost and higher power supply reliability, its applications have been extended beyond that of auxiliary power. During transient events in the network caused by the operation of switching equipment or short circuits, the transformers are affected by the oscillating voltage, which, under certain conditions, can cause resonance overvoltage inside their windings. Based on the ATP-EMTP platform, the ferromagnetic resonance of SSVT is simulated and its simulation model, simulation algorithm, and waveform are analyzed. Based on the simulation analysis results, this paper puts forward the preventive measures of transformer ferromagnetic resonance from the perspective of voltage harmonics and insulation coordination. |
14,131 | Please write an abstract with title: Erratum to “A Smoothed Raster Scanning Trajectory Based on Acceleration-Continuous B-Spline Transition for High-Speed Atomic Force Microscopy” [Feb 21 24-32], and key words: Atomic force microscopy, Smoothing methods, Splines (mathematics), Piezoelectric devices. Abstract: The affiliations of Linlin Li, Jie Huang, and Sumeet S. Aphale, authors of the above-named article [ibid., vol. 26, no. 1, pp. 24–32, Feb. 2021] are corrected here. |
14,132 | Please write an abstract with title: Forensic Event Reconstruction for Drones, and key words: Seminars, Sentiment analysis, Forensics, Directed graphs, Reconstruction algorithms, Intelligent systems, Information technology. Abstract: Event reconstruction is one of the forensic processes used to determine and reconstruct event sequences of cyberse-curity attacks or incidents. In drone forensics, existing research focuses on artifact extraction and analysis. Therefore, in this paper, we propose an event reconstruction method for drones using a directed graph representation. The sentiment analysis technique is used to investigate any events of interest that have been represented as graph vertices. Experimental results on drone public datasets indicate that the proposed method can reconstruct events and show the suspicious activities of a drone to assist in an investigation. |
14,133 | Please write an abstract with title: Allometric Relationships Between Above-Ground Biomass and Lidar Full Waveform Measurements - Potential Applications for Global Ecosystem Dynamics Investigation (GEDI) Mission, and key words: Biomass, Forestry, Laser radar, Vegetation, Indexes, Measurement, Vegetation mapping. Abstract: To reduce the site-dependent calibration effort for large scale above-ground biomass density (AGBD) estimation using the Ecosystem Dynamics Investigation (GEDI) lidar measurements, this study investigates the allometric relationship between the lidar waveform measurements and ABGD in forests with different ecosystem structure characteristics. We developed a biomass index directly from full waveform measurements. This index shows a consistent linear relationship with AGBD in different forest biomes. The index explains 87% of biomass variation (R2 ~ 0.87). For regions with relative narrow range of above-ground biomass, the index has similar performance with lidar height metrics. However it significantly outperforms the commonly used lidar height metrics for forests with large variations of vegetation structure and above-ground biomass range. The results indicate intrinsic allometric relationships between forest ABGD and lidar full waveform data. This index has a great potential to map large scale above-ground biomass using the GEDI measurements. |
14,134 | Please write an abstract with title: An FPGA based co-processor for GLCM texture features measurement, and key words: Field programmable gate arrays, Coprocessors, Feature extraction, Image analysis, Image texture analysis, Statistical analysis, Image classification, Image segmentation, Remote sensing, Acceleration. Abstract: Gray Level Co-occurrence Matrix (GLCM), one of the best known texture analysis methods, estimates image properties related to second-order statistics. These image properties commonly known as texture features can be used for image classification, image segmentation, and remote sensing applications. In this paper, we present an FPGA based co-processor to accelerate the extraction of texture features from GLCM. Handel-C, a recently developed C-like programming language for hardware design, has been used for the FPGA implementation of GLCM texture features measurement. Results show that the FPGA has better speed performances when compared to a general purpose processor for the extraction of GLCM features. |
14,135 | Please write an abstract with title: Looking Into a Future Which Hopefully Will Not Become Reality: How Computer Graphics Can Impact Our Behavior—A Study of the Potential of VR, and key words: Games, Visualization, Human factors, Behavioral sciences, Sustainable development, Virtual realty. Abstract: Humans tendency to engage in behaviors that are harmful to themselves, the environment, and the society has always been present on a personal and collective level. However, the concern for this kind of phenomena is increasing, as demographic and economic growth is amplifying its impact on people health, economies, and ecosystems. As a consequence, we have seen the rise of research fields as design for behavior change, with a growing interest in the use of tools as persuasive technologies, serious games and interactive systems to affect people awareness, attitude, and behavior. To these purposes, computer graphics and especially virtual reality (VR) has great potential since it can provide experiences to deepen users’ understanding and emotional involvement regarding a variety of social and environmental issues. Here, we discuss the use of VR as a powerful, versatile, and cost-effective tool to deliver virtual experiences that inform and motivate users to change behavior. We describe and relate different aspects regarding sustainable behavior and VR experience design with respect to their potential to support behavior change. |
14,136 | Please write an abstract with title: Bitcoin's Adoption as Legal Tender: A Tale of Two Developing Countries, and key words: Law, Bitcoin, Developing countries. Abstract: The Central African Republic and El Salvador are the only two countries in the world that have adopted bitcoin as legal tender. This article examines the stated motivations of bitcoin's adoption as a legal tender in these two countries and looks at their implementation strategies. |
14,137 | Please write an abstract with title: Robust and cost-efficient group communication using overlay multicast in mobile ad hoc networks, and key words: Robustness, Mobile communication, Intelligent networks, Mobile ad hoc networks, Unicast, Communication system control, Classification tree analysis, Multicast protocols, Computer science, Adaptive systems. Abstract: Previous multicast schemes for MANET (mobile ad hoc networks) are mostly classified as tree-based schemes and mesh-based schemes depending on their multicast delivery structure. Tree-based schemes cannot cope with network mobility due to frequent tree reconfiguration. On the other hand, mesh-based schemes waste unnecessary resource due to delivery along multiple paths. We propose to use an overlay multicast to handle network mobility efficiently with minimized resource. In our scheme, DDT (data delivery tree) can remain static as long as unicast route between members that are related to data forwarding remains reachable. Thus, it can not only minimize the effects of network mobility, but also bring about low additional control overhead. Such distinct advantages are specifically evaluated through the results of the simulation. |
14,138 | Please write an abstract with title: Secrecy Performance Analysis of Mixed-ADC/DAC Cell-Free Massive MIMO in the Presence of Multiple Eavesdroppers, and key words: Massive MIMO, Quantization (signal), Antennas, Power control, Downlink, Channel estimation, Uplink. Abstract: This paper studies the secrecy performance of the cell-free massive multi-input multi-output (MIMO) system, where access points (APs) are equipped with a mixed analog-to-digital converter (ADC) and digital-to-analog converter (DAC) architecture. The distributed antenna structure is prone to multiple eavesdropping network threats. Specifically, legitimate transmissions can be affected by non-colluding and colluding eavesdroppers. Based on the above considerations, we determine the expressions of the sum achievable secrecy rate and secrecy energy efficiency (SEE) with applications of the additive quantization noise model and the conjugate performing precoding method. These provide the composite measures to analyze the effects of the mixed-ADC/DAC architecture on secrecy performance. We also propose a SEE-maximization power control (SEEMPC) scheme, which can be solved by the sequential convex approximation algorithm. In addition to verifying the effectiveness of the proposed SEEMPC algorithm, numerical simulations are carried out to evaluate the impact of some key design parameters, including the number of APs, quantization bit of coarse ADCs/DACs, ratio of ideal ADCs/DACs, and power control strategy. |
14,139 | Please write an abstract with title: Now you see it and now you don't [RFID technology], and key words: Radiofrequency identification, Privacy, RFID tags, Radio frequency, Transponders, Batteries, Electromagnetic heating, Food technology, Jamming, Microwave technology. Abstract: This paper reports on radiofrequency identification technology and several possible approaches to protect consumer privacy in the context of RFID. |
14,140 | Please write an abstract with title: Wavelet-based image processing: edge detection and noise reduction, and key words: Image processing, Image edge detection, Noise reduction, Wavelet coefficients, Discrete wavelet transforms, Radar imaging, Filtering, Data mining, Airborne radar, Wavelet domain. Abstract: A novel wavelet-based algorithm for radar image processing is proposed. The algorithm is based on a representation of image edges with template wavelet coefficients. Edge enhancement, noise reduction, and image object extraction capabilities of the proposed algorithm are discussed. The algorithm has been used to process data obtained with a dual frequency 36 and 95 GHz airborne side-looking radar. |
14,141 | Please write an abstract with title: Wave propagation in the atrial myocardium: dispersion properties in the normal state and before fibrillation, and key words: Myocardium, Fibrillation, Resonance, Electrodes, Microscopy, Signal analysis, Frequency, Biomedical engineering, Heart rate, Humans. Abstract: The formalism of wave propagation in passive media is applied to the spread of the electrical excitation in the human atrial myocardium. From an analog of the classical dispersion dependence that is obtained by wavelet decomposition a precursor parameter is calculated that serves to predict fibrillation already before its onset. |
14,142 | Please write an abstract with title: PeR-ViS: Person Retrieval in Video Surveillance using Semantic Description, and key words: Computer vision, Image segmentation, Image color analysis, Filtering, Conferences, Semantics, Video surveillance. Abstract: A person is usually characterized by descriptors like age, gender, height, cloth type, pattern, color, etc. Such descriptors are known as attributes and/or soft-biometrics. They link the semantic gap between a person's description and retrieval in video surveillance. Retrieving a specific person with the query of semantic description has an important application in video surveillance. Using computer vision to fully automate the person retrieval task has been gathering interest within the research community. However, the Current, trend mainly focuses on retrieving persons with image-based queries, which have major limitations for practical usage. Instead of using an image query, in this paper, we study the problem of person retrieval in video surveillance with a semantic description. To solve this problem, we develop a deep learning-based cascade filtering approach (PeR-ViS), which uses Mask R-CNN [14] (person detection and instance segmentation) and DenseNet-161 [16] (soft-biometric classification). On the standard person retrieval dataset of SoftBioSearch [6], we achieve 0.566 Average IoU and 0.792 %w IoU > 0.4, surpassing the current state-of-the-art by a large margin. We hope our simple, reproducible, and effective approach will help ease future research in the domain of person retrieval in video surveillance. The source code will be released after the paper is accepted for publication with base-line and pretrained weights. The source code and pre-trained weights available at https://parshwa1999.github.io/PeR-ViS/. |
14,143 | Please write an abstract with title: Online Prediction of DGA Results for Intelligent Condition Monitoring of Power Transformers, and key words: Gases, Oils, Oil insulation, Predictive models, Real-time systems, Power transformers, Circuit faults. Abstract: Transformers form a major part of a power system in transmission as well as distribution of power. Considering the criticality, finance, and time involved in repair, periodic condition monitoring and maintenance of transformers are the key to ensure electrical safety as well as stable operation of the large interconnected power system. Dissolved Gas Analysis (DGA) is an established tool used to determine the incipient faults within the transformer by analyzing the concentration of different gases in the transformer oil and giving early warnings and diagnoses. Currently, transformers worldwide utilise online sensors to monitor dissolved gases and moisture content in oil. The online DGA sensor uses a small amount of oil from transformer to perform real-time DGA analysis and gives the ppm content of dissolved gases for further course of action. Considering the large quantity of assets and the huge amount of data produced, it is imperative to develop a tool to aid the operators in assimilating the available data for diagnosis and proactive decision making. The present study improvises AI techniques to predict future dissolved gas concentrations using real time DGA data collected from the transmission utility of the country. The prediction helps to forecast the trend of development of incipient faults in the transformer. The complete project scope is to develop a highly reliable diagnostic tool to emulate the decision-making ability of a human expert in transformer DGA analysis to enhance transformer life. In the present paper, models based on Auto-regressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), and Vector Auto Regression (VAR) are implemented to predict DGA data of three in-service transformers. DGA data is forecasted for up to 8 monthly samples in the future, and the accuracy of results is compared with each other. The LSTM-VAR combined model is seen to provide the best results among them. |
14,144 | Please write an abstract with title: Work in progress - the WSU model for engineering mathematics education, and key words: Mathematical model, Mathematics, Calculus, Biomedical engineering, Computer science, Computer science education, Switches, Differential equations, Biological materials, Biomedical materials. Abstract: This paper summarizes progress to date on the WSU model for engineering mathematics education, an NSF funded curriculum reform initiative at Wright State University. The WSU model seeks to increase student retention, motivation and success in engineering through application-driven, just-in-time engineering math instruction. The WSU approach involves the development of a novel freshman-level engineering mathematics course EGR 101, as well as a large-scale restructuring of the engineering curriculum. By removing traditional math prerequisites and moving core engineering courses earlier in the program, the WSU model shifts the traditional emphasis on math prerequisite requirements to an emphasis on engineering motivation for math, with a just-in-time structuring of the new math sequence. This paper summarizes the development to date of the WSU model for engineering mathematics education, including a preliminary assessment of student performance and perception during the initial implementation of EGR 101. In addition, an assessment of first-year retention results is anticipated in time for the conference. |
14,145 | Please write an abstract with title: Big Data Security and Privacy Implementation: The way Ahead, and key words: Data privacy, Privacy, Companies, Machine learning, Big Data, Internet, Safety. Abstract: Due to the rapid advancement in ICT has made technology to become an essential necessity in most areas of life. The volume of information recorded in data warehouses in the past is starting to grow rapidly over time. Thus the condition of storing information has to change at the same rate in order to reflect such vast growth, and new opportunities for increasing its volume must evolve. The most actively topic by many global information technology companies is big data. At present and in the future as anticipated, one of the engines for the development of information technology is big data. It is due to the fact that a huge amount of information has begun to accumulate for all Internet users. With the advent of global computer networks, particularly the Internet, access to information has been greatly simplified, which has led to an increase in the threat of data security breaches in the absence of measures to protect them. The aim of this research is to investigate the approaches that can be adapted in order to secure such a vast amount of information that is accumulated from Big data. The paper is divided into five sections; including the introduction, issues associated with privacy and security, requirements for data privacy is also highlighted. The consequences of losing privacy are also described. Security problems and decisions are also presented and the conclusion summarizes our findings of the topics associated with big data security challenges. |
14,146 | Please write an abstract with title: HL-Pow: A Learning-Based Power Modeling Framework for High-Level Synthesis, and key words: Power demand, Hardware, Field programmable gate arrays, Estimation, Training, Power measurement, Feature extraction. Abstract: High-level synthesis (HLS) enables designers to customize hardware designs efficiently. However, it is still challenging to foresee the correlation between power consumption and HLS-based applications at an early design stage. To overcome this problem, we introduce HL-Pow, a power modeling framework for FPGA HLS based on state-of-the-art machine learning techniques. HL-Pow incorporates an automated feature construction flow to efficiently identify and extract features that exert a major influence on power consumption, simply based upon HLS results, and a modeling flow that can build an accurate and generic power model applicable to a variety of designs with HLS. By using HL-Pow, the power evaluation process for FPGA designs can be significantly expedited because the power inference of HL-Pow is established on HLS instead of the time-consuming register-transfer level (RTL) implementation flow. Experimental results demonstrate that HL-Pow can achieve accurate power modeling that is only 4.67% (24.02 mW) away from onboard power measurement. To further facilitate power-oriented optimizations, we describe a novel design space exploration (DSE) algorithm built on top of HL-Pow to trade off between latency and power consumption. This algorithm can reach a close approximation of the real Pareto frontier while only requiring running HLS flow for 20% of design points in the entire design space. |
14,147 | Please write an abstract with title: Models of metal-poor stars with different initial abundances of C, N, O, Mg, and Si – I. Bolometric corrections derived from new MARCS synthetic spectra and their implications for observed colour–magnitude diagrams, and key words: stars: abundances, stars: evolution, Hertzsprung–Russell and colour–magnitude diagrams, stars: Population II, globular clusters: individual: NGC 6496. Abstract: New, high-resolution MARCS synthetic spectra have been calculated for more than a dozen mixtures of the metals allowing, in turn, for variations in C:N:O, [CNO/Fe], and enhanced abundances of C, O, Mg, and Si. Bolometric corrections (BCs) for many of the broad-band filters currently in use have been generated from these spectra. Due to improved treatments of molecules that involve atoms of C, N, and O, the BCs for UV and blue passbands, in particular, differ substantially from those derived from previous MARCS models. These differences, and the effects on the BCs of varying the abundances of the metals, are shown in a number of instructive plots. Stellar evolutionary grids for −2.5 ≤ [Fe/H] ≤−0.5 have also been computed for the different mixtures. Isochrones based on these tracks are intercompared on the theoretical H–R diagram and on a few of the colour–magnitude diagrams that can be constructed from HST Wide Field Camera 3 (WFC3) F336W, F438W, F606W, F814W, F110W, and F160W observations. For the first application of these models, isochrones have been fitted to WFC3 photometry of the globular cluster NGC 6496 from the HST UV Legacy Survey, with very encouraging results. |
14,148 | Please write an abstract with title: Collaborative Learning for Teaching the Topic “Design of Differentiators and Integrators in MATLAB” in Digital Signal Processing Course, and key words: Learning systems, Leadership, Federated learning, Pandemics, Conferences, Knowledge acquisition, Education. Abstract: The paper presents the use of the collaborative learning approach when teaching the topic “Design of Differentiators and Integrators in MATLAB” in the Course “Digital Signal Processing” during the COVID-19 pandemic. Some issues about digital differentiators and integrators are described in the paper as well as the problems solved by students during the workshops and students' feedback about their satisfaction with this approach. |
14,149 | Please write an abstract with title: The Design and Implementation of a Power Management Solution for Smart Glasses, and key words: Power demand, Power measurement, Power system management, Switches, User interfaces, User experience, Smart glasses. Abstract: This study investigates the power management issues on smart glasses running Android system in order to develop an effective power management solution for wearable smart devices. While considering that CPU, display device, and WakeLocks are the main sources of power consumption that should be managed on Android platforms, this study focuses on managing the power consumption of CPU on smart glasses. The reason is that, based on the features of smart glasses, the much smaller display device and the potentially less misuse of WakeLock do not seem to be the power drains and, therefore, the supplied power is mostly consumed by CPU. The solution developed in this study is presented in the form of a user app (short for application) of power management in order not to directly modify the system internals of Android and to achieve portability. Its implementation takes advantage of the built-in power management mechanism of Android system in order to achieve its functionalities and uses the technique of dynamic messages to assist users in applying, setting up, and saving the desired power plans. The app works by extending the built-in power management functions of the host Android system and imposes no impact on the built-in power governors. For the purpose of enhancing user experience, customized power plans are built as the preset user defined power plans. The settings in these power plans are derived from measuring the real power consumption in common use cases of smart glasses. Compared to the default built-in power plan of Android system, one of the presettings shows power saving close to 20%. |
14,150 | Please write an abstract with title: Anti-Synchronization Control of Fuzzy Inertial Neural Networks with Distributed Time Delays, and key words: Neuromorphic engineering, Delay effects, Neural networks, Delays, Adaptive control, Lyapunov methods. Abstract: This paper investigates the global anti-synchronization control for a class of fuzzy inertial neural networks(FINNs) with distributed time delays. By using Lyapunov stability theory and some inequality techniques, some new results are derived to get global anti-synchronization of the investigated FINNs. The systems considered in this paper are with inertial terms and fuzzy terms, which are more general and meaningful. And we get the global anti-synchronization results directly from the FINNs themselves without the reduced-order method. At last, illustrative examples are given to show the effectiveness of the results. |
14,151 | Please write an abstract with title: Joint audio-video processing for biometric speaker identification, and key words: Biometrics, Speech, Signal processing, Streaming media, Hidden Markov models, Robustness, Multimedia systems, Graphics, Laboratories, Educational institutions. Abstract: In this paper we present a bimodal audio-visual speaker identification system. The objective is to improve the recognition performance over conventional unimodal schemes. The proposed system exploits not only the temporal and spatial correlations existing in speech and video signals of a speaker, but also the cross-correlation between these two modalities. Lip images extracted for each video frame are transformed onto an eigenspace. The obtained eigenlip coefficients are interpolated to match the rate of the speech signal and fused with mel frequency cepstral coefficients (MFCC) of the corresponding speech signal. The resulting joint feature vectors are used to train and test a hidden Markov model (HMM) based identification system. Experimental results are also included for demonstration of the system performance. |
14,152 | Please write an abstract with title: Flexible resource allocation strategy with prioritisation levels, and key words: Resource management, US Department of Transportation, Degradation, Quality of service, Switching circuits, Packet switching, Ground penetrating radar, GSM, Base stations, Hydrogen. Abstract: A new flexible resource allocation (FRA) scheme called flexible resource allocation strategy with prioritised levels (FRASPL) is proposed. FRASPL meets the upper capacity bound for FRA strategies while providing acceptable quality to the admitted request by using degradation and compensation of all active calls. FRASPL can trade-off capacity and QoS. FRASPL is deliberately designed to cope with several service types defining also prioritisation rules that makes it different to the rest of the strategies previously proposed in the literature. |
14,153 | Please write an abstract with title: Transforming Online Learning with CNN and NLP: Personalized Education, and key words: Virtual Learning, Virtual Classroom, Deep Learning, Text Analytics, Easy Learning, Well-being in Education. Abstract: In the rapidly evolving landscape of online education, ensuring easy and healthy learning experiences has become paramount. This research paper presents "Sparkle Edu," an innovative application that integrates multiple components to address the unique challenges of online learning. The components include stress detection through facial emotions and drowsiness analysis, facial authentication with personalized course recommendations, an AI-powered mental health therapist utilizing voice-to-text input, and document reconstruction for damaged images to predict missing letters and words. Through the implementation of these components, Sparkle Edu aims to create an engaging and supportive platform that prioritizes students' well-being and promotes effective learning. This research contributes valuable insights into the advancement of online education, fostering a brighter and more accessible future for learners worldwide. |
14,154 | Please write an abstract with title: Mitigating the Impact of Variability in NCFET-based Coupled-Oscillator Networks Applications, and key words: Performance evaluation, Monte Carlo methods, Neural networks, Field effect transistors, Hopfield neural networks, Information processing, Nanoscale devices. Abstract: Coupled oscillators are attracting increasing interest because of their potential to perform computation efficiently, enabling new applications in computing and information processing. Coupled nano-oscillator implementations using emerging devices have arisen, but the immaturity of these technologies has allowed only simple experimental demonstrations. The potential of Negative Capacitance FET (NCFET) for such applications has recently been recognized, which is a step towards the physical realization given their ease of co-integration with commercial CMOS technologies. However, the design of circuits using these devices can be seriously compromised by the variability inherent in them. In this paper, we will highlight this problem through the design of an oscillatory neural network for pattern recognition applications. We propose the application of subharmonic injection mechanisms to mitigate the impact of NCFET transistor variability and present results showing that the performance of these circuits improves significantly. |
14,155 | Please write an abstract with title: Performance evaluating the evaluator, and key words: Humans, Labeling, Video sequences, Layout, Informatics, Surveillance, Positron emission tomography, Testing, Java, Computer vision. Abstract: When evaluating the performance of a computer-based visual tracking system one often wishes to compare results with a standard human observer. It is a natural assumption that humans fully understand the relatively simple scenes we subject our computers to and because of this, two human observers would draw the same conclusions about object positions, tracks, size and even simple behaviour patterns. But is that actually the case? This paper provides a baseline for how computer-based tracking results can be compared to a standard human observer. |
14,156 | Please write an abstract with title: 3D imaging of microscopic structures using a proton beam, and key words: Particle beams, Ion beams, Computed tomography, Probes, Collimators, Visualization, Optical microscopy, Energy loss, Helium, Imaging phantoms. Abstract: The use of ion beams a few micrometers in diameter as a tomographic probe could constitute a powerful tool for displaying the 3D structure of samples a few tens or hundreds of micrometers thick in a non-destructive way. At CENBG, ion beam micro-tomography has been developed for biomedical applications at the cell level. The combination of STIM and computed tomography gives access to the 3D distribution of density (in g/cm/sup 3/) within the analysed volume. The aim is to explore intracellular micro-structures, the sole preparation required being freeze-drying permitting analysis under vacuum. |
14,157 | Please write an abstract with title: Evaluating Swift-to-Kotlin and Kotlin-to-Swift Transpilers, and key words: Computer languages, Program processors, Codes, Documentation, Software engineering. Abstract: Unlike most popular mobile cross-platform development frameworks, transpilers promise maintainable code bases that are independent of the continued life of the development tools used. As more and more transpiler projects using the native programming languages Kotlin (Android) and Swift (iOS) were presented in recent years, this paper provides an overview of the language coverage of three representative transpilers, Gryphon (Swift-to-Kotlin), Kotlift (Kotlin-to-Swift), and SequalsK (both directions). For the test cases based on the overview chapters of the Swift and Kotlin documentation, good results were obtained in terms of functionality and readability of the output code for Gryphon and SequalsK. Although some shortcomings are visible in all transpilers, Kotlift is classified as a less mature project. |
14,158 | Please write an abstract with title: On New Laplacian Matrix with a User-Assigned Nullspace in Distributed Control of Multiagent Systems, and key words: Laplace equations, Standards, Convergence, Decentralized control, Multi-agent systems, Protocols, Architecture. Abstract: Most distributed control results utilize the benchmark consensus algorithm, which is built on the well-known Laplacian matrix whose nullspace spans the vector of ones. Since this algorithm is the key building block for many distributed control architectures, extensions of this algorithms are also predicated on this Laplacian matrix. To this end, we explore how one can generalize the Laplacian nullspace, which can span any vector with positive elements, to pave the way for composing complex cooperative behaviors in multiagent systems. Specifically, a new Laplacian matrix is introduced for undirected and connected graphs that generalizes the well-known, standard Laplacian matrix, where it is based on a desired, user-assigned nullspace. We first give the mathematical definition of this Laplacian matrix and show that it inherits some fundamental properties of the standard Laplacian matrix. We then present distributed control architectures for convergence to the desired nullspace and for convergence to a specific vector within that nullspace. Finally, an application of the proposed Laplacian matrix to formation tracking and scaling problem is given. |
14,159 | Please write an abstract with title: Longitudinal Short-Period Aircraft Motion Control Under Loadcase Variation, and key words: Atmospheric modeling, Aircraft, Load modeling, Aerospace control, Current measurement, Aerodynamics. Abstract: In this paper, an LPV longitudinal flight controller design is presented, which takes variations of mass and mass distribution into account without the need for additional measurements or estimation of the current loadcase (a certain combination of mass, center of gravity and inertia tensor). This means the loadcase variation is included in the LPV model, but the obtained controller depends on the measurable variations of altitude and airspeed only. Therefore, a technique based on LPV systems with partly-measurable parameters is used. This approach is applied to the control of the short-period dynamic on a model of a small regional aircraft. The obtained controller is evaluated on a more detailed linear model, which takes parts of the real control system into account, as well as within a 6DOF high-fidelity nonlinear simulation environment, which is used to analyze flight controllers before real-life flight tests. |
14,160 | Please write an abstract with title: Confidence-Aware Subject-to-Subject Transfer Learning for Brain-Computer Interface, and key words: Training, Deep learning, Transfer learning, Neural networks, Process control, Brain modeling, Brain-computer interfaces. Abstract: The inter/intra-subject variability of electroencephalography (EEG) makes the practical use of the brain-computer interface (BCI) difficult. In general, the BCI system requires a calibration procedure to tune the model every time the system is used. This problem is recognized as a major obstacle to BCI, and to overcome it, approaches based on transfer learning (TL) have recently emerged. However, many BCI paradigms are limited in that they consist of a structure that shows labels first and then measures "imagery", the negative effects of source subjects containing data that do not contain control signals have been ignored in many cases of the subject-to-subject TL process. The main purpose of this paper is to propose a method of excluding subjects that are expected to have a negative impact on subject-to-subject TL training, which generally uses data from as many subjects as possible. In this paper, we proposed a BCI framework using only high-confidence subjects for TL training. In our framework, a deep neural network selects useful subjects for the TL process and excludes noisy subjects, using a co-teaching algorithm based on the small-loss trick. We experimented with leave-one-subject-out validation on two public datasets (2020 international BCI competition track 4 and OpenBMI dataset). Our experimental results showed that confidence-aware TL, which selects subjects with small loss instances, improves the generalization performance of BCI. |
14,161 | Please write an abstract with title: Machine Learning Aided Performance Estimation in Single Retry/Threshold Loss Models, and key words: Measurement, Deep learning, Machine learning algorithms, Communication systems, Simulation, Computational modeling, Neural networks. Abstract: In this paper, we show that the exploitation of machine learning algorithms can significantly improve the accuracy of estimations in single retry/threshold multi-rate loss systems when it is combined with analytical expressions. In particular, we propose machine learning as a solution only in cases where the analytical solutions are erroneous due to their employed approximations. As a consequence, by using this methodology not only the modelling error can be significantly decreased when it is compared against simulation results but also the computational complexity of the combined solution remains very low. To validate our approach, we exploit seven machine learning algorithms and we examine their improvement for 3000 different operational cases. We show that the absolute relative error can be decreased to below 10% for all four examined metrics when a deep neural network is combined with closed-form expressions. |
14,162 | Please write an abstract with title: A call to action look beyond the horizon, and key words: Data privacy, Computer security, Usability, Software design, Data security, Computer architecture, Software engineering, Computer bugs, Software maintenance. Abstract: Today's most prevalent and widely discussed attacks exploit code-level flaws such as buffer overruns and type-invalid input. Now we should turn to tomorrow's attacks, and think beyond buffer overruns, beyond code-level bugs, and beyond the horizon. This article is a call to arms to the research community to look toward the future. The author outlines a few suggestions for important research directions: software design, usability, and privacy. He argues that if we can make any progress on the first two, we could make a strong impact. He highlights the third topic because he thinks it deserves more attention from the scientific and technical communities, to complement the attention it already receives from the policy and legal communities. Because of the author's background in software engineering, he elaborates more on the first research direction than the other two, but believes all three deserve equal attention. |
14,163 | Please write an abstract with title: Challenges in the Development of Mobile Online Services in the Automotive Industry - A Case Study, and key words: Resistance, Manufacturing processes, Companies, Software, Manufacturing, Automobiles, Interviews. Abstract: Today's automotive companies face new opportunities but also new challenges. With the development of new technologies, cars are increasingly integrated into the life of their owners for example by connecting their smartphones with their cars. This enables the development of new services for the owners of cars, e.g. monitoring of driving behavior. These so-called mobile online services demand an iterative and user-centered development and automotive companies have to align their processes with these demands. However, the necessary transition for that is difficult because automotive companies are often rigid in their structure, resistant to change, and still focused on the manufacturing of cars. Although mobile online services have become increasingly important for companies, there is, so far, only limited research in this field, especially about the challenges in the development of mobile online services. Therefore, we conduct a case study in a project that develops mobile online services to manage vehicle fleets in an automotive company. By using interviews, we investigate the challenges the project faces and the means that the project already implements to address these challenges. Our results show that the automotive company considers mobile services rather as a by-product and is still more focused on the manufacturing of cars. That is expressed by the number of external employees and a missing user-centric development that already starts in the manufacturing process. |
14,164 | Please write an abstract with title: The Trap Of Random Sampling and How to Avoid It - Alternative Sampling Strategies for a Realistic Estimate of the Generalization Error in Remote Sensing, and key words: Machine learning algorithms, Correlation, Benchmark testing, Sensors, Remote sensing, Standards. Abstract: Many benchmark datasets in remote sensing still consist of only a single image that is used to train and evaluate machine learning algorithms. Random sampling - while being the virtual standard in the field to divide the available data into train and test set - is the worst choice in this scenario as it leads to a large degree of spatial correlation between these two sets which are assumed to be independent. Already pointed out in several earlier works, this paper reconfirms this fact and compares several alternatives. Two of the evaluated techniques allow to draw a large amount of unbiased test samples and lead to significantly less biased error estimates. The urgent recommendation is using multi-image datasets or - if only a single image is available - refraining to use random sampling and instead rely on either of these or similar methods. |
14,165 | Please write an abstract with title: Monitoring the Self-Heating in a High Frequency GaN HFET, and key words: Monitoring, Frequency, Gallium nitride, HEMTs, MODFETs, Voltage, Temperature dependence, Councils, Testing, Contacts. Abstract: Self-heating in GaN HFETs is a consequence of the high power and current levels common in such devices, and the limited ability of the substrates to conduct heat away from the devices. Most high frequency test devices are usually composed of 2 separate devices, laid out in a parallel electrical configuration but spatially symmetric with shared gate and drain contacts. The self-heating at high current densities causes the drain current to decrease as a function of drain bias, as the temperature of the active area increases above that of the substrate and device mount. Since a high frequency device is essentially 2 devices, one can bias the two parts to have different currents. Effectively one can then use one side of the device to monitor the self-heating and heat flow from the other side, if they are biased differently. This paper describes such experiments |
14,166 | Please write an abstract with title: Data acquisition system for measurements in free moving subjects and its applications, and key words: Data acquisition, Instruments, Humans, Condition monitoring, Transducers, Connectors, Biosensors, Analog-digital conversion, Computer interfaces, Writing. Abstract: A low-cost, portable acquisition system for monitoring and processing human biomechanical parameters is presented. It is equipped with 16 input channels, each one linked to an external transducer by a suitable connector. Input signals from sensors are converted into a digital form by a 12-bit analog-to-digital converter and stored in a removable memory (memory card) respecting the PCMCIA standard interface, allowing the download of acquired data toward the host computer. The acquisition operating mode is programmable by a host PC, writing proper values into the memory card; then, the instrument acquires the defined number of channels at the selected sampling rate. The instrument is battery powered; then, it can be used in all those applications, like rehabilitation and sports medicine, where the freedom for subject movement is a constraint for the test. In fact, this instrument does not require an arranged environment for measurements, and it is not connected to a PC. Three sample applications are presented in which the instrument is used to evaluate human motor capability, physical parameters in amputees, and motor performance in athletes. |
14,167 | Please write an abstract with title: Classifying human-robot interaction: an updated taxonomy, and key words: Taxonomy, Collaboration, Robot sensing systems, Human robot interaction, Collaborative work, Application software, Control systems, Sensor systems, Computer science, Teleconferencing. Abstract: This paper extends taxonomy of human-robot interaction (HRI) introduced in 2002 to include additional categories as well as updates to the categories from the original taxonomy. New classifications include measures of the social nature of the task (human interaction roles and human-robot physical proximity), task type, and robot morphology. |
14,168 | Please write an abstract with title: 2D DOA Estimation Exploiting Vertical Synthetic Planar Arrays, and key words: Sensor arrays, Sensors, Two dimensional displays, Estimation, Direction-of-arrival estimation, Planar arrays, Array signal processing. Abstract: In this paper, vertical motions of sparse linear arrays (SLAs) are utilized to generate equivalent synthetic planar arrays for two-dimensional (2D) direction-of-arrival (DOA) estimation. The proposed array geometry named vertical synthetic planar array (VSPA) consists of an arbitrary SLA on the x-axis and a series of its time-shifted arrays in the vertical orientation. With the original linear array and the moving trail known, the difference coarray of VSPA can be easily obtained. By utilizing both the synthetic aperture processing and the coarray technique, VSPA has the ability to construct a synthetic planar array with only an SLA used. Compared with the traditional sparse planar arrays (SPAs), such as 2D nested array and 2D coprime array, VSPA can achieve higher degree-of-freedom and improved 2D DOA estimation performance with the same number of sensors. Moreover, as different original linear arrays and moving trails can be chosen for different applications, the construction of VSPA is of high flexibility. Numerical simulations are presented to verify the superiority of the proposed VSPA geometry over other typical SPAs. |
14,169 | Please write an abstract with title: A Novel Video Coding Scheme based on Principal Component Analysis, and key words: Video coding, Principal component analysis, Video sequences, Eigenvalues and eigenfunctions, Video compression, Decoding, Face recognition. Abstract: This paper presents a novel video coding technique where most frames are represented as their projection onto a proper basis (eigenspace) computed using principal component analysis (PCA). Since a video sequence contains regions with high time variations, a learning procedure is used to obtain an adequate basis. We also introduce the idea of bidirectional predicted frames to denote those frames that can be estimated from the nearest past and future PCA coefficients. Experimental results show the high quality/compression achieved using the new scheme with different eigenspace updating algorithms |
14,170 | Please write an abstract with title: A Flow Blocking Model for IP Overflow Traffic, and key words: Traffic control, Routing, Probability, IP networks, Mathematical model, Communication system traffic control, Telecommunication traffic, Multiprotocol label switching, Australia, Circuits. Abstract: Overflow routing is well known in the circuit switched world, but not used in the IP context. The scheme for advanced packet overflow routing (SAPOR) is a method that allows flow based routing, and can enable overflow routing in IP networks. This paper presents an analytical model to calculate overflow probabilities for flows with known flow rate distributions. It discusses implications of this model and compares the method to results found by simulation. The paper particularly targets blocking calculations in the highly loaded case, i.e. a non trivial part of the load is subject to overflow. The proposed model can also be used in general context for other applications |
14,171 | Please write an abstract with title: AR-based interactive exploration of a museum exhibit, and key words: Space technology, Virtual reality, Augmented reality, Computer graphics, Humans, Knowledge transfer, Fires, Tires, Animation, Videos. Abstract: In this paper we describe the development of a new augmented reality-based user interface for a museum exhibit at the Heinz Nixdorf Museums Forum at Paderborn, Germany. In opposite to existing traditional presentation technologies in museums, the new user Interface will provide Interactive exploration of a real exhibit, In this case a personal computer Apple G4. For the Implementation we used the AR-ToolKit, a marker-based AR-Software. Furthermore, the user acceptance of the new interface has been evaluated with a poll based on personal interviews among the museum visitors. |
14,172 | Please write an abstract with title: Ultra-low-profile micromachined power inductors with highly laminated NiFe cores: application to low MHz DC-DC converters, and key words: Inductors, DC-DC power converters, Fabrication, Copper, Circuits, Frequency, Magnetic films, Magnetic anisotropy, Perpendicular magnetic anisotropy, Magnetic flux. Abstract: Micromachined inductors with sub-mm profiles and comparable electrical performance to thicker, commercially-available surface-mount devices, have been fabricated and characterized for low MHz DC-DC converters. The fabrication approach involves micron-scale lamination of nickel-iron cores, combined with 3D-micromachined copper windings. The dimensions of the fabricated inductor are 11.5 mm/spl times/5.7 mm/spl times/0.65 mm, and the DC resistance is 190 m/spl Omega/. Use of this inductor in a prototype DC-DC boost converter circuit (6 V-9 V) yielded 1.6 W power output at 84% efficiency. |
14,173 | Please write an abstract with title: On frequency regulation control strategy of wind turbine based on disturbance adaptiveness, and key words: Time-frequency analysis, Simulation, Switches, Wind power generation, Control systems, Frequency conversion, Robustness. Abstract: To solve the frequency problem caused by high wind power penetration, control strategies such as rapid power compensation (RPC) have been adopted to release the frequency regulation capability of new energy sources quickly. However, when the wind turbine (WT) adopts the RPC strategy to participate in the system frequency regulation, it cannot adapt to the random disturbance. In this paper, a disturbance adaptive RPC (ARPC) strategy is proposed. When the system is disturbed, the signal excitation method is used to estimate the external disturbance. According to the estimated disturbance, the WT rotational inertia is quickly used to compensate for the grid's unbalanced power. When the system frequency deviation and the rate of change of frequency (RoCoF) evaluation indexes meet the threshold requirements, the control strategy switches from ARPC to droop control, which can ensure the WT exit frequency regulation smoothly, and further reduce the frequency deviation and improve the frequency quality. Finally, analyzing the operation mode and determining the relevant switching logic, the proposed ARPC strategy's detailed implementation is developed. Simulation results proved the effectiveness and advancement of the ARPC based strategy. |
14,174 | Please write an abstract with title: Advanced Training Set Generator for Use in Self-Organizing Neural Networks, and key words: Training, Shape, Training data, Scattering, Artificial neural networks, Tools, Generators. Abstract: Success in training of artificial neural networks (ANNs) depends on properly selected training data set. The problem is not trivial, especially in situations in which the structure of data to be classified by the neural network (NN) after completing the learning phase is not known. To cope with this problem, one of the solutions is to conduct comprehensive tests of the ANN with training it with data sets that differ in the distribution of the learning patterns in the input data space. In order to prepare such sets, appropriate tools are required that introduce the ability of a broad parameterization. In the proposed work, an advanced data generator has been developed, which based on a specific variability of particular predefined parameters, generates a collection of learning data sets. The obtained sets are then used to optimize the learning process of selected algorithms of self-organizing ANNs. The NN then automatically retrieves subsequent data sets from specific location, and as a response generates reports with an assessment of the quality of the learning process. The aim of the proposed investigations is to optimize the structure of selected ANNs, so as to obtain their minimum complexity, important in case of their hardware implementation. |
14,175 | Please write an abstract with title: A new ZVZCS full bridge converter with an auxiliary center tapped rectifier, and key words: Rectifiers, Bridge circuits, Switches, Schottky diodes, DC-DC power converters, Windings, Zero voltage switching, Zero current switching, Leg, Stress. Abstract: A new ZVZCS full bridge DC-DC converter is proposed based on the phase shift control. With an auxiliary center tapped rectifier a voltage source is gained to reset the primary current of the transformer winding. Therefore ZVS for the leading lag switches and ZCS for the lagging leg switches can be achieved respectively without any increase of current and voltage stresses. This converter also can achieve high efficiency by reducing the circulating energy and employing Schottky diodes as rectifier diodes, especially in high input voltage applications. A 1 kW prototype is made to verify the theoretical analysis. |
14,176 | Please write an abstract with title: Hierarchical semi-numeric method for pairwise fuzzy group decision making, and key words: Decision making, Fuzzy sets, Computational modeling, Open wireless architecture, Mathematics, Art, Humans. Abstract: Gradual improvements to a single-level semi-numeric method, i.e., linguistic labels preference representation by fuzzy sets computation for pairwise fuzzy group decision making are summarized. The method is extended to solve multiple criteria hierarchical structure pairwise fuzzy group decision-making problems. The problems are hierarchically structured into focus, criteria, and alternatives. Decision makers express their evaluations of criteria and alternatives based on each criterion by using linguistic labels. The labels are converted into and processed in triangular fuzzy numbers (TFNs). Evaluations of criteria yield relative criteria weights. Evaluations of the alternatives, based on each criterion, yield a degree of preference for each alternative or a degree of satisfaction for each preference value. By using a neat ordered weighted average (OWA) or a fuzzy weighted average operator, solutions obtained based on each criterion are aggregated into final solutions. The hierarchical semi-numeric method is suitable for solving a larger and more complex pairwise fuzzy group decision-making problem. The proposed method has been verified and applied to solve some real cases and is compared to Saaty's (1996) analytic hierarchy process (AHP) method. |
14,177 | Please write an abstract with title: Multi-objective optimization of wind turbine via controllers coordination and sensitivity analysis, and key words: WIND TURBINE, MULTI-OBJECTIVE OPTIMIZATION, COORDINATION CONTROL, SENSITIVITY, FATIGUE DAMAGE. Abstract: In this paper, a sensitivity-analysis-based wind turbine optimization strategy is introduced to improve the power output stability while reducing the shaft and tower loads. Both generator torque and blade pitch are controlled coordinately to achieve the optimization. During the wind turbine control process, blade pitch and generator torque are controlled proportionally to the generator speed tracking error, which simplifies the controller structure, thus, the wind turbine performance can be evaluated with control variables sensitivities directly. The wind turbine performance is considered in output power stability, shaft bending moment and tower bending moment. Both load parameters are analysed in fatigue damage lifetime. A conflicting relationship is realized between the load-power characteristic during the optimization, and a global coordination solution is selected on the pareto optimal frontier. Essential, this work is an exploration for the quantitative analysis from the wind turbine load performance to the control variables sensitivities directly without the limitation of controller forms. Simulation results show the effectiveness of the proposed controller. |
14,178 | Please write an abstract with title: Hyperspectral Image Classification Based on Semi-Supervised Dual-Branch Convolutional Autoencoder with Self-Attention, and key words: Feature extraction, Hyperspectral imaging, Training, Fuses, Data mining, Convolutional neural networks, Unsupervised learning. Abstract: Deep learning method shows its powerful classification performance with sufficient available data. However, the labeled data is limited in hyperspectral images (HSIs). Semi-supervised algorithms have unique advantages on dealing with this problem. Therefore, a semi-supervised convolutional neural network is proposed in this paper. It consists of two branches, which use limited labeled samples and a large number of unlabeled samples, respectively. The first branch includes an encoder-decoder model to extract contextual information of unlabeled samples. The other one uses the similar construction except extra classification layers to extract discriminative features of labeled samples. In order to fuse contextual and discriminative information, we cascade the features of low-level layers from different branches. Furthermore, self-attention is added to the first branch, which focuses more on the global information for classification. The experiment results show that the proposed model provides a competitive result compared with state-of-the-art methods. |
14,179 | Please write an abstract with title: Privacy-Preserving and Distributed Algorithms for Modular Exponentiation in IoT With Edge Computing Assistance, and key words: Outsourcing, Edge computing, Task analysis, Servers, Internet of Things, Cloud computing, Image edge detection. Abstract: With the development of Internet of Things (IoT) and 5G, edge computing, as a new computing paradigm, has been widely popularized in academia and industry. Due to the distributed architecture and being close to the user, edge computing can faster respond to the IoT device's request and provide a better quality of service for IoT applications. An important application of edge computing is to outsource the complicated computation task to the nearby edge nodes. Modular exponentiation is widely considered as one of the most common and expensive operations in cryptographic protocols. As far as we know, all secure outsourcing algorithms of modular exponentiation are based on the centralized cloud server, but not based on multiple edge nodes. In this article, we propose the first secure and distributed outsourcing algorithm for modular exponentiation (fixed base and variable exponent) under the multiple noncolluding edge node model. In our algorithm, the exponent is divided into a certain number of parts. In addition, we propose another secure and distributed outsourcing algorithm of modular exponentiation (variable base and variable exponent). The user can protect the privacy in the process of outsourcing and detect the invalid results from edge nodes with high probability. Finally, we provide the experimental evaluation to support that our proposed algorithms are efficient on both the user side and the edge node side. |
14,180 | Please write an abstract with title: Detecting TensorFlow Program Bugs in Real-World Industrial Environment, and key words: Deep learning, Industries, Computer bugs, Time factors, Python, Software engineering. Abstract: Deep learning has been widely adopted in industry and has achieved great success in a wide range of application areas. Bugs in deep learning programs can cause catastrophic failures, in addition to a serious waste of resources and time.This paper aims at detecting industrial TensorFlow program bugs. We report an extensive empirical study on 12,289 failed TensorFlow jobs, showing that existing static tools can effectively detect 72.55% of the top three types of Python bugs in industrial TensorFlow programs. In addition, we propose (for the first time) a constraint-based approach for detecting TensorFlow shape-related errors (one of the most common TensorFlow-specific bugs), together with an associated tool, ShapeTracer. Our evaluation on a set of 60 industrial TensorFlow programs shows that ShapeTracer is efficient and effective: it analyzes each program in at most 3 seconds and detects effectively 40 out of 60 industrial TensorFlow program bugs, with no false positives. ShapeTracer has been deployed in the platform-X platform and will be released soon. |
14,181 | Please write an abstract with title: PWM Based Sliding Mode Control of a fast charger for supercapacitors, and key words: Sliding mode control, Inductors, Pulse width modulation, Numerical models, Supercapacitors, Standards. Abstract: The paper deals with the design and control of a fast charger circuit for Energy Storage Systems based on supercapacitor. The proposed solution finds natural application in the recharge stations of electrical vehicles (e.g., electrical buses, forklift, etc.) typically alternating short runs to periodic stops. It performs the charge migration from a module to supercapacitors to another, following a constant current profile to minimize the charging time. The control law, designed to be implemented in a commercial microcontroller, exploits a sliding mode technique properly modified to operate in PWM mode. Numerical simulations in MATLAB/SIMULINK environment with SimScape have been performed to prove the effectiveness of the proposed control. |
14,182 | Please write an abstract with title: Enhancement and depletion-mode pHEMT using 6 inch GaAs cost-effective production process, and key words: PHEMTs, Gallium arsenide, Production, Voltage, Transconductance, Radio frequency, Circuits, Costs, MMICs, Temperature. Abstract: A cost effective enhancement/depletion mode pHEMT MMIC process on 6-inch GaAs wafer is demonstrated by using 0.5/spl mu/m gate-length optical stepper pHEMT technology. E-mode and D-mode gates are deposited simultaneously in this process simplification. The E-mode pHEMT exhibits a pinch-off voltage of +0.22V (defined at 0.1mA/mm), and a maximum extrinsic transconductance of 400mS/mm at room temperature. The off-state current of E-mode device is typically 0.15/spl mu/A/mm at V/sub gs/=0V and V/sub ds/=3V. This current is extreme low and is suitable for high density digital circuits with minimized power consumption. On the other hand, a pinch-off voltage of -0.75V and a transconductance of 370mS/mm has been measured for D-mode pHEMT. Due to excellent DC/RF characteristics and good uniformity of E/D pHEMTs from optimized optical gate lithography and front-side process, the D-mode switch and E-mode digital control circuit constitute a monolithic solution to RF control circuits in WLAN and cell phone applications. |
14,183 | Please write an abstract with title: Par4: very high speed parallel robot for pick-and-place, and key words: Parallel robots, Manipulators, Service robots, Acceleration, Optimization methods, Actuators, Prototypes, Robotic assembly, Belts, Pulleys. Abstract: This paper introduces a four-degree-of-freedom parallel manipulator dedicated to pick-and-place. It has been developed with the goal of reaching very high speed. This paper shows that its architecture is particularly well adapted to high dynamics. Indeed, it is an evolution of Delta, H4 and 14 robots architectures: it keeps the advantages of these existing robots, while overcoming their drawbacks. In addition, an optimization method based on velocity using adept motion has been developed and applied to this high speed parallel robot. All these considerations led to experimentations that proved we can reach high accelerations (13 G) and obtain a cycle time of 0.28 s. |
14,184 | Please write an abstract with title: Grid-controlled electron emission from a hollow-anode electron source, and key words: Electron emission, Electron sources, Plasma accelerators, Plasma properties, Plasma sources, Acceleration, Ferroelectric materials, Anodes, Fault location, Plasma density. Abstract: Summary form only given. The operation of a hollow-anode (HA) electron source with a biased output grid and an incorporated ferroelectric plasma source (FPS) in a diode powered by a 200 kV, 400 ns pulse is described. It was found that the FPS allows reliable ignition and sustaining of the HA discharge with current amplitude /spl les/1.2 kA and pulse duration /spl les/2/spl times/10/sup -5/ s at N/sub 2/ gas pressure of (1-3)/spl times/10/sup -4/ Torr. Parameters of the hollow-anode plasma were studied by different electrical, optical and spectroscopic diagnostics. It was found that the plasma density is /spl sim/2/spl times/10/sup 14/ cm/sup -3/ and /spl sim/4/spl times/10/sup 12/ cm/sup -3/ at the vicinity of the ferroelectric surface and at the output anode grid, respectively. Three different electrical schemes for the hollow-anode grid bias were tested and compared. The use of an auto-bias grid allows electron beam extraction with current I/sub b//spl les/1.2 kA in an emission-limited mode and insignificant plasma pre-filling of the accelerating gap. The use of an externally biased hollow-anode grid (either with a positive or negative potential) showed the possibility to control the plasma emission properties (I/sub b//spl les/2 kA) without changing the amplitude of the discharge current. Drastic changes in the parameters of the plasma were obtained during the accelerating pulse. The applied accelerating pulse causes a significant increase of the plasma potential (/spl phi//sub pl/) inside the hollow anode. For a discharge current amplitude of 0.3-1 kA, /spl phi//sub pl/ increases relative to the hollow-anode electrode as 6.6-3.1 kV, relative to the ferroelectric plasma source as 0.2-0.4 kV, and relative to the hollow-anode grid as 2.9-1.2 kV. A model which explains the electron emission from the positively charged plasma is proposed. The model suggests screening of the hollow-anode grid potential by the space charge of ions oscillating through the hollow-anode output grid. These oscillations occur inside the potential well formed between the hollow-anode plasma boundary and a virtual anode formed inside the accelerating gap. Generation and characterization of a high-current electron beam with current amplitude of /spl sim/1.2 kA was achieved under an accelerating pulse amplitude /spl les/300 kV and /spl sim/400 ns pulse duration. |
14,185 | Please write an abstract with title: Learning Meta Soft Prompt for Few-Shot Language Models, and key words: Meta learning, few-shot learning, prompt tuning, domain adaptation, language model. Abstract: Prompt-based learning is powerful to utilize the large-scaled pre-trained language model (PLM) for language understanding where the input sentences are augmented by either adding the hard prompt using word tokens or the soft prompt in a form of trainable tokens. However, the learned soft prompt in training domain may not really help a frozen PLM to handle domain shift in test domain. This paper presents an approach to incorporate meta learning into domain adaptation to train new soft prompt which sufficiently generalizes the frozen PLM to a number of domains. The meta soft prompt is then developed for few-shot unsupervised domain adaptation where a frozen PLM can be quickly adapted to a target domain. This soft prompt is optimized according to meta learning where the domain adaptation loss and the prompt-based classification loss are jointly minimized. The experiments on multi-domain natural language understanding show the benefits of the proposed meta soft prompt in pre-trained language model by using BERT under the few-shot setting. |
14,186 | Please write an abstract with title: Predicting Mental Health of Scholars Using Contextual Word Embedding, and key words: Correlation, Social networking (online), Blogs, Bit error rate, Support vector machine classification, Mental health, Forestry. Abstract: Frustration, anger and mental fatigue are some of the most prevalent issues faced by scholars these days which are often due to the cut-throat competition and peer pressure among adolescents increasing day by day. The objective of the work was to predict the mental health of scholars by tracking strongly negative words or offensive slangs used very deliberately by them in their tweets. The data to analyze the sentiments exhibited by them has been used from their Twitter timelines. The most common topics they talked about and the common keywords for each of these topics were identified and thereafter using BERT, the word embedding and cosine similarities had been found between these keywords and a bag of words that contained a number of strongly negative emotion words collected manually. In this paper, contextual word embedding has been done on the twitter data of frustrated individuals to analyze their temperament and behavior exhibited by them. Also, we have found if there was any correlation between frequently used negative words and frustrated individuals or not. We then found that there was a correlation and individuals using such words had negative emotions prevalent among them. |
14,187 | Please write an abstract with title: Research on photovoltaic power abnormal data identification method based on popular learning, and key words: Photovoltaic systems, Economics, Temperature distribution, Radiation effects, Statistical analysis, Meteorological factors, Power systems. Abstract: As an important distributed power generation, solar photovoltaic power generation is gradually being used from independent system to large-scale grid connection. The development of output power prediction of photovoltaic power station is of great significance to maintain the power balance and economic operation of power system. By discussing the influencing factors of photovoltaic power generation power prediction, the effects of various meteorological factors such as solar irradiation, temperature and cloud cover on the output power of photovoltaic power station are analyzed, and the advantages and disadvantages of mathematical statistical methods and artificial intelligence methods are analyzed and compared. |
14,188 | Please write an abstract with title: Utilizing Self-Learning Software for the Acquisition and Exploration of Standard Dance Notation Fundamentals in Krabi Krabong Arts Education, and key words: Self-Learning, Software for Learning, Acquisition and Exploration, Dance Notation, Thai sword. Abstract: This research focuses on applying self-learning software in teaching basic Labanotation and Krabi Krabong. The study involves 45 teacher trainees with no prior knowledge of Krabi Krabong. Three steps were followed: analyzing course content, creating a learning model using video clips, and measuring outcomes. Tools included a Labanotation manual and tests for reading and performing Krabi Krabong. Results showed significant improvements in scores and understanding. The self-learning software enhanced dance notation skills and complemented Krabi Krabong teaching. The research concludes that the application of self-learning software in teaching Labanotation can effectively improve dance notation skills and be used in conjunction with Krabi Krabong instruction. |
14,189 | Please write an abstract with title: Chaotic Neural Network-Based Hysteresis Modeling With Dynamic Operator for Magnetic Shape Memory Alloy Actuator, and key words: Magnetic hysteresis, Actuators, Computational modeling, Neurons, Artificial neural networks, Strain, Shape memory alloys. Abstract: The magnetic shape memory alloy (MSMA) is a new family of smart materials, which exhibits great strain deformation and high energy density. Based on these properties, the MSMA has excellent potential to represent an available means for developing a novel generation of actuators in the micro-positioning application. However, the MSMA-based actuator suffers from the inherent hysteresis and it has become a bottleneck in the industrial application. A hybrid hysteresis model, which consists of a simple dynamic hysteresis operator (SDHO) and chaotic neural network (CNN), is proposed in this article. This developed model possesses a concise construction and distinguished generalization capability. By conducting comparative experiments, the proposed approach has a superior ability to predict the hysteresis behaviors under various input signals. |
14,190 | Please write an abstract with title: Fast coupling estimation in PCB environment, and key words: Transmission line matrix methods, Geometry, Capacitance, Dielectrics, Crosstalk, Microstrip, Circuit simulation, Frequency domain analysis, Stripline, Wires. Abstract: The paper presents an implementation of a multidisciplinary method of estimating the time domain and frequency domain crosstalk (coupling) between several adjacent transmission lines. The method is applicable for PCB configurations including microstrip and stripline. The method also handles some elementary configurations, such as: two wires over ground plane, ribbon, wires in a circular shield, etc. An experiment, conducted with a microstrip configuration, is presented, verifying the accuracy of the model over a wide frequency range. |
14,191 | Please write an abstract with title: Pricing Fresh Data, and key words: Pricing, Data models, Real-time systems, Computational modeling, Predictive models, Data integrity, Cloud computing. Abstract: We introduce the concept of fresh data trading, in which a destination user requests, and pays for, fresh data updates from a source provider, and data freshness is captured by the age of information (AoI) metric. Keeping data fresh relies on costly frequent data updates by the source, which motivates the source to price fresh data. In this work, the destination incurs an age-related cost, modeled as a general increasing function of the AoI. The source designs a pricing mechanism to maximize its profit, while the destination chooses a data update schedule to trade off its payments to the source and its age-related cost. Depending on different real-time applications and scenarios, we study both a finite-horizon model and an infinite-horizon model with time discounting. The key challenge of designing the optimal pricing scheme lies in the destination's time-interdependent valuations, due to the nature of AoI, and the infinite-dimensional dynamic optimization. To this end, we exploit three different dimensions in designing pricing by studying three pricing schemes: a time-dependent pricing scheme, in which the price for each update depends on when it is requested; a quantity-based pricing scheme, in which the price of each update depends on how many updates have been previously requested; and a simple subscription-based pricing scheme, in which the price per update is constant but the source charges an additional subscription fee. Our analysis reveals that (1) the optimal subscription-based pricing maximizes the source's profit among all possible pricing schemes under both finite-horizon and infinite-horizon models; (2) the optimal quantity-based pricing scheme is only optimal with a finite horizon; and (3) the time-dependent pricing scheme, under the infinite-horizon model with significant time discounting, is asymptotically optimal. Numerical results show that the profit-maximizing pricing schemes can also lead to significant reductions in AoI and social costs, and that a moderate degree of time discounting is enough to achieve a close-to-optimal time-dependent pricing scheme. |
14,192 | Please write an abstract with title: Low Phase Noise Direct-Modulation Optoelectronic Oscillator, and key words: Optical fibers, Phase noise, Optical saturation, Optical amplifiers, Optical fiber amplifiers, Optical feedback, Optical modulation, Optoelectronic devices. Abstract: A direct-modulation OEO (DM-OEO) generating stable 10 GHz and 20 GHz signals is presented. A single loop and a dual loop approach are implemented and compared. We show an output signal of 15 dBm RF power, and a phase noise as low as −135 dBc/Hz at 10 kHz offset from the 10 GHz carrier. The 20 GHz second harmonic exhibits a noise level of −127 dBc/Hz at 10 kHz. A high spur level reduction is also obtained in the dual loop architecture. |
14,193 | Please write an abstract with title: Demo: Cloak: A Framework For Development of Confidential Blockchain Smart Contracts, and key words: Privacy, Annotations, Conferences, Smart contracts, Supply chains, Finance, Programming. Abstract: In recent years, as blockchain adoption has been expanding across a wide range of domains, e.g., digital asset, supply chain finance, etc., the confidentiality of smart contracts is now a fundamental demand for practical applications. However, while new privacy protection techniques keep coming out, how existing ones can best fit development settings is little studied. Suffering from limited architectural support in terms of programming interfaces, state-of-the-art solutions can hardly reach general developers. In this paper, we proposed the CLOAK framework for developing confidential smart contracts. The key capability of Cloak is allowing developers to implement and deploy practical solutions to multi-party transaction (MPT) problems, i.e., transact with secret inputs and states owned by different parties by simply specifying it. To this end, CLOAK introduced a domain-specific annotation language for declaring privacy specifications and further automatically generating confidential smart contracts to be deployed with trusted execution environment (TEE) on blockchain. In our evaluation on both simple and real-world applications, developers managed to deploy business services on blockchain in a concise manner by only developing CLOAK smart contracts whose size is less than 30% of the deployed ones. |
14,194 | Please write an abstract with title: Info-Gap-Based Optimization of Microgrids Integrated with Power, Cooling and Hydrogen Generation Units, and key words: Costs, Uncertainty, Hydrogen storage, Cooling, Hydrogen, Optimal scheduling, Microgrids. Abstract: The emerging concept of integrated demand response (IDR) is a promising platform for promoting the utilization of renewable energy sources (RES) and improving energy efficiency in multi-energy systems. In this paper, a robust scheduling model for a power, cool, and hydrogen-based islanded microgrid (MG) in the presence of hydrogen fueling stations (HFSs) and EV parking lots (EVPLs) is proposed. Additionally, the impact of power and cooling-based IDR is investigated in reducing the operating cost of the proposed system. The proposed multi-energy MG is equipped with power generation, wind turbine, electrical, cooling and hydrogen storage systems, power to hydrogen (P2H) facility and an electrical chiller to meet power, cooling, and hydrogen demands simultaneously. In order to deal with wind power generation uncertainty, a robust optimization approach is employed without the need for probability density function (PDF) or scenario generation, which strengthens the optimal operation of the proposed multi-energy MG against the wind power uncertainty and allows the operator to apply a risk-averse approach. Numerical results demonstrate that the establishment of IDR in the presence of storage systems reduces the total operating costs by 5.6%. |
14,195 | Please write an abstract with title: A 10 Gb/s On-chip Jitter Measurement Circuit Based on Transition Region Scanning Method, and key words: Semiconductor device measurement, Voltage measurement, Detectors, Jitter, Delay lines, Very large scale integration, Silicon. Abstract: This paper proposes a 10-Gb/s On-chip jitter measurement (OCJM) circuit to measure peak-to-peak jitter of data/clock signals in high-speed transceivers and system-on-chips (SOCs). The peak-to-peak jitter measurement circuit is based on a novel transition region scanning (TRS) technique. The maximum transition region (TR) width of data/clock first converts to an equivalent pulse, and subsequently, the pulse width is scanned by a slowly moving clock edge to construct peak-to-peak jitter width. The peak-to-peak jitter width finally converts to an equivalent peak-to-peak voltage which gives the on-chip jitter information in the form of voltage. The proposed OCJM circuit uses a sub-rate (sub-multiple of data/clock frequency to be measured) clock signal and a voltage-controlled delay line (VCDL) circuit to carry out the scanning process of the TR width of jittery data/clock. The time-to-voltage (TVC) circuit is used for converting timing jitter to voltage, and the peak detector (PD) circuit is responsible for giving the peak voltage corresponding to the peak-to-peak jitter. This OCJM architecture is capable of characterizing the jitter performance at any arbitrary node inside the chip. Implementation wise this OCJM circuit is a fully on-chip and complete analog solution. A test chip has been designed and fabricated using 65 nm CMOS technology with a core silicon area of $910 ~\mu \mathrm{m} \times 300 ~\mu \textbf{m}$. The complete architecture consumes 11.4-mW at a 10-Gb/s data rate. The measurement result confirms that the architecture is working fine as the output voltage varies proportionally with the peak-to-peak jitter of target jittery data or clock signal. |
14,196 | Please write an abstract with title: Self-Supervised Monocular Trained Depth Estimation Using Self-Attention and Discrete Disparity Volume, and key words: Estimation, Uncertainty, Videos, Training, Computational modeling, Convolution, Cameras. Abstract: Monocular depth estimation has become one of the most studied applications in computer vision, where the most accurate approaches are based on fully supervised learning models. However, the acquisition of accurate and large ground truth data sets to model these fully supervised methods is a major challenge for the further development of the area. Self-supervised methods trained with monocular videos constitute one the most promising approaches to mitigate the challenge mentioned above due to the wide-spread availability of training data. Consequently, they have been intensively studied, where the main ideas explored consist of different types of model architectures, loss functions, and occlusion masks to address non-rigid motion. In this paper, we propose two new ideas to improve self-supervised monocular trained depth estimation: 1) self-attention, and 2) discrete disparity prediction. Compared with the usual localised convolution operation, self-attention can explore a more general contextual information that allows the inference of similar disparity values at non-contiguous regions of the image. Discrete disparity prediction has been shown by fully supervised methods to provide a more robust and sharper depth estimation than the more common continuous disparity prediction, besides enabling the estimation of depth uncertainty. We show that the extension of the state-of-the-art self-supervised monocular trained depth estimator Monodepth2 with these two ideas allows us to design a model that produces the best results in the field in KITTI 2015 and Make3D, closing the gap with respect self-supervised stereo training and fully supervised approaches. |
14,197 | Please write an abstract with title: 25-GHz-spacing wavelength-monitor integrated DFB laser module for DWDM applications, and key words: Wavelength division multiplexing, Monitoring, Channel spacing, Laser tuning, Fiber gratings, Optical design, Laboratories, Photodiodes, Laser applications, Associate members. Abstract: For the first time, a 25-GHz-spacing wavelength monitor is successfully integrated into an industry standard 14-pin butterfly laser module through the use of a unique configuration. The temperature-induced wavelength drift of these wavelength-monitor integrated laser modules for a case temperature ranging from -5/spl deg/C to 70/spl deg/C is less than /spl plusmn/10 pm. |
14,198 | Please write an abstract with title: Power Flow Control and Voltage Profile Improvement Using HPFC with Genetic Algorithm, and key words: Power System, UPFC, HPFC Neuton-Raphson Method, Genetic Algorithm, MATLABcomponent; formatting; style; styling; insert, Power System, UPFC, HPFC Neuton-Raphson Method, Genetic Algorithm, MATLABcomponent, formatting, style, styling, insert. Abstract: Power flow control is the critical factor affecting power transmission system. In power transmission line the Hybrid Power Flow Controller (HPFC) is applied for standardize the power flow control. Then the results presented using UPFC and HPFC equations. So these equations of HPFC power balance equations of network are united in to only one set of non-linear algebraic equations. The UPFC and HPFC are calculated primarily with the help of Neuton Raphson Method. Even though this kind of controller is a very expensive controller it provides about its arrangement. The performance evaluation of various FACTS controllers in a wide selection of working and blame circumstances has been completed. Then UPFC has a better quality power flow control attribute when contrasted or balanced with different FACTS controllers. The distinctive HPFC designs intended by the specialist have been executed on a MMIB framework. A power system of UPFC and HPFC are produced utilizing limitation conditions and target capacities. Here ideal situation of UPFC and HPFC are acquired by utilizing Genetic Algorithm (GA) based approach. A power system model of UPFC and HPFC are created utilizing very important conditions and target capacities and it is contrasted the uncompensated system. Then the proposed methodology established for IEEE-30 bus test system utilizing MATLAB satisfied record. Finally the results are compared with and without UPFC and HPFC. Then real and reactive power flows in the line and check bus voltages are to be analyzed the performance of UPFC. |
14,199 | Please write an abstract with title: Adaptive feedforward amplifier using pilot signal, and key words: Adaptive filters, Multiaccess communication, Base stations, Frequency locked loops, Radio transmitters, Mobile communication, High power amplifiers, Voltage control, Attenuators, Phase shifters. Abstract: We designed and implemented a feedforward amplifier for a WCDMA base station. The feedforward amplifier has the capability of adjusting the center frequency of linearization loops to get the better cancellation performance in the interesting frequency band. The controller detects the power of a pilot signal and the frequency of the pilot signal can be changed for the better cancellation performance in the interesting frequency band. The principles of control algorithm and the cancellation performance of the implemented feedforward amplifier are presented. The cancellation performance of 1st loop is about 20 dB over 2110 MHz /spl sim/ 2170 MHz and 20 dB for 2nd loop over 2090 MHz /spl sim/ 2190 MHz. For two-tone test, the IMD cancellation performance is about 25 dB. For the WCDMA signal, the cancellation performance is about 14 dB. |
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