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"title": "Hierarchical feature based matching for motion correspondence",
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"title": "Algorithmic Expressions for Assessing Algorithmic Thinking Ability of Elementary School Children",
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"abstract": "This Research to Practice Full Paper presents the development of the algorithmic expressions for the assessment tools for assessing algorithmic thinking ability of elementary school children. In Japan, elementary school children will be required to learn computer programming as an interdisciplinary element appearing throughout the curriculum in 2020. The purpose of this programming education is to nurture Computational Thinking (CT) for elementary school children in Japan. However, almost no discussion has been conducted in Japan on how to measure the level of CT an elementary school child has acquired. Since the definition of CT is not very firm, it is not easy to measure the levels of CT. Therefore, several organizations have issued operational definitions of CT. Among the concepts of CT in those operational definitions, Algorithmic Thinking was chosen as a representative of CT, and the assessment tools for evaluating Algorithmic Thinking ability have been developed in this research. The assessment tool was conducted in the experimental Computer Science Unplugged classes and in the control classes in two elementary schools in Japan. There were in total 152 children in the classes, and all of them were 5th grade children. By answering the questions in the assessment tool, each child got a score between 0 and 15. The scores were statistically analyzed.",
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"abstract": "This paper describes the Smart Survey Tool, a novel multi-device application for museum visitor tracking and tracking data visualization. The application allows museum staff to capture detailed information describing how visitors move around an exhibition and interact with individual exhibits. They can then visualize the results of tracking either on a single mobile device or with multiple mobile devices connected to a large display. The platform uses orthogonal views of the exhibition space for tracking and visualization, with a chess-piece icon to represent visitors during tracking, and curved semi-transparent lines with animated semi-circles to communicate the path and direction of visitor movement. Our visualization is novel in its use of an orthogonal projection for pedestrian tracking and animation to communicate the flow of visitors around the exhibition space, as well as allowing users to dynamically switch between views representing different groups of visitors. The design of our application was informed through an extensive requirements analysis study conducted with Nanjing Museum and evaluated by conducting expert interviews with museum managers who considered that the application allowed for more effective and efficient recording and analysis of visitor tracking data.",
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"normalizedAbstract": "This paper describes the Smart Survey Tool, a novel multi-device application for museum visitor tracking and tracking data visualization. The application allows museum staff to capture detailed information describing how visitors move around an exhibition and interact with individual exhibits. They can then visualize the results of tracking either on a single mobile device or with multiple mobile devices connected to a large display. The platform uses orthogonal views of the exhibition space for tracking and visualization, with a chess-piece icon to represent visitors during tracking, and curved semi-transparent lines with animated semi-circles to communicate the path and direction of visitor movement. Our visualization is novel in its use of an orthogonal projection for pedestrian tracking and animation to communicate the flow of visitors around the exhibition space, as well as allowing users to dynamically switch between views representing different groups of visitors. The design of our application was informed through an extensive requirements analysis study conducted with Nanjing Museum and evaluated by conducting expert interviews with museum managers who considered that the application allowed for more effective and efficient recording and analysis of visitor tracking data.",
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"abstract": "Situational awareness applications require a highly detailed geospatial visualization covering a large geographic area. Conventional polygon based terrain modeling would exceed the capacity of current computer rendering. Terrain visualization techniques for a situational awareness application are described in this case study. Visualizing large amounts of terrain data has been achieved using very large texture maps. Sun shading is applied to the terrain texture map to enhance perception of relief features. Perception of submarine positions has been enhanced using a translucent, textured water surface. Each visualization technique is illustrated in the accompanying video tape.",
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"abstract": "Vessels move 90% of international cargo by volume, with the marine economy contributing to 5.1% of global GDP. As one of the oldest industries, the marine industry has yet to embrace innovations in modern technology to safeguard the blue economy. Situational awareness from intelligent vessel systems can enable enhanced safety and decision-making for mariners. As the foundation for these intelligent systems, advanced perception technology requires sufficient real-world operational data to leverage recent AI technologies. In this work, we introduce the Sea Situational Awareness (SeaSAw) dataset - a novel dataset that is comprised of 1.9 million images with 14.6 million objects associated with 20.4 million attributes from 12 object classes, making it the largest maritime dataset for object detection, fine-grained classification and tracking. Furthermore, this dataset consists of 9 sources in combination with various RGB cam-eras, mounted on different moving vessels, operating in different geographic locations globally, having variations in scenario, weather and illumination conditions. This data collection took place across 4 years with rigorous efforts on data selection, annotation, management and analysis to enhance the marine perception technology.",
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"title": "Is Twitter Enough? Investigating Situational Awareness in Social and Print Media during the Second COVID-19 Wave in India",
"normalizedTitle": "Is Twitter Enough? Investigating Situational Awareness in Social and Print Media during the Second COVID-19 Wave in India",
"abstract": "The COVID-19 pandemic required efficient allocation of public resources and transforming existing ways of societal functions. To manage any crisis, governments and public health researchers ex-ploit the information available to them in order to make informed decisions, also defined as situational awareness. Gathering situational awareness using so-cial media, has been functional to manage epidemics. Previous research focused on using discussions during periods of epidemic crises on social media platforms like Twitter, Reddit, or Facebook and developing NLP techniques to filter out important/relevant discussions from a huge corpus of messages and posts. Social media usage varies with internet penetration and other socio-economic factors, which might induce disparity in an-alyzing discussions across different geographies. How-ever, print media is a ubiquitous information source, irrespective of geography. Further, topics discussed in news articles are already ‘newsworthy’, while on social media ‘newsworthiness' is a product of techno-social processes. Developing this fundamental difference, we study Twitter data during the second wave in India focused on six high-population cities with varied macro-economic factors. Through a mixture of qualitative and quantitative methods, we further analyze two Indian newspapers during the same period and compare topics from both Twitter and the newspapers to evaluate sit-uational awareness around the second phase of COVID on each of these platforms. We conclude that factors like internet penetration and GDP in a specific city influence the discourse surrounding situational updates on social media. Thus, augmenting information from newspapers to information extracted from social media would provide a more comprehensive perspective in resource-deficit cities",
"abstracts": [
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"content": "The COVID-19 pandemic required efficient allocation of public resources and transforming existing ways of societal functions. To manage any crisis, governments and public health researchers ex-ploit the information available to them in order to make informed decisions, also defined as situational awareness. Gathering situational awareness using so-cial media, has been functional to manage epidemics. Previous research focused on using discussions during periods of epidemic crises on social media platforms like Twitter, Reddit, or Facebook and developing NLP techniques to filter out important/relevant discussions from a huge corpus of messages and posts. Social media usage varies with internet penetration and other socio-economic factors, which might induce disparity in an-alyzing discussions across different geographies. How-ever, print media is a ubiquitous information source, irrespective of geography. Further, topics discussed in news articles are already ‘newsworthy’, while on social media ‘newsworthiness' is a product of techno-social processes. Developing this fundamental difference, we study Twitter data during the second wave in India focused on six high-population cities with varied macro-economic factors. Through a mixture of qualitative and quantitative methods, we further analyze two Indian newspapers during the same period and compare topics from both Twitter and the newspapers to evaluate sit-uational awareness around the second phase of COVID on each of these platforms. We conclude that factors like internet penetration and GDP in a specific city influence the discourse surrounding situational updates on social media. Thus, augmenting information from newspapers to information extracted from social media would provide a more comprehensive perspective in resource-deficit cities",
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"affiliation": "International Institute of Information and Technology,Hyderabad,Telangana,India",
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"abstract": "With the rise of the internet many new data sources have emerged that can be used to help us gain insights into the cyber threat landscape and can allow us to better prepare for cyber attacks before they happen. With this in mind, we present an end to end real time cyber situational awareness system which aims to efficiently retrieve security relevant information from the social networking site Twitter.com. This system classifies and aggregates the data retrieved and provides real time cyber situational awareness information based on sentiment analysis and data analytics techniques. This research will assist security analysts to evaluate the level of cyber risk in their organization and proactively take actions to plan and prepare for potential attacks before they happen as well as contribute to the field through a cybersecurity tweet dataset.",
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"abstract": "Remanufacturing end-of-use product is considered as one effective way to provide ecologically sustainable production industry. Realizing promising business opportunities of remanufacturing in addition to its contribution in saving the environment, this is the time for manufacturers to consider performing remanufacturing production activities accompanying their existing manufacturing. Including remanufacturing, production system is significantly different from conventional manufacturing production system. Instead of single forward flow of material in conventional supply chain, system now contains two material flows, named conventional manufacturing flow sourcing from new materials, and recovery flow sourcing from end-of-use products returned back to the production system. Therefore, to use current conventional production planning models in remanufacturing/manufacturing production system (RMPS) is questionable, and the optimal structure of the production system is still need to be further explored. This research focuses on this two flows characteristic and the return process that occurred in RMPS. We recognize that return process of end-of-use products forms sort of cyclical, or looping process in the system, that product release (sales to fulfill demands) and return affect each other, and have significant influence for system performance. For optimal production planning, a cyclic optimization approach is introduced here. The basic idea is to simultaneously consider the whole cyclical process in the system that caused by the return of end-of-use products, and allowing product release and return process to be treated as variables to be determined in generating optimal production plan. Besides remanufacturing and manufacturing production activities, disposing or sending excessive returned end-of-use parts (products) to material recycler are also carefully considered in production planning mechanism, along with all respective inventories. Based on the approach, a linear programming model for generating production plan in capacitated RMPS producing multi products with common parts is constructed, and applied in a numerical example. The result shows a superior optimality performance compared to conventional approach, as a merit that the whole cyclical process are now being included in optimal solution generation model.",
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"abstract": "Some of the methodological aspects that emerged during the design of AERPLAN are presented. The system supports the medium term production planning for the seven plants of an aircraft manufacturing company. Given the tremendous amount of possible plans, an effective support must be able to make different kinds of autonomous decisions, to prune alternatives, during the plan formulation. The complexity of these composite decision processes calls for heuristic search approaches since exact methods cannot be pursued in practice. The authors describe the architectural and methodological approach adopted to cope with this open problem within AERPLAN, a system developed for ALENIA.<>",
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"abstract": "A major problem in production planning is to determine when to release products into production to meet forecasted requirements. Riano et al. (2002) proposed the stochastic production planning (SPP) model for a multiperiod, multiproduct system, where the lead time to produce a product may be random. The model determines release times for the products that ensure the requirements in each time period are met with desired probabilities at a minimum cost. We describe how an advanced planning model like SPP can be integrated with discrete event simulation models to make the simulations more realistic and informative. We also compare the performance of the SPP model with the classical MRP (materials requirements planning) model, and with a stochastic variation of the MRP model in a simulation study. The costs associated with the production plans from SPP are about 10% less than the costs from the other two models.",
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"abstract": "Remanufacturing end-of-use product is considered as one effective way to provide ecologically sustainable production industry. Realizing promising business opportunities of remanufacturing in addition to its contribution in saving the environment, this is the time for manufacturers to consider performing remanufacturing production activities accompanying their existing manufacturing. Including remanufacturing, production system is significantly different from conventional manufacturing production system. Instead of single forward flow of material in conventional supply chain, system now contains two material flows, named conventional manufacturing flow sourcing from new materials, and recovery flow sourcing from end-of-use products returned back to the production system. Therefore, to use current conventional production planning models in remanufacturing/manufacturing production system (RMPS) is questionable, and the optimal structure of the production system is still need to be further explored. This research focuses on this two flows characteristic and the return process that occurred in RMPS. We recognize that return process of end-of-use products forms sort of cyclical, or looping process in the system, that product release (sales to fulfill demands) and return affect each other, and have significant influence for system performance. For optimal production planning, a cyclic optimization approach is introduced here. The basic idea is to simultaneously consider the whole cyclical process in the system that caused by the return of end-of-use products, and allowing product release and return process to be treated as variables to be determined in generating optimal production plan. Besides remanufacturing and manufacturing production activities, disposing or sending excessive returned end-of-use parts (products) to material recycler are also carefully considered in production planning mechanism, along with all respective inventories. Based on the approach, a linear programming model for generating production plan in capacitated RMPS producing multi products with common parts is constructed, and applied in a numerical example. The result shows a superior optimality performance compared to conventional approach, as a merit that the whole cyclical process are now being included in optimal solution generation model.",
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"content": "Remanufacturing end-of-use product is considered as one effective way to provide ecologically sustainable production industry. Realizing promising business opportunities of remanufacturing in addition to its contribution in saving the environment, this is the time for manufacturers to consider performing remanufacturing production activities accompanying their existing manufacturing. Including remanufacturing, production system is significantly different from conventional manufacturing production system. Instead of single forward flow of material in conventional supply chain, system now contains two material flows, named conventional manufacturing flow sourcing from new materials, and recovery flow sourcing from end-of-use products returned back to the production system. Therefore, to use current conventional production planning models in remanufacturing/manufacturing production system (RMPS) is questionable, and the optimal structure of the production system is still need to be further explored. This research focuses on this two flows characteristic and the return process that occurred in RMPS. We recognize that return process of end-of-use products forms sort of cyclical, or looping process in the system, that product release (sales to fulfill demands) and return affect each other, and have significant influence for system performance. For optimal production planning, a cyclic optimization approach is introduced here. The basic idea is to simultaneously consider the whole cyclical process in the system that caused by the return of end-of-use products, and allowing product release and return process to be treated as variables to be determined in generating optimal production plan. Besides remanufacturing and manufacturing production activities, disposing or sending excessive returned end-of-use parts (products) to material recycler are also carefully considered in production planning mechanism, along with all respective inventories. Based on the approach, a linear programming model for generating production plan in capacitated RMPS producing multi products with common parts is constructed, and applied in a numerical example. The result shows a superior optimality performance compared to conventional approach, as a merit that the whole cyclical process are now being included in optimal solution generation model.",
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"abstract": "This paper presents a simulation-based method to aid multi-period production capacity planning by quantifying the trade-off between product quality and production cost. The product quality is estimated as the statistical variation from the target performances obtained from the output tolerances of the production machines that manufacture the components. The production cost is estimated as the total cost of owning and operating a production facility during the planning horizon. Given demand forecasts in future production periods, a multi-objective genetic algorithm searches for the optimal types and quantity of the production machines to be purchased during each period, which simultaneously maximize the product quality and minimize the production cost during the entire planning horizon. Case studies on automotive valvetrain production are presented as a demonstration",
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"normalizedAbstract": "The accurate estimation of environment is a precursor to awareness of the situation around subject(s) of interest. It is imperative that awareness leads to better, improved and safer surroundings and in many cases averts disasters. Following clues from human cognitive nature there have been a significant progress in the development of situation awareness (SAW) models and its implementation in wide ranging industrial, medical and defense applications. The information collected, when utilized in hierarchical order of priority, allows for accurate decision making up to certain degree of confidence. The challenges faced in current applications are the dissemination of information and its demonstration to make artificially intelligent decisions when it goes beyond the perception or comprehension of human mind. In this paper a design methodology is detailed related to adaptive situation awareness (SAW), and the components that are required for its development. The features of intelligent visual analytics and its importance in the development of SAW are also explained. Finally an approach is laid out for arriving at an adaptive SAW with the help of visual analytics model in a bottom up approach, starting from data generation, fusion, logical search algorithm, protocol development and using mathematical modeling for probabilistic approach to a certainty based adaptive SAW model.",
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"abstract": "Cognitive radio technology enables secondary users to access licensed spectrum without interfere with the primary user in the network, however, at the same time, it also brings a lot of additional hidden security problems. In order to grasp the attack situation over a wide range when malicious users emulate the primary user to attack the channel timely and accurately, and display the spectrum situation correctly, this paper proposes a PUEA detection-based situation awareness scheme to study the interference situation of malicious users. Decision-makers can know the attack situation over a wide range better, by detecting the energy and location of PUE attacker, building the interference situation, and drawing the interference situation map. This method can separate the energy and position of the primary users from malicious users, so as to improve the accuracy of the spectrum map by fully exploiting the potential of spectrum holes, and improve the safety and system capacity of the channels.",
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"content": "Cognitive radio technology enables secondary users to access licensed spectrum without interfere with the primary user in the network, however, at the same time, it also brings a lot of additional hidden security problems. In order to grasp the attack situation over a wide range when malicious users emulate the primary user to attack the channel timely and accurately, and display the spectrum situation correctly, this paper proposes a PUEA detection-based situation awareness scheme to study the interference situation of malicious users. Decision-makers can know the attack situation over a wide range better, by detecting the energy and location of PUE attacker, building the interference situation, and drawing the interference situation map. This method can separate the energy and position of the primary users from malicious users, so as to improve the accuracy of the spectrum map by fully exploiting the potential of spectrum holes, and improve the safety and system capacity of the channels.",
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"fno": "06694555",
"keywords": [
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"Cognitive Radio Network",
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"affiliation": "Chongqing Key Lab of Mobile Communications Technology, Chongqing University of Posts and Telecommunications, China",
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"title": "A Mobile Visual Analytics Approach for Law Enforcement Situation Awareness",
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"abstract": "The advent of modern smart phones and handheld devices has given analysts, decision-makers, and even the general public the ability to rapidly ingest data and translate it into actionable information on-the-go. In this paper, we explore the design and use of a mobile visual analytics toolkit for public safety data that equips law enforcement agencies with effective situation awareness and risk assessment tools. Our system provides users with a suite of interactive tools that allow them to perform analysis and detect trends, patterns and anomalies among criminal, traffic and civil (CTC) incidents. The system also provides interactive risk assessment tools that allow users to identify regions of potential high risk and determine the risk at any user-specified location and time. Our system has been designed for the iPhone/iPad environment and is currently being used and evaluated by a consortium of law enforcement agencies. We report their use of the system and some initial feedback.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The advent of modern smart phones and handheld devices has given analysts, decision-makers, and even the general public the ability to rapidly ingest data and translate it into actionable information on-the-go. In this paper, we explore the design and use of a mobile visual analytics toolkit for public safety data that equips law enforcement agencies with effective situation awareness and risk assessment tools. Our system provides users with a suite of interactive tools that allow them to perform analysis and detect trends, patterns and anomalies among criminal, traffic and civil (CTC) incidents. The system also provides interactive risk assessment tools that allow users to identify regions of potential high risk and determine the risk at any user-specified location and time. Our system has been designed for the iPhone/iPad environment and is currently being used and evaluated by a consortium of law enforcement agencies. We report their use of the system and some initial feedback.",
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"Mobile Visual Analytics",
"Situation Awareness",
"Public Safety",
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"affiliation": null,
"fullName": "Ahmad M. M. Razip",
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"fullName": "Abish Malik",
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"affiliation": null,
"fullName": "Shehzad Afzal",
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"affiliation": null,
"fullName": "Matthew Potrawski",
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"affiliation": null,
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"fullName": "Yun Jang",
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"abstract": "The radio monitoring knowledge acquisition is one of the important theoretical foundations of knowledge-driven radio regulatory. Adopting the idea of edge computing, seven kinds of radio monitoring knowledge acquisition algorithms based on spectrum engineering and rules were proposed in this paper. By means of studying the method which acquiring multi-dimensional data of radio signals with spectrum sensors, the electromagnetic environment, radio services application status, quantity changes of radio signals in designated directions and other radio monitoring knowledge were obtained. It is very conducive for building the complete radio regulatory knowledge system and is of great practical significance for intelligent radio regulation exploring.",
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"abstract": "Risk handling and evaluation plays an importantrole in optimizing an investment portfolio. This paper's goal isto describe a system that determines, classifies and handles riskassociated to any type of investment based on sentiment analysis, price movement, information related to companies, certain characteristics, the traders confidence level, and by measuring thepotential loss over a certain period of time. This research impliesanalyzing trader's risk, market risk, risk associated to eachevaluated company or financial group, political and governmentalrisk. The system is able to create different types of portfoliooptions based on the investor/trader profile, which is build basedon the user's tolerance to risk (determined by the results froman interactive quiz that the user must complete when entering thesystem). We propose a multi-agent system that uses different typeof data(numerical, textual) in order to choose the appropriate mixof investments in order to minimize the risk and maximize thegain on a stock portfolio. In order to validate the result a systemwas constructed.",
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"abstract": "Based on the Markowitz portfolio model, this paper considered the liquidity of the risk assets, set the minimum expected return rate of investors, and changed the inequality constraint to semi-gradient fuzzy number. Then used the penalty factor to adjust the objective function, taking the maximum liquidity and minimum risk of portfolio as the objectives, we established the Multi-objective portfolio optimization model. Using the weekly return rate and weekly turnover rate data of eight stocks that are typical in several industries, we can get the Pareto optimal solution set of risk assets investment proportion by fuzzy genetic algorithm. Investors can accord to the personal attitude toward return, risk, liquidity to choose better investment combination proportion of risk assets.",
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"abstract": "In software visualization and algorithm animation it is important that advances in system technologies are accompanied by corresponding advances in animation presentations. The authors describe methods for animating three manipulation algorithms, one of the most challenging algorithm animation domains. In particular, they animate operations on pairing heap data structures which are used to implement priority queues. Their animations use tree layout heuristics and smooth transitions for illustrating intermediate algorithm states to promote viewer understanding.<>",
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"abstract": "This article focuses on the distributed state estimation problem for large-scale systems in the presence of data packet drops. The large-scale system is structured in several correlated subsystems in the physical space, and each subsystem only communicates with its neighbors. In particular, the states of different subsystems are measured by different sensors, and the sensor broadcasts measurement information to the subestimator and its neighbors through the lossy communication channel. Thus, subestimators obtain different local information in the presence of data packet drops. In this article, the distributed estimator is designed and the optimal gain is obtained under the minimum mean square error (MMSE) estimation criterion by using local information set. Finally, the effectiveness of the distributed estimator is illustrated by a simulation experiment.",
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"title": "2019 Eighth International Conference of Educational Innovation through Technology (EITT)",
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"title": "Reforming PE Curriculum Evaluation Using Wearable Devices: A Case Study",
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"abstract": "The aim of this study was to explore the possibility of wearable devices to promote students' health and the implications to PE curriculum evaluation. 2765 undergraduates wearing smart wristbands took part in this study and data were recorded by a sever for a whole semester. Two measurements were established based on physical activity and sleep quality. Machine learning tools were used for classification. The results showed that more than half of students finished the PE curriculum tasks and that physical activity level was lower during weekends than weekdays; The participants were later sleep onset times and shorter total sleep times in weekdays compared to weekends; there is a strong negative correlation between physical activity and total sleep period, which indicated that low intensity physical activity(PA) was related to increasing total sleep period. The value of study is that the smart wristbands can be considered as a viable option for monitoring undergraduates' activity levels in interventions and physical fitness programs.",
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"content": "The aim of this study was to explore the possibility of wearable devices to promote students' health and the implications to PE curriculum evaluation. 2765 undergraduates wearing smart wristbands took part in this study and data were recorded by a sever for a whole semester. Two measurements were established based on physical activity and sleep quality. Machine learning tools were used for classification. The results showed that more than half of students finished the PE curriculum tasks and that physical activity level was lower during weekends than weekdays; The participants were later sleep onset times and shorter total sleep times in weekdays compared to weekends; there is a strong negative correlation between physical activity and total sleep period, which indicated that low intensity physical activity(PA) was related to increasing total sleep period. The value of study is that the smart wristbands can be considered as a viable option for monitoring undergraduates' activity levels in interventions and physical fitness programs.",
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"fno": "428800a216",
"keywords": [
"Health Care",
"Learning Artificial Intelligence",
"Pattern Classification",
"Sleep",
"Smart Wristbands",
"Physical Fitness Programs",
"PE Curriculum Evaluation",
"Wearable Devices",
"Sleep Quality",
"Machine Learning Tools",
"Physical Activity Level",
"Education",
"Biomedical Monitoring",
"Monitoring",
"Atmospheric Measurements",
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"authors": [
{
"affiliation": "Southwest University",
"fullName": "Chaohua Gong",
"givenName": "Chaohua",
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{
"affiliation": "Southwest University",
"fullName": "Tao Xie",
"givenName": "Tao",
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"proceeding": {
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"title": "2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM)",
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"title": "Reliability and validity of revised scale -the Coping Strategies Scale after COVID-19 based on SPSS 18.0 and AMOS 22.0",
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"abstract": "A cross-section research was conducted on 1969 participants in February 2020 who were randomly selected from public in China. This study evaluated the reliability and validity of revised scale-the Coping Strategies Scale after COVID-19 (CSSC) by using the sample of 420 Chinese from the research. The purpose of the questionnaire revision was to measure people's coping strategies under the threat of COVID-19. Exploratory factor analyses were performed on 200 participants, and confirmatory factor analysis were on 220 participants. SPSS version 18.0 and AMOS 22.0 were used to analyze the data. Regarding the reliability of the scale, internal consistency revealed acceptable coefficient. The T -test was also used to examine the discrimination of the items. The exploratory factor analysis revealed that the scale was suitable for the application of factor analysis. Confirmatory factor analysis via Amos 22.0 was distinguished three dimensions for CSSC: distract, maintain, and escape (GFI=.96; AGFI=.93; RMR=.07; TLI=.95; NFI=.90; RMSEA=.05). The Cronbach's coefficient of the total scale was.79. The revised CSSC shows appropriate structural validity and relatively appropriate reliability, which can be used to measure coping strategies.",
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"content": "A cross-section research was conducted on 1969 participants in February 2020 who were randomly selected from public in China. This study evaluated the reliability and validity of revised scale-the Coping Strategies Scale after COVID-19 (CSSC) by using the sample of 420 Chinese from the research. The purpose of the questionnaire revision was to measure people's coping strategies under the threat of COVID-19. Exploratory factor analyses were performed on 200 participants, and confirmatory factor analysis were on 220 participants. SPSS version 18.0 and AMOS 22.0 were used to analyze the data. Regarding the reliability of the scale, internal consistency revealed acceptable coefficient. The T -test was also used to examine the discrimination of the items. The exploratory factor analysis revealed that the scale was suitable for the application of factor analysis. Confirmatory factor analysis via Amos 22.0 was distinguished three dimensions for CSSC: distract, maintain, and escape (GFI=.96; AGFI=.93; RMR=.07; TLI=.95; NFI=.90; RMSEA=.05). The Cronbach's coefficient of the total scale was.79. The revised CSSC shows appropriate structural validity and relatively appropriate reliability, which can be used to measure coping strategies.",
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"normalizedAbstract": "A cross-section research was conducted on 1969 participants in February 2020 who were randomly selected from public in China. This study evaluated the reliability and validity of revised scale-the Coping Strategies Scale after COVID-19 (CSSC) by using the sample of 420 Chinese from the research. The purpose of the questionnaire revision was to measure people's coping strategies under the threat of COVID-19. Exploratory factor analyses were performed on 200 participants, and confirmatory factor analysis were on 220 participants. SPSS version 18.0 and AMOS 22.0 were used to analyze the data. Regarding the reliability of the scale, internal consistency revealed acceptable coefficient. The T -test was also used to examine the discrimination of the items. The exploratory factor analysis revealed that the scale was suitable for the application of factor analysis. Confirmatory factor analysis via Amos 22.0 was distinguished three dimensions for CSSC: distract, maintain, and escape (GFI=.96; AGFI=.93; RMR=.07; TLI=.95; NFI=.90; RMSEA=.05). The Cronbach's coefficient of the total scale was.79. The revised CSSC shows appropriate structural validity and relatively appropriate reliability, which can be used to measure coping strategies.",
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"SPSS 18 Software",
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"China",
"Cronbach Coefficient",
"COVID 19",
"Atmospheric Measurements",
"Education",
"Particle Measurements",
"Software Reliability",
"Information Management",
"Resilience",
"Reliability",
"Validity",
"Coping Strategies",
"COVID 19",
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"affiliation": "School of Humanities, Jiangxi University of Traditional Chinese Medicine,Nanchang,China",
"fullName": "Ting Wang",
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"affiliation": "School of Humanities, Jiangxi University of Traditional Chinese Medicine,Nanchang,China",
"fullName": "Xingyu Liu",
"givenName": "Xingyu",
"surname": "Liu",
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{
"affiliation": "School of Public Administration, Nanchang University,Nanchang,China",
"fullName": "Ruochen Wang",
"givenName": "Ruochen",
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"affiliation": "School of Public Administration, Nanchang University,Nanchang,China",
"fullName": "Xinyi Pan",
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{
"affiliation": "School of Public Administration, Nanchang University,Nanchang,China",
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"abstract": "An object model for genome data at all levels of resolution is described. The model was derived by considering the requirements for representing genome related objects in three application domains: genome maps, large-scale DNA sequencing, and exploring functional information in gene and protein sequences. The methodology used for the object-oriented analysis is also described.<>",
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"abstract": "Combination of Chromatin immunoprecipitation (ChIP) and high-throughput sequencing (Seq) is one of the most effective ways for studying the genome-wide binding sites, which helps to understand protein-DNA interactions on a genomic-wide scale. Several algorithms have been proposed to take advantage of ChIP-Seq abilities. However, despite many elaborations, it is still difficult to accurately determine individual peaks corresponding to each binding event. We developed a constrained multi-level thresholding algorithm which has the ability of targeting regions within a user-defined range. We show that out proposed method has higher accuracy in detecting enriched regions by assessing its performance relative to other previously proposed peak finders.",
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"content": "Combination of Chromatin immunoprecipitation (ChIP) and high-throughput sequencing (Seq) is one of the most effective ways for studying the genome-wide binding sites, which helps to understand protein-DNA interactions on a genomic-wide scale. Several algorithms have been proposed to take advantage of ChIP-Seq abilities. However, despite many elaborations, it is still difficult to accurately determine individual peaks corresponding to each binding event. We developed a constrained multi-level thresholding algorithm which has the ability of targeting regions within a user-defined range. We show that out proposed method has higher accuracy in detecting enriched regions by assessing its performance relative to other previously proposed peak finders.",
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"abstract": "We propose a new generative model for layout generation. We generate layouts in three steps. First, we generate the layout elements as nodes in a layout graph. Second, we compute constraints between layout elements as edges in the layout graph. Third, we solve for the final layout using constrained optimization. For the first two steps, we build on recent transformer architectures. The layout optimization implements the constraints efficiently. We show three practical contributions compared to the state of the art: our work requires no user input, produces higher quality layouts, and enables many novel capabilities for conditional layout generation.",
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"content": "We propose a new generative model for layout generation. We generate layouts in three steps. First, we generate the layout elements as nodes in a layout graph. Second, we compute constraints between layout elements as edges in the layout graph. Third, we solve for the final layout using constrained optimization. For the first two steps, we build on recent transformer architectures. The layout optimization implements the constraints efficiently. We show three practical contributions compared to the state of the art: our work requires no user input, produces higher quality layouts, and enables many novel capabilities for conditional layout generation.",
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