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Block based approach for key frame extraction on large video sequences

ICIC Express Letters, Part B: Applications 2016年第12期7卷 2713-2717页

作者： Tin, Mie Mie Myo, Nyein Nyein Khin, Mie Mie Zin, Thi Thi Myanmar Institute of Information Technology P.O. Box 05053 73rd Street Ngu Shwe War Street Chanmyathazi Township Mandalay05053 Myanmar Information Science Department University of Computer Studies Mandalay Pathangyi Mandalay Myanmar Electrical and System Engineering Faculty of Engineering University of Miyazaki Kibana Campus 1-1 Gakuen Kibanadai-nishi Miyazaki-shi889-2192 Japan

Video segmentation and key frame extraction are very important in real world video systems. Key frames are essential to analyze on large amount of video frame sequences. This paper emphasizes surveillance video and the aim is to extract some meaningful key frames from long video sequences. This purpose is to reduce weak transaction frames in a large video stream by using block base algorithm and cluster the transition video shots. Kullback-Leible divergence method is used in key frame extraction for strong transition video shot. For weak transition video shot, the system will find three candidate key frames and they are compared. Key frames are meaningful frames for video sequences. These frames which represent video streams can be analyzed. Duplicated key frames from the video stream are analyzed in order to be extracted from different shots. Finally, key frames have many assets such as stability, accuracy, and summarize information for a large video. © 2016 ISSN 2185-2766.

关键词： Extraction

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Learning the continuous-time optimal decision law from discrete-time rewards

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National science Open 2024年第5期3卷 130-147页

作者： Ci Chen Lihua Xie Kan Xie Frank Leroy Lewis Yilu Liu Shengli Xie School of Automation Guangdong University of TechnologyGuangdong Key Laboratory of IoT Information TechnologyGuangzhou 510006China Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of EducationGuangzhou 510006China School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore 111 Center for Intelligent Batch Manufacturing Based on IoT Technology Guangzhou 510006China UTA Research Institute the University of Texas at ArlingtonFort Worth 76118USA Department of Electrical Engineering and Computer Science University of TennesseeKnoxville 37996USA Oak Ridge National Laboratory Oak Ridge 37830USA Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou 510006China

The concept of reward is fundamental in reinforcement learning with a wide range of applications in natural and social *** an interpretable reward for decision-making that largely shapes the system's behavior has always been a challenge in reinforcement *** this work,we explore a discrete-time reward for reinforcement learning in continuous time and action spaces that represent many phenomena captured by applying physical *** find that the discrete-time reward leads to the extraction of the unique continuous-time decision law and improved computational efficiency by dropping the integrator operator that appears in classical results with integral *** apply this finding to solve output-feedback design problems in power *** results reveal that our approach removes an intermediate stage of identifying dynamical *** work suggests that the discrete-time reward is efficient in search of the desired decision law,which provides a computational tool to understand and modify the behavior of large-scale engineering systems using the optimal learned decision.

关键词： continuous-time state and action decision law learning discrete-time reward dynamical systems reinforcement learning

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Electrodynamics of plasma oscillations in semiconductor microdevices with two-dimensional electron channels

Electrodynamics of plasma oscillations in semiconductor micr...

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International Conference on Mathematical Methods in Electromagnetic Theory (MMET)

作者： V.V. Popov O.V. Polischuk G.M. Tsymbalov M.S. Shur W. Knap Institute of Radio Engineering and Electronics (Saratov Division) Russian Academy of Science Saratov Russia Institute of Radio Engineering and Electronics (Saratov Division) Russian Academy of Sciences Zelyonaya 38410019 Saratov Russia Department of Electrical Computer and System Engineering and RPI/IBM Broadband Data Transfer Rensselaer Polytechnic Institute Troy NY USA GES CNRS University of Montpellier 2 Montpellier France

Electromagnetic theory of plasma oscillations in field-effect transistor with two-dimensional electron channel is presented. Two different key electromagnetic problems are considered. They are the problems of diffraction of the plane electromagnetic wave (i) on the slot in infinite perfectly conductive plane, which is bridged by 2D electron channel and (ii) on the perfectly conductive strip, which screens partially an infinite 2D electron sheet located at a given distance from the strip. New physics inherent in these problems is revealed.

关键词： Electrodynamics Electrons Plasma waves Plasma devices Frequency FETs Electromagnetic scattering Plasma properties Electrostatics Impedance

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Clinical validation of single-chamber model-based algorithms used to estimate respiratory compliance

arXiv

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arXiv 2021年

作者： Rehm, Gregory B. Nguyen, Jimmy Gilbeau, Chelsea Bomactao, Marc T. Chuah, Chen-Nee Adams, Jason Department of Computer Science University of California Davis 1 Shields Ave DavisCA95616 United States Department of Respiratory Care University of California Davis Health System Department of Computer and Electrical Engineering University of California Davis 1 Shields Ave DavisCA95616 United States Division of Pulmonary and Critical Care Medicine University of California Davis 4150 V Street Suite 3400 SacramentoCA95817 United States

Non-invasive estimation of respiratory physiology using computational algorithms promises to be a valuable technique for future clinicians to detect detrimental changes in patient pathophysiology. However, few clinical algorithms used to non-invasively analyze lung physiology have undergone rigorous validation in a clinical setting, and are often validated either using mechanical devices, or with small clinical validation datasets using 2-8 patients. This work aims to improve this situation by first, establishing an open, and clinically validated dataset comprising data from both mechanical lungs and nearly 40,000 breaths from 18 intubated patients. Next, we use this data to evaluate 15 different algorithms that use the "single chamber" model of estimating respiratory compliance. We evaluate these algorithms under varying clinical scenarios patients typically experience during hospitalization. In particular, we explore algorithm performance under four different types of patient ventilator asynchrony. We also analyze algorithms under varying ventilation modes to benchmark algorithm performance and to determine if ventilation mode has any impact on the algorithm. Our approach yields several advances by 1) showing which specific algorithms work best clinically under varying mode and asynchrony scenarios, 2) developing a simple mathematical method to reduce variance in algorithmic results, and 3) presenting additional insights about single-chamber model algorithms. We hope that our paper, approach, dataset, and software framework can thus be used by future researchers to improve their work and allow future integration of "single chamber" algorithms into clinical practice. © 2021, CC BY.

关键词： computer programming

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FetalNet: Low-light fetal echocardiography enhancement and dense convolutional network classifier for improving heart defect prediction

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Informatics in Medicine Unlocked 2022年 35卷

作者： Sutarno, Sutarno Nurmaini, Siti Partan, Radiyati Umi Sapitri, Ade Iriani Tutuko, Bambang Naufal Rachmatullah, Muhammad Darmawahyuni, Annisa Firdaus, Firdaus Bernolian, Nuswil Sulistiyo, Deny Intelligent System Research Group Faculty of Computer Science Universitas Sriwijaya Indonesia Doctoral Program Faculty of Engineering Universitas Sriwijaya Indonesia Faculty of Medicine Universitas Sriwijaya Indonesia Division of Fetomaternal Department of Obstetrics and Gynaecology Mohammad Hoesin General Hospital Indonesia

Background: Fetal heart defect (FHD) examination by ultrasound (US) is challenging because it involves low light, contrast, and brightness. Inadequate US images of fetal echocardiography play an important role in the failure to detect FHDs manually. The automatic interpretation of fetal echocardiography was proposed in a previous study. However, the low quality of US images reduces the prediction rate of computer-assisted diagnosis results. Methods: To increase the FHD prediction rate, we propose low-light fetal echocardiography enhancement stacking with a dense convolutional network classifier named “FetalNet.” Our proposed FetalNet model was developed using 460 US images to produce an image enhancement model. The results showed that all raw US images could be improved with satisfactory performance in terms of increasing the peak signal-to-noise ratio of 30.85 dB, a structural similarity index of 0.96, and a mean squared error of 18.16. Furthermore, all reconstructed images were used as inputs in a convolutional neural network to generate the best classifier for predicting FHD. Results: The proposed FetalNet model increased the FHD prediction rate by approximately 25% in terms of accuracy, sensitivity, and specificity and produced 100% predictive negative using unseen data. Conclusions: The proposed deep learning model has the potential to identify FHD accurately and shows potential for practical use in identifying congenital heart diseases in the future. © 2022 The Author(s)

关键词： Congenital heart disease Deep learning Low light image enhancement Ultrasound

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Mining data from simulation of beer production

Mining data from simulation of beer production

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IEEE International Conference on Natural Language Processing and Knowledge engineering (NLP-KE)

作者： Yanbing Ju Aihua Wang Fengchun Zhu Chuanliang Xia School of Management and Economics Beijing Institute of Technology Haidian China Graduate School of Education Peking University Haidian China School of Information and Electrical Engineering Shandong University of Science and Technology Shandong China School of Information Linyi Normal University Shandong China Department of Computer Science Academy of Mathematics and System Sciences Chinese Academy and Sciences Beijing China

Data mining is a methodology for the extraction of knowledge from data, especially, knowledge relating to a problem that we want to solve. Data mining from simulation outputs is performed in this paper, it focuses on techniques for extracting knowledge from simulation outputs for beer production and optimizing devices and labors with certain target. We first set up one simulation model for beer production process and construct optimization objective. Then we set up one data mining model based on witness miner. The mining results show that the model is able to fund important information affecting target, make manager diagnose the bottlenecks of the beer production process, and help manager to make decisions rapidly under uncertainty.

关键词： Data mining Manufacturing systems Delta modulation Testing Technology management Educational technology Clustering algorithms Machine learning algorithms Production systems Analytical models

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Current Problems and Proposed Solutions for the Electronic Commerce Sector

Current Problems and Proposed Solutions for the Electronic C...

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computer science and Emerging Technologies (CSET), International Conference on

作者： Hassan Al Wahshat Riyad Al-Rousan Wafa Abdulkarem Al-Haithami Syarilla Iryani Ahmad Saany Fatma Susilawati Mohamad Rohit Kumar Department of Management Information System Faculty of Business Ajloun National University Ajloun Jordan Department of Virtual and Augmented Reality College of Information Technology University of Petra (UOP) Jordan Faculty of Finance and Administrative Sciences MEDIU Malaysia Faculty of Informatics and Computing UniSZA Malaysia School of Computer Science and Engineering Jain Deemed To Be University Bangalore India

The rapid growth of electronic commerce (e-commerce) has revolutionized the global business landscape, transforming the way consumers and businesses interact, purchase, and sell goods and services. However, this sector faces a myriad of challenges that impede its sustainable growth and development. This research paper critically examines the current problems encountered by the electronic commerce sector and proposes viable solutions to address these issues. The study identifies three major problem areas affecting the sector: (1) Security and Privacy Concerns, (2) Logistics and Supply Chain Bottlenecks, and (3) Customer Experience and Trust. Regarding security and privacy, the proliferation of cyber-attacks, data breaches, and identity theft has eroded consumer confidence, hindering e-commerce adoption. The paper aims to investigate the latest technologies and best practices, such as blockchain, advanced encryption techniques, and robust authentication methods, to fortify e-commerce platforms against cyber threats and safeguard user data. The second problem area, logistics and supply chain bottleneck, poses challenges related to order fulfilment, inventory management, and last-mile delivery. Through an in-depth analysis, the research proposes innovative approaches like utilizing machine learning algorithms for predictive inventory management, integrating Internet of Things (IoT) devices for real-time tracking, and exploring drone and autonomous vehicle deliveries to enhance overall logistics efficiency. The third issue addressed in this paper pertains to customer experience and trust. The inability to tangibly experience products before purchase, coupled with ambiguous return policies, often deters potential customers from engaging in e-commerce transactions. The study delves into augmented reality (AR) and virtual reality (VR) applications to simulate product experiences and advocates for transparent and customer centric return policies. This research paper sheds li

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Strike a Balance in Continual Panoptic Segmentation

arXiv

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arXiv 2024年

作者： Chen, Jinpeng Cong, Runmin Luo, Yuxuan Ip, Horace Ho Shing Kwong, Sam Department of Computer Science City University of Hong Kong Hong Kong School of Control Science and Engineering Shandong University Shandong Jinan China Key Laboratory of Machine Intelligence and System Control Ministry of Education Shandong Jinan China Centre for Innovative Applications of Internet and Multimedia Technologies City University of Hong Kong Hong Kong Lingnan University Hong Kong

This study explores the emerging area of continual panoptic segmentation, highlighting three key balances. First, we introduce past-class backtrace distillation to balance the stability of existing knowledge with the adaptability to new information. This technique retraces the features associated with past classes based on the final label assignment results, performing knowledge distillation targeting these specific features from the previous model while allowing other features to flexibly adapt to new information. Additionally, we introduce a class-proportional memory strategy, which aligns the class distribution in the replay sample set with that of the historical training data. This strategy maintains a balanced class representation during replay, enhancing the utility of the limited-capacity replay sample set in recalling prior classes. Moreover, recognizing that replay samples are annotated only for the classes of their original step, we devise balanced anti-misguidance losses, which combat the impact of incomplete annotations without incurring classification bias. Building upon these innovations, we present a new method named Balanced Continual Panoptic Segmentation (BalConpas). Our evaluation on the challenging ADE20K dataset demonstrates its superior performance compared to existing state-of-the-art methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Distillation

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The Development of Self-Service Application at Martabak Air Mancur Restaurant

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Journal of Physics: Conference Series 2020年第1期1566卷

作者： N T M Sagala Andreas E Putro Department of Information System Faculty of Engineering and Computer Science Krida Wacana Christian University Jakarta Indonesia

The amount of time spent in requesting and waiting for the meal in Martabak Air Mancur restaurant may permanently multiply the number of customers in the line waiting especially during peak hours and on weekend. It will affect the quality service of the restaurant and the loyalty of the customer. From the observation, most of the customers spent a great deal of time making an order when faced with many proportionate choices. The study proposed a system by using self-service technology and the waterfall model. In the beginning, the time needed from making an order to finishing the payment is 15 minutes. The system built can reduce the transaction time to 10 minutes.

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Inception of the Indian Digital Health Mission:Connecting…the…Dots

Health Care Science

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Health Care science 2023年第5期2卷 345-351页

作者： Gerard Marshall Raj Sathian Dananjayan Neeraj Agarwal Department of Pharmacology All India Institute of Medical Sciences(AIIMS)BibinagarHyderabadTelanganaIndia Hospital Management Information System(HMIS) All India Institute of Medical Sciences(AIIMS)BibinagarHyderabadTelanganaIndia School of Computer Science and Engineering Vellore Institute of TechnologyChennaiTamil NaduIndia Department of Community and Family Medicine All India Institute of Medical Sciences(AIIMS)BibinagarHyderabadTelanganaIndia

1|NATIO NAL DIGITAL HEALTH MISSION(NDHM):THE BEGINNING Ever since the National Health Policy,2017 was released,the drive to digitalize the Indian healthcare system has been given more importance,in line with the United Nations'Sustainable Development Goals(SDGs).The Policy empha-sizes the implementation of digital health in all levels of care—primary,secondary,and tertiary—to maintain the continuity of patient *** application of digital technology tools and their integration in all facets of healthcare services is expected to improve the functional efficiency and outcomes of the Indian healthcare system[1].

关键词： Indian maintain sizes

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