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Analysis and Treatment of Missing Data in Happiness Score Using Machine Learning 21

Analysis and Treatment of Missing Data in Happiness Score Us...

21st IEEE International Conference on Smart Communities: Improving Quality of Life using AI, Robotics and IoT, HONET 2024

作者： Touati, Wassim El Touati, Yamen Hadj-Alouane, Nejib Ben Jemai, Abderrazek Polytechnic School of Tunisia Carthage University SERCOM Laboratory Tunis Tunisia Northern Border University Faculty of Computing and Information Technology Department of Computer Science Saudi Arabia ENIT University of Tunis EI Manar OASIS Laboratory Tunisia American University in Dubai Electrical Engineering and Computer Engineering Department Dubai United Arab Emirates

ISBN: (纸本)9798350378078

Machine learning, a vital part of artificial intelli-gence, improves our ability to make predictions from complex data. The success of these predictions relies heavily on the model's fit with its data and the data's consistency. Accurate predictions depend on closely matching the model to the data patterns. However, missing data can seriously disrupt the accuracy of predictions, causing errors. To address this, we recommend adopting a proposed framework that enhances predictions by effectively filling in missing data. Our objective is to refine the accuracy of our predictions, especially in scenarios where the data might be incomplete and features exhibit patterns of dependency. In the context of missing data, our approach concentrates on enhancing regression performance to minimize the effects of missing data as effectively as possible. © 2024 IEEE.

关键词： Adversarial machine learning

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A Wireless Charging System with Bipolar Partial Power Conversion for 400V/800V EV Battery 50

A Wireless Charging System with Bipolar Partial Power Conver...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Wu, Muxing Iam, Io-Wa Gong, Cheng Lam, Chi-Seng State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau China Institute of Microelectronics University of Macau China Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau China

ISBN: (纸本)9781665464543

Currently, electric vehicle (EV) battery platforms typically vary in standard, commonly rated at either 800V or 400V. Conventional wireless charging system (WCS) are limited to single voltage level charging, necessitating wireless communication or additional complex circuits for achieving multi-voltage level charging, which can compromise operational stability and overall efficiency. This article proposes a WCS based on the concept of bipolar partial power conversion. By incorporating reversing series switches on the secondary of the DC/DC converter, regulation voltage control enables switching between positive and negative polarity to supply power to either 800V or 400V battery for EV. This approach ensures high power transmission efficiency, without relying on wireless communication, thereby ensuring stable charging process. Furthermore, this article also presents various combinations of bipolar topologies that can be selectively employed based on application requirements. Finally, simulation results validate the feasibility of the proposed 3.2KW WCS. © 2024 IEEE.

关键词： State of charge

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Model Predictive Robust Control for A Capacitive-Coupling Grid-Connect Inverter (CGCI) in Power Quality Compensation 50

Model Predictive Robust Control for A Capacitive-Coupling Gr...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Chan, Pak-Ian Sou, Wai-Kit Lam, Chi-Seng State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau China Institute of Microelectronics University of Macau China Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau China

ISBN: (纸本)9781665464543

In this paper, a model predictive robust control (MPRC) is proposed for a three-phase capacitive-coupling grid-connect inverter (CGCI) to improve the power quality compensation performance under deviating system parameters. A detail stability study and parameter design of the proposed MPRC is provided, while the robustness and power quality compensation performance of the proposed MPRC are verified by the simulation in comparison to the conventional model predictive control (MPC). © 2024 IEEE.

关键词： Predictive control systems

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Comprehensive Overview of Multi-agent Systems for Controlling Smart Grids

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CSEE Journal of Power and Energy Systems 2022年第1期8卷 115-131页

作者： Om Prakash Mahela Mahdi Khosravy Neeraj Gupta Baseem Khan Hassan Haes Alhelou Rajendra Mahla Nilesh Patel Pierluigi Siano Power System Planning Division Rajasthan Rajya Vidyut Prasaran Nigam Ltd.Jaipur-302005India Media Integrated Communication Laboratory Graduate School of EngineeringOsaka UniversityOsakaJapan Computer Science and Engineering Department Oakland UniversityRochesterUSA Department of Electrical and Computer Engineering Hawassa UniversityHawassa 1530Ethiopia Faculty of Mechanical and Electrical Engineering Tishreen UniversityLattakiaSyria Department of Electrical Engineering National Institute of Technology Kurukshetra Department of Management&Innovation Systems University of Salerno84084 SalernoItaly

Agents are intelligent entities that act flexibly and autonomously and make wise decisions based on their intelligence and experience.A multi-agent system(MAS)contains multiple,intelligent,and interconnected collaborating agents for solving a problem beyond the ability of a single agent.A smart grid(SG)combines advanced intelligent systems,control techniques,and sensing methods with an existing utility power *** controlling smart grids,various control systems with different architectures have already been ***-based control of power system operations has been shown to overcome the limitations of time required for analysis,relaying,and protection;transmission switching;communication protocols;and management of plant *** systems provide an alternative for fast and accurate power network *** paper provides a comprehensive overview of MASs used for the control of smart *** paper provides a wide-spectrum view of the status of smart grids,MAS-based control techniques and their implementation for the control of smart *** of MASs in the control of various aspects of smart grids-including the management of energy,marketing energy,pricing,scheduling energy,reliability,network security,fault handling capability,communication between agents,SG-electrical vehicles,SG-building energy systems,and soft grids—have been critically *** than a hundred publications on the topic of MAS-based control of smart grids have been critically examined,classified,and arranged for fast reference.

关键词： Coordinated control multi-agent systems renewable energy sources smart energy infrastructure smart grid

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Retinal disorder diagnosis based on hybrid deep learning models

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Multimedia Tools and Applications 2025年 1-25页

作者： Sedik, Ahmed El-Shafai, Walid El-Hag, Noha A. El-Banby, Ghada M. Abd El-Samie, Fathi E. Smart Systems Engineering Laboratory College of Engineering Prince Sultan University Riyadh11586 Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial Intelligence Kafrelsheikh University Kafr el-Sheikh Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt The Higher Institute of Commercial Sciences Algarbia Al Mahalla Al Kubra31951 Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Anomaly detection from medical images is badly needed for automated diagnosis. For example, medical images obtained with several modalities, such as magnetic resonance (MR) and confocal microscopy, need to be classified for anomaly detection. The MR images may contain tumors that need to be detected with anomaly detection techniques. In MR imaging, brain tumors are represented as areas composed of abnormal cells that need to be detected. On the other hand, confocal microscopy can be used for retinal imaging. Hence, there is a need to apply classification techniques for diagnosing diseases of the eye, such as Diabetic Retinopathy (DR), which leads to exudates in different regions of the retina. The detection of exudates is necessary for the diagnosis of DR. In this paper, two models are presented for the classification of MR and retinal images. Much research has been done in this area, but it did not achieve high accuracy of classification in an acceptable time. In addition, the previous models did not consider both types of image modalities considered in this paper. The suggested models are Convolutional Neural Network (CNN) and Convolutional Long Short-Term Memory (Conv-LSTM). They are used to classify normal and abnormal cases of both brain tumor and DR diseases. The CNN model is composed of six convolutional layers and six max-pooling layers. A soft-max activation function takes the classification decision. The proposed Conv-LSTM model is composed of three stages: pre-processing, feature extraction, and classification. The deep learning model performance is better than those of traditional networks. The CNN gives an accuracy of 94.26% for DR classification and 95.8% for brain tumor classification, while the Conv-LSTM gives the maximum accuracy of 96.41% for DR classification and 97.4% for brain tumor classification. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Confocal microscopy

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Studying the Role of Non-Player Users (Spectator and Operator) in XR Single and Multiplayer Experiences

Studying the Role of Non-Player Users (Spectator and Operato...

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International Conference on Cognitive Infocommunications (CogInfoCom)

作者： Uršul'a Žákovská David Sedláček Department of Computer Graphics and Interaction Faculty of Electrical Engineering Czech Technical University in Prague Czech Republic

This paper presents a study on non-player users (NPUs) in experiences where active users (players) use Virtual Reality (VR), Augmented reality (AR) or any other spectrum of Extended Reality (XR). The spectator, a type of NPU, is hidden from players and does not actively participate in the virtual environment but observes the world and the activities of other users to understand their behaviour further, while the operator, another type of NPU, can manipulate the virtual environment without participating in the gameplay and is responsible for a smooth run of the experience. Both types can be implemented in AR or VR but usually have a desktop design. In most XR experiences, the presence of NPUs is unnecessary due to the nature of the application leading to the user base being composed of only players. However, in cases like location-based entertainment, XR training, or onboarding new hires, NPUs can significantly improve the process. The study examines the impact of NPUs on the user experience and the potential benefits and drawbacks of including them in XR experiences. Specifically, in a VR multi-user experience for assessing soft skills, the study found that with a desktop mode of the spectator, the preset camera views, timestamped notes, and audio activity visualization were the most appreciated functionalities.

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Spatial Quality Assessment of Pansharpened Images Based on Gray Level Co-Occurrence Matrix 12

Spatial Quality Assessment of Pansharpened Images Based on G...

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12th Iranian/2nd International Conference on Machine Vision and Image Processing, MVIP 2022

作者： Aghapour Maleki, Shiva Ghassemian, Hassan Tarbiat Modares University Image Processing and Information Analysis Laboratory Faculty of Electrical and Computer Engineering Tehran Iran

ISBN: (纸本)9781665412162

Assessing the quality of pansharpened images is a critical issue in order to obtain a quantitative score to represent the quality and compare the performance of different fusion methods. Most of the introduced metrics for pansharpened image quality assessment, evaluate the spectral content of the image, while in different applications of remote sensing like detection and identification of image objects, spatial quality has an important role. In the current study, a new index for spatial quality assessment is introduced that extracts gray level co-occurrence matrix (GLCM) from distorted and reference images and compares the similarities of these features. The tempere image database 2013 (TID2013) that provides reference and different types of distorted images with subjective scores of each image is used as the desired database. To solve the high computational complexity of obtaining GLCM features, the fast GLCM method is employed. In this way, 16 different features are extracted. To select the features that have the most consistency with the human visual system (HVS), the forward floating search method is used as a feature selection method and five features are obtained as the final features to form the desired index. Experimental results show the efficiency of the proposed method in determining the spatial quality of fused images compared with that of the available quality assessment metrics. © 2022 IEEE.

关键词： Remote sensing

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Smart transmission matrix measurement of multimode fibers using digital holography and deep learning for confidential data transmission

Smart transmission matrix measurement of multimode fibers us...

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Digital Holography and Three-Dimensional Imaging, DH 2022

作者： Rothe, Stefan Zhang, Qian Pohle, Dennis Koukourakis, Nektarios Czarske, Juergen W. TU Dresden Faculty of Electrical and Computer Engineering Laboratory of Measurement and Sensor System Technique Dresden01062 Germany

We present smart measurements of the transmission matrix of multimode fibers (MMF). The modal crosstalk of the MMF is exploited by authorized communication participants against an eavesdropper towards physical layer s... 详细信息

ISBN: (纸本)9781957171128

关键词： Multimode fibers

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Towards a Longitudinal Comparison Between Different Strategies for Android Malware Detection 3

Towards a Longitudinal Comparison Between Different Strategi...

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3rd International Conference on Theoretical and Applicative Aspects of computer Science, ICTAACS 2023

作者： Mesbah, Abdelhak Baddari, Ibtihel Riahla, Mohamed Amine University m'Hamed Bougara of Boumerdes Faculty of Sciences Limose Laboratory Department of Computer Science Boumerdes Algeria University m'Hamed Bougara of Boumerdes Faculty of Technology Limose Laboratory Department of Electrical Systems Engineering Boumerdes Algeria

ISBN: (纸本)9798350385854

The growing popularity of the Android platform makes it a target of malware authors. The effective identification of such malware is an ongoing challenge. Several methods using machine learning have been proposed to prevent this threat. These methods are usually conventionally evaluated without considering the extent of performance over time. Given the evolving nature of both malware and benign apps, conventional evaluation may lack information. To imitate reality, this study compares the longitudinal performance of different machine learning models, using different strategies that combine permissions and API calls as features extracted through static analysis. Thus, to determine which strategy of features on which classifier are most effective to characterize malware for building a robust malware detector. To achieve this goal, on the one hand, we use a large real-world app set consisting of 100K (50k benign, 50k malware) apps date-labeled, collected across ten years, first seen between 2013 and 2022. On the other hand, each feature's strategy is fed into five classifiers (i.e., SVM, RF, LR, DT, and ANN), using old apps for the training and new apps for the evaluation. Among the assessed machine learning models, the SVM achieves the most promising results over time by employing the combination strategy of the high difference usage of API calls and permissions. © 2023 IEEE.

关键词： Static analysis

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FAST CHARGING ELECTRIC BUSES IN MARIBOR: A COMPARATIVE ANALYSIS OF SIMULATION AND REAL-WORLD RESULTS 12th

FAST CHARGING ELECTRIC BUSES IN MARIBOR: A COMPARATIVE ANALY...

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12th International Conference on Environmental engineering, ICEE 2023

作者： Klemenčič, Mitja Španer, Marijan Lep, Marjan Moharić, Matej Department of Transportation Engineering Faculty of Civil Engineering Transportation Engineering and Architecture University of Maribor Smetanova 17 Maribor Slovenia Laboratory for Power Electronics Institute of Robotics Faculty of Electrical Engineering and Computer Science University of Maribor Koroška cesta 46 Maribor Slovenia

This paper presents a study of the energy consumption of a full electric bus charged at a fast-charging station with pantographs in the city of Maribor. The results of simulated and real tests on the PT line 6 are compared and analysed. The partly electrified PT line 6 provides insights on comparison between simulated energy consumption and re-al-life energy consumption, charging time and reliability of charging. The results reveal that the simulation considered several important factors like real life turnaround time, driving cycle, regenerative braking, charging time, peak hour charging time, heating/cooling systems, full passenger load as important and critical to identify the appropriate concept for charging. Technical and operational errors were identified in real world, due to connectivity failures or driver errors in positioning the vehicle, which were not considered in the simulation. The real-world data and procedure for selection of the most appropriate charging technology represent a good basis for full electrified Public Transport in Maribor. © 2023 The Author(s). Published by Vilnius Gediminas Technical University.

关键词： Electric buses

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