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2023 Global conference on Wireless and Optical Technologies, GCWOT 2023

2023 Global Conference on Wireless and Optical Technologies,...

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6th Global conference on Wireless and Optical Technologies, GCWOT 2023

ISBN: (纸本)9798350333718

the proceedings contain 30 papers. the topics discussed include: e-education application using flutter: concepts and methods;performance analysis & latency calculation of cooperative communication protocols;estimation of chromatic dispersion by means of innovative rectification element;warming trends over the major urban centers of Pakistan due to climate change;an energy-efficient communication protocol for power-constrained IoT networks: a deep reinforcement learning approach;implementation of convolutional neural networks deep learning approach to classify melanoma skin cancer;task scheduling in fog computing: parameters, simulators and open challenges;comparative analysis of intrusion detection systems in SDN;design and development of a portable spectrophotometer for glass characterization;linear regression based crop suggestive system for local Pakistani farmers;and applications of machine learning in medicine: current trends and prospects.

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2023 international Future Energy Electronics conference, IFEEC 2023

2023 International Future Energy Electronics Conference, IFE...

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6th international Future Energy Electronics conference, IFEEC 2023

ISBN: (纸本)9798350339888

the proceedings contain 114 papers. the topics discussed include: real-time implementation of online adaptive space vector modulation for a three-level NPC inverter;reliability assessment of selected boost-converter-based three-port DC/DC converters;magnetic field distribution prediction of wireless power transfer based on machine learning;fuzzy-based model predictive control for bidirectional charging of EV: an adaptive weighting factor algorithm;review of data-driven artificial intelligence applications in electric machines and drive systems;enhanced control of photovoltaic voltage regarding mixed conduction modes of power interfaces;recent advances in data preprocessing and machine learning approaches for battery’s state of charge and state of health estimation: a review;power balance of a delta-connected CHB converter with MPC for photovoltaic systems;and boosting efficiency of wireless power transfer in a near-to-receiver manner: metamaterials versus relay coils.

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On the use of AI for 6G Signal Decoding in DVB - S.2 Applications

On the use of AI for 6G Signal Decoding in DVB - S.2 Applica...

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2024 IEEE conference on Standards for Communications and Networking, CSCN 2024

作者： Christopoulou, Andreani Chaikalis, Costas Kosmanos, Dimitrios Xenakis, Apostolos Chatzimisios, Periklis University of Thessaly Dept. of Digital Systems Larissa Greece International Hellenic University Thessaloniki Greece University of New Mexico AlbuquerqueNM United States

ISBN: (纸本)9798331507428

the use of Artificial Intelligence (AI) techniques and algorithms increases the last few years at all layers of wireless signal processing chain, paving the path towards 6th Generation (6G) networks. In this work, we focus on physical layer and we examine the use of Log - Likelihood Ratio Neural Network (LLRNnet), at the well - known decoding and demodulation receiver processes. Digital Video Broadcasting (DVB) - S. 2 Satellite communications standard covers a variety of modulation and channel coding rates combinations at physical layer. Our work analyzes and compares Packet Error Rate (PER) performance of all these combinations for three decoding options: Neural Network (NN), log - MAP, max log - MAP. Additionally, we examine 3 hidden layer sizes. Our analysis shows that for 16 simulation scenarios derived from the DVB-S. 2 standard, NN and log - MAP exhibit nearly the same PER, verifying the use of NN as a potential decoding option with negligible loss, as compared to traditional options. Finally, the effect of modulation scheme, coding rate and NN size on PER is investigated. © 2024 IEEE.

关键词： Digital video broadcasting (DVB)

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Reinforcement Learning Approaches In Open-Ended Environments 6

Reinforcement Learning Approaches In Open-Ended Environments

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6th international conference on Electrical, Control and Instrumentation Engineering, ICECIE 2024

作者： Hossain, Zakir Ahmed, Nisher Jahan, Sheikh Nusrat Yoshi, Areyfin Mohammed Rohan, Arafat College of Engineering and Computer Science California State University NorthridgeCA United States College of Engineering and Technology Westcliff University IrvineCA United States International American University Business Administration in Business Analytics Los AngelesCA United States Naveen Jindal School of Management The University of Texas at Dallas RichardsonTX United States

ISBN: (纸本)9798350380040

Reinforcement learning (RL) has traditionally excelled in well-defined environments with clear objectives and boundaries. However, the growing interest in open-ended environments, where the rules, goals, and dynamics can evolve or remain undefined, has posed significant challenges to conventional RL methodologies. this paper explores the adaptations and innovations in RL that address the unique demands of open-ended environments. Key approaches that we will examine include hierarchical reinforcement learning, intrinsic motivation-driven exploration strategies, meta-learning, and skill discovery without supervision. these methods are analyzed in conjunction with the open-ended goals of the study, which is to address the issues of complexity, uncertainty, and extensiveness inherent in considering the design of the open-ended systems. At the same time, we look at real-world uses in computer games, robotics, and autonomous systems, where RL is already used to deal with changing and uncertain environments. Lastly, we discuss the future directions of the work and the problems that are still not resolved, stating that there is a need for scalable solutions and a multidisciplinary approach in order to harness the maximum potential that RL demonstrates in open-ended situations. © 2024 IEEE.

关键词： Adversarial machine learning

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Artificial Intelligence and Machine Learning. Use Cases for Organizations 4th

Artificial Intelligence and Machine Learning. Use Cases for ...

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4th international conference on Reliable systems Engineering, ICoRSE 2024

作者： Țîțu, Aurel Mihail Toderici, Marius Suteu, Dorin Vasile Deac Popa, Maria Stanciu, Andreea Lungu, Florin-Alexandru Faculty of Engineering Industrial Engineering and Management Department "Lucian Blaga" University of Sibiu 10 Victoriei Street Sibiu550024 Romania Faculty of Industrial Engineering and Robotics National University of Science and Technology POLITEHNICA Bucharest Splaiul Independentei No. 313 6th District Bucharest Romania "1 December 1918" University of Alba Iulia Alba Iulia Romania Sos. Pantelimon Nr. 6-8 Sector 2 Bucharest Romania National Research and Development Institute for Cryogenics and Isotopic Technologies - ICSI Uzinei Street No. 4 Ramnicu Valcea240050 Romania Faculty of Power Engineering National University of Science and Technology Politehnica Bucharest Bucharest060042 Romania

ISBN: (纸本)9783031706691

In this paper we present Artificial Intelligence (AI) and how it can be used within an organization. Artificial Intelligence is one of the fastest growing areas of technological development in recent years and is the most important technology of the last decade and probably the next. the term artificial intelligence, encompasses a wide range of technologies and applications today, from expert systems to cognitive algorithms and applications that are able to provide solutions to various more or less complex problems. these technologies are changing the way organizations do business, the way they interact with customers to meet their needs. Artificial intelligence and machine learning help organizations by reducing human effort, improving productivity, processing large amounts of data, automating processes all of which have direct benefits for the organization. In this paper, we will present some of the most important uses of artificial intelligence and machine learning in the areas of marketing, sales, IT operations, security, finance and machine translations. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Adversarial machine learning

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Research and implementation of onboard heterogeneous resource scheduling 5

Research and implementation of onboard heterogeneous resourc...

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5th IEEE international conference on Civil Aviation Safety and Information Technology, ICCASIT 2023

作者： Lu, Xuesong Li, Zhigang Li, Yucheng Tao, Lei Zhou, Xuanwen The 52th Research Institute of Cetc Computing and Recording Systems Division Hangzhou China

ISBN: (纸本)9798350310603

For cutting-edge fields such as aerospace exploration that require high real-time and low power consumption, the scheduling of onboard resources is closely related to the configuration ability and management efficiency of spatial information networks. therefore, designing a reasonable resource scheduling plan has great practical significance. the open-source container orchestration management system represented by Kubernetes cannot fully meet the needs of heterogeneous resource scheduling in onboard environments. It is not lightweight enough for onboard embedded environments, and scheduling strategies have problems such as a large gap between requested and actual resources, and node resource imbalance. therefore, this article proposes a lightweight onboard heterogeneous resource scheduling scheme and designs a resource balancing scheduling algorithm based on historical load. through experiments, it has been shown that this scheme has certain effects in improving the degree of cluster resource balancing and reducing resource waste. © 2023 IEEE.

关键词： Scheduling algorithms

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Research on vegetable automated operation decision-making based on data mining methods using random forest, LSTM-Seq2Seq, and NSGA-II 6

Research on vegetable automated operation decision-making ba...

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6th international conference on Information Science, Electrical, and Automation Engineering, ISEAE 2024

作者： Zhou, Kai Liu, Zhaofeng Ai, Weixi Yang, Qiteng International College Chongqing University of Posts and Telecommunications Chongqing400065 China College of Science Hebei Agricultural University Hebei Baoding071001 China

ISBN: (纸本)9781510682924

Vegetables, characterized by short shelf life and easily perishable features, pose operational challenges for fresh food supermarkets in replenishing and pricing vegetable products within limited sales space. this study proposes an automated decision-making framework based on machine learning, data mining, and intelligent optimization algorithms, using a random forest model for regression prediction and an LSTM-based Seq2Seq model for time series prediction to address these challenges. the random forest model is trained using historical wholesale price data for regression prediction, with an average root mean square error (RMSE) of 0.7046 on the test set. In the time series prediction based on historical sales data, an LSTM-based Seq2Seq model is used, resulting in an average RMSE of 0.9631 on the test set. Subsequently, the random forest model is trained to predict actual sales volume based on the relationship between sales volume, wholesale price, and sales price, combining it with a multi-objective optimization model. the NSGA-II intelligent optimization algorithm is employed to solve the model. Ultimately, we determined various vegetables' sales prices and replenishment quantities by maximizing profits and minimizing supply surplus losses. the method proposed in this study helps improve supermarkets' operational efficiency and profits, providing new insights and methods for fresh food management decision-making. © 2024 SPIE.

关键词： Vegetables

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6^th KidRec Workshop: Information Retrieval systems for Children in the COVID-19 Era 22

6<SUP>th</SUP> KidRec Workshop: Information Retrieval System...

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21st ACM Interaction Design and Children (IDC)

作者： Pera, Maria Soledad Landoni, Monica Murgia, Emiliana Huibers, theo Fails, Jerry Alan Boise State Univ Dept Comp Sci PIReT Boise ID 83725 USA Univ Svizzera Italiana Lugano Switzerland Univ Milano Bicocca Milan Italy Univ Twente Enschede Netherlands Boise State Univ Boise ID USA

ISBN: (纸本)9781450391979

the role that technology plays in supporting children at school and at home is more prominent than ever before due to the global COVID-19 pandemic. this has prompted us to focus the 6(th) international and Interdisciplinary Perspectives on Children & Recommender and Information Retrieval systems (KidRec) workshop on what the lasting changes will be to the design and development of child information retrieval systems. After two years, are information retrieval systems used more in and out of the classroom? Are they more interactive, more or less personalized? What is the impact on the research and business community? Are there long-term and unexpected changes on the design, ethics, and algorithms? the primary goal of our workshop continues to be to build community by bringing together researchers, practitioners, and other stakeholders from various backgrounds and disciplines to understand and advance information retrieval systems for children.

关键词： children information retrieval human-computer interaction classroom search recommendation COVID-19

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10th IFIP international Workshop on Artificial Intelligence for Knowledge Management, AI4KMES 2023

10th IFIP International Workshop on Artificial Intelligence ...

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10th IFIP international Workshop on Artificial Intelligence for Knowledge Management, AI4KMES 2023

ISBN: (纸本)9783031610684

the proceedings contain 17 papers. the special focus in this conference is on Artificial Intelligence for Knowledge Management. the topics include: An Intelligent Chatbot Based on Hybrid Approach Implementing Technical Knowledge to Support Maintenance and Training Activities at Electricity of France (EDF);supporting Food computing with Ontologies and Artificial Intelligence Methods for Sustainability;the Use of Semantic Networks for the Categorization of Prosumers: Expanded Version;methods for Mitigating Gender Bias in Binary Classification Models – A Comparative Analysis;ChatGPT as a Learning Tool in Business Education. Research on Students’ Motivation;integrating Artificial Intelligence into Electric Vehicle Energy systems: A Survey;towards Sustainable Power systems: Exploring the Opportunities of Multi-task Learning for Battery Degradation Forecasting;Classification Tree Based AI System for Short Term Prediction for Heat and Power Plants;the Influence of Neural Networks on Hydropower Plant Management in Agriculture: Addressing Challenges and Exploring Untapped Opportunities;usability of Honeybee algorithms in Practice. Towards Nature-Inspired Sustainable Development;Automatic Coral Morphotypes Detection with YOLO: A Deep Learning Approach for Efficient and Accurate Coral Reef Monitoring;Answering Key Questions About Air Pollution Dynamics in Ho Chi Minh City: A Spatiotemporal Analysis Using the XAI-SHAP Clustering Approach;crowdsourcing as a Tool for Smart City Within Sustainable Development;model of Relationship Between Circular Economy and Industry 5.0;Reduction of Carbon Dioxide Emissions of IT Hardware.

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16th international Symposium on Advanced Vehicle Control, AVEC 2024

16th International Symposium on Advanced Vehicle Control, AV...

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16th international Symposium on Advanced Vehicle Control, AVEC 2024

ISBN: (纸本)9783031703911

the proceedings contain 138 papers. the special focus in this conference is on Advanced Vehicle Control. the topics include: Study on Linear Actuators for Intake and Exhaust systems of Internal Combustion Engines (Analytical Consideration of thrust Characteristics by Permanent Magnet Array);drifting Maneuver Investigation via Phase Plane Analysis of Experimental Data;effects of External Tire Heating on Rolling Resistance Energy Consumption;bifurcation Analysis of a Nonlinear Vehicle Model on Banked Road;regenerative Brake Blending in Electric Hypercars: Benchmarking and Implementation;a Method for Obtaining Reference Friction Values for Validation of Road Friction Estimation algorithms;computing the Lateral Compliance of the Racing Line Using Trajectory Optimization;state Estimation and Sensorimotor Noise in a Driver Steering Model with a Gaussian Process Internal Model;energy Efficiency Oriented Robust Model Predictive Stability Control for Autonomous Electric Vehicles;profile Generation of Cooperative Driving in Urban Intersections for Energetic Evaluation;energetic Impact of Urban Cooperative Driving on the Example of Intersections;speed Control in the Presence of Road Obstacles: A Comparison of Model Predictive Control and Reinforcement Learning;a Geometric Electric Motor Model for Optimal Vehicle Family Design;road Friction Adaptive Lateral Control of Automated Vehicles with Differential Braking;model-Free Automated Reversing of Articulated Heavy Goods Vehicles;nonlinear Dynamics of a Controlled Two-Wheeled Trailer;yaw Stability Control of Vehicles Using a Slip Polytope Validated with Real Tests;Study on Accident-Avoidance Mechanism in Driver-Vehicle System When Activating Level-2 ADAS;motion Control of a 6 × 4 Heavy Vehicle: Autonomous Collision Avoidance Using Integrated Chassis Control.

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