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共 6595 条记录，以下是1561-1570 订阅

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Dimensional Reduction Applied to an Intelligent Model for Boost Converter Switching Operation 17th

Dimensional Reduction Applied to an Intelligent Model for...

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17th international conference on Soft computing Models in Industrial and Environmental Applications, SOCO 2022

作者： Fernandez-Serantes, Luis-Alfonso Casteleiro-Roca, José-Luis Novais, Paulo Simić, Dragan Calvo-Rolle, José Luis University of A Coruña CTC CITIC Department of Industrial Engineering A Coruña Ferrol Spain Department of Informatics University of Minho Algoritmi Center Braga Portugal Faculty of Technical Sciences University of Novi Sad Trg Dositeja Obradovića 6 Novi Sad21000 Serbia

ISBN: (纸本)9783031180491

the dimensional reduction algorithms are applied to a hybrid intelligent model that distinguishes the switching operating mode of a boost converter. thus, the boost converter has been analyzed and both operating mode are explained, distinguishing between Hard-switching and Soft-switching modes. then, the dataset is created out of the data obtained from simulation of the real circuit and the hybrid intelligent classification model is implemented. Finally, the dimensional reduction of the input variables is carried out and the results are compared. As result, the proposed model with the applied dimensional reduced dataset is able to distinguish between the HS and SS operating modes with high accuracy. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Boost converter Classification Dimensional reduction Hard-switching Power electronics Soft-switching

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A Hybrid Discrete Symbiotic Organisms Search Algorithm and List-Based Simulated Annealing Algorithm for Traveling Salesman Problem 17th

A Hybrid Discrete Symbiotic Organisms Search Algorithm and L...

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17th international conference on Soft computing Models in Industrial and Environmental Applications, SOCO 2022

作者： Ilin, Vladimir Simić, Dragan Veličković, Marko Garunović, Nemanja Faculty of Technical Sciences University of Novi Sad Trg Dositeja Obradovića 6 Novi Sad21000 Serbia

ISBN: (纸本)9783031180491

A discrete symbiotic organisms search (DSOS) and list-based simulated annealing (LBSA) are new metaheuristic search algorithms used for solving different complex optimization problems. DSOS mimics the symbiotic relationship strategies adopted by organisms in the ecosystem for survival, while LBSA simplify parameter tuning of the simulated annealing algorithm. In this paper, we propose a hybrid algorithm, named DSOS-LBSA, to solve the well-known traveling salesman problem (TSP) which belongs to the class of NP-hard problems. Additionally, an arbitrary insertion algorithm is introduced to produce organisms in the initial ecosystem. the proposed DSOS-LBSA is implemented in the MATLAB environment and it is tested on symmetric and asymmetric instances from TSPLIB. the overall results demonstrate that the proposed DSOS-LBSA offers promising results, particularly for small-size symmetric instances and large-size asymmetric instances. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Traveling salesman problem

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Synergistic Effect of Adaptive Synapse Arrangement and Column-based Decoder in Cortical Learning Algorithm

Synergistic Effect of Adaptive Synapse Arrangement and Colum...

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international Symposium on Soft computing and Intelligent systems (SCIS)

作者： Takeru Aoki Keiki Takadama Hiroyuki Sato Department of Computer and Information Technology Tokyo University of Science 6-3-1 Niijuku Katsushika-ku Tokyo Japan Department of Informatics The University of Electro-Communications 1-5-1 Chofugaoka Chofu Tokyo Japan

the cortical learning algorithm (CLA) is a time-series forecast method designed based on the human neocortex. CLA has memory components named columns. A column synapse links a column to an input data bit. CLA encodes real value input data in each time step into a discrete representation based on column synapse relationships. CLA also represents the data incoming next time step as a discrete representation. A column-based decoder decodes the discrete representation into a real value based on column synapse relationships. therefore, column synapse relationships have a large impact on forecast accuracy. In this work, we propose a CLA introducing an adaptive column synapse arrangement that improves the column synapse relationships for the column-based decoder. We showed that the adaptive column synapse arrangement boosts the forecast accuracy improvement of the column-based decoder on artificial time-series data and real-world electricity load forecast.

关键词： Load forecasting Heuristic algorithms Benchmark testing Prediction algorithms Decoding Synapses

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thE IMPACT OF FINANCIAL DEVELOPMENT AND UNEMPLOYMENT ON POVERTY RATE IN thE CONTEXT OF DIGITAL ECONOMY IN UZBEKISTAN 22

THE IMPACT OF FINANCIAL DEVELOPMENT AND UNEMPLOYMENT ON POVE...

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proceedings of the 6th international conference on Future Networks & Distributed systems

作者： Aziza Usmanova Department of International Business Management Tashkent State University of Economics Uzbekistan

ISBN: (纸本)9781450399050

the aim of this paper is to analyze the impact of financial development index and unemployment rate on poverty rate in Uzbekistan in the context of digital economy. To reach this aim, data covering the period 2000-2021 years was analyzed using correlation analysis and applying Vector Autoregressive (VAR) model. It was revealed that there is a negative association between poverty and financial development as well as poverty and unemployment rate. VAR model showed that in Uzbekistan lags of poverty serve to the increase of the current level of poverty. It was found that financial development does not affect the poverty rate. To analyze the individual effects of variables on poverty, the Granger causality test was conducted, which showed that there is a uni-directional relationship between poverty and unemployment rate. It was revealed that poverty causes the decrease in unemployment rate. As regards the relationship between poverty and financial development, it had a bi-directional character.

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EMERGING thREAT OF DEEP FAKE: HOW TO IDENTIFY AND PREVENT IT 22

EMERGING THREAT OF DEEP FAKE: HOW TO IDENTIFY AND PREVENT IT

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proceedings of the 6th international conference on Future Networks & Distributed systems

作者： Murooj Amer Taha Wijdan Mahood Khudhair Ahmed Mahmood Khudhur Omar Abdulkareem Mahmood Yousif I. Hammadi Riyam Shihab Ahmed Al-husseinawi Ahmed Aziz Department of Computer Engineering Techniques Bilad Alrafidain University College Iraq Department of Communications Engineering University of Diyala Iraq Department of Medical Instruments Engineering Techniques Bilad Alrafidain University College Iraq Department of International Business Management Tashkent State University of Economics Uzbekistan

ISBN: (纸本)9781450399050

Although manipulations of visual and aural media have been around for as long as there have been media, the relatively recent introduction of deep fakes has marked a turning point in the creation of fake information. Deep fakes are automated methods that allow the creation of fake information that is becoming increasingly difficult for human observers to see. these procedures are made possible by the most recent technological advancements in artificial intelligence and deep learning. Deep Learning is a powerful method that is now being implemented in a variety of industries, including natural language processing, computer vision, image processing, and machine vision. Deep fakes are created by the use of deep learning algorithms in order to synthesize and modify photos, videos, or sounds of a person, to the point that human people are unable to discern the fake from the real one. In this article, we present a workable description of deep fakes as well as an outline of the technology that lies underneath them. In order to assist people in thinking about the future of deep fakes, we outline the benefits of the deepfake as well as the potential threats. this study presents a complete analysis of deep fake methods and discusses the most effective strategies for preventing counterfeiting.

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Pioneering AI in UAV-Assisted 6G Networks for the Advancement of Mobile Robotics in Industry 5.0

Pioneering AI in UAV-Assisted 6G Networks for the Advancemen...

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international conference on Contemporary computing and Informatics (IC3I)

作者： Manjunatha S Aswini Sorabh Lakhanpal Bolleddu Devananda Rao Abhinav Srivastava K Smitha Department of Mechanical Engineering New Horizon College of Engineering Bangalore India Department of Computer Science and Engineering Institute of Aeronautical Engineering Hyderabad Telangana India Lovely Professional University Phagwara India Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Telangana India FS University Shikohabad Firozabad India Lloyd Law College Greater Noida Uttar Pradesh India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

New methods are needed to keep up with the fast growth of Industry 5.0 when UAVs are added to 6G networks. this study talks about new ways to make tracking, communication, security, resource sharing, and finding problems better in 6G networks that use unmanned aerial vehicles (UAVs). Using exploration-exploitation loops, the Bellman equation, and dynamic adaptation, the Reinforcement Learning for UAV Navigation method makes decisions that are flexible. Machine Learning is used in Dynamic Network Adaptability to make communication methods better in real time. this makes UAV networks more flexible and efficient. Using AI algorithms to design a secure communication protocol gives great security. Important data is sent safely in 6G networks with UAVs using encryption driven by AI. the Scalable Resource Allocation using Genetic algorithms Algorithm also offers a fresh way of allocating resources, which makes it flexible and scalable for a range of task situations. Anomaly detection in real time is needed for Industry 5.0 apps, and the Real-time Anomaly Detection using Deep Learning Algorithm makes security better. A full test of comparison shows that the suggested options do better in terms of accuracy, dependability, freedom, and openness. the pictures support the idea that the suggested options are better than the current ones. A research paper on Reinforcement Learning for UAV Navigation focuses on the exploration-exploitation, dynamic adaptation, and Bellman equation use of the method. Overall, these options give you all the tools you need to make UAV activities better over 6G networks in Industry 5.0. they make it easier to use UAVs in many situations by encouraging flexible choices, smart use of resources, safe contact, and instant discovery of strange events.

关键词： 6G mobile communication Navigation Reinforcement learning Autonomous aerial vehicles Real-time systems Mathematical models Security Resource management Fifth Industrial Revolution Vehicle dynamics

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MODELING AND CREATING SOFTWARE FOR thE OPTIMAL MANAGEMENT OF PASTURE RESOURCES IN thE CONTEXT OF thE DIGITAL ECONOMY 22

MODELING AND CREATING SOFTWARE FOR THE OPTIMAL MANAGEMENT OF...

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proceedings of the 6th international conference on Future Networks & Distributed systems

作者： Janibek Kazievish Saukhanov Sabit Nietalievich Gabbarov Rashid Nietalievich Jaksibaev Zoya Kalekeva Department of International Business Management Karakalpak State University Uzbekistan Department of International Business Management Distance education system of Nukus Mining institute Uzbekistan Department of International Business Management Tashkent institute of irrigation and agricultural mechanization engineers Uzbekistan Department of Finance Tashkent State University of Economics Uzbekistan

ISBN: (纸本)9781450399050

In this article, the Kungirot region with the largest area in the Republic of Karakalpakstan, the optimal use of the available land and fodder fund for raising livestock in this area, the option of forming its composition, practical and scientific recommendations are given. A comparative analysis of cattle, cows, sheep and goats, horses, camels was evaluated on the basis of a correlation-regression analysis of the efficiency of pasture use by the number of livestock. Using statistical data for 1990-2021, forecasts were developed using the ARIMA model."the Pasture Livestock Efficiency Program" was created to solve the problem of forming the optimal composition of the livestock based on the available opportunities for using pastures using digital technologies.

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Individual's intention to subscribe to freemium music streaming services: A conceptual framework 13

Individual's intention to subscribe to freemium music stream...

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13th IADIS international conference ICT, Society and Human Beings 2020, ICT 2020 and 6th IADIS international conference Connected Smart Cities 2020, CSC 2020 and 17th IADIS international conference Web Based Communities and Social Media 2020, WBC 2020, Part of the 14th Multi conference on Computer Science and Information systems, MCCSIS 2020

作者： Mohamed, Norshidah Haghshenas, Hanif College of Business Administration Prince Sultan University P.O. Box 53073 Riyadh11586 Saudi Arabia Azman Hashim International Business School Universiti Teknologi Malaysia Jalan Sultan Yahya Petra Kuala Lumpur54100 Malaysia

ISBN: (纸本)9789898704191

While the music industry continues to undergo through significant revolution, the last few years show that growth in freemium music streaming services continue to be noteworthy, in particular, in the American music industry. the research aspires to gain insights into individual's intention to subscribe to freemium music streaming services. this paper reports a research in progress. the research integrates the theory of Reasoned Action, Dual Mediation Hypothesis, Motivation theory, and Social Identity theory to develop a conceptual framework toward explaining individual's intention to subscribe to freemium music streaming services. © proceedings of the 13th IADIS international conference ICT, Society and Human Beings 2020, ICT 2020 and proceedings of the 6th IADIS international conference Connected Smart Cities 2020, CSC 2020 and proceedings of the 17th IADIS international conference Web Based Communities and Social Media 2020, WBC 2020 - Part of the 14th Multi conference on Computer Science and Information systems, MCCSIS 2020. All rights reserved.

关键词： Information systems

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6th international Workshop on Ophthalmic Medical Image Analysis, OMIA 2019, held in conjunction with the 22nd international conference on Medical Imaging computing and Computer-Assisted Intervention, MICCAI 2019

6th International Workshop on Ophthalmic Medical Image Analy...

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6th international Workshop on Ophthalmic Medical Image Analysis, OMIA 2019, held in conjunction with the 22nd international conference on Medical Imaging computing and Computer-Assisted Intervention, MICCAI 2019

ISBN: (纸本)9783030329556

the proceedings contain 22 papers. the special focus in this conference is on international Workshop on Ophthalmic Medical Image Analysis, held in conjunction with the international conference on Medical Imaging computing and Computer-Assisted Intervention. the topics include: Aggressive Posterior Retinopathy of Prematurity Automated Diagnosis via a Deep Convolutional Network;structure-Aware Noise Reduction Generative Adversarial Network for Optical Coherence Tomography Image;Fovea Localization in Fundus Photographs by Faster R-CNN with Physiological Prior;multi-discriminator Generative Adversarial Networks for Improved thin Retinal Vessel Segmentation;encoder-Decoder Attention Network for Lesion Segmentation of Diabetic Retinopathy;An Improved MPB-CNN Segmentation Method for Edema Area and Neurosensory Retinal Detachment in SD-OCT Images;Network Pruning for OCT Image Classification;fundus Image Based Retinal Vessel Segmentation Utilizing a Fast and Accurate Fully Convolutional Network;the Channel Attention Based Context Encoder Network for Inner Limiting Membrane Detection;robust Optic Disc Localization by Large Scale Learning;u-Net with Spatial Pyramid Pooling for Drusen Segmentation in Optical Coherence Tomography;deriving Visual Cues from Deep Learning to Achieve Subpixel Cell Segmentation in Adaptive Optics Retinal Images;preface;Dictionary Learning Informed Deep Neural Network with Application to OCT Images;Shape Decomposition of Foveal Pit Morphology Using Scan Geometry Corrected OCT;semi-supervised Adversarial Learning for Diabetic Retinopathy Screening;3D-CNN for Glaucoma Detection Using Optical Coherence Tomography;guided M-Net for High-Resolution Biomedical Image Segmentation with Weak Boundaries;foveal Avascular Zone Segmentation in Clinical Routine Fluorescein Angiographies Using Multitask Learning;An Amplified-Target Loss Approach for Photoreceptor Layer Segmentation in Pathological OCT Scans.

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Digital Twin-based Dynamic Resource Provisioning Using Deep Q-Network on 6G-enabled Mobile Edge Networks

Digital Twin-based Dynamic Resource Provisioning Using Deep ...

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international Communication systems and Networks and Workshops, COMSNETS

作者： Suja A. Alex Neha Singh Mainak Adhikari Department of Information Technology St. Xavier’s Catholic College of Engineering Nagercoil India Department of Computer Science Indian Institute of Information Technology Lucknow Lucknow India School of Data Science Indian Institute of Science Education and Research Thiruvananthapuram Thiruvananthapuram India

ISBN: (数字)9798331531195

ISBN: (纸本)9798331531201

the advancement of Digital Twin (DT) technology has enabled the creation of digital replicas of physical entitics, significantly enhancing the functionality and performance of mobile networks. However, this innovative approach also introduces considerable overload and performance challenges for mobile edge networks. To address these issucs, we propose a novel DT-enabled edge architecture for 6G-capable technology, employing a dynamic resource allocation strategy. the proposed approach, termed DT-based Dynamic Resource Provisioning (DT-DRP), leverages the capabilities of DT technology and Decp Reinforcement Learning (DRL) to dynamically allocate incoming tasks from mobile devices to edge devices. An intelligent DT server facilitates this allocation, optimizing resource use and improving network performance. the predictive capabilities of the framework are validated using the K-Nearest Neighbor (KNN) dlassifier at the edge network. Experimental results demonstrate that the proposed DT-DRP framework incorporates mobile devices into the DT network scamlessly, achieving superior performance in terms of minimum latency and high accuracy compared to bascline Q-learning algorithms across two medical datasets and various exccution scenarios. this research underscores the potential of DT technology in 6G networks and highlights its efficacy in enhancing mobile edge computing performance through intelligent resource management.

关键词： Performance evaluation 6G mobile communication Training Analytical models Nearest neighbor methods Dynamic scheduling Mobile handsets Resource management Servers Time factors

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