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检索条件"任意字段=7th International Conference on Algorithms, Computing and Systems, ICACS 2023"

共 249 条记录，以下是91-100 订阅

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Robot Path Planning using Rapidly-Exploring Random Trees: A Membrane computing Approach 7

Robot Path Planning using Rapidly-Exploring Random Trees: A ...

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7th international conference on Computers Communications and Control (ICCCC)

作者： Perez-Hurtado, Ignacio Perez-Jimenez, Mario J. Zhang, Gexiang Orellana-Martin, David Univ Seville Dept Comp Sci & Artificial Intelligence Res Grp Nat Comp Seville Spain Southwest Jiaotong Univ Sch Elect Engn Chengdu Sichuan Peoples R China

ISBN: (纸本)9781538619346

Methods based on Rapidly-exploring Random Trees (RRTs) have been in use in robotics to solve motion planning problems for nearly two decades. On the other hand, in the membrane computing framework, models based on Enzymatic Numerical P systems (ENPS) have been applied to robot controllers. these controllers handle the power of motors according to motion commands usually generated by planning algorithms, but today there is a lack of planning algorithms based on membrane computing for robotics. With this motivation, we provide a new variant of ENPS called Random Enzymatic Numerical P systems with Proteins and Shared Memory (RENPSM) addressed to implement RRT algorithms and we illustrate it by presenting a model for path planning of mobile robots based on the bidirectional RRT algorithm. A software for RENPSM has been developed within the Robot Operating System (ROS) and simulation experiments have been conducted by means of the Pioneer 3-DX robot simulation platform.

关键词： Robot kinematics Path planning Robot sensing systems Mobile robots Planning Numerical models

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HASP: High Availability SFC Placement Approach in Data Center Network 23

HASP: High Availability SFC Placement Approach in Data Cente...

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23rd IEEE international conference on High Performance computing and Communications, 7th IEEE international conference on Data Science and systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Xu, Ziqi Han, Qingmian Cheng, Bo Niu, Meng Chen, Junliang Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology China The 54th Research Institute of China Electronics Technology Group Corporation Beijing China

ISBN: (纸本)9781665494571

Network Function Virtualization (NFV) is a promising technology that decouples network functions from the hardware. Virtual Network Functions (VNFs) can form service function chains (SFCs) and be orchestrated like internet applications. However, there are higher availability requirements for SFCs because the network's failure causes more severe consequences. this paper proposes the High Availability SFC Placement Approach (HASP) for SFC placement in Data Center. HASP includes a cross-backup (CB) model to improve the availability of SFCs. the software runs on the physical machine (PM), and once the PM fails, the software assigned to it will also fail. the CB model adopts offsite redundant VNF instances to avoid PM failure and guarantee SFC availability. HASP also considers the impact of data link reliability on SFC availability. In addition, a heuristic limited area search optimization (LASO) algorithm is incorporated to place the VNFs of SFCs. the evaluation results show that the LASO algorithm is 300% faster than the traditional heuristic algorithm. Combining the CB model and the LASO algorithm, HASP can improve the availability of SFCs and obtain the optimal placement scheme. © 2021 IEEE.

关键词： Data centers Smart cities Service function chaining Heuristic algorithms Software algorithms Software Network function virtualization

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Bird Call Recognition using Acoustic based Feature Selection approach in Machine Learning 7

Bird Call Recognition using Acoustic based Feature Selection...

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2023 7th international conference On computing, Communication, Control And Automation, ICCUBEA 2023

作者： Mishra, Shivam Ghatak, Rumpa Singh, Vishal Kumar Singh, Shivam Kumar Mahato, Anisha Information Technology Techno International New Town Kolkata India

ISBN: (纸本)9798350304268

the recognition of bird calls has been a challenging task in the field of bioacoustics. With the advancement of machine learning algorithms, automatic bird call recognition has become an active research area. In this paper, acoustic feature selection is used which involves the extraction of relevant features from audio recordings of bird calls. then different classification algorithms are explored for the recognition of the bird calls. Evaluation of the approach is done on a dataset consisting of recordings from multiple bird species and compared it with other state-of-the-art machine learning algorithms. this research has the potential to contribute to the conservation of bird species and their habitats by enabling the efficient monitoring of bird populations. the data is classified into four different classes (namely Astfly, Bulori, Warvir and Woothr). All of which is found in the depths of Amazon Rainforest. © 2023 IEEE.

关键词： acoustic features bird call recognition machine learning

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Diffusion LMS algorithms for Sensor Networks over Non-ideal Inter-sensor Wireless Channels

Diffusion LMS Algorithms for Sensor Networks over Non-ideal ...

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7th IEEE international conference on Distributed computing in Sensor systems (DCOSS)

作者： Abdolee, Reza Champagne, Benoit McGill Univ Montreal PQ H3A 2A7 Canada

ISBN: (纸本)9781457705137

In this paper, we propose diffusion-based least mean square (LMS) algorithms that are robust against fading phenomena in wireless channels. the proposed algorithms, developed by combining diffusion LMS and classical estimation approaches, are able to estimate and update the underlying system parameters at each node by exploiting the sensor measurements and the fused data obtained from the neighboring nodes. the fusion of the information at each node takes place based on a convex combination strategy whose coefficients are determined according to the channel state information, the noise statistics and the output error of the local adaptive filter. In this work, we assume the broadcast data from the sensors experience Rayleigh fading and are further contaminated by the additive noise. Numerical results demonstrate the efficiency of the proposed algorithms and show their satisfactory performance compared with the costly centralized adaptive techniques.

关键词： Distributed adaptive algorithms wireless sensor networks diffusion cooperative strategy non-ideal inter-sensor channels

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Secured Framework for Banking Chatbots using AI, ML and NLP 7

Secured Framework for Banking Chatbots using AI, ML and NLP

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7th international conference on Intelligent computing and Control systems, ICICCS 2023

作者： Chanda, Rajat Prabhu, Sandeep Symbiosis Institute of Digital and Telecom Management Aff. Symbiosis InternationalDeemed University Pune India

ISBN: (纸本)9798350397253

Artificial intelligence (AI) Machine Learning (ML), and Natural Language Processing (NLP)are being employed in a growing number of sectors and is evolving as the technology of the future. It has been widely used to improve the quality of decision-making and problem-solving. this research study proposes a secured framework for banking chatbots using AI-ML and NLP. the framework based on qualitative in-depth experts interviews can be used for developing efficient chartbots for managing customer interactions of various data forms. AI enabled chatbots involves use of machine learning algorithms that can communicate with consumers in a conversational manner. AI enabled chatbots can speak common man's language language and utilize voice as a user interface. Chatbots are used in the public and private sectors to provide virtual help in areas such as telecommunications, media, tourism, retail, stock markets, and banking. In the banking business, chatbot can act as a communication tool between customers and banks. It has a special advantage in financial industry as it can be automated and does not necessitate human interaction;and can enhance accessibility and provide a lot of features to customers. © 2023 IEEE.

关键词： Decision making

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Emerging Cybersecurity Attacks in the Era of Digital Transformation 7

Emerging Cybersecurity Attacks in the Era of Digital Transfo...

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7th international conference on Intelligent computing and Control systems, ICICCS 2023

作者： Mishra, Sweta Gochhait, Saikat Symbiosis Institute of Digital and Telecom Management Constituent of Symbiosis International University/Neurosciences Research Institute: Samara State Medical UniversityRussia Pune India

ISBN: (纸本)9798350397253

the rapid digital transformation across industries, including manufacturing, has created significant blind spots for organizations when it comes to security. the threat surface grows as businesses engage more in automation, scale their operations, and integrate IoT, and many security teams struggle to stay up. However, in the age of digitalization, the emphasis must move from protecting network perimeters to protecting data that is dispersed across systems, devices, and the cloud. Organizations must maintain a strong asset management process, be resilient to cyber risks, and generate business value by being ahead of the curve when it comes to managing cyber threats. © 2023 IEEE.

关键词： Cybersecurity

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Engineering Applications of Neural Networks 2011

引用

丛书名： IFIP Advances in Information and Communication Technology

2011年

作者： Lazaros S. Iliadis Chrisina Jayne

ISBN: (数字)9783642239571

ISBN: (纸本)9783642239564

the two-volume set IFIP AICT 363 and 364 constitutes the refereed proceedings of the 12th international conference on Engineering Applications of Neural Networks, EANN 2011, and the 7th IFIP WG 12.5 international conference, AIAI 2011, held jointly in Corfu, Greece, in September 2011. the 52 revised full papers and 28 revised short papers presented together with 31 workshop papers were carefully reviewed and selected from 150 submissions. the first volume includes the papers that were accepted for presentation at the EANN 2011 conference. they are organized in topical sections on computer vision and robotics, self organizing maps, classification/pattern recognition, financial and management applications of AI, fuzzy systems, support vector machines, learning and novel algorithms, reinforcement and radial basis function ANN, machine learning, evolutionary genetic algorithms optimization, Web applications of ANN, spiking ANN, feature extraction minimization, medical applications of AI, environmental and earth applications of AI, multi layer ANN, and bioinformatics. the volume also contains the accepted papers from the Workshop on Applications of Soft computing to Telecommunication (ASCOTE 2011), the Workshop on Computational Intelligence Applications in Bioinformatics (CIAB 2011), and the Second Workshop on Informatics and Intelligent systems Applications for Quality of Life Information Services (ISQLIS 2011).

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Cyberbullying and Hate Speech Detection on Kazakh-Language Social Networks 7

Cyberbullying and Hate Speech Detection on Kazakh-Language S...

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7th IEEE international conference on Big Data Security on Cloud, 7th IEEE international conference on High Performance and Smart computing, and 6th IEEE international conference on Intelligent Data and Security, BigDataSecurity/HPSC/IDS 2021

作者： Sultan, Daniyar Mussiraliyeva, Shynar Toktarova, Aigerim Nurtas, Marat Iztayev, Zhalgasbek Zhaidakbaeva, Lyazzat Shaimerdenova, Lazzat Akhmetova, Oxana Omarov, Batyrkhan Al-Farabi Kazkah National University Faculty of Information Systems Almaty Kazakhstan A. Yassawi International Kazakh-Turkish University Turkistan Kazakhstan International Information Technology University Kazakh-British Technical University Almaty Kazakhstan M.Auezov South Kazakhstan University Shymkent Kazakhstan

ISBN: (纸本)9781665439275

Currently, there is a growing number of online bullying, attacks, and propaganda of prohibited materials over the Internet. the main means of exchanging information, selecting and promoting personnel for such structures is the Internet, namely web resources, social networks and e-mail. In this regard, the task of identifying, identifying communication topics, connections, as well as monitoring behavior and predicting threats emanating from individual users, groups and network communities that generate and distribute information of a bullying network on the Internet. the article is devoted to the research and data mining related to the topic of detecting bullying on the Internet. the study examines the development of the data set aimed to train the machine learning algorithms in the Kazakh language and marking them as con-sist of bullying phrasesor not. © 2021 IEEE.

关键词： Machine learning

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the Intersection of AI and Blockchain in Education: A Bibliometric and thematic Analysis 7

The Intersection of AI and Blockchain in Education: A Biblio...

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2023 7th international conference On computing, Communication, Control And Automation, ICCUBEA 2023

作者： Kaul, Natashaa Deshpande, Amruta Mittal, Amit Raut, Rajesh Symbiosis International University Symbiosis Center for Management and Human Resource Development Pune India Indira School of Business Studies Pgdm Pune India Chitkara Business School Chitkara University Punjab India

ISBN: (纸本)9798350304268

Two cutting-edge technologies that are revolutionizing the education industry are artificial intelligence (AI) and blockchain. the study on AI and blockchain in education is bibliometrically analyzed in this paper, emphasizing topics, frameworks, and potential future research areas. the analysis uses the Scopus database to pinpoint essential works and sketch out the conceptual framework of this field of study. the findings show an increasing interest in applying AI and blockchain technology in various educational settings, from K-12 to higher education, as well as the various research paradigms and methodologies used in this field. Studies emphasize creating knowledge management tools, learning algorithms, and decision support systems to strengthen the educational process and enhance learning results. the study also emphasizes the growing demand for cutting-edge technologies like deep learning and the Internet of things. this paper provides a comprehensive evaluation of research on AI and blockchain in education by highlighting key ideas and frameworks that have been applied in this area. the results offer relevant information on the current level of research in this field and suggest potential directions for advancement. © 2023 IEEE.

关键词： Artificial Intelligence Bibliometrics Blockchain Education thematic Analysis

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Colored ICP: Advancing 2D-to-3D Shape Registration for Enhanced Accuracy and Visualization 7

Colored ICP: Advancing 2D-to-3D Shape Registration for Enhan...

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7th international conference on algorithms, computing and systems, icacs 2023

作者： Vrochidis, Alexandros Krinidis, Stelios Tzovaras, Dimitrios Information Technologies Institute Center for Research and Technology Hellas Thessaloniki57001 Greece Department of Management Science & Technology International Hellenic University Kavala65404 Greece

ISBN: (纸本)9798400709098

Robust and accurate registration is a fundamental capability for numerous computer vision and robotics applications. this paper proposes a novel colored 2D to 3D registration method that exploits keypoints from Scale-Invariant Feature Transform (SIFT) and Intrinsic Shape Signatures (ISS). the proposed method works on multiple models without utilizing a neural network or requiring a training dataset. After detecting keypoints and their colors in the L*a*b* color space, a modified Iterative Closest Point (ICP) algorithm is utilized to find the correspondences between the image and 3D model points and the transformation matrix. Additionally, there is an experimental evaluation using publicly available colored models for 3D-3D and 2D-3D registration to show that color information can increase accuracy in both tasks. On 3D-3D registration, the use of color information decreased Relative Root Mean Square Error (RRMSE) by 85.69% when the k-d tree was used and 92.63% when color was utilized in combination with the geometric information. For the 2D-3D registration, the mean distance decreased by 25.52% for the k-d tree and 28.76% for the weighted colored ICP, proving that color can efficiently enhance accuracy in this task. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Color

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