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11th IEEE International Conference on Intelligent Systems, IS 2022

作者： Guzowski, Hubert Smolka, MacIej Byrski, Aleksander Pekar, Libor Oplatkova, Zuzana Kominkova Senkerik, Roman Matusu, Radek Gazdos, Frantisek Agh University of Science and Technology Institute of Computer Science Krakow Poland Tomas Bata University in Zlín Faculty of Applied Informatics Czech Republic

ISBN: (纸本)9781665456562

Heating-cooling processes are widely used in industry and are often subject to latencies and delays. Although the parameters of such processes can be identified using mathematical and physical modeling, this technique is highly demanding both when it comes to the amount of a priori knowledge required and the time it takes to find a solution. In this work, we provide a robust formulation of a time-delay control problem and propose a numerical approach to finding its parameters in a form of an optimization task. Consequently, we apply various techniques and metaheuristics to obtain a high quality solution and discuss key observations made in the process. © 2022 IEEE.

关键词： Time delay

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Research on Big Data Center System Based on computer Internet technology

Research on Big Data Center System Based on Computer Interne...

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Control, Electronics and computer technology (ICCECT), IEEE International Conference on

作者： Changjiang Huang Liuchun Zhan College of Computer Science Guangzhou College of Applied Science and Technology Guangdong Guangzhou China

In this paper, the introduction of big data technology, from the hardware and software two aspects of communication security protection system design research. With the support of hardware equipment, the secure communication channel of the system is constructed by using the big data processing center as the support. The network data in the communication is stored in the specified network space to build the network communication link database. In this paper, the results of variance measurement are converted into the similarity between data and the similarity relationship of network communication big data is constructed. In this way, the similarity matrix of network communication big data is obtained. Experimental results show that the system designed by the proposed method has fast communication speed, low energy consumption, and low packet loss rate during communication.

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A Short Note on Solving Partial Differential Equations Using Convolutional Neural Networks 27th

A Short Note on Solving Partial Differential Equations Using...

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27th International Conference on Domain Decomposition Methods in science and Engineering, DD 2022

作者： Grimm, Viktor Heinlein, Alexander Klawonn, Axel Department of Mathematics and Computer Science University of Cologne Weyertal 86-90 Koln50931 Germany Delft University of Technology Delft Institute of Applied Mathematics Mekelweg 4 Delft2628 CD Netherlands Center for Data and Simulation Science University of Cologne Cologne Germany

ISBN: (纸本)9783031507687

Solving partial differential equations (PDEs) is a common task in numerical mathematics and scientific computing. Typical discretization schemes, for example, finite element (FE), finite volume (FV), or finite difference (FD) methods, have the disadvantage that the computations have to be repeated once the boundary conditions (BCs) or the geometry change slightly;typical examples requiring the solution of many similar problems are time-dependent and inverse problems or uncertainty quantification. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Boundary conditions

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Socio-cognitive Optimization of Time-delay Control Problems using Evolutionary Metaheuristics 11

Socio-cognitive Optimization of Time-delay Control Problems ...

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11th IEEE International Conference on Intelligent Systems, IS 2022

作者： Kipinski, Piotr Guzowski, Hubert Urbanczyk, Aleksandra Smolka, MacIej Kisiel-Dorohinicki, Marek Byrski, Aleksander Oplatkova, Zuzana Kominkova Senkerik, Roman Pekar, Libor Matusu, Radek Gazdos, Frantisek Agh University of Science and Technology Institute of Computer Science Krakow Poland Tomas Bata University in Zlín Faculty of Applied Informatics Czech Republic

ISBN: (纸本)9781665456562

Metaheuristics are universal optimization algorithms which should be used for solving difficult problems, unsolvable by classic approaches. In this paper we aim at constructing novel socio-cognitive metaheuristic based on castes, and apply several versions of this algorithm to optimization of time-delay system model. Besides giving the background and the details of the proposed algorithms we apply them to optimization of selected variants of the problem and discuss the results. © 2022 IEEE.

关键词： Optimization

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Deep Broad Learning for Emotion Classification in Textual Conversations

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Tsinghua science and technology 2024年第2期29卷 481-491页

作者： Sancheng Peng Rong Zeng Hongzhan Liu Lihong Cao Guojun Wang Jianguo Xie Center for Linguistics and Applied Linguistics and Laboratory of Language Engineering and ComputingGuangdong University of Foreign StudiesGuangzhou 510006China Guangdong Provincial Key Laboratory of Nanophotonic Functional Materials and Devices South China Normal UniversityGuangzhou 510006China School of Computer Science and Cyber Engineering Guangzhou UniversityGuangzhou 510006China Modern Education Technology Center Guangdong University of Foreign StudiesGuangzhou 510006China

Emotion classification in textual conversations focuses on classifying the emotion of each utterance from textual *** is becoming one of the most important tasks for natural language processing in recent ***,it is a challenging task for machines to conduct emotion classification in textual conversations because emotions rely heavily on textual *** address the challenge,we propose a method to classify emotion in textual conversations,by integrating the advantages of deep learning and broad learning,namely *** aims to provide a more effective solution to capture local contextual information(i.e.,utterance-level)in an utterance,as well as global contextual information(i.e.,speaker-level)in a conversation,based on Convolutional Neural Network(CNN),Bidirectional Long Short-Term Memory(Bi-LSTM),and broad *** experiments have been conducted on three public textual conversation datasets,which show that the context in both utterance-level and speaker-level is consistently beneficial to the performance of emotion *** addition,the results show that our proposed method outperforms the baseline methods on most of the testing datasets in weighted-average F1.

关键词： emotion classification textual conversation Convolutional Neural Network(CNN) Bidirectional Long Short-Term Memory(Bi-LSTM) broad learning

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Applications in Home Improvement Retailer, Koctas 2

Applications in Home Improvement Retailer, Koctas

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2nd International Conference on Business Analytics for technology and Security, ICBATS 2023

作者： Mourad, Nahia Raza, Hammad Amjad, Muhamamd Ullah, Muhammed Ubaid Sabri Elmitwally, Nouh University in Dubai College of Engineering & IT British Dubai United Arab Emirates College of Business Administration and Economics Department of Computer Science National Lahore Pakistan NCBA&E Lahore School of Computer Science Pakistan Applied Science Private University Applied Science Research Center Amman11937 Jordan Minhaj University Lahore Pakistan Birmingham City University School of Computing and Digital Technology BirminghamB4 7XG United Kingdom Cairo University Faculty of Computers and Artifcial Intelligence Department of Computer Science Giza12613 Egypt

ISBN: (纸本)9798350335644

It sounds like Koçtaş is a leader in the home improvement sector in Turkey, and they are focused on providing the best service and customer experience possible. They are also actively working to accelerate their digital investments and use their vast amount of customer data to innovate in the industry. One way they are using this data is by collecting and analyzing video camera images using AI. This allows them to detect humans and identify which products and shelves are most viewed in their stores. This information can then be used to optimize store layout and product placement for a better customer experience. Another way Koçtaş is innovating is through the implementation of kiosks that use Natural Language Processing (NLP) to interact with customers. These kiosks can understand and respond to questions asked by customers using AI, providing a more personalized and human-like ***, Koçtaş is using Dynamic Creative Optimization to create personalized advertisements for their customers. This method allows them to optimize the content and format of their ads based on the individual preferences and behavior of their customers, leading to more effective ***, Koçtaş is using technology and data to drive innovation and provide a better customer experience in the home improvement industry. © 2023 IEEE.

关键词： Video cameras

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Leveraging Information-Centric Edge Computing in Private 5G Cellular Networks via the W3C Web of Things

Leveraging Information-Centric Edge Computing in Private 5G ...

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Jan Romann Hugo Hakim Damer T M Rayhan Gias Olaf Bergmann Department of Electrical Engineering and Computer Science Faculty of Technology University of Applied Sciences Emden/Leer Emden Germany

ISBN: (数字)9798331508050

ISBN: (纸本)9798331508067

In this paper, we present an architecture for the deployment of an edge computing system based on Named Data Networking (NDN) as part of a private 5G network. Our proposed architecture integrates IP-based and non-IP-based components using the W3C Web of Things (WoT) standards, including a Thing Description Directory (TDD). Our results highlight the potential of both edge computing and WoT concepts for private 5G deployments but also reveal several standardization gaps that need to be closed to make effective use of the new technologies.

关键词： Cellular networks 5G mobile communication W3C computer architecture Service-oriented architecture Standards Edge computing

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Scaling LLM-Based Knowledge Graph Generation: A Case Study of Italian Geopolitical News

Scaling LLM-Based Knowledge Graph Generation: A Case Study o...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Russo, Diego Orlando, Gian Marco Romano, Antonio Riccio, Giuseppe La Gatta, Valerio Postiglione, Marco Moscato, Vincenzo University of Naples Federico II Department of Electrical Engineering and Information Technology via Claudio 21 80125 Naples Italy Northwestern University Department of Computer Science McCormick School of Engineering and Applied Science 2233 Tech Dr Evanston IL 60208 United States

ISBN: (纸本)9798350362480

Geopolitical news provides vast amounts of information essential for understanding international relations and political events. However, organizing this information into a coherent, structured format poses challenges due to the complexity and dynamic nature of the domain. This paper introduces a scalable system leveraging Large Language Models to build continuously updated Knowledge Graphs from Italian geopolitical news. The system features a modular architecture, including a Collector Node for scalable article extraction, a Redis-based reliable queue to manage large-scale data ingestion, and a Named Entity Recognition/Relation Extraction Engine to standardize entity-relation triples. The framework addresses key challenges, such as continuous updating and hallucination mitigation, ensuring the reliability of the graph. Our evaluations demonstrate significant improvements in scalability, uniformity of extracted triples, and graph accuracy, making this architecture particularly suitable for real-time geopolitical analysis. © 2024 IEEE.

关键词： Knowledge graph

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Classifying Arabian Gulf Tweets to Detect People's Trends: A case study 9

Classifying Arabian Gulf Tweets to Detect People's Trends: A...

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9th International Conference on Social Networks Analysis, Management and Security, SNAMS 2022

作者： Balhaf, Khaled Darwish, Omar Rawashdeh, Emad Awad, Mohammad Abu Darweesh, Dirar Tashtoush, Yahya Rawashdeh, Saif Department of Computer Science Jordan University of Science and Technology Irbid Jordan Information Security and Applied Computing Eastern Michigan University Ypsilanti United States

ISBN: (纸本)9798350320480

Recently, media and business companies are utilizing social media to reach a large set of users to maximize the amount of gained profit. Actually, these companies are looking for the best ways to satisfy their user's requirements. It is very difficult to understand these requirements because of the large set of users on social media like Twitter. For this reason, the goal of our research project is to build a classifier that can detect Arabian trends among Gulf area Twitter users. The new built classifier can assist these companies to deliver the convenient products and media contents like photos and videos according to users' trends. By using our own designed Java-based tool, we have collected a significant dataset of tweets. Also, two experiments of tweet classification have been implemented to compare the effects of balanced and imbalanced training data and to measure the effect of data size on the accuracy of classifiers. In both experiments, Support Vector Machine (SVM), K-Nearest Neighbors (KNN) and Naïve Bayes algorithms are used as classifiers. The first experiment uses small, imbalanced data sets and four classes of data, which are Sport, Politics, Islam and Culture. The Light and Root Stemmers were used with each classifier. The best outcome achieved in our research project by utilizing a Naïve Bayes algorithm with the Light Stemmer technique. It achieved an accuracy reaching 76.27%. In the second experiment, we used a balanced large data set with the same classifiers. In addition, we have added one more class to the new data set which is Economics. The experimental results showed that the best accuracy (81.17%) is obtained by using SVM with the Light Stemmer method. The Light Stemmer achieved the best outcomes for all classifiers since almost all of the tweets were written in dialects. © 2022 IEEE.

关键词： Classification (of information)

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Resource Exhaustion Attack Detection Scheme for WLAN Using Artificial Neural Network

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computers, Materials & Continua 2023年第3期74卷 5607-5623页

作者： Abdallah Elhigazi Abdallah Mosab Hamdan Shukor Abd Razak Fuad A.Ghalib Muzaffar Hamzah Suleman Khan Siddiq Ahmed Babikir Ali Mutaz H.H.Khairi Sayeed Salih Faculty of Engineering Future UniversityKhartoum 10553Sudan Faculty of Computing and Informatics Universiti Malaysia SabahKota Kinabalu88400Malaysia Information Assurance and Security Research School of ComputingUniversiti Teknologi MalaysiaJohor81310Malaysia School of Psychology and Computer Science University of Central LancashirePreston PR12HEUK Deaptement of Management Information Systems College of Administrative ScienceApplied Science UniversityAl Eker623Bahrain Deaptement of Information Technology College of Computer and Information SciencesKing Saud UniversityRiyadh11461Saudi Arabia

IEEE 802.11 Wi-Fi networks are prone to many denial of service(DoS)attacks due to vulnerabilities at the media access control(MAC)layer of the 802.11 *** to the data transmission nature of the wireless local area network(WLAN)through radio waves,its communication is exposed to the possibility of being attacked by illegitimate ***,the security design of the wireless structure is vulnerable to versatile *** example,the attacker can imitate genuine features,rendering classificationbased methods inaccurate in differentiating between real and false *** security standards have been proposed over the last decades to overcome many wireless network attacks,effectively detecting such attacks is crucial in today’s real-world *** paper presents a novel resource exhaustion attack detection scheme(READS)to detect resource exhaustion attacks *** proposed scheme can differentiate between the genuine and fake management frames in the early stages of the attack such that access points can effectively mitigate the consequences of the *** scheme is built through learning from clustered samples using artificial neural networks to identify the genuine and rogue resource exhaustion management frames effectively and efficiently in *** proposed scheme consists of four modules whichmake it capable to alleviates the attack impact more effectively than the related *** experimental results show the effectiveness of the proposed technique by gaining an 89.11%improvement compared to the existing works in terms of detection.

关键词： 802.11 media access control(MAC) wireless local area network(WLAN) artificial neural network denial-of-service(DoS)

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