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Gaussian Backbone-Based Spherical Evolutionary Algorithm with Cross-search for engineering Problems

Journal of Bionic engineering 2024年第2期21卷 1055-1091页

作者： Yupeng Li Dong Zhao Ali Asghar Heidari Shuihua Wang Huiling Chen Yudong Zhang College of Computer Science and Technology Changchun Normal UniversityChangchun130032JilinChina School of Surveying and Geospatial Engineering College of EngineeringUniversity of TehranTehranIran School of Computing and Mathematical Sciences University of LeicesterLeicesterLE17RHUK Department of Biological Sciences Xi’an Jiaotong-Liverpool UniversitySuzhou215123JiangsuChina Key Laboratory of Intelligent Informatics for Safety and Emergency of Zhejiang Province Wenzhou UniversityWenzhou325035China School of Computer Science and Engineering Southeast UniversityNanjing210096China

In recent years,with the increasing demand for social production,engineering design problems have gradually become more and more *** novel and well-performing meta-heuristic algorithms have been studied and developed to cope with this *** them,the Spherical Evolutionary Algorithm(SE)is one of the classical representative methods that proposed in recent years with admirable optimization ***,it tends to stagnate prematurely to local optima in solving some specific ***,this paper proposes an SE variant integrating the Cross-search Mutation(CSM)and Gaussian Backbone Strategy(GBS),called *** this study,the CSM can enhance its social learning ability,which strengthens the utilization rate of SE on effective information;the GBS cooperates with the original rules of SE to further improve the convergence effect of *** objectively demonstrate the core advantages of CGSE,this paper designs a series of global optimization experiments based on IEEE CEC2017,and CGSE is used to solve six engineering design problems with *** final experimental results fully showcase that,compared with the existing well-known methods,CGSE has a very significant competitive advantage in global tasks and has certain practical value in real ***,the proposed CGSE is a promising and first-rate algorithm with good potential strength in the field of engineering design.

关键词： Meta-heuristic algorithms engineering optimization Spherical evolution algorithm Global optimization

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Evaluating Gaze Detection for Children with Autism Using the ChildPlay-R Dataset

Evaluating Gaze Detection for Children with Autism Using the...

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International Conference on Automatic Face and Gesture Recognition

作者： Nursena Boluk Hatice Kose Department of Computer Engineering Faculty of Computer and Informatics Engineering Istanbul Technical University Istanbul Turkey Department of Artificial Intelligence and Data Engineering Faculty of Computer and Informatics Engineering Istanbul Technical University Istanbul Turkey

ISBN: (数字)9798350394948

ISBN: (纸本)9798350394955

This study focuses on detecting two-dimensional (2D) gaze points in interactions between children both with and without autism and adults. Within the scope of this objective, a novel subset called ChildPlay-R has been created based on the open-source ChildPlay dataset. This new dataset includes explicitly the interactions of children with and without autism with adults in similar uncontrolled environments and relevant 2D gaze points. Moreover, the analyses using the Modified Spatiotemporal Gaze Detection (M-STGD) model, compared to the traditional Spatiotemporal Gaze Architecture (STGA), reveal significant improvements in the Area Under the Curve values and out-of-sample precision. These advancements indicate the M-STGD model's potential to provide a deeper understanding of the social engagement patterns of children with autism. This study contributes to the automatic detection of 2D gaze points in social interactions and supports the social development of children with autism.

关键词： Autism Analytical models Adaptation models Accuracy Two-dimensional displays Face recognition Gesture recognition

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Enhancing Emotion Classification with a Hybrid BERT and CNN Architecture

Enhancing Emotion Classification with a Hybrid BERT and CNN ...

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International Workshop on Semantic Media Adaptation and Personalization (SMAP)

作者： Orestis Papadimitriou Athanasios Kanavos Gerasimos Vonitsanos Manolis Maragoudakis Panagiotis Karkazis Phivos Mylonas Department of Information and Communication Systems Engineering University of the Aegean Greece Computer Engineering and Informatics Department University of Patras Greece Department of Informatics Ionian University Greece Department of Informatics and Computer Engineering University of West Attica Athens Greece

ISBN: (数字)9798331504502

ISBN: (纸本)9798331504519

In computational linguistics, effectively encoding and systematizing emotional expressions in language is a significant challenge. Existing machine learning (ML) models for text analysis often only recognize primary emotional states such as anger, happiness, and sadness, missing the more nuanced spectrum of human emotions. These models frequently overlook the complex semantic interplays and fail to capture the full diversity of emotional expressions, focusing instead on simplistic categorization. This paper proposes a robust ML framework that enhances emotion classification by discriminating among nuanced emotion categories—Anger, Joy, and Fear. Leveraging a sophisticated combination of Convolutional Neural Networks (CNNs) and the Bidirectional Encoder Representations from Transformers (BERT) architecture, our framework demonstrates exceptional accuracy in emotion detection. Evaluating a diverse dataset of text samples, each meticulously tagged with its expressed emotion, confirms the model’s superior performance in recognizing and classifying a broad range of emotional states.

关键词： Emotion recognition Text analysis Text recognition Computational modeling Semantics computer architecture Bidirectional control Transformers Encoding Convolutional neural networks

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Development of Gamification and Live Coding-Based Programming Learning Platform to Foster Learning Motivation of Vocational Students

Development of Gamification and Live Coding-Based Programmin...

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2023 International Conference on Electrical and Information Technology, IEIT 2023

作者： Hidayat, Wahyu Nur Dwi Prasetyo, Wiji Zahiroh, Ayu Najmatus Maydi Syahri, Esa Pramudheva Afdloly, Mochammad Mu'iz Sari, Rahajeng Kartika Universitas Negeri Malang Department of Electrical Engineering and Informatics Malang Indonesia Smk Negeri 10 Malang Departement of Computer Network Engineering and Telecommunications Malang Indonesia

ISBN: (纸本)9798350327298

The current utilization of e-learning has not been able to increase participation and learning experience and motivate students to achieve educational goals. This research focuses on developing gamification-based learning media in Object-Oriented Programming (OOP) subjects to increase student learning motivation, determine the feasibility level of learning media, and determine the increase in student learning motivation. The method of the research is design thinking It is used to identify and better understand users in the use of applications, find problems faced by users, and can explore new ideas in the creation of appropriate application features in accordance with user needs. The results of expert media validation from the teacher, lecturer, and programmer amounted to 89.78% in the good category, for the material validation results of 91.33% in the very good category. Media use was implemented by 23 students of class XI RPL SMKN 12 Malang. The user trial results showed a percentage of 83.48% with good criteria. The student learning motivation test results showed a percentage of 81.26% with very high criteria. This shows the effect of gamification implementation in fostering student learning motivation. Gamification-based media has been tested for feasibility by media experts, material experts, and students. Therefore, the media is feasible and can be used as a learning support media in object-oriented programming subjects in Vocational High School. © 2023 IEEE.

关键词： Students

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Abridged Neat Key Instance: An Integrity Property for Digital Multimedia Asset of Non-fungible Token 9

Abridged Neat Key Instance: An Integrity Property for Digita...

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9th International Conference on informatics and Computing, ICIC 2024

作者： Damastuti, Fardani Annisa Fachri, Moch Ramadhani, Nugrahardi Prasetyo, Didit Barakbah, Aliridho Hariadi, Mochamad Institut Teknologi Sepuluh Nopember Electrical Engineering Department Surabaya Indonesia Politeknik Elektronika Negeri Surabaya Informatics and Computer Engineering Dept Surabaya Indonesia Institut Teknologi Sepuluh Nopember Computer Engineering Department Surabaya Indonesia

ISBN: (纸本)9798331517601

The non-fungible token (NFT) is a record used to ensure the privilege and ownership of a certain digital asset with a distinctive digital identifier in a blockchain. In digital-multimedia assets i.e. images, videos, audio, etc. NFTs generally retain references to the properties of the asset. Due to the nature of blockchain technology, NFT is oftentimes associated with its immutability. NFTs that represent digital multimedia assets may utilize blockchain-based file servers, but oftentimes time the associated file is stored off-chain. This makes the assets themselves vulnerable to link rot and causes the NFT owner to lose access to their assets since the off-chain storageis not immutable like the NFT. To preserve the integrity of the NFT's associated digital assets, we introduce Abridged Neat Key Instance (ANKI). ANKI is a property embedded inside NFT that contains the seed number of the digital multimedia asset to be procedurally generated. We are taking advantage of Procedural Content Generation (PCG) technology to reproduce the digital multimedia asset presented by the information available inside the NFT itself. By leveraging Procedural Content Generation(PCG) technology, our approach can regenerate the exact digital asset directly from the information encoded within the *** our experiments, we successfully recreated music files using the ANKI seed and a PCG engine, verifying their accuracy by comparing the MD5 and SHA-512 checksums of the generated files with those of the original NFT assets. All 50 generated musicfiles produced identical checksums to their original counterparts,confirming the integrity of our method. © 2024 IEEE.

关键词： Abridged neat key instance Blockchain Digital asset Non-fungible token Procedural content generation

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A Cloud-Based Key Rolling Technique for Alleviating Join Procedure Replay Attacks in LoRaWAN-based Wireless Sensor Networks

A Cloud-Based Key Rolling Technique for Alleviating Join Pro...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Papatsaroucha, Dimitra Astyrakakis, Nikolaos Pallis, Evangelos Grammatikis, Panagiotis I. Radoglou Sarigiannidis, Panagiotis G. Markakis, Evangelos K. Hellenic Mediterranean University Department of Computer & Electrical Engineering Heraklion Greece University of West Attica Department of Industrial Design and Production Engineering Athens Greece K3Y Sofia Bulgaria University of Western Macedonia Department of Informatics and Telecommunication Engineering Kozani Greece

ISBN: (纸本)9798350362480

Nowadays, numerous devices are utilizing the IoT world, connecting and providing access to data and sensor measurements in vast networks of interconnected objects and devices. Considering the great communication distances that need to be covered occasionally, the LoRaWAN network was proposed as it employs Low Power (LP) and Long Range (LoRa) protocols that reduce device energy consumption while maximizing communication range. A gateway to the cloud authenticates LoRaWAN IoT devices before data transmission. This procedure begins with an unencrypted Join Request. A Join Request includes, among others, a Message Integrity Code (MIC), which is the result of encrypting the unencrypted contents of the message using an AppKey that is securely stored both in the cloud and the IoT device. However, malicious actors acting as Man-In-the-Middle (MITM) can interfere in the communication channel, reverse engineer the MIC value, and derive the AppKey. They can then initiate a Join Request that is misinterpreted as coming from a legitimate device and gain access to the communication channel. This paper introduces a novel approach that focuses on the continuous regeneration of the AppKey, necessitating frequent re-joining and re-authentication of IoT devices within the network. The suggested method, which can be added as an extra layer of security in LoRaWAN networks, uses a key rolling technique similar to the one used in automobile central locking systems, and is developed as an optimised and scalable microservice for various LoRaWAN installations and versions. Through the evaluation process, significant findings emerged, demonstrating the effectiveness of the proposed security solution in mitigating replay attacks. The system successfully prevented the server from getting flooded by malicious packets, distinguishing it from a system lacking the proposed mechanism. Remarkably, this accomplishment was made without causing any noticeable delay to the communication process. In addit

关键词： Network security

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Analyzing intuitionistic fuzzy reliability of LNG-fuel gas supply system using simplified Lambda-tau techniques

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Computational and Applied Mathematics 2025年第6期44卷 1-28页

作者： Khajuria, Rocky Komal Lee, Seong Yeob Pamucar, Dragan Stevan Simic, Vladimir Department of Mathematics School of Physical Sciences Doon University Uttarakhand Dehradun248001 India Daejeon Korea Republic of Department of Operations Research and Statistics Faculty of Organizational Sciences University of Belgrade Belgrade Serbia College of Engineering Yuan Ze University Taoyuan City Taiwan Faculty of Transport and Traffic Engineering University of Belgrade Belgrade11010 Serbia Department of Computer Science and Engineering College of Informatics Korea University Seoul02841 Korea Republic of

Liquefied natural gas-fuel gas supply system (LNG-FGSS) play a crucial role in the global energy sector, particularly in supplying natural gas (NG). Studying this system is pivotal for tackling energy needs, environmental issues, and energy infrastructure reliability. Thus, the objective of this paper is to introduce some new methodologies for assessing the intuitionistic fuzzy reliability (IFR) of LNG-FGSS that can incorporate the uncertainty by accumulating fuzziness and hesitation factors during the data processing. This paper presents two simplified IFR analysis techniques for repairable systems that include Min-Max operators based simplified intuitionistic fuzzy lambda-tau methodology (MBSIFLTM) and Min-Max operators and the weakest t-norm (Tω) based simplified intuitionistic fuzzy lambda-tau methodology (MWBSIFLTM). In MBSIFLTM, we used Min-Max operators based simplified arithmetic operations for intuitionistic fuzzy set (IFS), Lambda-tau methodology, and fault tree analysis (FTA) for analyzing different reliability indices of the system. Whereas in MWBSIFLTM, various reliability parameters of the system are assessed by using the Min-Max operators along with the weakest t-norm based simplified arithmetic operations of IFS, Lambda-tau methodology, and FTA. Further to analyzed the credibility and precision of the suggested methodologies, an investigation has been carried out for a LNG-FGSS. Both the proposed techniques and four existing methods are employed to assess the IFR of LNG-FGSS. Consequently, to show the flexibility of the proposed models, a sensitivity analysis is also conducted. Moreover, the ranking of the system’s components has been carried out by utilizing the V-index method, aiming to optimize its overall performance. Comparing the outcomes of the suggested techniques with four other established methods leads to the conclusion that the suggested techniques offer simplicity, ease of application, and optimized IFR indices. © The Author(s) under exc

关键词： Fault tree analysis

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Detecting Abusive Activity with Enhanced Convolutional Neural Networks

Detecting Abusive Activity with Enhanced Convolutional Neura...

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2023 Al-Sadiq International Conference on Communication and Information Technology, AICCIT 2023

作者： Khalaf, Suadad Zaidan Shujaa, Mohamed Ibrahim Alwahhab, Ahmed Bahaaulddin A. Middle Technical University Department of Computer Techniques Engineering Baghdad Iraq Middle Technical University Technical College of Management Department of Informatics Baghdad Iraq

ISBN: (纸本)9798350341881

There is a growing reliance on surveillance systems for law enforcement and public safety purposes. Video surveillance scenarios, such as those seen in train stations, schools, and hospitals, must automatically detect hostile and suspicious behavior to avoid social, economic, and environmental harm. Human contact can now be seen using intelligent video surveillance systems. Crowds and the camera's field of view reduce the system's effectiveness as a security procedure. As a result, there is a lot of study on the many strategies for detecting violent behavior. The method of detection discussed in this study can be divided into three categories. These groups were established as a result of the classification procedures that were used. Among the categorizations is a refined CNN for using AI to identify instances of violence. Principal Component Analysis (PCA) is used to develop techniques for feature extraction and violence detection. The AIRTLab dataset was utilized to analyze models based on dataset learning for violence detection by testing the resilience of algorithms against false positives. To evaluate the proposed model's robustness against false positives, we calculated accuracy measures and utilized them to establish a baseline on the AIRTLab dataset. The study literature claims a 99.98% success rate for the suggested models, with transfer learning-based networks boasting greater generalization abilities. © 2023 IEEE.

关键词： computer vision

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Leveraging Digital Twin Technologies for Public Space Protection and Vulnerability Assessment

Leveraging Digital Twin Technologies for Public Space Protec...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Stefanidou, Artemis Cani, Jorgen Papadopoulos, Thomas Radoglou-Grammatikis, Panagiotis Sarigiannidis, Panagiotis Varlamis, Iraklis Papadopoulos, Georgios Th. Harokopio University Department of Informatics and Telematics Athens Greece Regional Unit of Kastoria Region of Western Macedonia Kastoria Greece University of Western Macedonia Department of Electrical and Computer Engineering Kozani Greece

ISBN: (纸本)9798350362480

In recent years, the protection of so-called "soft targets", has become an increasingly important and challenging issue. The complexity and seriousness of this security threat have been growing exponentially, particularly with the advent of advanced technologies such as Artificial Intelligence (AI), Autonomous Vehicles (AVs), and 3D printing, especially in the context of large-scale, popular, and diverse public spaces. In this paper, a novel Digital Twin-as-a-Security-Service (DTaaSS) architecture is introduced for holistically and significantly enhancing the protection of public spaces (e.g. metro stations, leisure sites, urban squares, etc.). The proposed framework combines a Digital Twin (DT) conceptualization with additional cutting-edge technologies, including Internet of Things (IoT), cloud computing, Big Data analytics and AI. In particular, DTaaSS comprises a holistic, real-time, large-scale, comprehensive and data-driven security solution for the efficient/robust protection of public spaces, supporting: a) data collection and analytics, b) area monitoring/control and proactive threat detection, c) incident/attack prediction, and d) quantitative and data-driven vulnerability assessment. Overall, the designed architecture exhibits increased potential in handling complex, hybrid and combined threats over large, critical and popular soft-targets. The applicability and robustness of DTaaSS is discussed in detail against representative and diverse real-world application scenarios, including complex attacks to: a) a metro station, b) a leisure site, and c) a cathedral square. © 2024 IEEE.

关键词： Subway stations

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Smart vegetable cutter for Smart Home 1

Smart vegetable cutter for Smart Home

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1st International Conference in Advanced Innovation on Smart City, ICAISC 2023

作者： Singhal, Saurabh Mangal, Deepak Kumar, Rakesh Sharma, Bhisham Dhaou, Imed Ben GLA University Department of Computer Engineering & Applications Mathura India Jain University Department of Computer Science and IT Bangalore India Dar Al-Hekma University Hekma School of Engineering Computing and Informatics Department of Computer Science Jeddah Saudi Arabia Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9781665472753

Modern society strives for simpler, more efficient, dependable, speedier, and more automated lifestyle. Existing vegetable cutters in the market have drawbacks such as high investment costs, additional manpower, and time consumption. Moreover, none of them provide the feature of cleaning, peeling, and cutting in a single machine. The veggies offered in the market have pesticides and chemicals, and many people, in their haste, do not wash them properly, endangering their health. To reduce human labor while also providing good health care, a solution to this problem is required. This paper offers a novel method for developing a vegetable cutter and chopper using an Android application and IoT devices. In addition, smart vegetable cutters clean, peel, and cut veggies all in one piece of equipment. This strategy will assist human society in reducing the amount of additional manpower needed and would save them time. © 2023 IEEE.

关键词： Real time systems

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