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Painlevé Analysis and Kink-Type Solitary Waves of the Geophysical KdV Equation Involving a Source

International Journal of Applied and Computational Mathematics 2024年第2期10卷 1-10页

作者： Hosseini, K. Baleanu, D. Hincal, E. Manukure, S. Salahshour, S. Kaymakamzade, B. Mathematics Research Center Near East University TRNC Nicosia Mersin 10 99138 Turkey Department of Mathematics Near East University TRNC Nicosia Mersin 10 99138 Turkey Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon Faculty of Art and Science University of Kyrenia Kyrenia TRNC Mersin 10 Turkey Institute of Space sciences-Subsidiary of INFLPR Magurele-Bucharest Romania Department of Mathematics Florida A & amp Faculty of Engineering and Natural Sciences Istanbul Okan University Istanbul Turkey Faculty of Engineering and Natural Sciences Bahcesehir University Istanbul Turkey Faculty of Science and Letters Piri Reis University Tuzla Istanbul Turkey

The geophysical KdV equation is used to explore the propagation of oceanic waves. In the present paper, the geophysical KdV equation involving a source (The source is a polynomial of degree n in the unknown function) is formally introduced. Through the Painlevé analysis, it is shown that the geophysical KdV equation with the source is not integrable. Under some necessary conditions for integrability, several kink-type solitary waves to the special cases of the governing model when n=2 and n=4 are derived using the classical Kudryashov method. © The Author(s), under exclusive licence to Springer Nature India Private Limited 2024.

关键词： Geophysical KdV equation Integrability Kink-type solitary waves Kudryashov method Painlevé analysis Source

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On heterogeneity or sub-classes aspect in construction of stylometric input datasets 26

On heterogeneity or sub-classes aspect in construction of st...

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26th International Conference on Knowledge-Based and Intelligent Information and engineering systems, KES 2022

作者： Stanczyk, Urszula Baron, Grzegorz Department of Graphics Computer Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A Gliwice44-100 Poland

Stylometric analysis of texts relies on learning characteristic traits of writing styles for authors. Once these patterns are discovered, they can be compared to the ones present in other text samples, to recognise their authorship. This recognition can be compromised if input datasets are prepared without taking into consideration possible stratification of the input space, leading to specific grouping of datapoints, or sub-classes within distinguished classes. The paper shows research dedicated to construction of various structures of input datasets, and combinations of such structures between train and test sets. In the research the influence of different stratification forms on the performance of selected popular classification systems was observed. To minimise the number of influencing factors, a task of authorship attribution was performed as binary classification with balanced classes. Stylometric descriptors exploited belonged to lexical and syntactic group, giving frequencies of occurrence for chosen style-markers. It resulted in real-valued attributes and these values were explored without applying discretisation, in order to avoid the possible bias of this procedure on observations. © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the 26th International Conference on Knowledge-Based and Intelligent Information & engineering systems (KES 2022)

关键词： Knowledge based systems

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Creating Robust and Secure Decentralized Autonomous Organizations (DAOs) for the Metaverse Using Blockchain Technology 6th

Creating Robust and Secure Decentralized Autonomous Organiza...

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6th International Conference on Recent Innovations in Computing, ICRIC 2023

作者： Goyal, S.B. Rajawat, Anand Singh Shaari, Rosnizah Bt Verma, Chaman Singh, Pradeep Kumar City University Petaling Jaya Malaysia School of Computer Sciences and Engineering Sandip University Nashik India City University Petaling Jaya46100 Malaysia Department of Media and Educational Informatics Faculty of Informatics Eötvös Loránd University Budapest1053 Hungary Department of Computer Science and Engineering Central University of Jammu Jammu India

ISBN: (纸本)9789819778614

This paper presents an all-encompassing exploration on the conception and implementation of sturdy and impregnable decentralized autonomous organizations (DAOs) custom-made for the Metaverse, capitalizing on the capabilities of blockchain technology. The Metaverse, an incorporation of virtual shared space, is evolving at a rapid pace, necessitating governance structures that are decentralized, transparent, efficient, and impervious to points of failure. DAOs, governed by smart contracts and consensus mechanisms, offer a promising resolution to this exigency. To commence by scrutinizing the distinctive prerequisites of the Metaverse milieu, encompassing scalability, interoperability, and user involvement. Subsequently, we delve into the framework of DAOs, accentuating blockchain’s essential role in ensuring security, transparency, and decentralized governance. Our approach involves a stratified method to DAO design, amalgamating blockchain’s immutable ledger, smart contract functionality, and advanced cryptographic techniques to safeguard against potential hazards and susceptibilities that are specific to the Metaverse. To propose innovative mechanisms for decentralized decision-making, asset management, and dispute resolution within DAOs, ensuring consonance with the dynamic and engrossing essence of the Metaverse. Moreover, to tackle the obstacles of incorporating DAOs with existing Metaverse platforms, with a focus on interoperability between distinct blockchain protocols and virtual domains. Our proposed model encompasses a collection of exemplary practices for DAO deployment in the Metaverse, ensuring adaptability and resilience. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Smart contract

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Improving performance in collaborative games through personality-based matchmaking 1

Improving performance in collaborative games through persona...

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Actas del I Congreso Espanol de Videojuegos, CEV 2022 - 1st Spanish Congress on Videogames, CEV 2022

作者： Villar, Alejandro León, Carlos Department of Software Engineering and Artificial Intelligence Computer Science Faculty Universidad Complutense de Madrid Madrid28040 Spain

Automatic player matchmaking in video games is usually focused on balancing players by taking into account their past performance. The objectives of video games in which the winning condition is clear and specifically defined by their design make this approach widely used and effective. However, this approach is not necessarily optimal when the main objective is not only winning but also obtaining other rewards like creative achievements, enjoyment, socialization or world construction. This paper describes a formal approach for automatic matchmaking that takes into account the players' personality traits. This form of matchmaking is oriented towards game genres in which competition is not necessarily the general dynamic. An implementation of the system, evaluation in a virtual escape room and results are provided. Preliminary results suggest that the approach is potentially effective. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

关键词： Interactive computer graphics

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A Computational Intelligence Inspired Framework for Intrusion Detection in WSN

A Computational Intelligence Inspired Framework for Intrusio...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Pandey, Vivek Kumar Prakash, Shiv Gupta, Tarun Kumar Yang, Tiansheng Singh, Abhishek Rathore, Rajkumar Singh University of Allahabad Department of Electronics and Communication Prayagraj India University of Delhi Department of Computer Science Miranda House Delhi India University of South Wales Faculty of Business and Creative Industries Pontypridd United Kingdom Institute of Engineering & Technology Department of Computer Science & Engineering Dr. A.P. J. Abdul Kalam Technical University Lucknow India Cardiff School of Technologies Cardiff Metropolitan University Cardiff United Kingdom

ISBN: (纸本)9798350369106

In this growing world of technology, the wide range of uses of wireless sensor networks (WSNs), such as tracking the environment and keeping an eye on the military, makes them indispensable in many applications. However, due to their open nature and limited resources, WSNs have become an easy target for different security threats, like intrusion attempts. Intrusion detection systems (IDSs) protect WSNs from these threats. This research examines the intrusion detection methods for WSNs and focuses on those that use computational intelligence. This review explores the usefulness of different computational intelligence methods in detecting intrusions in WSNs. It also suggests areas where more research is needed and offers possible directions for further exploration. © 2024 IEEE.

关键词： Network intrusion

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Advancing HRM with AI Powered Recruitment Performance Management and Employee Engagement Using One Class SVMs 3

Advancing HRM with AI Powered Recruitment Performance Manage...

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3rd International Conference on Integrated Circuits and Communication systems, ICICACS 2025

作者： Banu, Rafiya Tripathi, Ruchi Sharma, Saumya Chenniappan, Loganathan Chandrasekaran, K. Umanesan, R. B. S. Abdur Rahman Crescent Institute of Science and Technology Department of Commerce Chennai India SRM-IST Faculty of Management Studies Ghaziabad India The Northcap University Department of Management & Commerce Gurugram India Business Administration IBRI Oman K.S.R College of Engineering Department of Mechanical Engineering Tiruchengode India School of Computing Vel Tech Rangarajan Dr Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331508456

AI is making labour-intensive HRM operations like hiring, performance review, and employee engagement more efficient and effective. The incorporation of AI technology in HRM could change several sectors. Through efficient applicant sourcing, screening, and selection, AI-driven solutions simplify hiring processes and ensure fair and accurate picks. Performance management using AI-powered solutions provides data-driven feedback and customized development plans to align individual progress with organizational goals. Predictive analytics improve employee engagement by personalizing experiences and meeting needs. The method focuses on preprocessing and model training. Data are cleansed, ordinal and categorical variables encoded, scaling characteristics and engineering features applied, and dimensional homogeneity assured before processing. For model training, the simple and robust one-class SVM technique is used. One-class SVM model outperformed others with 95.28%. This method worked best compared to GAN and GRU models. AI could improve HRM by improving decision-making and offering data-driven solutions. The findings show that the proposed model outperforms current options, providing the framework for HRM AI applications. © 2025 IEEE.

关键词： Human resource management

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Thermal Modelling of IPT Coil Embedded in Resin for the Roadway

Thermal Modelling of IPT Coil Embedded in Resin for the Road...

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Wireless Power Week (WPW)

作者： Naoya Sasa Takahiro Yamahara Seho Kim Takehiro Imura Grant Covic Yoichi Hori Hiroyuki Mashito Hiroki Tanaka Faculty of Science and Engineering Tokyo University of Science Department of Electrical Computer and Software Engineering University of Auckland Technical Research Institute Toa Road Corporation

ISBN: (数字)9798350349139

ISBN: (纸本)9798350349146

This paper presents an investigation into the thermal behaviour of a copper coil embedded into a block of resin that is bound to the asphalt in the roadway. The roadway is made up of three layers of 50mm asphalt and the resin block surrounding the coil was placed within the surface layer. The thermal behaviour of the coil and the surrounding environment is presented when the coil is energised at 90A DC to be within the electromagnetic radiation limits. Based on the exerpimental results, simulations are conducted in ANSYS Maxwell and Icepak to predict the temperature rise using AC energisation at 85kHz. The coil is energised in the simulation with a range of currents to predict the thermal stress the resin block will withstand at steady-state conditions. The simulation findings predict the thermal behaviour of the resin block and the surrounding asphalt when the coil is transferring 10kW.

关键词： Coils Wireless communication Asphalt Simulation Predictive models Steady-state Resins

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A public data-set for synchronous motor electrical faults diagnosis with CNN and LSTM reference classifiers

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Energy and AI 2023年第4期14卷 221-237页

作者： Zhenglong Sun Ram Machlev Qianchao Wang Juri Belikov Yoash Levron Dmitry Baimel Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)JilinChina The Andrew and Erna Viterbi Faculty of Electrical&Computer Engineering Technion-Israel Institute of TechnologyHaifa 3200003Israel Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education School of Energy and EnvironmentSoutheast UniversityNanjing210096China Department of Software Science Tallinn University of TechnologyAkadeemia tee 15a12618 TallinnEstonia Department of Electrical and Electronics Engineering Sami Shamoon College of EngineeringBeer-Sheva84100Israel

In the last two decades,motor operation monitoring tools have become a necessity,and many studies focus on the detection and diagnosis of motor electrical ***,at present,a core obstacle that prevents the direct comparison of such classification techniques is the lack of a standard database that can be used as a *** view of this,we offer here a public experimental data-set that has beendesigned specifically for the comparison of synchronous motor electrical fault *** data-set comprises five types of motor electrical faults:open phase between inverter and motor;short circuit/leakage current between two phases;short circuit/leakage current in phase-to-neutral;rotor excitation voltage disconnection;and variation of rotor excitation *** addition,each fault has been recorded as a four-dimensional signal:three phase voltages;three phase currents;motor speed;and motor *** package includes two deep-learning reference classifiers that are based on a convolutional neural network(CNN)and long short term memory(LSTM).Due to the good performance of these classifiers,we suggest that they can be used by the community as benchmarks for the development of new and better motor electrical fault classification *** database and the reference classifiers are examined and insights regarding different combinations of features and lengths of recording points are *** developed code is available online,and is free to use.

关键词： Motor faults Synchronous motors Public data-set Classification Deep-learning CNN LSTM

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Development of A Chatbot for the Online Application Telegram Chat with An Approach to the Emotion Classification Text Using the Indobert-Lite Method 4

Development of A Chatbot for the Online Application Telegram...

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4th International Conference on Cybernetics and Intelligent System, ICORIS 2022

作者： Hulliyah, Khodijah Rayyan, Faishal Bakar, Normi Sham Awang Abu Syarif Hidayatullah State Islamic University Jakarta Faculty of Science and Technology Department of Informatics Engineering Jakarta Indonesia KICT International Computer Science Department Gombak Malaysia

ISBN: (纸本)9781665453950

The increasing preference for text-based communication on online chat applications has caused the number of social interactions to increase rapidly. However, text-based communication usually results in misunderstandings resulting from the absence of feeling intonation and emotions in the text. This study aims to create a chatbot that can detect emotions text to be entered into online chat applications. This study used a pre-trained model specifically trained from a collection of Indonesian-language datasets, namely IndoBERT-lite. The dataset used to train the model is a collection of Indonesian tweets totaling 4,403 which have been labeled with 5 classes of emotions, namely love, happy, anger, sadness, and fear. The hyperparameters used in this study to train the model were 5 epochs, batch size 16, learning rate 0.000003, and adam optimizer. Based on the test results with the parameters already mentioned, the accuracy, F1 score, recall, and precision values were obtained in the training set of 89%, 89%, 89%, and 90%, while the validation set obtained 70%, 71%, 70%, and 72%. © 2022 IEEE.

关键词： Social networking (online)

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Light-weight Sketch Recognition with Knowledge Distillation 6

Light-weight Sketch Recognition with Knowledge Distillation

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6th International Conference on Multimedia Analysis and Pattern Recognition, MAPR 2023

作者： Huynh, Viet-Tham Nguyen, Tam.V Tran, Minh-Triet Software Engineering Laboratory Faculty of Information Technology University of Science VNU-HCM Viet Nam Vietnam National University Ho Chi Minh City Viet Nam University of Dayton Department of Computer Science United States

ISBN: (纸本)9798350327410

Recognizing hand-drawn sketches is a promising starting point for various applications, such as assisting artists in creating 3D environments for games or virtual environment scenes quickly and efficiently from concept arts. In addition, by understanding drawings, we can generate 3D models that can be used for further design and development. Thus, in this paper, we aim to develop a novel lightweight network that can accurately recognize sketch drawings. We propose a lightweight-yet-efficient neural network based on MobileNetV2 for sketch recognition and employ knowledge distillation to train the proposed model from EfficientNet-B4. To evaluate the accuracy of the proposed method, we collect a dataset of sketches comprising 1800 drawings in 12 categories, ranging from furniture to animals. The experimental results show that our network model achieves an accuracy of 96.7%, with 96.9% precision, 96.7% recall, and 96.7% F1-score. These results demonstrate that the proposed approach has great potential for practical sketch recognition applications, such as interior design or VR scene generation. © 2023 IEEE.

关键词： Distillation

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