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Journal of Central South University 2023年第8期30卷 2616-2626页

作者： KHALID Abdulkhaliq M-alharbi HINA Gul MUHAMMAD Ramzan SEIFEDINE Kadry ABDULKAFI Mohammed-saeed Mechanical Engineering Department College of EngineeringUmm Al-Qura UniversityMakkah 24382Sandi Arabia Department of Computer Science Bahria UniversityIslamabad 44000Pakistan Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) Ajman UniversityAjman 346United Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Mathematics College of ScienceQassim UniversityBuraydah 51452Saudi Arabia

当两种不同密度和扩散速率的纳米流体混合时,会发生三重扩散和对流现象。本文主要目的是比较对流水平板上二次混合的三重扩散纳米流体的流体力学和流体磁学。文中建立的模型其他新特征考虑了可变导热系数和非线性热辐射热通量。该问题... 详细信息

当两种不同密度和扩散速率的纳米流体混合时,会发生三重扩散和对流现象。本文主要目的是比较对流水平板上二次混合的三重扩散纳米流体的流体力学和流体磁学。文中建立的模型其他新特征考虑了可变导热系数和非线性热辐射热通量。该问题由一组方程组成,借助MATLAB bvp4c包进行求解。为了使参数与相关剖面的影响可视化,给出了图形说明,并利用图表来评估关键参数变化是如何影响相关场及其相应的物理量。通过对盐1和盐2的Dufour参数的多次估计,可以推断出流体流速的波动。验证了流体动力流相对于流体磁流的优势。此外,还将特定情景下已发表的结果与当前研究结果进行了比较。

关键词：三重扩散纳米流体二次混合对流可变导热系数非线性热辐射

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Using Sparse Autoencoders to Perform Blind Source Separation of High-Density Myoelectric Signal 33

Using Sparse Autoencoders to Perform Blind Source Separation...

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33rd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2023

作者： Romano, Marcelo Ramos Duarte, Leonardo Tomazeli Elias, Leonardo Abdala University of Campinas School of Applied Sciences SP Limeira Brazil University of Campinas Neural Engineering Research Laboratory Center for Biomedical Engineering SP Campinas Brazil University of Campinas Department of Electronics and Biomedical Engineering School of Electrical and Computer Engineering SP Campinas Brazil

ISBN: (纸本)9798350324112

A recent approach to address the blind source separation (BSS) problem relies on autoencoders with a discriminator as a generative adversarial network (GAN). However, this model is difficult to train due to the lack of metrics that ensure the convergence of a GAN. In this study, we try to provide an alternative solution by replacing the discriminator with appropriate regularization functions based on prior information on the sources. We tested this solution in the high-density electromyogram (HD-EMG) separation problem for a scenario with synthetic but realistic data and compared it with a classic algorithm from the literature. An interesting feature of the proposal is that it can be easily adapted for other source separation problems. Moreover, although the performance is slightly worse than the state-of the-art HD-EMG algorithm, which considers very detailed information on the problem, our proposal provides good results with a mean rate of agreement of 91.88% between the true and estimated spikes. © 2023 IEEE.

关键词： Generative adversarial networks

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A Mobile App Game Based on the Development and Design of a Puzzle Created for Educational Learning 13th

A Mobile App Game Based on the Development and Design of a P...

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13th International Conference on Methodologies and Intelligent Systems for Technology Enhanced Learning, mis4TEL 2023

作者： Sapundzhi, Fatima Kitanov, Anton Lazarova, Meglena Georgiev, Slavi Department of Communication and Computer Engineering Faculty of Engineering South-West University "Neofit Rilski" 66 Ivan Myhailov Street Blagoevgrad2700 Bulgaria Faculty of Applied Mathematics and Informatics Technical University of Sofia 8 Kliment Ohridski Blvd. Sofia1000 Bulgaria Institute of Mathematics and Infromatics Bulgarian Academy of Sciences 8 Acad. Georgi Bonchev Street Sofia1113 Bulgaria Department of Applied Mathematics and Statistics University of Ruse "Angel Kanchev" 8 Studentska Street Ruse7004 Bulgaria

ISBN: (纸本)9783031421334

This paper presents a mobile app game designed for educational learning. The game is created by using contemporary software tools, featuring five different puzzle levels in which players have to solve jigsaw puzzles and eventually the player learns an interesting fact about the scene they arranged. The game aims to improve the young player’s spatial imagination, problem-solving skills, memory, patience, concentration and motor skills. In this study the steps how to develop and implement the game are thoroughly explained. The article highlights the importance of the educational games and their potential to enhance learning outcomes in a fun and engaging way. The game’s development process and design are discussed along with its potential to be utilized as an educational tool in various settings. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： E-learning

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Leaf Classification of Jackfruit (Artocarpus heterophyllus) and Cempedak (Radermachera integra) Using Deep Learning 14

Leaf Classification of Jackfruit (Artocarpus heterophyllus) ...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Pratondo, Agus Budiman, Gelar Utoro, Rio Korio Rizqyawan, Muhammad Ilham Rudawan, Rikman A. Novianty, Astri Telkom University School of Applied Sciences Department of Multimedia Engineering Bandung Indonesia Telkom University The University Center of Excellence for Advanced Intelligent Communications Bandung Indonesia Research Center of Smart Mechatronics National Research and Innovation Agency Bandung Indonesia Telkom University School of Electrical Engineering Department of Computer Engineering Bandung Indonesia

ISBN: (纸本)9798350335095

Plant identification and categorization tasks require accurate leaf classification. In this study, we investigate the use of deep learning approaches for categorizing the leaves of cempedak (Artocarpus integra) and jackfruit (Artocarpus heterophyllus). We use the well-known deep learning architectures VGG16 and Inception v3 to correctly categorize the leaf images. A dataset of 204 leaf images, with equal representation from jackfruit and cempedak, is used to train and assess the models. According to the experimental findings, the VGG16 and Inception v3 architectures both perform exceptionally well when classifying leaves. Jackfruit and cempedak leaves are accurately classified with 97.57% accuracy by the VGG16 model. These high accuracy rates demonstrate how well deep learning models are able to differentiate between the two leaf varieties. © 2023 IEEE.

关键词： Deep learning

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Resource Allocation in Edge Computing Environment Using Deterministic Policy Gradient Algorithm

Resource Allocation in Edge Computing Environment Using Dete...

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International Conference on Advanced Computing and Communication Systems (ICACCS)

作者： C. P. Shabariram N. Shanthi P. Priya Ponnuswamy V. Subramaniyaswamy V. Sathana Department of Computer Science and Engineering PSG Institute of Technology and Applied Research Coimbatore India Department of Computer Science and Engineering Kongu Engineering College Erode India Department of Computer Science and Engineering School of Computing SASTRA University Thanjavur India

ISBN: (数字)9798350384369

ISBN: (纸本)9798350384376

In recent years, the edge computing paradigm enables the movement of processing units and storage nearer to the data available locations. The mechanism completes the computation in a short span of time in minimum bandwidth. Edge ecosystem is a type of distributed computing that is sensitive to topology and geography; the Internet of Things is a prime instance of this. Rather than referring to a single technology, Edge computing refers to an architecture. This paper proposes a resource allocation methodology that will enliven the situation between users and edge servers. By creating continuous control at the edge servers to determine resource allocation, edge computing improves reaction time, provides high security with decreased risk, scalability, lowers transmission costs, and versatility (offload targets, migration bandwidth and computing resources). The Deterministic Policy Gradient, Deep learning and Quality Network concepts are combined in the proposed system. The continuous action space is achieved by a deterministic policy gradient. The experience relay includes a quality network. In the proposed system, the actor-critic network produces a single continuous action instead of resulting probability based actions. The critic-part uses Q-value from a quality network based on current status and activity. The goal of the proposed system is to develop a Deep Deterministic Policy Gradient methodology to allocate servers for mobile users with the help of the Edge computing while taking computation resources, offloading goals and migration bandwidth into consideration. The simulation result indicates that deterministic policy gradients integrated deep learning models improve the system performance compared with Game theory.

关键词： Deep learning System performance Simulation Scalability Bandwidth Topology Servers Resource management Security Edge computing

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Visualization of Syntax and Semantics for Simple Functional Language of Natural Numbers and Boolean Values 10

Visualization of Syntax and Semantics for Simple Functional ...

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10th IEEE Jubilee International Conference on Computational Cybernetics and Cyber-Medical Systems, ICCC 2022

作者： Perháč, Ján Ferencsik, Michal Zhukovskyy, Viktor Zhukovska, Nataliia Shatnyi, Serhii Technical University of Košice Faculty of Electrical Engineering and Informatics Department of Computers and Informatics Košice Slovakia National University of Water and Environmental Engineering Department of Computer Science and Applied Mathematics Rivne Ukraine

ISBN: (数字)9781665481779

ISBN: (纸本)9781665481779

Building an abstract syntax tree is an integral part of compilers. We analyze a few of the popular techniques providing such analysis in the web environment. Based on the analysis of these solutions, we deal with the implementation of our parser solution, which also provides a graphical representation of abstract syntax trees as well as proof trees. This solution is then used in our application designed to interpret the expressions of the simple teaching functional language of natural numbers and boolean values. In addition, the application supports the evaluation (semantics) of expressions (step by step), and also their individual properties: the depth of the syntax tree, syntax tree nodes count, and the constants used in the expression. © 2022 IEEE.

关键词： Semantics

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Data-Driven Identification of Remaining Useful Life for Plastic Injection Moulds 8th

Data-Driven Identification of Remaining Useful Life for Plas...

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8th Changeable, Agile, Reconfigurable and Virtual Production Conference, CARV 2021 and 10th World Mass Customization and Personalization Conference, MCPC 2021

作者： Böttjer, Till Ørnskov Rønsch, Georg Gomes, Cláudio Ramanujan, Devarajan Iosifidis, Alexandros Gorm Larsen, Peter Department of Electrical and Computer Engineering Aarhus University Aarhus Denmark DIGIT Center Aarhus University Aarhus Denmark Department of Mechanical and Production Engineering Aarhus University Aarhus Denmark Department of Applied Mathematics and Computer Science Technical University of Denmark Kongens Lyngby Denmark

ISBN: (纸本)9783030906993

Throughout their useful life, plastic injection moulds operate in rapidly varying cyclic environments, and are prone to continual degradation. Quantifying the remaining useful life of moulds is a necessary step for minimizing unplanned downtime and part scrap, as well as scheduling preventive mould maintenance tasks such as cleaning and refurbishment. This paper presents a data-driven approach for identifying degradation progression and remaining useful life of moulds, using real-world production data. An industrial data set containing metrology measurements of a solidified plastic part, along with corresponding life-cycle data of 13 high production volume injection moulds, was analyzed. Multivariate Statistical Process Control techniques and XGBoost classification models were used for constructing data-driven models of mould degradation progression, and classifying mould state (early run-in, production, worn-out). Results show the XGBoost model developed using element metrology & relevant mould lifecycle data classifies worn-out moulds with an in-class accuracy of 88%. Lower in-class accuracy of 73% and 61% were achieved for the compared to mould-worn out less critical early run-in and production states respectively. © 2022, Springer Nature Switzerland AG.

关键词： Data-driven model Injection moulding Machine learning Predictive maintenance Smart manufacturing

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A Comparative Study of the Coulomb’s and Franklin’s Laws Inspired Algorithm (CFA) with Modern Evolutionary Algorithms for Numerical Optimization 1st

A Comparative Study of the Coulomb’s and Franklin’s Laws I...

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1st International Conference on Pervasive Knowledge and Collective Intelligence on Web and Social Media, PerSOM 2022

作者： Ghasemi, Mojtaba Zare, Mohsen Zahedi, Amir Hemmati, Rasul Abualigah, Laith Forestiero, Agostino Department of Electronics and Electrical Engineering Shiraz University of Technology Shiraz Iran Department of Electrical Engineering Faculty of Engineering Jahrom University Fras Jahrom Iran Department of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran Department of Electrical and Computer Engineering Marquette University MilwaukeeWI United States Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman Jordan Faculty of Information Technology Middle East University Amman11831 Jordan Applied Science Research Center Applied Science Private University Amman11931 Jordan School of Computer Sciences Universiti Sains Malaysia Pulau Pinang George Town11800 Malaysia Computer Science Department Prince Hussein Bin Abdullah Faculty for Information Technology Al Al-Bayt University Mafraq25113 Jordan Institute for High Performance Computing and Networking National Research Council of Italy Rende Italy

ISBN: (纸本)9783031314681

Coulomb and Franklin’s electricity laws are used in this paper to model an efficient optimization algorithm based on electric particle searches, which has been named CFA. For the CFA optimizer, the influence of electrically charged particles on each other in charged things has been predicated on the forces of attraction and repulsion. Evolutionary algorithms (EA) such as hybrid real coded genetic algorithm (RCGA) which combines the global and local search (GL-25), differential evolution (DE) with strategy adaptation (SaDE), composite DE (CoDE), the improved standard particle swarm optimization 2011 (SPSO2013) and the grouped comprehensive learning PSO (GCLPSO) are compared to the CFA optimizer for finding global solutions of seven basic benchmark functions of high dimension D = 50. (GCLPSO). Experiments have shown that the suggested CFA optimizer is quite effective and competitive for the benchmark functions. Note that the source code of the CFA algorithm is publicly available at https://***/projects/cfa, https://***/matlabcentral/fileexchange/127727-franklin-s-laws-inspired-algorithm-cfa. © 2023, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Charged particles

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Mobile Game Development Using Unity Engine 13th

Mobile Game Development Using Unity Engine

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13th International Conference on Methodologies and Intelligent Systems for Technology Enhanced Learning, mis4TEL 2023

作者： Sapundzhi, Fatima Kitanov, Anton Lazarova, Meglena Georgiev, Slavi Department of Communication and Computer Engineering Faculty of Engineering South-West University "Neofit Rilski" 66 Ivan Mihailov Street Blagoevgrad2700 Bulgaria Faculty of Applied Mathematics and Informatics Technical University of Sofia 8 Kliment Ohridski Blvd. Sofia1000 Bulgaria Institute of Mathematics and Infromatics Bulgarian Academy of Sciences 8 Acad. Georgi Bonchev Street Sofia1113 Bulgaria Department of Applied Mathematics and Statistics University of Ruse "Angel Kanchev" 8 Studentska Street Ruse7004 Bulgaria

ISBN: (纸本)9783031421334

Unity is a popular game development platform. Various industries are inspired by it and this can be a positive impact on the learning motivation, career growth and job opportunities. The aim of this paper is to develop and implement a 3D game application for education promoting through innovation and digital skills. The game consists of two parts. The first part of the developed application is a maze that the player must overcome. In this labyrinth the player has to collect a certain number of specific bags that contain pieces of the needed puzzle. The second part is a puzzle that the player begins to arrange. If the puzzle is arranged correctly, then the player can read an interesting fact about what is seen on the picture. The theme given on the picture is an educational theme and it main aim is to develop the educational and mental abilities of the playersp who may also be students. The game is suitable for a wide range of potential players as it can be interesting and educational for children, teenagers and even adults. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Image processing

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AI Based Prediction for Heart Disease: A Comparative Analysis and an Improved Machine Learning Approach 6

AI Based Prediction for Heart Disease: A Comparative Analysi...

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6th Asian Conference on Artificial Intelligence Technology, ACAIT 2022

作者： Raval, Jay Verma, Jai Prakash Islam, Sardar N.M. Jain, Rachna Thakur, Narina Institute of Technology Nirma University Computer Science Engineering Department Ahmedabad India Victoria University Applied Informatics Research Melbourne Australia Bhagwan Parshuram Institute of Technology Department of Computer Science and Engineering Delhi India

ISBN: (纸本)9781665453110

Heart disease problems are growing day by day in the world. Many factors are responsible for increasing the chance of heart attack and any other disease. Many countries have a low level of cardiovascular competence in predicting heart disease-related issues. Finding the best accurate machine learning classifiers for various diagnostic uses by data mining and machine learning techniques aids in predicting whether or not the heart disease-related issue will occur. To predict heart disease, a number of supervised machine-learning algorithms are used and their effectiveness are evaluated. With the exceptionof MLP and KNN, all applied algorithms had their estimated feature significance scores for each feature. This helps to find the main factors affecting heart disease and the accuracy of the model, which helps to get the best prediction. At the end of the research the support vector machine gives us 87.91 % highest testing accuracy compare with all applied machine learning algorithm. © 2022 IEEE.

关键词： Data mining

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