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Artificial intelligence-assisted generative pretrained transformers for applications of ChatGPT in higher education among graduates

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SN Social Sciences 2024年第2期4卷 1-23页

作者： Prajapati, Jigna B. Kumar, Ashwini Singh, Sudarshan Prajapati, Bhupendra Thakar, Yash Tambe, Prashant R. Ved, Amit Acharya Motibhai Patel Institute of Computer Studies Ganpat University Gujarat Kherva 384012 India Department of Mechanical Engineering School of Engineering and Technology Manav Rachna International Institute of Research and Studies (Deemed to Be University) Haryana Faridabad 121004 India Department of Pharmaceutical Sciences Faculty of Pharmacy Chiang Mai University Chiang Mai 50200 Thailand Office of Research Administration Chiang Mai University Chiang Mai 50200 Thailand Shree S. K. Patel College of Pharmaceutical Education and Research Ganpat University Gujarat Kherva 384012 India Assistant Manager at Incubation Centre Ganpat University Gujarat Kherva 384012 India Technical Campus Akole Maharashtra Nawalewadi 422601 India Department of Electrical Engineering Marwadi University Gujarat Rajkot 360003 India

Education that aims at sustainable development is a growing field, notably over the last few decades. Measuring the level of technology-based educational development has become a necessity for well-rounded educational experience. The availability of numerous artificial intelligence-based software is leading education in dynamic way. technology based on artificial intelligence (AI) has been advancing constantly and becoming increasingly pervasive in various facets of our lives. AI in education is facilitating bit-sized learning with maintaining a human touch by digital courses and other low-storage study materials. Chatbots and other AI-enabled technologies assisting in enhancing education learning experience;however, their major drawbacks are algorithmic bias. The present study uses a qualitative case study to analyze chat Generative Pre-trained Transformer (ChatGPT) in education among youngsters and explore its potential opportunities in the fields of higher education. Also, the present survey-based analysis highlights the difficulties, risks, limitations of AI in higher education, and recent developments in AI among the graduates. The survey-based analysis indicated that AI-assisted ChatGPT has gained tremendous popularity among researchers of varied fields. The discussion has led to the conclusion that AI holds a significant promise to be the best solution for all future educational developments in a variety of ways. However, safe usage with ethics is required while working with AI from an academic perspective. Furthermore, a broad investigation is required among various users of different streams and age groups to strengthen utilization of AI-enabled technologies for enhance learning process. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Artificial intelligence Case study Chatbots ChatGPT GPT Higher education

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Dual-Band Planar Microstrip Monopole Antenna Design Using Multi-Objective Hybrid Optimization Algorithm

Dual-Band Planar Microstrip Monopole Antenna Design Using Mu...

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Progress in Electromagnetic research Symposium (PIERS)

作者： V. Hosseini F. Shapour P. Pinho Y. Farhang K. Majidzadeh Ch. Ghobadi J. Nourinia S. Barshandeh M. Shokri Zh. Amiri M. Jalilirad K. Kaboutari Department of Computer Engineering and Information Technology Payame Noor University Tehran Iran Computer Engineering Department Urmia Branch Islamic Azad University Urmia Iran Instituto de Telecomunicações Aveiro Portugal Department of Electronics Telecommunications and Informatics University of Aveiro Aveiro Portugal Department of Computer Engineering Khoy Branch Islamic Azad University Khoy Iran Department of Electrical Engineering Urmia University Urmia Iran Department of Computer Science School of Engineering Afagh Higher Education Institute Urmia Iran

This research uses a new proposed multi-objective optimization algorithm that utilizes an untested combined chaotic map to integrate Customized Mutated PSO (CM-PSO) with a Modified Genetic Algorithm (MGA) to design an antenna with specific electromagnetic characteristics. The hybrid approach achieves preferred outcomes faster than PSO, CM-PSO, GA, and MGA by avoiding being trapped in local minimums. The proposed Metaheuristic Algorithm (MA) functionality has been authenticated successfully using Benchmark Functions (BFs) like Rastrigin Function (RaF), Ackley Function (AF), Rosenbrock Function (RoF), and Booth Function (BoF). Finally, the validity of the offered approach for electromagnetic applications is demonstrated by optimizing a dual-band planar microstrip monopole antenna with a simple structure, such that its optimized $S_{11}$ be less than -10 dB at two frequency bands encompasses 2.4 to 2.484 and 5.15 to 5.825 GHz for Wireless Local Area Network (WLAN) with IEEE 802.11 standards. The proposed algorithm allows the optimization criteria to be customized. The optimization algorithm developed in MATLAB is used to determine the necessary parameter adjustments in order to achieve expected frequency bands using CM-PSO or an innovative MGA, while high-frequency and electromagnetic simulations are performed using computer Simulation technology (CST) Studio Suite. The dimensions of the proposed antenna's elements are critical input parameters of the algorithm, named decision variables.

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User-experience oriented POI recommendation with pseudo rating

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Multimedia Tools and Applications 2025年第16期84卷 16583-16603页

作者： Yi, Kun Yamagishi, Ryu Li, Jiyi Li, Taishan Bai, Zhengyang Ma, Qiang Kyoto Institute of Economic Research Kyoto University Yoshida-honmachi Sakyo-ku Kyoto Kyoto606-8501 Japan Graduate School of Informatics Kyoto University Yoshida-honmachi Sakyo-ku Kyoto Kyoto606-8501 Japan Department of Computer Science and Engineering University of Yamanashi Takeda 4-3-11 Kofu 400- 8511 Yamanashi Japan Research Institute of Non-Timber Forestry Chinese Academy of Forestry Key Laboratory of Non-Timber Forest Germplasm Enhancement & Utilization of State Administration of Forestry and Grassland No. 3 Weiwu Road Jinshui District Zhengzhou450003 China RIKEN Center for Computational Science RIKEN Nihonbashi 1-chome Mitsubishi Bld. 15th floor 1-4-1 Nihonbashi Chuo-ku Tokyo103-0027 Japan Department of Information Science Kyoto Institute of Technology Matsugasaki Sakyo-ku Kyoto Kyoto606-8585 Japan

Point-of-interest (POI) recommendation faces challenges in managing data sparsity and cold-start problems, particularly in terms of personalized recommendation. Firstly, most existing users only visit a small number of POIs, which results in severe data sparsity and makes most conventional methods unsuitable because they require adequate historical data from each user to learn the model. In addition, new users have little or no historical record. Existing ask-to-rate methods for cold start user scenarios treat user answers as historical data, which is inappropriate and causes difficulty in capturing user preferences. Therefore, in this paper, to tackle the data sparsity problem, we propose a user-experience model (UEM) to uncover user behaviors from several aspects. The proposed UEM involves four factors: Who (does it), What (the user does), Where (the user does it), and When (the user does it). In contrast to other methods that model user behavior from individual records, our model introduces a latent variable of user experience to extract similarity among users. This feature makes our model suitable for mitigating the severe sparse-data issue in POI recommendations. Furthermore, to handle the cold-start problem for new users, we propose a pseudo-rating mechanism (PRM) to capture new users’ preferences and recommend POIs. For new users, photos are provided for rating, and these ratings are then used to capture their preferences and estimate the probability of their visits. Extensive experimental results demonstrate that the proposed method achieves better recommendation performance and fairness than the state-of-the-art methods. Moreover, user study results validates that the users’ preferences captured via PRM are satisfactory, and UEM provides satisfactory POI recommendations. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Behavioral research

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Classification of Microstructure Images of Metals Using Transfer Learning 8th

Classification of Microstructure Images of Metals Using Tran...

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8th International Conference on Modelling and Development of Intelligent Systems, MDIS 2022

作者： Khan, Mohammed Abdul Hafeez Sabnis, Hrishikesh Jothi, J. Angel Arul Kanishkha, J. Prasad, A. M. Deva Department of Computer Science Engineering Birla Institute of Technology and Science Pilani Dubai Campus Dubai International Academic City Dubai United Arab Emirates Department of Mechanical Engineering Birla Institute of Technology and Science Pilani Dubai Campus Dubai International Academic City Dubai United Arab Emirates Department of Mechanical Engineering Rochester Institute of Technology of Dubai Dubai Silicon Oasis Dubai United Arab Emirates

ISBN: (纸本)9783031270338

This research focuses on the application of computer vision to the field of material science. Deep learning (DL) is revolutionizing the field of computer vision by achieving state-of-the-art results for various vision tasks. The objective of this work is to study the performance of deep transfer learned models for the classification of microstructure images. With light optical microscopes, microstructure images of four different metals were acquired for this task, including copper, mild steel, aluminum, and stainless steel. The proposed work employs transfer learned powerful pre-trained convolutional neural network (CNN) models namely VGG16, VGG19, ResNet50, DenseNet121, DenseNet169 and DenseNet201 to train and classify the images in the acquired dataset into different classes of metals. The results showed that the transfer learned ResNet50 model has obtained the highest accuracy of 99%, outperforming other transfer learning models. This also shows that DL models can be used for automatic metal classification using microstructure images. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Microstructure

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Creating Resilient Digital Asset Management Frameworks in Financial Operations Using Blockchain technology 2

Creating Resilient Digital Asset Management Frameworks in Fi...

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2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2024

作者： Geetha, B.T. Kafila Ram, S Tulasi Amar Prabhakar Narkhede, Dr. Bani Ahmad, Ahmad Y. A. Tiwari, Mohit Saveetha School of Engineering Simats Department of Ece Tamil Nadu India Sr University School of Business Telangana Warangal India Chaitanya Bharathi Institute of Technology School of Management Studies Hyderabad India Isms Sankalp Business School Vadgon Pune India Middle East University Faculty of Business Department of Accounting and Finance Amman11831 Jordan Applied Science Private University Applied Science Research Center Jordan Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering Delhi India

ISBN: (纸本)9798350384277

Using blockchain technology to build strong digital asset management tools for financial operations is a revolutionary way to bring financial systems up to date. Blockchain technology is changing the way money works by making transfers decentralised, open, and safe. Digital Asset Management (DAM) systems help businesses easily store and share digital assets like cryptocurrencies and blockchain-based assets. Using blockchain tools like smart contracts and tokenization makes financial deals safer and more trustworthy by using cryptographic encryption and ledger systems that can't be changed. Streamlining processes and payment makes financial operations more efficient. But problems like scaling and following the rules must be dealt with. Blockchain technology has many uses in finance, such as cross-border payments, tokenizing assets, and smart contracts. It is also changing how financial services are regulated. This study uses secondary data from academic research papers, peer-reviewed journals, and industry reports to look the use of blockchain technology to financial transactions, learn about DAM basics, look into blockchain tools in financial services, and judge how blockchain is used in financial transactions. This study helps us understand and use strong digital asset management systems in financial transactions that use blockchain technology by doing a thorough analysis. © 2024 IEEE.

关键词： Decentralized finance

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Prioritizing TWAS Genetic Biomarkers for Melanoma Metastasis via Gene Expression Profiling*

Prioritizing TWAS Genetic Biomarkers for Melanoma Metastasis...

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Data Science and engineering in Healthcare, Medicine and Biology, IEEE EMBS Special Topic Conference on

作者： Mohamed N. Saad Belal Medhat Mohamed Hamed Biomedical Engineering Department Faculty of Engineering Minia University Egypt Institute for Biostatistics and Informatics in Medicine and Ageing Research (IBIMA) Rostock University Medical Center Rostock Germany Computer Science and Engineering Department Faculty of Media Engineering and Technology German University in Cairo Egypt Faculty of Media Engineering and Technology German University in Cairo Egypt

The development of novel therapeutic approaches that target gene alterations in melanoma cells remains an area of active research. This study prioritized ten genes out of 76 genes - associated with melanoma through a transcriptome-wide association study (TWAS). We investigated the potential of the identified ten genes in prognosis of metastasis in melanoma *** Relevance: Our findings have clinical implications for melanoma treatment strategies. Targeted therapies that specifically address the dysregulation of our 10 genes may hold promise in preventing or slowing melanoma metastasis.

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Sentence Embedding Models for Similarity Detection of Software Requirements

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SN computer Science 2021年第2期2卷 1-11页

作者： Das, Souvick Deb, Novarun Cortesi, Agostino Chaki, Nabendu Department of Computer Science and Engineering University of Calcutta Kolkata 700106 India Indian Institute of Information Technology Vadodara Gujarat Gandhinagar 382028 India Department of Environmental Science Informatics and Statistics Ca’ Foscari University Venezia 30172 Italy Department. of Computer Science and Engineering University of Calcutta Kolkata 700106 India

Semantic similarity detection mainly relies on the availability of laboriously curated ontologies, as well as of supervised and unsupervised neural embedding models. In this paper, we present two domain-specific sentence embedding models trained on a natural language requirements dataset in order to derive sentence embeddings specific to the software requirements engineering domain. We use cosine-similarity measures in both these models. The result of the experimental evaluation confirm that the proposed models enhance the performance of textual semantic similarity measures over existing state-of-the-art neural sentence embedding models: we reach an accuracy of 88.35%—which improves by about 10% on existing benchmarks. © 2021, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. part of Springer Nature.

关键词： Requirements similarity Semantic similarity Sentence embedding

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A Multi-Stream Scrambling and DNA Encoding Method Based Image Encryption

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computer Systems Science & engineering 2023年第11期47卷 1321-1347页

作者： Nashat Salih Abdulkarim Alsandi Dilovan Asaad Zebari Adel Al-Zebari Falah Y.H.Ahmed Mazin Abed Mohammed Marwan Albahar Abdulaziz Ali Albahr Information Technology Duhok Private Technical InstituteDuhokIraq Department of Computer Science College of ScienceNawroz UniversityDuhok42001Iraq Department of Information Technology Technical College of Informatics AkreDuhok Polytechnic UniversityDuhokIraq Faculty of Computing and Information Technology Sohar UniversityOman College of Computer Science and Information Technology University of AnbarAnbar31001Iraq Department of Science Umm Al Qura UniversityP.O.Box 715MeccaSaudi Arabia College of Applied Medical Sciences King Saud Bin Abdulaziz University for Health SciencesAl Ahsa31982Saudi Arabia King Abdullah International Medical Research Center Al-Ahsa36276Saudi Arabia

Information security has emerged as a key problem in encryption because of the rapid evolution of the internet and ***,the progress of image encryption techniques is becoming an increasingly serious issue and considerable *** space of the key,encryption-based low confidentiality,low key sensitivity,and easily exploitable existing image encryption techniques integrating chaotic system and DNA computing are purposing the main problems to propose a new encryption technique in this *** our proposed scheme,a three-dimensional Chen’s map and a one-dimensional Logistic map are employed to construct a double-layer image encryption *** the confusion stage,different scrambling operations related to the original plain image pixels are designed using Chen’s map.A stream pixel scrambling operation related to the plain image is ***,a block scrambling-based image encryption-related stream pixel scrambled image is *** the diffusion stage,two rounds of pixel diffusion are generated related to the confusing image for intra-image ***’s map,logistic map,and DNA computing are employed to construct diffusion operations.A reverse complementary rule is applied to obtain a new form of DNA.A Chen’s map is used to produce a pseudorandom DNA sequence,and then another DNA form is constructed from a reverse pseudorandom DNA ***,the XOR operation is performed multiple times to obtain the encrypted *** to the simulation of experiments and security analysis,this approach extends the key space,has great sensitivity,and is able to withstand various typical *** adequate encryption effect is achieved by the proposed algorithm,which can simultaneously decrease the correlation between adjacent pixels by making it near zero,also the information entropy is *** number of pixels changing rate(NPCR)and the unified average change intensity(UACI)both are very near to optimal values.

关键词： Grayscale image encryption stream scrambling-confusion DNA encoding XOR operation chaotic systems

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An Android App for Posture Analysis Using OWAS

An Android App for Posture Analysis Using OWAS

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16th International Joint Conference on Biomedical engineering Systems and Technologies, BIOSTEC 2023

作者： Lins, Christian Quang, Franziska Minh-Khai Dang Schulze, Rica Lins, Stefanie Hein, Andreas Fudickar, Sebastian Department of Computer Science Hamburg University of Applied Sciences Hamburg20099 Germany Assistance Systems and Medical Device Technology Carl von Ossietzky University Oldenburg Oldenburg26129 Germany MOVE Junior Research Group Institute of Medical Informatics University ofLuebeck Germany University of Hagen Hagen58097 Germany

In this paper the APA, an App for Posture Analysis, that incorporates the OWAS method (Ovako Working Posture Analysis System) for assessing potential harmful postures of physically hard working employees, is presented and evaluated. The app is intended as a tool for occupational safety experts in assessing the individual postures of workers to identify and prevent harmful working situations in regards to musculoskeletal hazards. For this, APA incorporates a digitized assessment sheet for the OWAS method and timing support that helps occupational safety experts structure and simplify the assessment workflow. To investigate whether the protocol sheet can be replaced with the app, a study was conducted in which the inter-rater reliability among the app and the paper protocol sheet (as control group) was evaluated. In addition, the usability of the app was determined via the User Experience Questionnaire (UEQ), In the study, the app achieved higher inter-rater reliability for watching a video recording of postures than the control group. The chi-square test revealed differences in the use of the app and paper only for leg postures. The UEQ indicated overall above average results, which indicates a sufficient usability, which was also confirmed by free-textual comments of the 13 study participants. The results suggest that it would be possible to replace the paper protocol sheet in the future with an app. © 2023 by SCITEPRESS – Science and technology Publications, Lda.

关键词： Musculoskeletal system

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Constructing an Evaluation Framework for English Teaching in Higher Education: Integrating Neural Networks and Natural Language Processing 3rd

Constructing an Evaluation Framework for English Teaching in...

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3rd International Conference on Mechanical and Energy Technologies, ICMET 2023

作者： Deshmukh, Ram Ramachandran, K. Anute, Nilesh Rajeswari, T.S. Chouhan, Kuldeep Fatma, Gulnaz School of Engineering SR University Telangana Warangal India Postdoctoral Researcher Jesselton University College Jalan Lintas Sabah Kota Kinabalu88300 Malaysia ASM’S Institute of Business Management and Research Pune India Department of English Koneru Lakshmaiah Education Foundation AP Vaddeswaram India Department of Computer Science and Applications Sharda School of Engineering and Technology Sharda University Greater Noida201310 India Department of English Jazan University Jazan Saudi Arabia

ISBN: (纸本)9789819727155

In the dynamic landscape of higher education, the effectiveness of English teaching is paramount, as it directly impacts students’ communication skills, academic success, and future career prospects. To enhance the quality of English instruction in higher education, this study presents an innovative evaluation model that harnesses the power of neural networks and natural language processing (NLP). The model's potential for customization and scalability makes it a valuable tool for higher education institutions seeking to optimize their English teaching programs. Furthermore, it contributes to the broader exploration of how AI and NLP technologies can transform the field of education, fostering more efficient and personalized learning experiences. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Quality control

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