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1st International Conference on Advances in Computing Research, ACR’23

作者： Salah, Ahmad Bekhit, Mahmoud Alkalbani, Asma M. Mohamed, Mohamed A. Lestari, Nur I. Fathalla, Ahmed Computer Science Department Faculty of Computers and Informatics Zagazig University Zagazig Sharkia Egypt Information Technology Department College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Ad Dhahirah516 Oman Faculty of Engineering and Information Technology University of Technology Sydney SydneyNSW Australia Kent Institute Australia SydneyNSW Australia 2P Perfect Presentation Riyadh Riyadh Saudi Arabia Computer Science Department Faculty of Computers and Informatics Suez Canal University Ismailia Egypt

ISBN: (纸本)9783031337420

The Internet of Things (IoT) systems include a massive number of connected devices. The communication between these devices requires a huge amount of communication. Thus, it is very crucial for an IoT system to reduce communication volumes by minimizing the amount of data transmission. There are several approaches to achieving the goal of data transmission reduction, such as data compression and dual prediction. Dual prediction schemes received more attention in comparison to data compression. The mainstream techniques for proposing dual prediction schemes in the literature can be classified into two main groups, namely, filter-based and deep learning-based methods. The filter-based methods, such as the 1-D Kalman filter, are lightweight in terms of running time and the model’s memory requirements. On the other hand, deep learning-based methods require more memory space and training time, but deep learning models are more accurate as predictive models in comparison to filter-based methods in dual prediction schemes. There are very limited efforts to utilize machine learning methods in dual prediction schemes as a compromise between the aforementioned mainstream techniques. In this work, we extended one of these limited efforts, which utilizes boosting ensemble learning as a machine learning predictive method in a proposed dual prediction scheme. The current work proposes exploring the performance gap between the three main approaches to ensemble learning, namely, boosting, stacking, and bagging. The three proposed ensemble learning models are evaluated on a real dataset and compared against state-of-the-art methods. The obtained results show that among the ensemble learning models, boosting and bagging models are better than the stacking model, but the three proposed ensemble learning models outperformed the state-of-the-art methods of comparison. For instance, the average numbers of mispredictions for all of the experiments were 580, 551, and 1,106 for boosting, ba

关键词： Forecasting

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IMPACT OF FEAR AND HARVESTING EFFORT ON A DIFFERENTIAL-ALGEBRAIC PREY-PREDATOR MODEL BASED ON SQUARE ROOT FUNCTIONAL RESPONSE

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Journal of Mathematical sciences (United States) 2025年 1-21页

作者： Elsadany, A.A. Mahapatra, G.S. Santra, P.K. Pal, D. Elsonbaty, A. Al-khedhairi, A. Department of Mathematics College of Science and Humanities in Al-Kharj Prince Sattam Bin Abdulaziz University Al-Kharj 11942 Saudi Arabia Department of Basic Science Faculty of Computers and Informatics Suez Canal University Ismailia 41522 Egypt Department of Mathematics National Institute of Technology Puducherry Karaikal 609609 India Maulana Abul Kalam Azad University of Technology Kolkata 700064 India Indian Institute of Engineering Science and Technology Shibpur Howrah 711103 India Department of Mathematics and Engineering Physics Faculty of Engineering Mansoura University Mansoura 35516 Egypt Department of Statistics and Operations Research College of Science King Saud University P.O. Box 2455 Riyadh 11451 Saudi Arabia

An economic differential-algebraic prey-predator model incorporating square root functional response and fear of predators is presented in this current paper. The article is developing a prey-predator structure on the intention to an economic viewpoint through harvesting on prey species. The equilibrium points and stability status of both the differential-only model and differential-algebraic model are identified and examined. Impacts of fear effect on the stabilities of the model equilibrium points are studied. The Hopf bifurcation analysis is carried out concerning the prey species’ intensity of fear and growth rate. The singularity-induced bifurcation for zero and non-zero economic profits is discussed for the proposed system. A state feedback controller is constructed for zero economic profit to keep the persistence property of the prey-predator model. Numerical simulations and graphical presentations are provided in support of our analytical findings. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Bifurcation Bioeconomics Differential-algebraic Fear effect Prey-predator

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Pre-trained Self-Attention Framework: An Efficient Mechanism for Source Separation 13th

Pre-trained Self-Attention Framework: An Efficient Mechanism...

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13th International Conference on Information technology and its Applications, CITA 2024

作者： Minh Tan, Ha Fhadli, Muhammad Kim Quoc, Nguyen Vu, Duc-Quang Faculty of Information Technology Nguyen Tat Thanh University Ho Chi Minh City Viet Nam Department of Informatics Faculty of Engineering Khairun University Ternate City Indonesia Department of Computer Science and Information System Thai Nguyen University of Education Thai Nguyen Viet Nam

ISBN: (纸本)9783031741265

In this work, the pre-trained model of the self-attention framework is proposed for single-channel speech separation. Firstly, all layers in the pre-trained self-attention framework are frozen. The model is then retrained through three stages using the scheduling mechanism for learning rates and the layers of the framework are unlocked following the schedule. This way, the model is relearned, enhanced, and updated from previous knowledge. This is an effective way to improve the advanced model performance while significantly reducing the time and cost of a training model. This method is beneficial in applying existing models to perform a similar task or enhancing model performance. In this strategy, the pre-trained system outperforms the non-pre-trained system since the following phases of the model’s training repurpose characteristics extracted through the previously trained early phases. The suggested method is tested and assessed on a conventional dataset. The findings from experiments suggest that the methodology has higher performance than the baseline framework and outperforms current methods for the monaural speech separation task. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： fine-tuning framework pre-trained model self-attention mechanism speech separation time masking framework Transformer

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Reduced graphene oxide (rGO) and 5, 10, 15, 20-tetra-p-tolyl-21H, 23H-porphine (TPTP) composite: highly reproducible and repeatable chemiresistive SO2 sensor

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Applied Physics A: Materials science and Processing 2024年第1期130卷 1-16页

作者： Khune, Abhaysinh S. Narwade, Vijaykiran N. Dole, B.N. Ingle, Nikesh N. Tsai, Meng-Lin Hianik, Tibor Shirsat, Mahendra D. RUSA Centre for Advanced Sensor Technology Department of Physics Dr. Babasaheb Ambedkar Marathwada University MS Aurangabad431 004 India MGM University MS Aurangabad431003 India Department of Materials Science and Engineering National Taiwan University of Science and Technology Taipei10607 Taiwan Department of Nuclear Physics and Biophysics Faculty of Mathematics Physics and Informatics Comenius University Bratislava842 48 Slovakia

In the current study, a chemiresistive SO2 sensor based on a composite of reduced graphene oxide (rGO) and 5, 10, 15, 20-tetra-p-tolyl-21H, 23H-porphine (TPTP) was developed and extensively studied. Improved Hummers methods were used to synthesize graphene oxide (GO), and a thermally heating bottom-up approach was used to reduce GO to rGO. Gold electrodes were thermally coated on the transparent sheet using a thermal evaporator. The composite of rGO/TPTP was synthesized using a simple chemical method. Structural, morphological, spectroscopic, electrical, and optical studies were carried out using X-ray diffraction, atomic force microscopy, field emission scanning electron microscopy, Fourier-transfer infrared spectroscopy, Raman spectroscopy, current–voltage, and UV–vis spectroscopy, respectively. The sensing response of rGO/TPTP for various concentrations of sulfur dioxide (SO2) was investigated in chemiresistive modality. The rGO/TPTP composite chemiresistive sensor displayed exceptional performance, with a consistent response spanning 1 ppm to 10 ppm. It exhibited outstanding repeatability, linearity, stability, and boasted an impressive limit of detection (LOD) of 1 ppm. This LOD is significantly lower than the recommended permissible exposure limit (PEL) of 5 ppm set by OSHA (Occupational Safety and Health Administration), USA. The sensor based on the rGO/TPTP composite exhibited a very fast response and recovery time of 33 s. and 27 s. respectively. Graphical abstract: [Figure not available: see fulltext.] © 2024, The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.

关键词： Graphene

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A New, Reconfigurable Circuit Offering Functionality of AND and OR Logic Gates for Use in Algorithms Implemented in Hardware 33

A New, Reconfigurable Circuit Offering Functionality of AND ...

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33rd IEEE International Conference on Microelectronics, MIEL 2023

作者： Talaska, Tomasz Dlugosz, Rafal Nikolic, Tatjana Nikolic, Goran Stefanski, Tomasz Dlugosz, Michal Talaska, Michal Bydgoszcz University of Science and Technology Faculty of Telecommunication Computer Science and Electrical Engineering Bydgoszcz85-796 Poland Aptiv Services Poland Kraków30-399 Poland University of Niš Faculty of Electronic Engineering Niš18000 Serbia Gdanśk Univeristy of Technology Faculty of Electronics Telecommunications and Informatics Gdanśk80-233 Poland Poznan University of Technology Faculty of Control Robotics and Electrical Engineering Poznan60-965 Poland Complex of Electronics Schools Bydgoszcz85-092 Poland

ISBN: (纸本)9798350347760

The paper presents a programmable (using a 1-bit signal) digital gate that can operate in one of two OR or AND modes. A circuit of this type can also be implemented using conventional logic gates. However, in the case of the proposed circuit, compared to conventional solutions, the advantage is a much smaller number of transistors necessary for its implementation. Circuit is also much faster than its conventional counterpart. The logic gate was implemented in the 180nm CMOS technology and verified using Hspice simulations. There are many possible applications for this gate, mostly in artificial intelligence and pattern recognition algorithms implemented at the transistor level. © 2023 IEEE.

关键词： Logic gates

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Systematic Literature Review Langchain Proposed 25

Systematic Literature Review Langchain Proposed

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25th International Electronics Symposium, IES 2023

作者： Asyrofi, Rakha Dewi, Mutia Rahmi Lutfhi, Muhammad Irfan Wibowo, Prasetyo Faculty of Marine Science and Engineering Universitas Hangtuah Surabaya Indonesia Department of Computer Science and Information Engineering National Central University Taiwan Department of Information Technology Politeknik Negeri Padang Padang Indonesia Faculty of Engineering Universitas Negeri Yogyakarta Indonesia Graduate Institute of Network Learning Technology National Central University Taiwan Department of Informatics and Computer Engineering Politeknik Elektronika Negeri Surabaya Surabaya Indonesia

ISBN: (纸本)9798350314731

While systematic literature reviews are frequently carried out within software engineering research, performing them in a rigorous and reproducible manner can be difficult. This paper proposes some new methods for evaluating and validating systematic literature reviews. Our approach consists of several steps, such as: Selecting a set of relevant scientific papers to analyze, Developing a list of questions and criteria to evaluate each literature review, and Determining what types of functionality and performance should be evaluated. We tested our method by having multiple experts evaluate the literature reviews based on our questions and criteria. We measured the similarity in scores between each expert to determine the reliability of the evaluations. The average similarity index between experts was 0.58 to 0.83, indicating a reasonable level of agreement in their assessments. This shows our evaluation method can produce fairly consistent results, even when different experts are involved. The relatively high level of agreement is notable considering each expert brings their perspectives and opinions in analyzing literature reviews. By providing concrete questions, criteria, and evaluation methods, we aimed to guide the experts toward more uniform evaluations. In summary, we developed and tested a new approach for evaluating and validating systematic literature reviews in software engineering. By assessing reliability via interrater agreement, we showed that consistent and reproducible results are possible using our evaluation framework and methodology. Our methods could help researchers gain more insight into what makes for an effective and high-quality literature review. © 2023 IEEE.

关键词： Software testing

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New Modified Controlled Bat Algorithm for Numerical Optimization Problem

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Computers, Materials & Continua 2022年第2期70卷 2241-2259页

作者： Waqas Haider Bangyal Abdul Hameed Jamil Ahmad Kashif Nisar Muhammad Reazul Haque Ag.Asri Ag.Ibrahim Joel J.P.C.Rodrigues M.Adil Khan Danda B.Rawat Richard Etengu Department of Computing and Technology Iqra University IslamabadPakistan Computer Science Kohat University of Science and Technology(KUST)KohatPakistan Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu88400SabahMalaysia Faculty of Computing&Informatics Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Federal University of Piauí(UFPI) Teresina-PLBrazil Instituto de Telecomunicacoes Covilh?6201-001Portugal Department Computer Science and Technology Chang’an UniversityXi’anChina Department of Electrical Engineering and Computer Science Howard UniversityWashingtonDCUSA

Bat algorithm(BA)is an eminent meta-heuristic algorithm that has been widely used to solve diverse kinds of optimization *** leverages the echolocation feature of bats produced by imitating the bats’searching *** faces premature convergence due to its local search *** of using the standard uniform walk,the Torus walk is viewed as a promising alternative to improve the local search *** this work,we proposed an improved variation of BA by applying torus walk to improve diversity and *** *** Computerized Bat Algorithm(MCBA)approach has been examined for fifteen well-known benchmark test *** finding of our technique shows promising performance as compared to the standard PSO and standard *** proposed MCBA,BPA,Standard PSO,and Standard BA have been examined for well-known benchmark test problems and training of the artificial neural network(ANN).We have performed experiments using eight benchmark datasets applied from the worldwide famous machine-learning(ML)repository of *** results have shown that the training of an ANN with MCBA-NN algorithm tops the list considering exactness,with more superiority compared to the traditional *** MCBA-NN algorithm may be used effectively for data classification and statistical problems in the future.

关键词： Bat algorithm MCBA ANN ML Torus walk

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Conceptual Model of Graph-based Individual Tree and Its Utilization in Digital Twin and Metaverse of Urban Forest

Conceptual Model of Graph-based Individual Tree and Its Util...

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2024 Symposium on Spatial Information to Empower the Metaverse

作者： Ambarwari, Agus Suwardhi, Deni Rani, Medria Shekar Husni, Emir Junaidy, Deny Willy Agirachman, Fauzan Alfi Murtiyoso, Arnadi Griess, Verena Christiane Doctoral Program of Electrical Engineering and Informatics School of Electrical Engineering and Informatics Institut Teknologi Bandung Jl. Ganesha No.10 Bandung40132 Indonesia Faculty of Earth Sciences and Technology Institut Teknologi Bandung Indonesia School of Architecture Planning and Policy Development Institut Teknologi Bandung Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Indonesia Faculty of Art and Design Institut Teknologi Bandung Indonesia Department of Environmental Systems Science Forest Resources Management Institute of Terrestrial Ecosystems Zurich8092 Switzerland

3D city models are an important cornerstone in the development of digital twin cities, allowing for various analyses and simulations. CityGML, as an open standard for 3D city models, emphasizes five main aspects: scale or level of detail (LoD), semantics, geometry, topology, and appearance. One of the important elements in CityGML 3D city models is representation of vegetation. Vegetation in CityGML, especially individual trees, is still limited in terms of detail and resolution, reducing its effectiveness for specific applications. This paper proposes a graph-based conceptual model for individual trees that conforms to the CityGML v2.0 specification. The model refers to the morphological structure of a tree consisting of roots, trunk, and crown (including branches, twigs, and leaves), and considers the five main aspects of CityGML. By enhancing semantic information and geometric details, the model aims to provide an information-rich and realistic representation of individual trees in a 3D city environment. The 3D tree model created based on this conceptual model may be applicable in the development of digital twin urban forests and virtual forest simulations that utilize immersive technologies such as the metaverse. This research opens up new opportunities in the development of solitary vegetation objects through CityGML ADE by including more detailed semantic and topological information. © Author(s) 2024.

关键词： Digital elevation model

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Sentiment Analysis of Israeli-Palestinian Conflict on Indonesian Tweets Using Machine Learning

Sentiment Analysis of Israeli-Palestinian Conflict on Indone...

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International Conference on Electrical engineering and Computer science (ICECOS)

作者： Majid Rahardi Muhammad Rezzha Riamrizal Arsya Afrig Aminuddin Ferian Fauzi Abdulloh Mohammad Badrul Alam Miah Heri Pratikno Faculty of Computer Science Universitas Amikom Yogyakarta Sleman Indonesia Faculty of Engineering Mawlana Bhashani Science and Technology University Tangail Bangladesh Faculty of Technology and Informatics Universitas Dinamika Surabaya Indonesia

ISBN: (数字)9798350368253

ISBN: (纸本)9798350368260

The social media of X has become a focal point for discussions on sensitive issues, including the Israeli-Palestinian conflict. This research analyzes sentiment toward tweets expressing support for Palestine on X, comparing the Support Vector Machine (SVM) and Naïve Bayes methods. Given the global attention to the conflict, sentiment analysis on this topic is crucial. The results reveal that the SVM model outperforms Naïve Bayes, achieving accuracy, precision, recall, and F1-score of 85%, 87%, 85%, and 85% for Naïve Bayes, and 91%, 92%, 90%, and 90% for SVM, respectively. It demonstrates the SVM model's capability to distinguish between positive and negative sentiments. Comparison with previous research indicates that this study surpasses the sentiment analysis results of previous SVM models, while Naïve Bayes excels in specific research. With superior performance, this research provides a new contribution to recognizing and classifying sentiments on a particular dataset related to the Israeli-Palestinian conflict on X social media.

关键词： Support vector machines Electrical engineering Sentiment analysis Analytical models Accuracy Social networking (online) Machine learning Vectors Bayes methods Reliability

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Analysis of YouTube Video Comments with NLP Methods

Analysis of YouTube Video Comments with NLP Methods

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International Conference on Electronics, Computers and Artificial Intelligence (ECAI)

作者： Pirnau Mironela Priescu Iustin Priescu Catalina Mihaela Pirnau Claudiu Ghiculescu Liviu Daniel Department of Informatics Faculty of Informatics “Titu Maiorescu” University Bucharest Romania Faculty of Automatic Control and Computer Science National University of Science and Technology POLITEHNICA Bucharest Bucharest Romania Manufacturing Engineering Department Faculty of Industrial Engineering and Robotics National University of Science and Technology POLITEHNICA Bucharest Bucharest Romania

ISBN: (数字)9798350371154

ISBN: (纸本)9798350371161

This study proposes methods that can be used to examine and interpret comments that users have made after watching videos on YouTube on a particular topic. YouTube tutorials are very popular among young people. They have become an important pillar in informal education, thus contributing to the rapid acquisition of skills and knowledge. Under these circumstances, we were interested in analysing the YouTube videos comments, knowing that the platform has a continuous increase in popularity, which is also due to the opportunities of sharing them. Since ChatGPT-themed YouTube videos have seen a significant surge in popularity since 2022, we were interested to analyse some videos that approach the topics of “ChatGPT, AI clone, AI robot and Deep Learning.”

关键词： Video on demand Social networking (online) Education Tutorials Chatbots Web sites Artificial intelligence

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