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67th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2023

作者： Giang, Wayne C. W. Iglar, Alyssa Chignell, Mark Samavi, Reza Nathan, Kopiha Department of Industrial and Systems Engineering University of Florida GainesvilleFL United States Department of Mechanical and Industrial Engineering University of Toronto TorontoON Canada Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University TorontoON Canada Vector Institute India Healthcare Insurance Reciprocal of Canada TorontoON Canada

Attitudes and concerns related to privacy are not homogeneous, but instead differ based on the individual and context at hand. Understanding how these attitudes and concerns vary could inform product, service, and policy design. Questionnaires, such as the Privacy Attitudes Questionnaire (PAQ), can be used to evaluate and derive implications from people’s privacy orientations in numerous domains, including healthcare, social media, and e-commerce. Our objective is to refine the PAQ to reflect areas of privacy concern in today’s landscape. The panel will serve as a forum for conversation about areas of privacy concern, guided by our panelists’ expertise and questions about demographic and user considerations for the revised PAQ, a framework-inspired understanding of privacy, and privacy in healthcare. Insights and perspectives arising from the discussion panel will be considered for subsequent revisions of the PAQ. © 2023 Human Factors and Ergonomics Society.

关键词： attitudes concerns context healthcare privacy questionnaire

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Portable Waste Bank for Plastic Bottles with Electronic-Money Payment 1

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International Conference on Innovative Technologies in Intelligent systems and industrial Applications, CITISIA 2022

作者： Herawan, Safarudin Gazali Suryaningrum, Kristien Margi Kristin, Desi Maya Gavrila, Ardito Yunus, Afa Ahmad Tanawi, Welldelin Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia IInformation Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

Plastic is the second largest amount of waste in Indonesia, reaching 17.3% of the total waste of 28.6 million tons for 2021. The type of plastic that is most often recycled is plastic bottle packaging. Plastic waste that is not managed properly can affect the health and safety of the ecosystem. The waste bank program is one of the government’s efforts to reduce the amount of waste heaps. The portable waste bank for plastic bottles has a function of automatically exchanging plastic bottle waste with points that can be exchanged into electronic-money. Therefore, This research are aims to design a mobile friendly website-based application to integrate in the use of portable waste banks by using the QR code scan feature to exchange points into electronic-money. The results of the design are found that the portable waste bank with the simulated application has functioned well and can be applied in the real condition. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Websites

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A Review of Algorithms's Complexities on Different Valued Sorted and Unsorted Data

A Review of Algorithms's Complexities on Different Valued So...

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2023 International Conference on IT and industrial Technologies, ICIT 2023

作者： Shabbir, Attia Majeed, Asad Iftikhar, Mahnoor Ali, Raja Hashim Arshad, Usama Shabbir, Muhammad Zeeshan Zeeshan Ijaz, Ali Ali, Nisar Aftab, Ali Gik Institute of Engg. Sciences & Technology Faculty of Computer Science & Engineering Topi Pakistan University of Europe for Applied Sciences Dept. of Technology & Software Engineering Berlin Germany Department of Electrical Engineering Lahore Pakistan University of Regina Faculty of Electronic Systems Engineering Regina Canada

ISBN: (纸本)9798350315974

Sorting and searching are critical processes for effecttive data analysis. In this paper, we evaluate the performance of various sorting and searching algorithms and compare their time and space complexities on both sorted and unsorted data. The algorithms we analyzed include six common sorting algorithms (insertion, radix, bucket, merge, bubble, and quick sort) and three search algorithms (linear, binary, and jump search). The results of our study provide insights into the best algorithms to use for different input sizes and types of data. It was found that for small input sizes, all algorithms perform similarly, but for larger input sizes, insertion and radix sorts are better for time complexity while bubble sort is better for space complexity. Additionally, jump search outperformed linear and binary search algorithms in both time and space complexity. Besides, difference between time and space complexity of sorted and unsorted data was significant. © 2023 IEEE.

关键词： Computational complexity

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Adisutjipto Institute of Aerospace Technology Virtual Tour with Artificial Intelligence (AI) Agent 1

Adisutjipto Institute of Aerospace Technology Virtual Tour w...

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1st International Conference of Adisutjipto on Aerospace electrical engineering and Informatics, ICAAEEI 2024

作者： Ayuningtyas, Astika Wahyudi Sumari, Arwin Datumaya Aryanto, Salam Nuryatno, Edi Triono Mulyani, Sri Kusumaningrum, Anggraini Adisutjipto Institute of Aerospace Technology Aerospace Intelligent Systems and Data Engineering Research Group Faculty of Industrial Technology Yogyakarta Indonesia Department of Electrical Engineering Malang Indonesia Adisutjipto Institute of Aerospace Technology Aerospace Modeling and Simulation Research Group Faculty of Industrial Technology Yogyakarta Indonesia The University of Western Australia Uwa Centre for Medical Research Perth Australia Adisutjipto Institute of Aerospace Technology Faculty of Aerospace Engineering Technology Yogyakarta Indonesia

ISBN: (纸本)9798331507930

This study aims to develop an interactive virtual tour based on Android with a first-person shooter approach to introduce the Adisutjipto Institute of Aerospace Technology (ITD Adisutjipto) virtually. This virtual tour utilizes an Artificial Intelligence (AI) agent as an intelligent guide who can answer questions and provide relevant information related to facilities and locations inside the ITD Adisutjipto building. The test results show that this virtual tour is effective and feasible to use, with a user satisfaction rate reaching 87.72%. This study contributes to the field of educational virtual technology by offering a more immersive and interactive experience. Users can easily explore the ITD Adisutjipto building virtually and obtain the information they need efficiently. This research is expected to be an innovative solution to introduce the ITD Adisutjipto to wider community, as well as support learning and research activities in the aerospace technology field. © 2024 IEEE.

关键词： Virtual environments

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Control System of Electric Drives of the Manipulator Using Neural Network Predictive Controller

Control System of Electric Drives of the Manipulator Using N...

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2024 Conference of Young Researchers in electrical and Electronic engineering, ElCon 2024

作者： Kozlova, Liudmila P. Kozlova, Olga A. Saint Petersburg Electrotechnical University 'LETI' Faculty of Industrial Automation and Electrical Engineering St. Petersburg Russia The Bonch-Bruevich St. Petersburg State University of Communication Faculty of Information Systems and Technologies St. Petersburg Russia

ISBN: (纸本)9798350360646

The article considers the control system of electric drive of the manipulator installed on the conveyor line. The control system uses Neural Network Predictive Controller as a nonlinear controllable object to work out the manipulator movement to various control signals. Using an optimisation algorithm, control signals are calculated to minimise the difference between the desired and actual signal changes at the model output and hence optimise the controlled process. © 2024 IEEE.

关键词： control system controller manipulator Neural network nonlinear system

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Application of Neural Network Control of Pump Unit 27

Application of Neural Network Control of Pump Unit

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27th International Conference on Soft Computing and Measurements, SCM 2024

ISBN: (纸本)9798350363708

The paper considers a neural network control system for a pump unit, which serves to maintain pressure in the boiler. For energy-efficient operation of the pump it is necessary to provide optimal control of the electric motor acceleration, excluding hydraulic impacts in pipeline. Using of neural network control will increase the reliability of the pump unit and energy savings. © 2024 IEEE.

关键词： Energy efficiency

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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

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International Journal of Cognitive Computing in engineering 2025年第1期6卷 74-99页

作者： Saat, Shahrizal Ahmad, Mohd Ashraf Ghazali, Mohd Riduwan Faculty of Electronics and Computer Technology and Engineering Universiti Teknikal Malaysia Melaka Durian Tunggal Melaka 76100 Malaysia Faculty of Electrical and Electronics Engineering Technology Universiti Malaysia Pahang Al-Sultan Abdullah Pahang Pekan26600 Malaysia Center for Telecommunication Research & Innovation Universiti Teknikal Malaysia Melaka Durian Tunggal Melaka 76100 Malaysia Center for Advanced Industrial Technology Universiti Malaysia Pahang Al-Sultan Abdullah Pahang Pekan26600 Malaysia

The increasing complexity of modern plant systems and the limitations of precise mathematical modeling have led to a shift towards data-driven control methods. These methods present an effective alternative that treats plants as black-box systems without requiring explicit models. The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. Nonetheless, control performance can be limited by the fixed probability coefficient used in the original SEDA to disrupt design parameters, especially when balancing exploration and exploitation phases. This study proposes an enhanced version of the SEDA: the modified SEDA (MSEDA), to address this issue. The MSEDA introduces a dynamic probability coefficient that decreases with each iteration. The adjustment improves the balance between exploration and exploitation phases, which enhances control accuracy. The MSEDA was used to tune the brain emotional learning-based intelligent controller (BELBIC) together with a proportional-integral-derivative (PID) controller. The result was the BELBIC-PID controller inspired by the limbic system of the human brain, which has high precision. The effectiveness of the proposed MSEDA-BELBIC-PID was validated using simulations on multi-input multi-output (MIMO) systems, with a focus on tracking performance and computational efficiency. The statistical analysis of 30 independent trials demonstrated that the proposed MSEDA-BELBIC-PID was significantly improved over the original SEDA-BELBIC-PID. Wilcoxon's rank test yielded a fitness function p-value © 2024 The Authors

关键词： Three term control systems

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Automated Deep Learning Driven Crop Classification on Hyperspectral Remote Sensing Images

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computers, Materials & Continua 2023年第2期74卷 3167-3181页

作者： Mesfer Al Duhayyim Hadeel Alsolai Siwar Ben Haj Hassine Jaber SAlzahrani Ahmed SSalama Abdelwahed Motwakel Ishfaq Yaseen Abu Sarwar Zamani Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Electrical Engineering Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Hyperspectral remote sensing/imaging spectroscopy is a novel approach to reaching a spectrum from all the places of a huge array of spatial places so that several spectral wavelengths are utilized for making coherent *** remote sensing contains acquisition of digital images from several narrow,contiguous spectral bands throughout the visible,Thermal Infrared(TIR),Near Infrared(NIR),and Mid-Infrared(MIR)regions of the electromagnetic *** order to the application of agricultural regions,remote sensing approaches are studied and executed to their benefit of continuous and ***,hyperspectral images(HSI)are considered the precise for agriculture as they can offer chemical and physical data on *** this motivation,this article presents a novel Hurricane Optimization Algorithm with Deep Transfer Learning Driven Crop Classification(HOADTL-CC)model onHyperspectralRemote Sensing *** presentedHOADTL-CC model focuses on the identification and categorization of crops on hyperspectral remote sensing *** accomplish this,the presentedHOADTL-CC model involves the design ofHOAwith capsule network(CapsNet)model for generating a set of useful feature ***,Elman neural network(ENN)model is applied to allot proper class labels into the input ***,glowworm swarm optimization(GSO)algorithm is exploited to fine tune the ENNparameters involved in this *** experimental result scrutiny of the HOADTL-CC method can be tested with the help of benchmark dataset and the results are assessed under distinct *** comparative studies stated the enhanced performance of the HOADTL-CC model over recent approaches with maximum accuracy of 99.51%.

关键词： Hyperspectral images remote sensing deep learning hurricane optimization algorithm crop classification parameter tuning

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systems of Intelligent Information Processing Using Fuzzy Logic 27

Systems of Intelligent Information Processing Using Fuzzy Lo...

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27th International Conference on Soft Computing and Measurements, SCM 2024

ISBN: (纸本)9798350363708

One of the main units of work of any system is information. That is why methods of its processing are important for the full functioning of the entire process. The article discusses the scope of intelligent information processing algorithms, the complexity and features of such systems, and proposes a fuzzy logic method for achieving high results. © 2024 IEEE.

关键词： Fuzzy logic

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A variable structure model of neurons’ application in computer vision

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Multimedia Tools and Applications 2025年 1-11页

作者： Sridi, Alaeddine Attia, Mouna Bouallegue, Kais Electronics and Micro-Electronics Laboratory Faculty of Sciences of Monastir University of Monastir Monastir Tunisia The Higher Institute of Computer Science and Communication Technologies of Hammam Sousse University of Sousse Sousse Tunisia Laboratory of Computer Science Parallelism and Intelligent Communicating Systems Faculty of Sciences of Tunisia University of Tunis ELManar Tunis Tunisia Department of Electrical Engineering Higher Institute of Applied Sciences and Technology of Sousse University of Sousse Sousse Tunisia

The neuron doctrine defines the neuron as the basic unit of the nervous system, which drives the dynamic behavior of our organs. This has led to neurons becoming the focus of modern neuroscience research and to the rise of neurocomputing, in which we try to digitally simulate human behavior. The goal being to better understand the human nervous system and gain more control over neuron-related diseases, helping doctors establish faster and more reliable medical diagnoses. In this context, we aim to simulate eye diseases and vision problems by convolving input images using a new class of neural networks based on a variable structure model of neurons presented in [1]. In this work, we focus on recreating the common convolution filters as a first step. This is the first time in neurocomputing literature that dendritic neurons have been used for dynamic convolution kernels generation and eye diseases simulation. We start with a presentation of our upgrades to the model’s flexibility and accuracy. Then, we propose a novel kernel generator algorithm to convolve the input images. Finally, we show its promising results in creating the outline, pixelization, and night convolution kernels, as well as control some metrics, including brightness and data retention. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Neurons

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