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Modeling uncertainties associated with decision-making algorithms based on similarity measures of possibility belief interval-valued fuzzy hypersoft setting

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Neutrosophic Sets and Systems 2025年 77卷 282-309页

作者： Romdhini, Mamika Ujianita Al-Sharqi, Faisal Al-Obaidi, R.H. Rodzi, Zahari Md. Department of Mathematics Faculty of Mathematics and Natural Science University of Mataram Mataram83125 Indonesia Department of Mathematics Faculty of Education for Pure Sciences University of Anbar Ramadi55431 Iraq Fuel and Energy Techniques Engineering Department College of Engineering and Technologies Al-mustaqbal University Babylon51001 Iraq College of Computing Informatics and Mathematics UiTM Cawangan Negeri Sembilan Kampus Seremban Negeri Sembilan 72000 Malaysia

Hypersoft sets (HSSs) were initiated as an extension of soft sets (SSs) to address real-life scenarios involving multiple disjoint sets with different traits. One such extension is the interval-valued fuzzy hypersoft set (IVFHSS), which has proven effective in decision-making (DM). However, the IVFHSS model lacks a mechanism to incorporate the degree of acceptance of DM opinions, which is crucial for accurate decision-making. To overcome this limitation, our work aims to develop a novel hyperstructure called a possibility interval-valued fuzzy hypersoft set (PIVFHS-set). We begin by introducing essential operations and their properties, such as PIVFHS-subset, PIVFHS-null set, PIVFHS-absolute set, and complement of a PIVFHS-set. These concepts are illustrated through numerical examples to demonstrate their practical applications. Next, we delve into set-theoretic operations of PIVFHS sets, including union, intersection, AND, OR, and relevant laws. These operations are further elucidated through numerical examples, matrix representations, and graphical illustrations. Additionally, we present two algorithms based on AND and OR operations, providing step-by-step explanations and showcasing their effectiveness through illustrative examples. Furthermore, we introduce a similarity measure to facilitate pattern recognition in PIVFHS-sets, aiding users in recruitment processes. Alongside an analytical study of the advantages and disadvantages of this model, we provide suggestions for future research based on the identified limitations. © 2025, University of New Mexico. All rights reserved.

关键词： Fuzzy sets

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Artificial intelligence−powered electrochemical sensor: Recent advances, challenges, and prospects

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Heliyon 2024年第18期10卷 e37964页

作者： Nashruddin, Siti Nur Ashakirin Binti Mohd Salleh, Faridah Hani Mohamed Yunus, Rozan Mohamad Zaman, Halimah Badioze Institute of Informatics and Computing in Energy (IICE) Department of Computing College of Computing & Informatics Universiti Tenaga Nasional Selangor Darul Ehsan Kajang 43000 Malaysia Fuel Cell Institute Universiti Kebangsaan Malaysia Selangor Bangi 43600 Malaysia

Integrating artificial intelligence (AI) with electrochemical biosensors is revolutionizing medical treatments by enhancing patient data collection and enabling the development of advanced wearable sensors for health, fitness, and environmental monitoring. Electrochemical biosensors, which detect biomarkers through electrochemical processes, are significantly more effective. The integration of artificial intelligence is adept at identifying, categorizing, characterizing, and projecting intricate data patterns. As the Internet of Things (IoT), big data, and big health technologies move from theory to practice, AI-powered biosensors offer significant opportunities for real-time disease detection and personalized healthcare. Still, they also pose challenges such as data privacy, sensor stability, and algorithmic bias. This paper highlights the critical advances in material innovation, biorecognition elements, signal transduction, data processing, and intelligent decision systems necessary for developing next-generation wearable and implantable devices. Despite existing limitations, the integration of AI into biosensor systems shows immense promise for creating future medical devices that can provide early detection and improved patient outcomes, marking a transformative step forward in healthcare technology. © 2024

关键词： Artificial neural networks Electrochemical energy saving Genetic algorithm Machine learning

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Real-Time Substation Detection and Monitoring Security Alarm System 11

Real-Time Substation Detection and Monitoring Security Alarm...

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11th IEEE Conference on Systems, Process and Control, ICSPC 2023

作者： Yiong, Yong Tzia Khairudin, Ahmad Rafiq Mohd Redzuwan, Redia Mohd College of Engineering Universiti Tenaga Nasional Sarawak Energy Berhad Department of Electrical Electronics Engineering Selangor Malaysia Institute of Informatics and Computing in Energy College of Engineering Universiti Tenaga Nasional Selangor Malaysia College of Engineering Universiti Tenaga Nasional Department of Electrical Electronics Engineering Selangor Malaysia

ISBN: (纸本)9798350340860

In real-world scenarios, conventional security alarms are commonly used to monitor and record occurrences. However, these alarms are often impractical as they lack the ability to warn security administrators in real-time when security threats are present. To address this issue, this project proposes an automated continuous security surveillance system utilizing Raspberry Pi 3B and Raspberry Pi Camera, along with deep learning tools namely Open-Source Computer Vision Library (OpenCV), You Only Look Once tiny version 4 (YOLOv4-tiny), Google Drive, Colab Notebook, and DarkNet framework. The proposed system aims to detect specific classes, such as people, cars, or fires, within a designated range and promptly send out alert notifications and sound an alarm in real-time. To achieve this, the YOLOv4-tiny machine learning model is used for object detection, and OpenCV is employed for image pre-processing tasks like scaling and normalization [21]. To overcome the computational limitations of the Raspberry Pi 3B, the YOLOv4-tiny model is trained on a custom dataset using the DarkNet framework, and Colab Notebook is utilized for training and optimizing the model, which is then saved on Google Drive for easy access. Various techniques like model quantization and network pruning are employed to improve the system's performance and efficiency. The experimental results demonstrate that the proposed system achieves high accuracy in detecting specific classes while remaining computationally efficient. Overall, this project offers a reliable and efficient solution by integrating the concepts of object recognition and detection, showcasing its potential for various practical applications. © 2023 IEEE.

关键词： Object recognition

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Influence of Rotational Speed on the Frequency Response Analysis of the Field Winding of Large Hydrogenerators 14

Influence of Rotational Speed on the Frequency Response Anal...

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14th IEEE International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, SDEMPED 2023

作者： Albizuri-Txurruka, Unai Guerrero, Jose M. Mahtani, Kumar Platero, Carlos A. Ge Renewable Energy Engineering Department Bilbao Spain Mondragon University Electronic and Computing Department Mondragon Arrasate Spain Universidad Politécnica de Madrid Automation Electrical and Electronic Engineering and Industrial Informatics Department Madrid Spain

ISBN: (纸本)9798350320770

Frequency Response Analysis (FRA) is a well-known technique used for power transformer condition monitoring for more than 40 years. Some research lines use this technique in other machines such as synchronous machines. This paper presents onsite tests on the field winding of a 125 MVA synchronous machine installed in a pumped storage power plant. The tests have been accomplished in standstill and rated speed conditions. The main contribution of this article is to demonstrate that the speed of the rotor has a significant influence on the field winding FRA test results. A comparison between standstill condition and rated speed FRA tests is presented. The frequency range where the differences take place indicates that centrifugal forces at rated speed change the capacitance of the field windings. © 2023 IEEE.

关键词： Winding

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Modeling the dynamical behavior of the interaction of T-cells and human immunodeficiency virus with saturated incidence

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Communications in Theoretical Physics 2024年第3期76卷 1-14页

作者： Salah Boulaaras Rashid Jan Amin Khan Ali Allahem Imtiaz Ahmad Salma Bahramand Department of Mathematics College of ScienceQassim UniversityBuraydah51452Saudi Arabia Institute of Energy Infrastructure(IEI) Department of Civil EngineeringCollege of EngineeringUniversiti Tenaga Nasional(UNITEN)Putrajaya CampusJalan IKRAM-UNITEN43000 KajangSelangorMalaysia Department of Mathematics University of SwabiSwabi 23561Pakistan Department of Mathematics College of SciencesQassim UniversitySaudi Arabia Institute of Informatics and Computing in Energy(IICE) Universiti Tenaga NasionalKajangSelangorMalaysia Department of Political Science Bacha Khan University CharsaddaCharsadda 24420KPK Pakistan

In the last forty years,the rise of HIV has undoubtedly become a major concern in the field of public health,imposing significant economic burdens on affected ***,it becomes imperative to undertake comprehensive investigations into the mechanisms governing the dissemination of HIV within the human *** this work,we have devised a mathematical model that elucidates the intricate interplay between CD4^(+)T-cells and viruses of HIV,employing the principles of fractional *** production rate of CD4^(+)T-cells,like other immune cells depends on certain factors such as age,health status,and the presence of infections or ***,we incorporate a variable source term in the dynamics of HIV infection with a saturated incidence rate to enhance the precision of our *** introduce the fundamental concepts of fractional operators as a means of scrutinizing the proposed HIV *** facilitate a deeper understanding of our system,we present an iterative scheme that elucidates the trajectories of the solution pathways of the *** show the time series analysis of our model through numerical findings to conceptualize and understand the key factors of the *** addition to this,we present the phase portrait and the oscillatory behavior of the system with the variation of different input *** information can be utilized to predict the long-term behavior of the system,including whether it will converge to a steady state or exhibit periodic or chaotic oscillations.

关键词： HIV infection fractional-calculus dynamics of HIV iterative scheme dynamical behaviour mathematical model fractional derivatives

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Willingness of Electricity Consumer in Malaysia to Share Electric energy Consumption Data

Willingness of Electricity Consumer in Malaysia to Share Ele...

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7th International Conference on Advances in Visual informatics, IVIC 2021

作者： Yussof, Salman Mohd Zulkefle, Nurul Nazeera Yusoff, Yunus Abu Bakar, Asmidar Institute of Informatics and Computing in Energy Universiti Tenaga Nasional Kajang Malaysia Tenaga Nasional Berhad Kuala Lumpur Malaysia College of Computing and Informatics Universiti Tenaga Nasional Kajang Malaysia

ISBN: (纸本)9783030902346

Data sharing is a process of interchanging data among multiple data sources in a controllable access manner. Successful data sharing of information belong to public depends on public support. Analyzing household electric consumption data and user behaviour profile based on household electricity demand are also vital to enhance energy efficiency in Malaysia. This research used quantitative methodology via survey method. A set of questionnaires was developed to identify the willingness of electricity consumer in Malaysia on sharing their electric energy consumption data and types of incentives preferred. A total of 424 responses were successfully gathered and was analyzed using SPSS software. This survey proves that electricity consumer in Malaysia are willing to share their energy consumption data regardless of demographic profiles, with or without awareness of PDPA and technology that may capture their data. These findings indicate that data sharing related to energy consumption can potentially be successful since statistic shows that the public are willing to share their energy consumption data. The result of this study may help researcher who are planning to develop data sharing platform to increase public willingness to share their energy data. The availability of data sharing platform can assist research community during data gathering process which later can be analyzed to identify areas of improvement to be undertaken by the industry. © 2021, Springer Nature Switzerland AG.

关键词： energy efficiency

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Enhanced resolution in solving first-order nonlinear differential equations with integral condition: a high-order wavelet approach

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The European Physical Journal Special Topics 2024年 1-14页

作者： Khan, Amir Ali Ahsan, Muhammad Ahmad, Imtiaz Alwuthaynani, Maher Department of Mathematics University of Swabi Khyber Pakhtunkhwa Pakistan Institute of Informatics and Computing in Energy (IICE) Universiti Tenaga Nasional Kajang Malaysia Department of Mathematics Taif University Taif Saudi Arabia

In this article, the Haar wavelet collocation method (HWCM) is proposed for the numerical solution of a first-order nonlinear differential equation with a two-point integral condition. A nonlinear ordinary differential equation with an initial condition, an integral condition, or a two-point integral condition can be solved using the proposed technique in a straightforward manner. Two nonlinear test problems have been solved: one with an integral condition and the other with a two-point integral condition. The accuracy of the proposed method is significantly higher than that of the traditional Haar wavelet technique.

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VR-Based Relaxation Therapy for Customer Service Staff: A Pilot Study

VR-Based Relaxation Therapy for Customer Service Staff: A Pi...

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7th International Conference on Advances in Visual informatics, IVIC 2021

作者： Ibrahim, Nazrita Mohd Mahidin, Eze Manzura Mohd Yusof, Azmi Rusli, Mohd Ezanee Iskandar, Nur Suria Zaharuddin, Farhah Amaliya Mahalil, Imran Institute of Informatics and Computing in Energy Universiti Tenaga Nasional Kajang Malaysia College of Computing and Informatics Universiti Tenaga Nasional Kajang Malaysia UNITEN R&D Sdn Bhd Kajang Malaysia

ISBN: (纸本)9783030902346

Customer service staff are the frontliners of any organisation. They act as the first stop centre for customer or client to report complaints or feedback. However, this job also comes with a stressful working condition. For this reason, XperionVR™, a Virtual Reality-based relaxation therapy system was developed with the intention of providing easy access for employees to manage their stress by practising relaxation techniques. This paper describes the evaluation of XperionVR™ conducted among the staff of a customer service unit of a large utility company. This pilot study aims to gather participants’ perception of the effectiveness of each element in the therapy component of the VR-based relaxation therapy system in helping them to relax or reduce their stress level. The procedure involves participants going through the therapy session, and feedback on the experience was gathered using questionnaire, direct observation, and interview. Forty participants had voluntarily participated in the pilot study. Based on the result of the analysis, it could be observed that most participants felt that the system managed to make them feel more relaxed and reduce their stress level. However, two challenges observed were i) due to the nature of customer service staff who only have short break time, it is important for any VR-based relaxation therapy system to be designed with the ability to provide optimal therapy outcome within a short period of time and ii) the system should consist of a feature that can provide a quick demonstration for users with no experience of using a virtual reality system on how to navigate the system. Without the demonstration, users will have difficulty using the system, which in turn, will cause adverse effect to the overall therapy experience. © 2021, Springer Nature Switzerland AG.

关键词： Virtual reality

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Simulation and Modelling of Water Injection for Reservoir Pressure Maintenance

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Computers, Materials & Continua 2022年第9期72卷 5761-5776页

作者： Rishi Dewan Adarsh Kumar Mohammad Khalid Imam Rahmani Surbhi Bhatia Md Ezaz Ahmed Department of Physics University of Petroleum&Energy StudiesDehradun 248007UttarakhandIndia Department of Computer Science University of Petroleum&Energy StudiesDehradun 248007UttarakhandIndia College of Computing and Informatics Saudi Electronic UniversityRiyadh 11673Saudi Arabia Department of Information Systems College of Computer Science and Information TechnologyKing Faisal UniversityAl Hasa 36362Saudi Arabia

Water injection has shown to be one of the most successful,efficient,and cost-effective reservoir management *** re-injecting treated and filtered water into reservoirs,this approach can help maintain reservoir pressure,increase hydrocarbon output,and reduce the environmental *** goal of this project is to create a water injection model utilizing Eclipse reservoir simulation software to better understand water injection methods for reservoir pressure maintenance.A basic reservoir model is utilized in this *** simulation designs,the reservoir length,breadth,and thickness may be changed to different *** water-oil contact was discovered at 7000 feet,and the reservoir pressure was recorded at 3000 pounds per square inch at a depth of 6900 *** aquifer chosen was of the Fetkovich type and was linked to the reservoir in the j+*** porosity was estimated to be varied,ranging from 9%to 16%.The residual oil saturation was set to 25%and the irreducible water saturation was set at 20%.The vertical permeability was set at 50 md as a *** Volume Temperature(PVT)data was used to estimate the gas and water characteristics.

关键词： Eclipse water injection reservoir modeling simulation oil saturation

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Electricity Anomaly Point Detection using Unsupervised Technique Based on Electricity Load Prediction Derived from Long Short-Term Memory 2

Electricity Anomaly Point Detection using Unsupervised Techn...

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2nd International Conference on Artificial Intelligence and Data Sciences, AiDAS 2021

作者： Salleh, Nur Shakirah Md Saripuddin, Mulyana Suliman, Azizah Jorgensen, Bo Norregaard College of Computing and Informatics Universiti Tenaga Nasional Kajang Malaysia Center for Energy Informatics Mærsk Mc-Kinney Moller Institutte Odense Denmark

ISBN: (纸本)9781665417266

Electricity theft caused a major loss for electricity power provider. The anomaly detection helps to predict the abnormal load usage of a consumer. Usually, the classification method used in anomaly detection. This research paper proposed to identify the potential anomaly points by using threshold and outliers. The prediction in time-series applied Long Short-Term Memory (LSTM) algorithm. The historical electricity load dataset of a single industrial consumer was used to generate the prediction of electricity load. There were five optimizers used to produce the model: Adam, Adadelta, Adagrad, RMSProp, and Stochastic gradient descent (SGD). The prediction model was evaluated using mean squared error (MSE) and mean absolute error (MAE). The best model among all five models was generated by Adadelta optimizer with the error rate value of 0.091982 for MSE and 0.018433 for MAE. The prediction values were generated by this model. The anomaly point was detected by using threshold and outliers. The threshold value was 0.218983. One week in August 2019 was chosen to detect any anomaly load occurrences. There were 24 outliers were found within the selected week. The study shall expand on the electricity usage trend during COVID-19 pandemic period. © 2021 IEEE.

关键词： Long short-term memory

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