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Electrical, computer, Communications and Mechatronics engineering (ICECCME), International Conference on

作者： Damian Kusnik Bogdan Smolka Milena Smolka Faculty of Automatics Electronics and Informatics Silesian University of Technology Gliwice Poland Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering AGH University of Science and Technology Krakow Poland

In this paper, a novel approach to the problem of mixed Gaussian and impulsive noise reduction in color images is proposed. The elaborated denoising framework is based on the Non-Local Means technique, which has been shown to effectively suppress Gaussian noise. To overcome the inability of this filter to deal with impulsive distortions, a robust similarity measure between image patches, that is insensitive to the impact of impulsive distortions, was developed. First, the distorted pixels of the image are detected using the concept of a peer group. If the number of neighbors of a pixel at the center of a filtering window, whose Euclidean distance in the RGB color space does not exceed a threshold value, is smaller than a predefined value, then the considered pixel is treated as corrupted. Afterwards, the similarity between image patches are calculated in a standard way omitting the noisy pixels. In this way, only the average of distances between pairs of unaffected pixels are calculated. Thus, the closeness measure of the patches, which serves as the coefficient in weighted averaging of pixels in the processing block, is not affected by impulsive noise and is still able to cope with the Gaussian noise component. The proposed filtering design is capable of reducing even strong mixed noise while preserving image details and edges. Moreover, it is not computationally intensive, so it can be used in real-time image processing scenarios.

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2D Polynomial Regression Modeling for Predictive Analysis of Glucose Concentration in NP-Model Fractal Microwave Sensor Using Frequency and Transmission Coefficient Disparities

2D Polynomial Regression Modeling for Predictive Analysis of...

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International Electrical engineering Congress (iEECON)

作者： Nutyada Nantapanich Pisit Mahatthanajatuphat Norakamon Wongsin Wilaiporn Lee Department of Electronics and Telecommunication Engineering Faculty of Engineering Rajamangala University of Technology Thanyaburi Pathum Thani Thailand Regular Program in Mathematics-Science Yothinburana School Bangkok Thailand Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut's University of Technology North Bangkok Bangkok Thailand

ISBN: (数字)9798331543952

ISBN: (纸本)9798331543969

The article introduces a two-dimensional polynomial regression model for the predictive analysis of glucose concentration in a fractal microwave sensor NP model, utilizing frequency and transmission coefficient differences to examine their correlation with glucose concentration levels. The sensor employed in this investigation is fabricated on an economical FR-4 substrate to minimize costs. The sensor structure is developed with the fractal structure reduction method established by the NP model to operate at a frequency of roughly 2.97 GHz. The CST Studio software is utilized to analyze the findings from the simulation of the suggested sensor structure. Furthermore, the proposed sensor is integrated into a test apparatus comprising a sensor platform and a liquid tube constructed from PPA material. The liquid under examination is a glucose and water mixture at varying concentrations. It was analyzed using a VNA instrument to evaluate its frequency response and the magnitude of the alteration in the transmission coefficient. The values are utilized to create a two-dimensional polynomial regression model. The experiments demonstrated that the proposed sensor model possesses an Adjusted R² value of 0.99499 and an average error of approximately 3.57% for glucose concentration analysis throughout the range of 5% to 30%, with sensitivities of 0.00879 dB/% for insertion loss and 0.092 MHz/% for frequency variation, facilitating accurate glucose concentration prediction analysis.

关键词： Analytical models Adaptation models Correlation Liquids Predictive models Microwave sensors Polynomials Fractals Glucose Predictive analytics

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Energy-Efficient Clustering Algorithm Analysis for Intelligent Marine Ecosystem Monitoring

Energy-Efficient Clustering Algorithm Analysis for Intellige...

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Renewable Energies and Smart Technologies (REST), International Conference on

作者： Qamil Kabashi Isak Shabani Almas Abbasi Aaqif Afzaal Abbasi Department of Electronics Faculty of Electrical and Computer Engineering University of Prishtina Prishtina Kosova Department of Computer Engineering Faculty of Electrical and Computer Engineering University of Prishtina Prishtina Kosova Department of Computer Science Faculty of Computing and Information Technology International Islamic University Islamabad Pakistan Department of Earth and Marine Sciences National Biodiversity Future Center University of Palermo Palermo Italy

ISBN: (数字)9798350358902

ISBN: (纸本)9798350358919

Marine ecosystems are complex and dynamic environments. Monitoring these ecosystems is essential for understanding and identifying potential threats and conservation needs. Different sensory devices such as wireless sensor networks (WSNs) are used to monitor these environments. WSN have been in industrial use for the last two decades. However, energy efficiency in WSNs remains a topic that requires attention. With the rise of artificial intelligence and machine learning, numerous techniques have been proposed for developing energy-efficient clustering algorithms. These algorithms aim to improve the efficiency of battery- driven sensors to prolong the network's lifetime by balancing the energy consumption among all nodes in the network. In this paper, we present a comprehensive evaluation and literature review of state-of-the-art energy-efficient clustering algorithms that can be used for intelligent marine ecosystem monitoring. The review aims to dive into the theoretical aspects of clustering in sensor networks and its application to energy optimization, offering insights into the various clustering schemes proposed for wireless sensors, specifically focusing on energy efficiency.

关键词： Wireless communication Wireless sensor networks Renewable energy sources Machine learning algorithms Reviews Clustering algorithms Marine ecosystems

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Reinforcement Learning for Dynamic Power Management in Embedded Systems 5

Reinforcement Learning for Dynamic Power Management in Embed...

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5th IEEE International Conference on Recent Trends in computer Science and technology, ICRTCST 2024

作者： Panigrahi, Bhawani Sankar Pattanaik, Balachandra Pattanaik, Ojasvi Tilak Babu, S.B.G. Pavithra, G. Shaik, Bazani Vardhaman College of Engineering Department of IT Telangana Hyderabad India Saveetha Institute of Medical and Technical Sciences Adjunct Faculty Saveetha School of Engineering Tamilnadu Chennai India JNTU Vignan Institute of Management and Technology for Women Department of Computer Science and Engineering Hyderabad Ghatkesar India Aditya Engineering College Department of ECE Surampalem India Dayananda Sagar College of Engineering Department of Electronics & Communication Engineering Karnataka Bangalore India Ramachandra College Of Engineering Department of Mechanical Engineering Andhra Pradesh Eluru India

ISBN: (纸本)9798350351378

Itaddresses the challenges that are associated with dynamic power management in embedded systems by utilizing techniques that are derived from the discipline of reinforcement learning (RL). Given the increasing complexity of embedded systems and the need for solutions that are efficient for energy consumption, RL is a potential technology that can dynamically optimize power utilization. This is particularly pertinent in light of the requirement for solutions that are efficient for energy consumption. The dynamic workload fluctuations that are inherent in embedded systems are taken into consideration in this research, which studies the integration of RL algorithms to control power levels in real time in an adaptive manner. This research also takes into account the variable workloads that are endemic to embedded systems. To evaluate the efficacy of RL-based dynamic power management strategies in comparison to traditional methods, with a specific emphasis on the potential for enhanced energy efficiency and system responsiveness, the goal of this is to evaluate the effectiveness of these strategies. The findings not only contribute to the improvement of understanding of the use of reinforcement learning in the setting of embedded systems, but they also provide insights into the utility of RL in meeting the evolving power management requirements in contemporary computing environments. © 2024 IEEE.

关键词： Reinforcement learning

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Knowledge-Enriched Graph Convolution Network for Hybrid Explainable Recommendation from Review Texts and Reasoning Path

Knowledge-Enriched Graph Convolution Network for Hybrid Expl...

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International Conference on Inventive Computation Technologies (ICICT)

作者： Rama Bastola Subarna Shakya Faculty of Science Health and Technology Nepal Open University Lalitpur Nepal Department of Electronics and Computer Engineering Pulchowk Campus Institute of Engineering Tribhuvan University Lalitpur Nepal

ISBN: (数字)9798350359299

ISBN: (纸本)9798350359305

In the digital era, organizations leverage technology to handle vast datasets, yet deriving meaningful insights remains a challenge. Recommender systems address this by using deep learning advancements to provide users with relevant content. However, ensuring transparency in recommendations, known as explainable recommendations, is difficult due to complex deep learning algorithms. Clarifying recommendations to both users and system designers to enhance comprehension and decision-making represents a significant research challenge in the field of explainable recommendation systems. Review-based explanations in human-like languages are intuitive to the general users while Reasoning-path based explanations are more informative to the system designers. The existing models focus on one of the above explanation approaches. This research proposes a hybrid explainable recommender model integrating review-based and reasoning path-based interpretation. The model utilizes external knowledge bases and review documents to create contextualized knowledge-enriched embeddings for users, items, and interactions. Path encoding with LSTM and attention mechanism is utilized for both rating prediction and reasoning path explanation. A Gated Recurrent Unit with a Copy Mechanism generates human-like recommendation explanations. The model yields both types of recommendation explanations and rating predictions comparable to state-of-the-art technologies.

关键词： Deep learning Reviews Convolution Knowledge based systems Organizations Predictive models Logic gates

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Cardiac Arrhythmia Disease Classifier Model Based on a Fuzzy Fusion Approach

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computers, Materials & Continua 2023年第5期75卷 4485-4499页

作者： Fatma Taher Hamoud Alshammari Lobna Osman Mohamed Elhoseny Abdulaziz Shehab Eman Elayat College of Technological Innovation Zayed UniversityDubaiUAE Department of Information Systems College of Computer and Information SciencesJouf UniversitySakakaSaudi Arabia Department of Electronics and Communications Engineering Delta Higher Institute for Engineering&TechnologyMansouraEgypt College of Computing and Informatics University of SharjahSharjahUnited Arab Emirates Department of Information Systems Mansoura UniversityMansoura35516Egypt Department of Teacher Preparation Faculty of Specific EducationMansoura UniversityMansouraEgypt

Cardiac diseases are one of the greatest global health *** to the high annual mortality rates,cardiac diseases have attracted the attention of numerous researchers in recent *** article proposes a hybrid fuzzy fusion classification model for cardiac arrhythmia *** fusion model is utilized to optimally select the highest-ranked features generated by a variety of well-known feature-selection *** ensemble of classifiers is then applied to the fusion’s *** proposed model classifies the arrhythmia dataset from the University of California,Irvine into normal/abnormal classes as well as 16 classes of ***,at the preprocessing steps,for the miss-valued attributes,we used the average value in the linear attributes group by the same class and the most frequent value for nominal ***,in order to ensure the model optimality,we eliminated all attributes which have zero or constant values that might bias the results of utilized *** preprocessing step led to 161 out of 279 attributes(features).Thereafter,a fuzzy-based feature-selection fusion method is applied to fuse high-ranked features obtained from different heuristic feature-selection *** short,our study comprises three main blocks:(1)sensing data and preprocessing;(2)feature queuing,selection,and extraction;and(3)the predictive *** proposed method improves classification performance in terms of accuracy,F1measure,recall,and precision when compared to state-of-the-art *** achieves 98.5%accuracy for binary class mode and 98.9%accuracy for categorized class mode.

关键词： Cardiac arrhythmia preprocessing missing values classification model fusion

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Millimeter-Wave Gap Waveguide-Based Broadband Slant-Polarized Slot Array Antenna

Millimeter-Wave Gap Waveguide-Based Broadband Slant-Polarize...

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European Conference on Antennas and Propagation, EuCAP

作者： Davood Zarifi Ali Farahbakhsh Michal Mrozowski Department of Microwave and Antenna Engineering Faculty of Electronics Telecommunications and Informatics Gdansk University of Technology Gdansk Poland School of Electrical and Computer Engineering University of Kashan Kashan Iran Department of Electrical and Computer Engineering Graduate University of Kerman Kerman Iran

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

This research deals with the design of a broadband, slant-polarized antenna array for 26–40 GHz frequency band. The design employs gap waveguide technology to minimize unwanted energy leakage, ensuring high gain and efficiency. In this configuration, the radiating slots are angled at 45°, and a two-layer feed network, utilizing compact folded E-plane groove gap waveguide power dividers, is used to energize the slots. Key advantages of the proposed antenna array include its low profile, low loss, wide bandwidth, and suitability for millimeter-wave applications.

关键词： Power dividers Slot antennas Millimeter wave technology Optical device fabrication Gap waveguide Bandwidth Millimeter wave propagation Broadband communication Broadband antennas Antenna arrays

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Epidemiologic Evolution Platform Using Integrated Modeling and Geographic Information System

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computers, Materials & Continua 2021年第5期67卷 1645-1663页

作者： Adrian Brezulianu Oana Geman Muhammad Arif Iuliana Chiuchisan Octavian Postolache Guojun Wang Faculty of Electronics Telecommunications and Information TechnologyGheorghe Asachi Technical University from IasiIasi700050Romania Faculty of Electrical Engineering and Computer Sciences Stefan cel Mare University of SuceavaSuceava720229Romania School of Computer Science Guangzhou UniversityGuangzhou510006China

At the international level, a major effort is being made to optimizethe flow of data and information for health systems management. The studiesshow that medical and economic efficiency is strongly influenced by the levelof development and complexity of implementing an integrated system of epidemiological monitoring and modeling. The solution proposed and describedin this paper is addressed to all public and private institutions involved inthe fight against the COVID-19 pandemic, using recognized methods andstandards in this field. The Green-Epidemio is a platform adaptable to thespecific features of any public institution for disease management, based onopen-source software, allowing the adaptation, customization, and furtherdevelopment of “open-source” applications, according to the specificities ofthe public institution, the changes in the economic and social environment andits legal framework. The platform has a mathematical model for the spreadof COVID-19 infection depending on the location of the outbreaks so thatthe allocation of resources and the geographical limitation of certain areascan be parameterized according to the number and location of the real-timeidentified outbreaks. The social impact of the proposed solution is due to theplanned applications of information flow management, which is a first stepin improving significantly the response time and efficiency of people-operatedresponse services. Moreover, institutional interoperability influences strategicsocietal factors.

关键词： Epidemiology evolution service-oriented architecture pandemic geographic information system epidemiological modeling

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Addressing Challenges and Solutions for Scaling up Project-Based Learning Initiatives in Large engineering Programs

Addressing Challenges and Solutions for Scaling up Project-B...

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World engineering Education Forum - Global engineering Deans Council (WEEF-GEDC)

作者： Rendani Wilson Maladzhi Fulufhelo Nemavhola Mbuyu Germain Ntunka Katlego Moloi Nomcebo Happiness Mthombeni Moholo Samuel Tsoe Mechanical Engineering Department Faculty of Engineering & the Built Environment Durban University of Technology Durban South Africa Chemical Engineering Department Faculty of Engineering & the Built Environment Durban University of Technology Durban South Africa Electrical and Power Engineering Department Faculty of Engineering & the Built Environment Durban University of Technology Durban South Africa Electronics and Computer Engineering Department Faculty of Engineering and the Built Environment Durban University of Technology Durban South Africa

ISBN: (数字)9798331519803

ISBN: (纸本)9798331519810

Project-based learning (PBL) has become one of the preferred pedagogical approaches in engineering education to promote active learning, problem-solving skills, and real-world application of knowledge. It is seen as a platform to promote deeper learning of knowledge-in-use within engineering and science practices rather than memorizing material. Both educators and communities accepted PBL as an invigorating tactic to motivate students to learn. Additionally, PBL historically succeeded when academics modified the pace of instruction, scaffolded learning, and created differentiation. Educators can easily change their teaching practices when they comprehend the dynamics and importance of creating a conducive environment of teaching and *** current study proposes to address challenges for scaling up project-based learning initiatives in large engineering programs to prepare students to excel in their future careers and contribute meaningfully to society through a project-based learning approach to address the quality, relevance, and impact of engineering *** intensive systematized literature review research methodology was conducted through renowned databases including Wiley, SAGE, Taylor and Francis, Elsevier, Springer IEEE Xplore, and Google Scholar. The research study targeted peer-reviewed conferences and journal papers published between 2010 and *** study findings highlighted the important role played by PBL in affording students an opportunity to put into practice their mastery of content coordinated the academics in preparation for their employability. It continues to challenge students to engage more in solving complicated content and they obtain critical thinking among others. In addition, fostering of PBL environment prepares engineering graduates for real-world challenges especially when factors such as curriculum design flexibility, supporting faculty readiness, investing in infrastructure, and refining assessment practices are conside

关键词： Databases Scalability Refining Aerospace electronics Internet Teamwork Problem-solving engineering education Sustainable development Systematic literature review

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2D Polynomial Regression Modeling for Predictive Analysis of Glucose Concentration in NP-Model Fractal Microwave Sensor Using Frequency and Transmission Coefficient Disparities

2D Polynomial Regression Modeling for Predictive Analysis of...

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13th International Electrical engineering Congress, iEECON 2025

作者： Nantapanich, Nutyada Mahatthanajatuphat, Pisit Wongsin, Norakamon Lee, Wilaiporn Rajamangala University of Technology Thanyaburi Faculty of Engineering Department of Electronics and Telecommunication Engineering Pathum Thani Thailand Yothinburana School Regular Program in Mathematics-Science Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand

ISBN: (纸本)9798331543952

关键词： Polynomial regression

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