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Journal of Electrical Systems and Information Technology
ISSN 2314-7172 · SpringerOpen · 592 artikel di indeks
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Artikel Jurnal
Optimization of power coefficient equation for standalone wind energy systems
Abstract Accurate modeling of wind turbine performance is essential for improving energy yield, with the power coefficient ( $$\:{C}_{p}$$ ) playing a key role in aerodynamic energy conversion. However, many existing $$\:{C}_{p}$$ models exhibit limited predictive accuracy and insufficient…
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Artikel Jurnal
Techno-economic analysis of an optimized renewable energy integrated combined heat and power system for a primary healthcare facility
Abstract Healthcare facilities depend heavily on regular and sustainable energy for unwavering operation and satisfactory service delivery. However, a significant challenge for healthcare center is the low financial allocation, which affects the provision of sustainable and cost-effective energy…
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Artikel Jurnal
Active detection of partial bypass in smart meters via embedded load injection
Abstract Electricity theft is still a challenge for utility providers. The bypass is a common technique, among other methods employed. The partial bypassing, where a fraction of the current is diverted, is particularly more difficult to detect. This paper proposes a novel, approach for identifying…
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Artikel Jurnal
Federated learning-driven digital twin framework for adaptive resource management in 6G edge networks
Abstract The anticipated transition to sixth-generation (6G) wireless systems is set to redefine how network resources are managed in environments characterized by vast device heterogeneity, stringent latency requirements, and increased autonomy at the network edge. As centralized control paradigms…
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Artikel Jurnal
An improved hide-and-seek augmentation technique for image classification using convolutional neural networks
Abstract In various machine learning tasks, including image classification, data augmentation is widely used to expand the training dataset and prevent overfitting. In traditional data augmentation techniques, images from training data are flipped, distorted, added with some noise, or cropped to…
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Artikel Jurnal
Operational improvement of hybrid-source microgrid using unified power quality conditioner optimized with reinforcement learning brainstorm algorithm
Abstract Power quality is a critical concern in modern microgrids, particularly those integrating renewable energy sources such as photovoltaic arrays, wind turbines, and batteries. However, variability in renewable generation often introduces problems such as voltage instability, harmonics, and…
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Artikel Jurnal
19-transistor single-phase clocking master-slave flip-flop with mixed topology
Abstract This paper presents a master–slave (MS) flip-flop design that employs a single-phase clock and a mixed latch topology, utilizing only 19 transistors (13 NMOS and 6 PMOS) to achieve ultra-low power consumption and high-speed operation. The proposed flip-flop is designed to minimize…
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Artikel Jurnal
Nam++: achieving interpretability and fairness without sacrificing accuracy through neural additive models with selective feature interactions
Abstract Machine learning is everywhere now-lending, criminal justice, healthcare-and with that comes a real problem: transparency and fairness. Deep learning models can be powerful, but they are also black boxes. People affected by these decisions have no clear understanding of how they are being…
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Artikel Jurnal
Performance of linear regression in predicting academic outcome
Abstract Predicting academic outcomes is crucial for enhancing educational strategies, improving student performance, and facilitating early interventions. Machine learning (ML) has emerged as a powerful tool in educational data analysis, with linear regression being one of the most widely used…
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Artikel Jurnal
Balancing accuracy and efficiency: detector–descriptor matching strategies for object tracking in autonomous vehicles
Abstract This paper presents a comparative analysis of various detectors, descriptors, and matching techniques used in computer vision for object tracking in autonomous driving scenarios. The study focuses on classical feature-based methods, including keypoint detectors such as Harris, FAST, and…
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Artikel Jurnal
Sensorless inter-turn short-circuit fault diagnosis in PMSG wind turbine generators using a sliding-mode observer and negative sequence voltage analysis
Abstract In this study, an intelligent fault diagnosis is introduced for the early identification of inter-turn short-circuit faults (ITSCF) in Permanent Magnet Synchronous Generators (PMSGs) deployed in wind power applications. The proposed method integrates the Negative Sequence Voltage (NSV)…
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Artikel Jurnal
A detailed review of large language models in the healthcare sector
Abstract Large Language Models (LLMs) are advanced systems designed to process and generate human-like language by leveraging vast data. LLMs are increasingly used in healthcare, performing tasks such as question-answer generation, medical image analysis, and translation. They have significantly…
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Artikel Jurnal
Investigating the impact of stop words in Hausa extractive summarization
Abstract Text preprocessing decisions play a critical role in natural language processing pipelines for morphologically rich, low-resource languages. Stop-word removal is commonly assumed to improve model performance; however, its effect on extractive summarization remains insufficiently examined…
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Artikel Jurnal
Bandwidth-aware federated reinforcement learning for real-time multi-agent autonomous systems under dynamic environments
Abstract The expansion of autonomous systems across fields such as transportation, robotics, and industrial automation demands dependable real-time decision-making, particularly in environments with limited communication resources. The core problem lies in traditional Federated Reinforcement…
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Artikel Jurnal
Sentiment analysis based on deep learning approaches for text classification
Abstract Recently, text-based sentiment analysis has been a hot area of research. The automatic identification of opinion words and their sentiment polarity is among the most notable efforts. Despite the success of sentiment analysis for text, the methodological issues are understudied. In this…
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Artikel Jurnal
A comparative study of distribution static compensator and distribution generation for techno-economic performances by optimizing location and sizing through intelligent systems (case study: Bahir Dar distribution network)
Abstract Radial distribution networks are often characterized by high active and reactive power losses, poor voltage profiles, and weak voltage stability. Addressing these challenges requires the deployment of effective reinforcement strategies. This study presents a comparative techno-economic…
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Artikel Jurnal
SheepFormers: vision transformer-based sheep breed classification on small datasets for smart farming
Abstract Accurate sheep breed classification is critical for modern livestock management, supporting decisions on breeding, productivity, and profitability in the farming industry. Traditional methods based on visual inspection or body measurements are often subjective, time-consuming, and…
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Artikel Jurnal
Optimal PI controller design for high-efficiency DC–DC boost converters with enhanced perturb-and-observe MPPT in photovoltaic systems
Abstract The maximum power point tracking (MPPT) algorithm and the power converter must be precisely controlled in order to maximize energy extraction from photovoltaic (PV) systems. Four high-power DC–DC boost converters are modeled, designed, and optimized in this work. The system uses a…
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Artikel Jurnal
A real-time ANN for estimation of digital twin parameters used in health indication of flyback converter
Abstract This paper addresses the critical need for real-time health monitoring in flyback converters, key components in renewable energy systems. Conventional methods often require additional sensors, increasing cost and complexity. To overcome this, this paper proposes a novel real-time…
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Artikel Jurnal
An Intelligent Hybrid Metaheuristic for assessing Techno-economic and Environmental Performance in Renewable-integrated Multi-objective Power Flow Framework
Abstract This paper introduces a Intelligent Hybrid Metaheuristic Multi-objective Optimal Power Flow framework for Renewable-integrated Power Systems (MOOPF–RE), aimed at improving Techno-economic and Environmental performance in uncertain operating conditions. The proposed framework introduces a…