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Multi-parameter Analysis of Active Energy Consumptions in a Municipal Hospital

Multi-parameter Analysis of Active Energy Consumptions in a ...

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International Conference on Applied and Theoretical Electricity (ICATE)

作者： Ileana-Diana Nicolae Denis Andrei Firulescu Petre-Marian Nicolae Marian-Stefan Nicolae Cristina-Diana Marinescu Dept. of Computer Science and IT University of Craiova Craiova Romania Dept. of Electrical Engineering Energetic and Aeronautics University of Craiova Craiova Romania Electrical and Energetic Engineering Doctoral School Dept. University of Craiova Craiova Romania

ISBN: (数字)9798350388107

ISBN: (纸本)9798350388114

The paper deals with the multi-parameter analysis of active energy consumptions in a Romanian municipal hospital. Minimum, mean, and maximum values are computed based on measurements recorded every 15 minutes by the energy provider, the analyzed time range being between the 1-st of July 2021 and the 30-th of June 2022. The analysis delved into monthly, daily, and hourly consumption trends. The investigation extended to seasonal variations, to discern the impact of climatic conditions. The study also differentiated between working and non-working days, recognizing the dynamic energy demands during operational and non-operational periods. Peak hours are examined to pinpoint instances of heightened consumption, providing valuable insights for optimizing resource utilization. Synthetic conclusions with respect to different categories of consumptions are provided. A solution based on photovoltaic panels is suggested in the end, along with the estimation of the time required for the full return of investment.

关键词： Photovoltaic systems Energy consumption Hospitals Electricity Estimation Lighting Market research Time measurement Resource management Investment

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An Overview of Virtual Reality 31st

An Overview of Virtual Reality

引用

31st International Conference on Software engineering and Data engineering, SEDE 2022

作者： Lewis, Christopher Harris, Frederick C. Dept. of Computer Science and Engineering University of Nevada Reno RenoNV89557 United States

Virtual Reality (VR) has existed for many years;however, it has only recently gained wide spread popularity and commercial use. This change comes from the innovations in head mounted displays (HMDs) and from the work of many software engineers making quality user experiences (UX). In this work we present a brief history, current research areas, and areas for improvement in virtual reality © 2022, EasyChair. All rights reserved.

关键词： Virtual reality

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A Novel Dual Channel Isolated Current Source Gate Driver for Fast Switching MOSFETs

A Novel Dual Channel Isolated Current Source Gate Driver for...

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Annual Conference of Industrial Electronics Society

作者： Asjad Elahi Mohamed Youssef Dept. of Electrical Computer and Software Engineering University of Ontario Institute of Technology Oshawa

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

A new dual-channel discontinuous mode isolated current source gate driver (ICSGD) is proposed in this paper. The proposed gate driver can provide two isolated gate drive signals for two power MOSFETs in circuits where these switches are in sync. The proposed gate driver can achieve very fast turn on and turn off transitions, due to its current mode nature. In addition, this technique can achieve partial gate energy recovery by recovering a fraction of the RMS (CV2) energy, which is typically dissipated over the gate drive resistors in voltage source gate drive (VSGD) techniques. Thus, provides better efficiency. The proposed circuit consists of six transistors and a small pulse transformer to allow swift operation over a wide range of duty cycles. Current through the transformer is discontinuous to avoid conduction losses due to circulating currents such as in some resonant gate drivers (RGD). Consequently, the proposed ICSGD provides superior performance over its VSGD counterparts, especially in high-frequency (HF) operation. The design is implemented in both PSIM and Typhoon HIL (hardware in the loop) platforms. The model is verified with a match of results from PSIM and Typhoon. The PSIM & HIL results show that the ICSGD achieves a minimum of 20% efficiency improvement.

关键词： MOSFET Tropical cyclones Circuits Switches Logic gates Drives Gate drivers Pulse transformers Transistors Synchronization

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Utility Point: An User Service Assistance Based Mobile Application For the Citizens of Bangladeshi City Corporation

Utility Point: An User Service Assistance Based Mobile Appli...

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2022 International Conference on Smart Information Systems and Technologies, SIST 2022

作者： Chowdhury, Mahfuzulhoq Ahmad, Alve Saha, Arup Chowdhury, Bibhas Roy Kurmasheva, Dinara Ahmed, Forkan Uddin Chittagong University Of Engineering And Technology Dept. Of Cse Chittagong Bangladesh West Kazakhstan University Dept. Of Computer Science Uralsk Kazakhstan

ISBN: (数字)9781665467902

ISBN: (纸本)9781665467902

City-corporation is one of the important institutions that can improve the city people lifestyles by providing necessary utility services along with socioeconomic development. Currently, most of the services offered by the city corporation are handled offline mode. To keep pace with the modern world, the incorporation of information and communication technology (ICT) based digital technology is necessary. At present, the existing works related to city corporation service do not consider multiple utility features, problem reporting, and fee payment features at the same time. Thus, the existing city corporation-related service delivery works may experience huge time and cost wastage. To cope up with the existing city corporation-related issues, in this paper we have presented a user service assistance mobile application for the citizens of the Bangladeshi city corporation. Our proposed utility point mobile application offers several features for the citizens like electricity, water, gas bill payment, trash service payment, cemetery plot booking service, holding tax payment, e-trade and vehicle license apply, birth and citizen certificate, problem reporting, among others. Our user survey results indicate that almost 80% of users are satisfied with the features of the proposed city corporation mobile application. © 2022 IEEE.

关键词： Surveys

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PSMGD: Periodic Stochastic Multi-Gradient Descent for Fast Multi-Objective Optimization 39

PSMGD: Periodic Stochastic Multi-Gradient Descent for Fast M...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Xu, Mingjing Ju, Peizhong Liu, Jia Yang, Haibo Dept. of Computing and Information Sciences Ph.D. Rochester Institute of Technology United States Dept. of Computer Science University of Kentucky United States Dept. of Electrical and Computer Engineering The Ohio State University United States

ISBN: (纸本)157735897X

Multi-objective optimization (MOO) lies at the core of many machine learning (ML) applications that involve multiple, potentially conflicting objectives. Despite the long history of MOO, recent years have witnessed a surge in interest within the ML community in the development of gradient manipulation algorithms for MOO, thanks to the availability of gradient information in many ML problems. However, existing gradient manipulation methods for MOO often suffer from long training times, primarily due to the need for computing dynamic weights by solving an additional optimization problem to determine a common descent direction that can decrease all objectives simultaneously. To address this challenge, we propose a new and efficient algorithm called Periodic Stochastic Multi-Gradient Descent (PSMGD) to accelerate MOO. PSMGD is motivated by the key observation that dynamic weights across objectives exhibit small changes under minor updates over short intervals during the optimization process. Consequently, our PSMGD algorithm is designed to periodically compute these dynamic weights and utilizes them repeatedly, thereby effectively reducing the computational overload. Theoretically, we prove that PSMGD can achieve state-of-the-art convergence rates for strongly-convex, general convex, and non-convex functions. Additionally, we introduce a new computational complexity measure, termed backpropagation complexity, and demonstrate that PSMGD could achieve an objective-independent backpropagation complexity. Through extensive experiments, we verify that PSMGD can provide comparable or superior performance to state-of-the-art MOO algorithms while significantly reducing training time. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Multiobjective optimization

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Wideband Circularly Polarized Array Using Tightly Coupled Dipole Array Theory

Wideband Circularly Polarized Array Using Tightly Coupled Di...

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US National Committee of URSI National Radio science Meeting (USNC-URSI NRSM)

作者： Muhammad Mubasshir Hossain Stavros Koulouridis Satheesh B. Venkatakrishnan John L. Volakis Electrical and Computer Engineering Dept. Florida International University Miami FL USA

Circularly polarized transceivers have shown superior characteristics over linearly polarized ones for space-to-ground communications. Specially, unlike linearly polarized (LP) waves that undergo Faraday rotation through the ionosphere, circularly polarized (CP) waves reduce Faraday rotation and cloud interference effects. Hence, wideband circularly polarized phased arrays are attractive for high-resolution spaceborne radars, especially at lower frequencies. For example, radar resolutions down to 1 meter require at least 150 MHz of bandwidth, viz. 150 MHz-300 MHz operation. Unfortunately, conventional wide-scanning CP phased arrays exhibit narrow-band axial ratio < 3 dB performance.

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Predicting Age from Brain Connectivity Matrix: A Stacked Regression Approach

Predicting Age from Brain Connectivity Matrix: A Stacked Reg...

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International Symposium on Applied Computational Intelligence and Informatics ( SACI)

作者： Gabriel Pojoga Victor Teslaru Otilia ZvoriȘteanu Ștefan-Daniel Achirei Dept. of Computer Science and Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iasi Iasi Romania

ISBN: (数字)9798331515478

ISBN: (纸本)9798331515485

Accurately predicting age from functional connectome data can provide valuable insights into brain development and neurodegenerative processes. In this study, we apply various machine learning algorithms to age prediction using functional connectivity features. The preprocessing pipeline included missing value imputation and categorical variable encoding. We experimented with traditional regression models and neural networks, ultimately achieving the best performance with a stacking ensemble. The ensemble leveraged a Multi-Layer Perceptron meta-learner to reduce base model biases, improving predictive accuracy. To enhance diversity, base models were selected based on their individual performance and prediction correlation. Our results demonstrate that ensemble learning can effectively handle the complexity of neuroimaging data, offering a robust approach for age prediction and potential applications in neurological research.

关键词： Neuroimaging Computational modeling Precision medicine Stacking Diversity reception Proteomics Predictive models Brain modeling Ensemble learning Biological neural networks

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Effective Pest Detection by YOLOv5 with BottleneckCSP

Effective Pest Detection by YOLOv5 with BottleneckCSP

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Power, electrical, and Electronics and Industrial Applications (PEEIACON), IEEE International Conference on

作者： Ishrat Zahan Tani Tasmia Jannat Dept. of Computer Science & Engineering Rajshahi University of Engineering & Technology Rajshahi Bangladesh

ISBN: (数字)9798331517984

ISBN: (纸本)9798331517991

Pest damage poses a significant risk to crop quality and productivity, underscoring the necessity for accurate and efficient detection methods for farmers. Artificial intelligence (AI) facilitates targeted pest management with reduced reliance on broad-spectrum insecticides and enables early detection of insect infestations. Object detection, a computer vision approach, is revolutionizing pest identification in agriculture by locating pests in digital crop photographs. However, the detection of tiny objects within these datasets presents challenges due to sparse spatial information. In response to this challenge, we have replaced the C3 block of YOLOv5 with the BottleneckCSP module, which is more effective for feature mapping of tiny objects. Our enhanced model demonstrates superior performance on the IP102 dataset, which is characterized by the presence of tiny objects. Comparative analysis reveals that our BottleneckCSP-integrated model significantly improves feature mapping, resulting in a notable increase in mean average precision (mAP). Specifically, our modified model achieves an mAP of 63.9%, outperforming many state-of-the-art methods on this dataset. This advancement in the YOLOv5 architecture sets a new benchmark for AI-powered precision agriculture, providing farmers with a highly efficient tool for crop protection and pest management. The significant performance gains highlight the potential of our approach to transform current agricultural practices, paving the way for more sustainable and effective pest control strategies.

关键词： YOLO Accuracy Crops computer architecture Transforms Feature extraction Object recognition Artificial intelligence Protection Resilience

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Breast Cancer Prediction Using Machine Learning 5

Breast Cancer Prediction Using Machine Learning

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5th International Conference on Emerging Systems and Intelligent Computing, ESIC 2025

作者： Dhondiyal, Shiv Ashish Luthra, Pooja Sharma, Bhupender Rajni, Rajni Uniyal, Ishita Graphic Era Deemed to be University Dept. of Computer Science and Engineering Dehradun India Chandigarh University Department of Computer Science & Engineering Punjab Mohali India Coer University Department of Computer Science and Application Uttarakhand Roorkee India Guru Jambheshwar University of Science and Technology Department Of Computer Science & Engineering Haryana Hisar India Graphic Era Hill University Department of Electrical Engineering India

ISBN: (纸本)9798331522100

The number of newly diagnosed cases of breast cancer exceeds 2.3 million annually worldwide. There is a severe lack of valid prognostic and predictive indicators for the clinical treatment of breast cancer patients at the present time. In order to decrease the mortality rate and increase the survival time of breast cancer patients, early detection of this deadly disease is crucial. Improving breast cancer prognosis relies on the analysis and processing of mammography data, the gold standard for screening and early detection. In order to detect breast cancer in mammograms, the Fuzzy C-means algorithm is employed for image segmentation. Next, we train it to identify the characteristics of the segmented regions, and then we use an effective classifier to categorise the trained pictures into their respective mammography classes. This research used the Breast Cancer Wisconsin Diagnostic dataset and two ML algorithms: K-Nearest Neighbours (KNN) and Random Forest. After getting the results, we compared and evaluated the performance of these two classifiers. Potentially useful tools for both early diagnosis and treatment planning include breast cancer prediction models that account for a wide range of risk factors. Effective disease management involves the collection, storage, and administration of many data sets, as well as intelligent systems based on several aspects for the prediction of breast cancer. © 2025 IEEE.

关键词： Image segmentation

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DC Fault Detection Using Time Derivative of High-Pass Filter Response in MTDC Systems

DC Fault Detection Using Time Derivative of High-Pass Filter...

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Annual Conference of Industrial Electronics Society

作者： Saad Ahmed Khan Abhisek Ukil Nirmal-Kumar C. Nair Dept. of Electrical Computer and Software Engineering The University of Auckland Auckland New Zealand

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

In the DC fault event, DC link capacitors immediately discharge a colossal current of high frequency. These large currents of high frequencies can instantly damage the components attached to the DC transmission system. Therefore, a rapid and robust DC fault detection topology is necessary, facilitating protection coordination in forthcoming Multi-Terminal Direct Current (MTDC) systems. This study introduces a novel fault detection technique using the time derivative of the High Pass Filter (HPF) response to identify fault currents in just a few microseconds (µs). This topology enables protection coordination for modern MTDC systems. Furthermore, this technique can identify different types of DC faults and remains unaffected by AC faults and load variation.

关键词： Fault diagnosis Accuracy Fault detection Load management electrical fault detection Topology Power systems High frequency Passband Protection

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