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15th IEEE International Conference on ASIC, ASICON 2023

作者： Zhao, Wanlong Zhang, Yuejun Ren, Mingze Wen, Liang Wang, Pengjun Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China Ningbo University Zhejiang Key Laboratory of Mobile Network Application Technology Ningbo China China Coast Guard Academy Department of Electronic Technology Ningbo China Wenzhou University College of Electrical and Electronic Engineering Wenzhou325035 China

ISBN: (纸本)9798350312980

This paper presents a novel design scheme for a decodable self-resetting Regfile circuit that aims to reduce the power consumption caused by massive data and high computing power. The scheme consists of three steps: first, it analyzes the working principle and the energy consumption process of the decoding circuit;second, it proposes a self-resetting decoding circuit structure that uses the clock to control the decoding state and automatically resets when the clock is low, thus avoiding the extra power consumption due to the inversion of the memory cell state during the non-working period of the decoding circuit;third, it implements a two-read, two-write, decodable self-resetting Regfile circuit using a full-custom design method under the TSMC 7nm FinFET process. The experimental results demonstrate that the circuit has an area of 5593μm2 and an energy-delay product of 0.41pJ•nS, and it can operate stably at 4GHz under various temperatures and process corner conditions. © 2023 IEEE.

关键词： 7nm process high speed low power consumption Regfile circuit

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Efficient Segmentation Approach for Different Medical Image Modalities

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computers, Materials & Continua 2022年第11期73卷 3119-3135页

作者： Walid El-Shafai Amira A.Mahmoud El-Sayed M.El-Rabaie Taha E.Taha Osama F.Zahran Adel S.El-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi E.Abd El-Samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

This paper presents a study of the segmentation of medical *** paper provides a solid introduction to image enhancement along with image segmentation *** the first step,the morphological operations are employed to ensure image detail protection and *** objective of using morphological operations is to remove the defects in the texture of the ***,the Fuzzy C-Means(FCM)clustering algorithm is used to modify membership function based only on the spatial neighbors instead of the distance between pixels within local spatial neighbors and cluster *** proposed technique is very simple to implement and significantly fast since it is not necessary to compute the distance between the neighboring pixels and the cluster *** is also efficient when dealing with noisy images because of its ability to efficiently improve the membership partition *** results are performed on different medical image ***(Us),X-ray(Mammogram),Computed Tomography(CT),Positron Emission Tomography(PET),and Magnetic Resonance(MR)images are the main medical image modalities used in this *** obtained results illustrate that the proposed technique can achieve good results with a short time and efficient image *** results on different image modalities show that the proposed technique can achieve segmentation accuracies of 98.83%,99.71%,99.83%,99.85%,and 99.74%for Us,Mammogram,CT,PET,and MRI images,respectively.

关键词： Image segmentation ultrasonic mammogram CT PET MRI morphological operations FCM active contours

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Hybrid Segmentation Approach for Different Medical Image Modalities

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computers, Materials & Continua 2022年第11期73卷 3454-3471页

作者： Walid El-Shafai Amira A.Mahmoud El-Sayed M.El-Rabaie Taha E.Taha Osama F.Zahran Adel S.El-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi E.Abd El-Samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

The segmentation process requires separating the image region into sub-regions of similar *** sub-region has a group of pixels having the same characteristics,such as texture or *** paper suggests an efficient hybrid segmentation approach for different medical image modalities based on particle swarm optimization(PSO)and improved fast fuzzy C-means clustering(IFFCM)*** extensive comparative study on different medical images is presented between the proposed approach and other different previous segmentation *** existing medical image segmentation techniques incorporate clustering,thresholding,graph-based,edge-based,active contour,region-based,and watershed *** paper extensively analyzes and summarizes the comparative investigation of these ***,a prediction of the improvement involves the combination of these techniques is *** obtained results demonstrate that the proposed hybrid medical image segmentation approach provides superior outcomes in terms of the examined evaluation metrics compared to the preceding segmentation techniques.

关键词： Image segmentation ultrasonic images X-ray images CT images PET images MR images fuzzy c-mean morphological operations active contour

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Zero-Shot Hashing Based on Reconstruction With Part Alignment

arXiv

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arXiv 2025年

作者： Jiang, Yan Qi, Zhongmiao Li, Jianhao Qian, Jiangbo Wang, Chong Xin, Yu The Faculty of Electrical Engineering and Computer Science Merchants’ Guild Economics and Cultural Intelligent Computing Laboratory Ningbo University Ningbo315211 China

Hashing algorithms have been widely used in large-scale image retrieval tasks, especially for seen class data. Zero-shot hashing algorithms have been proposed to handle unseen class data. The key technique in these algorithms involves learning features from seen classes and transferring them to unseen classes, that is, aligning the feature embeddings between the seen and unseen classes. Most existing zero-shot hashing algorithms use the shared attributes between the two classes of interest to complete alignment tasks. However, the attributes are always described for a whole image, even though they represent specific parts of the image. Hence, these methods ignore the importance of aligning attributes with the corresponding image parts, which explicitly introduces noise and reduces the accuracy achieved when aligning the features of seen and unseen classes. To address this problem, we propose a new zero-shot hashing method called RAZH. We first use a clustering algorithm to group similar patches to image parts for attribute matching and then replace the image parts with the corresponding attribute vectors, gradually aligning each part with its nearest attribute. Extensive evaluation results demonstrate the superiority of the RAZH method over several state-of-the-art methods. Copyright © 2025, The Authors. All rights reserved.

关键词： Zero-shot learning

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I-V characteristics of short sphere-plane air gaps: modelling using an ATPDraw object

I-V characteristics of short sphere-plane air gaps: modellin...

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23rd International Symposium on High Voltage engineering (ISH 2023)

作者： Pantelis N. Mikropoulos Pavlos K. Samaras High Voltage Laboratory School of Electrical & Computer Engineering Faculty of Engineering Aristotle University of Thessaloniki Thessaloniki Greece

ISBN: (数字)9781839539923

Corona inception and growth characteristics of short sphere-plane air gaps under positive ramp high voltages with variable rate of rise are experimentally investigated. I-V characteristics were obtained through continuous monitoring and measurement of the applied voltage and discharge current. Corona initiates in the form of streamer discharge whereas at slightly higher applied voltage a stable glow is established in the gap. The inception voltage of the various corona modes is experimentally determined using several processing methods. The associated corona inception field is theoretically estimated based on electrostatic field simulations and physical modelling of the glow and streamer discharge; reasonable agreement between experimentally determined and theoretically predicted values is shown to exist. With the aid of an empirical formula accounting for the effects of applied voltage and gap length on discharge current, I-V characteristics are dynamically modelled in ATP-EMTP by developing an ATPDraw object. Using the latter, simulated I-V characteristics of bundled conductors are in excellent agreement with measurements from literature.

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BHJO: A Novel Hybrid Metaheuristic Algorithm Combining the Beluga Whale, Honey Badger, and Jellyfish Search Optimizers for Solving engineering Design Problems

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computer Modeling in engineering & Sciences 2024年第10期141卷 219-265页

作者： Farouq Zitouni Saad Harous Abdulaziz S.Almazyad Ali Wagdy Mohamed Guojiang Xiong Fatima Zohra Khechiba Khadidja Â Kherchouche Department of Computer Science and Information Technology Kasdi Merbah UniversityP.O.Box 30000OuarglaAlgeria Department of Computer Science College of Computing and InformaticsUniversity of SharjahP.O.Box 27272SharjahUnited Arab Emirates Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11937Jordan Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China

Hybridizing metaheuristic algorithms involves synergistically combining different optimization techniques to effectively address complex and challenging optimization *** approach aims to leverage the strengths of multiple algorithms,enhancing solution quality,convergence speed,and robustness,thereby offering a more versatile and efficient means of solving intricate real-world optimization *** this paper,we introduce a hybrid algorithm that amalgamates three distinct metaheuristics:the Beluga Whale Optimization(BWO),the Honey Badger Algorithm(HBA),and the Jellyfish Search(JS)*** proposed hybrid algorithm will be referred to as *** this fusion,the BHJO algorithm aims to leverage the strengths of each *** this hybridization,we thoroughly examined the exploration and exploitation capabilities of the BWO,HBA,and JS metaheuristics,as well as their ability to strike a balance between exploration and *** meticulous analysis allowed us to identify the pros and cons of each algorithm,enabling us to combine them in a novel hybrid approach that capitalizes on their respective strengths for enhanced optimization *** addition,the BHJO algorithm incorporates Opposition-Based Learning(OBL)to harness the advantages offered by this technique,leveraging its diverse exploration,accelerated convergence,and improved solution quality to enhance the overall performance and effectiveness of the hybrid ***,the performance of the BHJO algorithm was evaluated across a range of both unconstrained and constrained optimization problems,providing a comprehensive assessment of its efficacy and applicability in diverse problem ***,the BHJO algorithm was subjected to a comparative analysis with several renowned algorithms,where mean and standard deviation values were utilized as evaluation *** rigorous comparison aimed to assess the performance of the BHJOalgorithmabout its counterparts,shedd

关键词： Global optimization hybridization of metaheuristics beluga whale optimization honey badger algorithm jellyfish search optimizer chaotic maps opposition-based learning

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A Robust Framework for Epileptic Seizure Diagnosis: Utilizing GRU-CNN Architectures in EEG Signal Analysis

A Robust Framework for Epileptic Seizure Diagnosis: Utilizin...

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International Symposium on Artificial Intelligence and Signal Processing (AISP)

作者： Maryam Nikoupour Mohammad Reza Keyvanpour Seyed Vahab Shojaedini Department of Computer Engineering Faculty of Engineering Data Mining Laboratory Alzahra University Tehran Iran Department of Computer Engineering Faculty of Engineering Alzahra University Tehran Iran Department of Electrical Engineering Iranian Research Organization for Science and Technology Tehran Iran

Seizures that take place repeatedly and without provocation are referred to as epilepsy. Epilepsy can be diagnosed with electroencephalography (EEG). One of the most influential challenges of the past few years has been the use of deep learning algorithms to replace manual inspection of medical signals by specialists, such as epilepsy signal classification. This paper presents a multi-label classification approach for epileptic seizures using deep learning. UCI machine learning repository’s epileptic seizure dataset has been used to classify epileptic seizure patients. 178 features are present in each of the 11500 samples in the dataset. Based on a variety of criteria, the proposed method may have a positive impact on epilepsy diagnosis, in most cases by approximately 6% compared with existing methods utilizing long short-term memory (LSTM) and autoencoder. It is possible thus to develop and apply gated recurrent unit-based methods with good potential for categorizing EEG signals for epilepsy diagnosis based on gated recurrent unit (GRU)-CNN based methods.

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First wetland mapping at 10-m spatial resolution in South America using multi-source and multi-feature remote sensing data

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Science China Earth Sciences 2024年第10期67卷 3252-3269页

作者： Weiwei SUN Gang YANG Yuling HUANG Dehua MAO Ke HUANG Lin ZHU Xiangchao MENG Tian FENG Chao CHEN Yong GE Department of Geography and Spatial Information Techniques Ningbo UniversityNingbo 315211China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences&Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Natural Resources and Planning Bureau Shanghai Pudong New DistrictShanghai 200100China Key Laboratory of Wetland Ecology and Environment Northeast Institute of Geography and AgroecologyChinese Academy of SciencesChangchun 130102China Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China School of Geography Science and Geomatics Engineering Suzhou University of Science and TechnologySuzhou 215009China

Wetland degradation has been accelerating in recent years globally. Accurate information on the geographic distribution and categories of wetlands is essential for their conservation and management. Despite being the world′s fourth largest continent, South America has limited research on wetland mapping, and there is currently no available map that provides comprehensive information on wetland distribution and categories in the region. To address this issue, we used Sentinel-1, Sentinel-2 and SRTM data, developed a sample collection method and a wetland mapping method with a collection of multi-source features such as optical features, polarization features and shape features for South American wetlands. We produced a 10-m resolution wetland map based on the Google Earth Engine(GEE) platform. Our Level-1 wetland cover map accurately captured six wetland sub-categories with an overall accuracy of 96.24% and a kappa coefficient of 0.8649, while our Level-2 water cover map included five sub-categories with an overall accuracy of 97.23% and a kappa coefficient of0.9368. The results show that the total area of existing wetlands in South America is approximately 1,737,000 km~2, which is6.8% of the total land area. Among the ten wetland categories, shallow sea had the largest area(960,527.4 km~2), while aquaculture ponds had the smallest area 1513.6 km~2. Swamp had the second largest area(306,240.1 km~2). Brazil, Argentina,Venezuela, Bolivia, and Colombia were found to have the largest wetland areas, with Brazil and Colombia having the most diverse wetland categories. This product can serve as baseline data for subsequent monitoring, management, and conservation of South American wetlands.

关键词： Wetland mapping Google Earth Engine Sentinel imagery South America

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The use of combined remote electronic monitoring and blood concentrations of antipsychotics for assessment of therapeutic adherence in patients with schizophrenia: results of a prospective study

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BMC Psychiatry 2025年第1期25卷 1-11页

作者： Šilhán, Petr Hýža, Martin Ambroš, Samuel Dostálek, Petr Schwarzová, Jana Skřont, Tomáš Perničková, Denisa Baarová, Pavla Augustynek, Martin Kacířová, Ivana Uřinovská, Romana Department of Psychiatry University Hospital Ostrava 17. listopadu 1790 Ostrava Poruba 708 52 Czech Republic Department of Clinical Neurosciences Faculty of Medicine University of Ostrava Ostrava Czech Republic Department of Cybernetics and Biomedical Engineering Faculty of Electrical Engineering and Computer Science VSB-Technical University Ostrava Ostrava Czech Republic Department of Clinical Pharmacology Institute of Laboratory Medicine University Hospital Ostrava Ostrava Czech Republic Institute of Clinical Pharmacology Faculty of Medicine University of Ostrava Ostrava Czech Republic

Background: Schizophrenia is a serious mental illness, the pharmacological treatment of which comprises primarily the use of antipsychotics. However, non-adherence to their use and its reliable determination present a serious clinical and economic problem. This study aimed to determine therapeutic adherence in outpatients with schizophrenia spectrum disorders by combining short-term electronic monitoring of dispenser opening with the measurement of antipsychotic blood concentrations. Methods: A total of 55 patients underwent a week-long electronic monitoring of dispenser opening and measurement of blood concentrations before and after monitoring. Patients who correctly opened the dispenser at least in 80% of scheduled time points during the weekly interval and, at the same time, did not show a change in blood concentration of the antipsychotic by more than 30% in any direction, were considered adherent. Results: 69.1% of the patients met the adherence criteria, which was less than that determined by the Drug Attitude Inventory (DAI-10), the Visual Analogue Scale (VAS), and the Clinician Rating Scale (CRS). 7.3% of the patients took less than 80% of the prescribed doses and a change in blood concentrations of the antipsychotic by more than 30% was detected in 25.4% of the patients. In 70.9% of patients, the detected concentrations were within the recommended therapeutic reference interval. The groups of adherent and non-adherent patients did not differ statistically significantly in the severity of their illness as determined by the Clinical Global Impression (CGI), the Personal and Social Performance scale (PSP), and the Positive and Negative Syndrome Scale (PANSS). Conclusions: The combined method of evaluating adherence in schizophrenia patients confirmed the results determined by other methods. The benefits of this approach are described in the paper. © The Author(s) 2025.

关键词： Antipsychotics Schizophrenia Telehealth Therapeutic adherence Therapeutic drug monitoring

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A Mobile Visitor Management System Using a QR Code and PIN for Access Control 2nd

A Mobile Visitor Management System Using a QR Code and PIN f...

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2nd International Conference on Connected Objects and Artificial Intelligence, COCIA 2024

作者： Awotunde, Joseph Bamidele Adeniyi, Abidemi Emmanuel Imoize, Agbotiname Lucky Mejdoub, Youssef Abdualazizu, Zakariyya Department of Computer Science Faculty of Information and Communication Sciences University of Ilorin Ilorin240003 Nigeria Department of Computer Science Bowen University Osun State Iwo Nigeria Department of Electrical and Electronics Engineering University of Lagos Akoka Nigeria RITM Laboratory Higher School of Technology ESTC Hassan II University Casablanca Morocco

ISBN: (纸本)9783031704109

Visitor management is a common activity that happens every day all around the world. Accepting visitors at home or in the office, going to the bank, or visiting a private residential area;some sort of visitor management goes on in all those activities to ensure access control and security. Insecurity is a big challenge that comes with receiving visitors and that is why visitor management is important. Traditionally, visitor management is handled physically by recording visitors’ information into a log book and asking visitors to contact their hosts before gaining access to a secured environment but this process is time-consuming and the visitor’s record is exposed to exploitation. Automated Visitor Management Systems (VMS) overcome the shortcomings of the traditional method of visitor management. VMS automates the process of recording visitors’ information, keeping a log of all visits, and ensuring some sort of access control or visitor authentication just in case of an imposter or if anything ever goes wrong. This study aims to design and model a flexible Mobile Visitor Management system that can be used to record visitors’ information and authenticate visitors for access control purposes. The study was achieved using Figma software to design and prototype the system and then using React Native and SQLite for the development of the system. The system has proven to be more convenient than the common traditional way of recording visitors’ information into a physical log book. The system protects its users from loss of information, waste of time, and insecurity. The flexible and inexpensive nature of the system makes it adaptable to almost any organization or property owner, this gives the general public a great opportunity to try out Visitor Management Technology. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Authentication

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