检索结果-内蒙古大学图书馆

2025 International Conference on Multi-Agent Systems for Collaborative Intelligence, ICMSCI 2025

作者： Kabilamani, P. Karthikeyan, R. Praanesh, J. Karthik Raja, R. Srm Institute of Science and Technology Faculty of Engineering Department of Electronics and Communication Engineering Vadapalani Campus Chennai India

ISBN: (纸本)9798331509828

The increasing prevalence of electric vehicles (EVs) highlights the need to create effective and accessible charging systems. However, wireless charging methods for electric vehicles currently face several obstacles. This encompasses challenges such as decreased efficiency resulting from energy losses, difficulties in coil alignment while charging, and the necessity for sophisticated safety devices to prevent overheating, overcurrent, and voltage swings. Furthermore, numerous current systems do not incorporate Internet of Things (IoT) technology, which is vital for real-time monitoring and predictive maintenance to improve user experience and system dependability. This study presents a smart wireless electric vehicle charging system that integrates low voltage inductive power transmission with Internet of Things capabilities to address these difficulties. The system facilitates real-time monitoring of critical parameters, including voltage, current, and temperature, through the integration of the IoT. The aggregated data are accessible via a simple web-based interface, enabling customers to remotely supervise and manage the charging process. In addition, the system has safety mechanisms that automatically identify and respond to irregular charging circumstances, guaranteeing efficient and secure functionality. So,the primary objective of this project is to demonstrate the feasibility of integrating wireless charging with IoT to improve the efficiency, convenience, and safety of EV infrastructure. Through this approach, the system aims to provide a seamless, automated, and user-centric EV charging experience, addressing the limitations of current systems and contributing to the advancement of sustainable transportation technology. © 2025 IEEE.

关键词： Charging stations

来源：评论

学校读者我要写书评

暂无评论

Investigations and Time Estimation on Federated Learning for Future Internet of Vehicles

引用

IEEE Internet of Things Journal 2025年第11期12卷 17387-17398页

作者： Fukumoto, Shun Li, Ruidong Zeng, Kai Nan, Haihan Su, Zhou Kanazawa University Intelligent Computation and Network Laboratory Division of Electrical Information and Communication Engineering Kanazawa920-1192 Japan Kunming University of Science and Technology Faculty of Information Engineering Automation Kunming066000 China Kanazawa University Division of Electrical Information and Communication Engineering Kanazawa920-1192 Japan George Mason University Electrical and Computer Engineering Department FairfaxVA22030 United States Xi’an Jiaotong University School of Cyber Science and Engineering Xi’an710049 China

For future Internet of Vehicles (IoV), communications and computing will converge to provide services. Federated learning (FL), as one of the typical distributed computing technologies, needs to be integrated with IoV. For such integration, FL suffers from the straggler effect that the entire learning speed is lowered down, because of the existence of the devices, such as low-powered road side units and vehicles, taking more time to complete their tasks. Although the existing mechanisms reduce straggler effects by adopting asynchronous mechanisms and clustering mechanisms, they lack the detailed analysis of the reasons and the impacts of each cause, leading to inefficiencies in the design of algorithm. Additionally, most of the existing work only considered the impact of a single factor in computation, communication, or data distribution, which lacks comprehensive on research for causes of stragglers effects. The bottleneck is that it is laborious to observe the time delay precisely with the existing high-calculating evaluations. In this article, we elaborately explore the effects of computing power, communication capability, and data distributions on the straggler effects with carefully designing and conducting the extensive experiments. After investigations, we propose a novel learning completion time estimation formula for low computing capability devices with mini-batch stochastic gradient decent (SGD). We compare our proposed estimation formula with the one based on floating operation per second (FLOPs). Through the evaluations, our formula can demonstrate the improvement up to 72.4% at docker and 32.4% at Raspberry Pi device compared to the existing work. © 2014 IEEE.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

Design and Modeling of a Photonic Crystal Multiplexer Using Artificial Intelligence

Advanced Electromagnetics

引用

Advanced Electromagnetics 2025年第1期14卷 59-64页

作者： Karami, Pouya Yahya, Salah I. Palash, Behnam Chaudhary, Muhammad Akmal Assaad, Maher Parandin, Fariborz Roshani, Saeed Hazzazi, Fawwaz Roshani, Sobhan Department of Electrical Engineering Kermanshah Branch Islamic Azad University Kermanshah Iran Department of Communication and Computer Engineering Cihan University-Erbil Erbil44001 Iraq Department of Software Engineering Faculty of Engineering Koya University KOY45 Koya Iraq Department of Electrical and Computer Engineering College of Engineering and Information Technology Ajman University 346 Ajman United Arab Emirates Department of Electrical Engineering College of Engineering Prince Sattam bin Abdulaziz University Al-Kharj11492 Saudi Arabia

In this paper, design and modeling of an all-optical 2×1 multiplexer based on 2D photonic crystals and artificial neural networks (ANNs) are presented. The proposed structure aims to maximize the difference between the output powers in logical states, which is critical for enhancing the system ability to distinguish between these states. In this study, an ANN model is employed to accurately predict the normalized output power of the designed photonic crystal multiplexer, providing a time-efficient alternative to conventional simulation methods for analyzing multiplexer behavior across various logical states. The results demonstrate significant improvements in signal separation and overall performance compared to previous works. Additionally, a detailed comparison of the normalized output power for different logic states is provided, highlighting the advantages of the proposed design. © 2025, Advanced Electromagnetics. All rights reserved.

关键词： Silicon photonics

来源：评论

学校读者我要写书评

暂无评论

VTAF-Ensemble: A Hybrid Vision Transformer and Attention-based Learning Approach for Enhanced Brain Tumor Detection and Classification 1

VTAF-Ensemble: A Hybrid Vision Transformer and Attention-bas...

引用

1st International Conference on Intelligent Systems and Computational Networks, ICISCN 2025

作者： Fathima, Mohammed Nazneen Singh, Prabhjot Singh, Simrandeep Chandigarh University Department of Electronic and Communication Engineering Mohali India Chandigarh University Department of Computer Science and Engineering Mohali India

ISBN: (纸本)9798331529246

This work introduces a new methodology, Vision Transformer with Attention-based Feature Mapping and Optimized Ensemble Learning (VTAF-Ensemble), which includes three advanced techniques: Vision Transformer-Based Segmentation (VT-Seg), Attention-Based Feature Mapping (AF-Map) and Optimized Ensemble Learning (OE-Ensemble), to boost the brain tumor detection and classification from Magnetic Resonance Imaging (MRI) images. Traditional practice of identifying tumor is error prone, time consuming, hence it requires automation. This thesis proposes an integrated method, which includes VT Seg for accurate segmentation, AF Map for feature enhancement, and OE Ensemble for Ensemble classification using SVM and CNN classifiers. We show that VTAF-Ensemble achieves 92.1% Intersection over Union (IoU), 94.5% Mean Average Precision (mAP), 93.2% Dice Coefficient (DC) and 95% sensitivity in segmentation. Moreover, the model also yields better results on classification metrics compared to others: Area Under the Curve (AUC) of 95.2% and F1 Score of 92.9% and recall of 93%. Overall, this hybrid approach provides substantial accuracy improvements, scalability and utility for medical image applications as they relate to medical imaging applications, in particular, brain tumor specific diagnostic applications. © 2025 IEEE.

关键词： Magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

An Iterative PRISMA Review of GAN Models for Image Processing, Medical Diagnosis, and Network Security

引用

computers, Materials & Continua 2025年第2期82卷 1757-1810页

作者： Uddagiri Sirisha Chanumolu Kiran Kumar Sujatha Canavoy Narahari Parvathaneni Naga Srinivasu Department of Computer Science and Engineering Prasad V Potluri Siddhartha Institute of TechnologyVijayawada520007India Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaram522302India Department of Electronics and Communication Engineering Sreenidhi Institute of Science and TechnologyHyderabad501301India Amrita School of Computing Amrita Vishwa VidyapeethamAmaravati522503India Department of Teleinformatics Engineering Federal University of CearáFortaleza60455-970Brazil Inti International University Nilai71800Malaysia

The growing spectrum of Generative Adversarial Network (GAN) applications in medical imaging, cyber security, data augmentation, and the field of remote sensing tasks necessitate a sharp spike in the criticality of review of Generative Adversarial Networks. Earlier reviews that targeted reviewing certain architecture of the GAN or emphasizing a specific application-oriented area have done so in a narrow spirit and lacked the systematic comparative analysis of the models’ performance metrics. Numerous reviews do not apply standardized frameworks, showing gaps in the efficiency evaluation of GANs, training stability, and suitability for specific tasks. In this work, a systemic review of GAN models using the PRISMA framework is developed in detail to fill the gap by structurally evaluating GAN architectures. A wide variety of GAN models have been discussed in this review, starting from the basic Conditional GAN, Wasserstein GAN, and Deep Convolutional GAN, and have gone down to many specialized models, such as EVAGAN, FCGAN, and SIF-GAN, for different applications across various domains like fault diagnosis, network security, medical imaging, and image segmentation. The PRISMA methodology systematically filters relevant studies by inclusion and exclusion criteria to ensure transparency and replicability in the review process. Hence, all models are assessed relative to specific performance metrics such as accuracy, stability, and computational efficiency. There are multiple benefits to using the PRISMA approach in this setup. Not only does this help in finding optimal models suitable for various applications, but it also provides an explicit framework for comparing GAN performance. In addition to this, diverse types of GAN are included to ensure a comprehensive view of the state-of-the-art techniques. This work is essential not only in terms of its result but also because it guides the direction of future research by pinpointing which types of applications require some

关键词： GAN CGAN WGAN DCGAN image analysis

来源：评论

学校读者我要写书评

暂无评论

AI Based Anomaly Detection for Bank Security Against Theft 3

AI Based Anomaly Detection for Bank Security Against Theft

引用

3rd International Conference on communication, Control, and Intelligent Systems, CCIS 2024

作者： Ramesh Prabhakaran, R. Quamar, Danish Guhan, P. Angel Maanu, P. Sherine, W.B. Raj, Aman Mizoram University Department of Computer Engineering Mizoram India Panimalar Engineering College Department of Electrical and Communication Engineering Chennai India Panimalar Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331528201

A critical component of video surveillance research and real-world applications is the detection of anomalous events. In order to improve public safety, more and more surveillance cameras are being installed in public spaces like roadways, crosswalks, banks, and shopping centers. Identification of odd occurrences, such as car accidents, crimes, or illicit activity, is a crucial duty in video surveillance. Because anomalous events are less often than normal activities, the goal of an efficient anomaly detection system is to quickly identify departures from the average and identify the abnormality's temporal span. One way to think of anomaly detection is as an early stage of video analysis that separates abnormalities from normal patterns. Using classification techniques, an anomaly can be further classified into particular activities once it has been discovered. An overview of anomaly detection with an emphasis on banking operations is given in this paper. Many every day and recurring transactions in the banking industry affect a number of stakeholders, including staff members, clients, debtors, and outside parties. Early detection of these anomalies can reduce or even eliminate any potential bad effects. In order to distinguish between normal and abnormal events, this work employs an anomaly detection technique based on machine learning. © 2024 IEEE.

关键词： Banking

来源：评论

学校读者我要写书评

暂无评论

An Optimal DPM Based Energy-Aware Task Scheduling for Performance Enhancement in Embedded MPSoC

引用

computers, Materials & Continua 2023年第1期74卷 2097-2113页

作者： Hamayun Khan Irfan Ud Din Arshad Ali Mohammad Husain Department of Electrical Engineering Faculty of Engineering&Technology Superior University Lahore54000Pakistan Department of Computer Science Faculty of Computer Science&IT Superior University Lahore54000Pakistan Faculty of Computer and Information Systems Islamic University of MadinahAl Madinah Al Munawarah42351Saudi Arabia

Minimizing the energy consumption to increase the life span and performance of multiprocessor system on chip(MPSoC)has become an integral chip design issue for multiprocessor *** performance measurement of computational systems is changing with the advancement in *** to shrinking and smaller chip size power densities onchip are increasing rapidly that increasing chip temperature in multi-core embedded *** operating speed of the device decreases when power consumption reaches a threshold that causes a delay in complementary metal oxide semiconductor(CMOS)circuits because high on-chip temperature adversely affects the life span of the *** this paper an energy-aware dynamic power management technique based on energy aware earliest deadline first(EA-EDF)scheduling is proposed for improving the performance and reliability by reducing energy and power consumption in the system on chip(SOC).Dynamic power management(DPM)enables MPSOC to reduce power and energy consumption by adopting a suitable core configuration for task *** migration avoids peak temperature values in the multicore *** utilization factor(ui)on central processing unit(CPU)core consumes more energy and increases the temperature *** technique switches the core bymigrating such task to a core that has less temperature and is in a low power *** proposed EA-EDF scheduling technique migrates load on different cores to attain stability in temperature among multiple cores of the CPU and optimized the duration of the idle and sleep periods to enable the low-temperature *** effectiveness of the EA-EDF approach reduces the utilization and energy consumption compared to other existing methods and *** simulation results show the improvement in performance by optimizing 4.8%on u_(i) 9%,16%,23%and 25%at 520 MHz operating frequency as compared to other energy-aware techniques for MPSoCs when the least number of tasks is in running state and can

关键词： Dynamic power management dynamic voltage&frequency scaling dynamic thermal management multiprocessor system on chip complementary metal oxide semiconductor reliability

来源：评论

学校读者我要写书评

暂无评论

Logistic Regression with Elliptical Curve Cryptography to Establish Secure IoT

引用

computer Systems science & engineering 2023年第6期45卷 2635-2645页

作者： J.R.Arunkumar S.Velmurugan Balarengadurai Chinnaiah G.Charulatha M.Ramkumar Prabhu A.Prabhu Chakkaravarthy Department of Information Technology Sree Vidyanikethan Engineering College(Autonomous)TirupatiAndhra PradeshIndia Department of Electronics and Communication Engineering TJS Engineering CollegeKavaraipettaiChennaiTamil NaduIndia Department of Computer Science and Engineering Vidyavardhaka College of EngineeringMysuruKarnatakaIndia Department of Electronics and Communication Engineering Peri Institute of TechnologyChennaiTamil NaduIndia Department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical ScienceChennaiTamil NaduIndia

Nowadays,Wireless Sensor Network(WSN)is a modern technology with a wide range of applications and greatly attractive benefits,for example,self-governing,low expenditure on execution and data communication,long-term function,and unsupervised access to the *** Internet of Things(IoT)is an attractive,exciting *** applying communication technologies in sensors and supervising features,WSNs have initiated communication between the IoT *** IoT offers access to the highest amount of information collected through WSNs,it leads to privacy management ***,this paper provides a Logistic Regression machine learning with the Elliptical Curve Cryptography technique(LRECC)to establish a secure IoT structure for preventing,detecting,and mitigating *** approach uses the Elliptical Curve Cryptography(ECC)algorithm to generate and distribute security *** algorithm is a light weight key;thus,it minimizes the routing ***,the Logistic Regression machine learning technique selects the transmitter based on intelligent *** main application of this approach is smart *** approach provides continuing reliable routing paths with small *** addition,route nodes cooperate with IoT,and it handles the resources proficiently and minimizes the 29.95%delay.

关键词： Wireless sensor network internet of things security elliptical curve cryptography machine learning regression analysis

来源：评论

学校读者我要写书评

暂无评论

Fabrication Classifiation in Visual Tweets by Using Machine Learning with Deep Features

Fabrication Classifiation in Visual Tweets by Using Machine ...

引用

2024 IEEE International Students' Conference on Electrical, Electronics and computer science, SCEECS 2024

作者： Deshmukh, Vaishnavi J Ambhaikar, Asha Kalinga University Department of Computer Science & Engineering Chattisgarh Raipur India Kalinga University Faculty of Engineering Department of Computer Science and Engineering Chattisgarh Raipur India

ISBN: (纸本)9798350348460

In the context of online news outlets like Twitter, our work gives a summary of the situation as of rumor identification utilizing visual content. The majority of studies in the literature use visual content to illustrate several solutions to the issue. As opposed to combining them, we suggested an approach for Twitter rumours. The majority of our research work focuses on the use of supervised techniques, particularly deep learning models by utilising the deduced feature sets from the Twitter MediaEval dataset, which included 3000 images in total, a VGG-19 deep neural network was trained and evaluated. The VGG-19 achieves a highest sensitivity and an accuracy of using features taken from images during training and testing, which struggle to function in situations other than those in which they were trained. The simulation findings show that compared to other state-of-the-art architecture, the suggested design is more accurate and sensitive. © 2024 IEEE.

关键词： deep learning machine learning Twitter VGG-19

来源：评论

学校读者我要写书评

暂无评论

A Study on Existing EHR Models Used for Validating the Clinical Records 6th

A Study on Existing EHR Models Used for Validating the Clini...

引用

6th International Conference on Innovative Computing and communication, ICICC 2023

作者： Sharma, Priyanka Kumar, Tapas Tyagi, S.S. Department of Computer Science Engineering Faculty of Engineering MRIIRS Faridabad India Department of Computer Science Engineering Faculty of Engineering IIMT Greater Noida India

ISBN: (纸本)9789819933143

EHR was a statistical database of electronic health records for individuals or demographics that can be accessed through diverse healthcare environments. Planning for long-term retention and handling of electronic health information is an important factor in the planning process. The majority of commercial EHR models were designed to integrate data from vast ancillary facilities like radiology, pharmacy, and laboratory with different clinical care components. Electronic health records (EHRs) were digital representations of hospital records that were renovated in real time. An (electronic health record (EHR) was a comprehensive statement on a person's health. EHRs relief in the provision of evidence-based care, the tracing of a patient's treatment development, and the enabling of improved healthcare judgments. This paper aims to review the comparison of different EHR models that are being used throughout the world. The usage of various machine learning approaches in existing EHR has also been explored in this study. A thorough introduction of EHR is provided initially, followed by a focus on some related work that explains the adoption principles employed by various authors in EHR. In addition, discuss the different EHR models and the methodologies they have used and challenges in existing EHR models, their advantages, need, and then finally the challenges of EHR. This paper can be concluded in a way that to create an effective framework of potential data exchange agreements between health services and patients more public dialogue around electronic health records is needed. Quantitative research, such as polls of a wide variety of customers and doctors, may also be performed in order to obtain better outcomes. In next paper, we intend to propose framework of such EHR model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Patient treatment

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：