检索结果-内蒙古大学图书馆

2025 International Conference on Electronics, Information, and Communication, ICEIC 2025

作者： Khan, Rehan Saeed, Umer Koo, Insoo University of Ulsan Department of Electrical Electronic and Computer Engineering Ulsan Korea Republic of School of Computer Science and Technology University of Bedfordshire Luton United Kingdom

ISBN: (纸本)9798331510756

Sensor-generated data is vital to the operation of numerous systems and services in the rapidly growing field of the Internet of Things. Wireless Sensor Networks, as an essential setup for these systems, are frequently deployed in large, diverse, and often harsh environments. However, these networks are highly vulnerable to various faults, potentially leading to improper data transmission, reliability, and financial stability of the systems. To address these challenges, we propose a hybrid model for sensor fault detection that integrates a machine learning classifier with the deep learning (DL) model, specifically VGG-16 and ResNet-50. Synthetic samples are generated using a Conditional Generative Adversarial Network and common sensor faults, such as hardover, drift, spike, erratic, and stuck fault are introduced by leveraging a publicly available temperature sensor dataset. Time-series data is transformed into Gramian Angular Field images, from which deep features are extracted using VGG-16 and ResNet-50. These extracted features are then fused to form a hybrid feature pool. Our framework effectively addresses problems related to data imbalance and enhances accuracy. The proposed model outperforms the individual feature sets, VGG-16 (89.22%) and ResNet-50 (84.21%), achieving notable accuracy of 92.55% with the fused feature set, underscoring its potential for robust sensor fault detection. © 2025 IEEE.

关键词： Gallium nitride

来源：评论

学校读者我要写书评

暂无评论

Prediction of Heart Disease Using ML Algorithms 1

Prediction of Heart Disease Using ML Algorithms

引用

1st International Conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Panda, Ashok Kumar Pati, Chinmayee Pradhan, Sonali Pradhan, Amrutanshu Rath, Naba Kumar Silicon University Department Of Computer Science & Engineering Bhubaneswar India School of Computer Sciences Odisha University of Technology and Research Bhubaneswar India Bhubaneswar India

ISBN: (纸本)9798331518578

There are a variety of approaches utilised in the processing of healthcare data. Data mining is utilised quite frequently. The majority of deaths are caused by cardiovascular disorders. It is a risk factor for heart disease. The proportions of risk factors for heart disease can be computed using this technique. Data sources can be categorised based on healthcare factors. Using a data mining classification approach, this system does analysis on such parameters. The datasets are analysed using the Decision Tree Algorithm and the Naive Bayes Algorithm, both of which are written in Python. The Decision Tree Algorithm has the highest precision for heart disease. © 2025 IEEE.

关键词： classification techniques Data mining Heart disease Machine Learning methods

来源：评论

学校读者我要写书评

暂无评论

Multifrequency Resonant Compensated Wireless Power Transfer SRM Drive System

引用

IEEE Transactions on Power Electronics 2025年第7期40卷 9709-9722页

作者： Cai, Jun Li, Bin Chen, Yangyang Song, Shoujun Zhang, Xin Nanjing University of Information Science and Technology C-MEIC CICAEET School of Automation Nanjing210044 China Anhui Jianzhu University School of Mechanical and Electrical Engineering Hefei230009 China Northwestern Polytechnical University College of Automation Xi'an710072 China Zhejiang University College of Electrical Engineering Hangzhou310027 China

In this article, a multifrequency resonant compensated wireless power transfer (WPT) switched reluctance motor (SRM) with zero voltage switching (ZVS) capability is proposed. The system utilizes dual decoupled resonant tanks on the transmitting side and hybrid compensation on the receiving side to achieve multifrequency resonant WPT. In addition, the operating frequencies of the primary inverter are regulated to drive the corresponding SRM phases. The implementation of this method mainly consists of the following steps: First, the number and value of resonant frequencies were optimized to construct multiple power channels, thereby avoiding unexpected energy transfer between the main resonant circuits and overcurrent of the transmitter, and reducing cross-interference between channels. Then, the transmitting coils are overlapped to avoid internal magnetic connections, while the position of the receiving coils is adjusted to realize asymmetric coupling, thereby achieving current equalization in the SRM windings. Moreover, the optimized design of multifrequency resonant compensation networks is developed to reduce the system sensitivity to inductance mismatching and achieve the ZVS of the inverter with the minimized input impedance angle. After that, alternating excitation of single or dual phases can be achieved via a hybrid resonant excitation strategy. Finally, experiments were implemented in a 6/4 SRM-based test-bed, which verified the feasibility of the proposed system. © 1986-2012 IEEE.

关键词： Inductive power transmission

来源：评论

学校读者我要写书评

暂无评论

A Review of Spectrum Sharing in 6G for IoT Environment 2

A Review of Spectrum Sharing in 6G for IoT Environment

引用

2nd International Conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2024

作者： Khan, Andleeb Nand, Parma Bhushan, Bharat Alazzawi, Esraa Mohammed Jamil, Akhtar Sharda School of Engineering & Technology Department of Computer Science & Engineering UP Greater Noida India University of Baghdad Al-Jadriya Department of Computer Engineering Baghdad10071 Iraq National University of Computer and Emerging Sciences Department of Computer Science Islamabad Pakistan

ISBN: (纸本)9798331529529

With increase in demand the resources have proven to be limited. Spectrum sharing is a way to use the limited resources to their full potential. These can exceptionally improve the way IoT devices work. The ever-increasing demand in communication can be revolutionized by 6G network as it proves to be superior in terms of latency, reliability, data rates, connectivity and coverage. Hence the concept of spectrum sharing in 6G holds a great prospect for the future. This paper reviews the recent advances in the field of spectrum sharing for 6G in the IoT environment. It lays down the important techniques and the security and privacy concerns in IoT environments. It further lays down the important future prospects in terms of mm Wave, THz and optical spectrum and their most important use cases. © 2024 IEEE.

关键词： Terahertz waves

来源：评论

学校读者我要写书评

暂无评论

Securing IoT Systems with AI-Infused Software and Virtual Replica Models 2

Securing IoT Systems with AI-Infused Software and Virtual Re...

引用

2nd IEEE International Conference on Integrated Intelligence and Communication Systems, ICIICS 2024

作者： Supriya, K. Sangeetha Jeno Lovesum, S.P. Arora, Renuka Bhatia, Rishu Yadwad, Sunita Natrayan, L. Department of Computer Science & Engineering Christ University Bengaluru India Department of Computer Science & Engineering Jagannath University NCR Bahadurgarh India Department of Electronics and Communication Engineering Ganga Institute of Technology and Management Jhajjar India Department of Computer Science and Engineering Faculty of Engineering and Technology Parul institute of Engineering and Technology Parul University Vadodara India Department of Mechanical Engineering Saveetha School of Engineering SIMATS Chennai India

ISBN: (纸本)9798331504960

The proliferation of Internet of Things (IoT) devices has introduced significant security challenges due to the increased attack surface and the inherent vulnerabilities of interconnected systems. This paper proposes a novel security framework that integrates Artificial Intelligence (AI)-infused software and Virtual Replica Models, or Digital Twins, to enhance the robustness of IoT systems. The framework leverages AI-driven anomaly detection and predictive analysis to identify potential threats in real-time, while Digital Twins provide a virtual replica of the IoT ecosystem for continuous monitoring and simulation-based threat assessment. By fusing these technologies, the proposed solution enables proactive security measures, ensuring rapid response to cyberattacks and continuous system optimization. Extensive simulations and experimental results demonstrate the system’s ability to reduce attack detection times by 30%, while improving overall system resilience and minimizing false positive rates. This approach provides a scalable and adaptable solution for securing IoT infrastructures in various industries. © 2024 IEEE.

关键词： Risk assessment

来源：评论

学校读者我要写书评

暂无评论

Runtime Verification of Neural-Symbolic Systems 10th

Runtime Verification of Neural-Symbolic Systems

引用

10th International Symposium on Dependable Software engineering: Theories, Tools and Applications, SETTA 2024

作者： Deng, Shaojun Liu, Wanwei Zhang, Miaomiao College of Computer Science and Technology National University of Defense Technology Changsha China School of Software Engineering Tongji Uniersity Shanghai China

ISBN: (纸本)9789819606016

Neural-symbolic systems (NSSs), which are typically cyber-physical systems integrated with artificial intelligence modules, have received much attention in both academic and industrial fields. However, thorough verification (such as model checking) of such systems in general leads to prohibitively high costs due to the scale of the state space, and this makes it barely accomplishable within desired time-span. Consequently, light-weight verification techniques are introduced to deal with such cases, e.g., runtime verification (RV, for short). In this paper, we investigate an RV framework for NSSs against signal temporal logic (STL) properties. To guarantee that the on-line monitoring could be accomplished in time, we utilize Euler-prediction to sample the system under scrutiny at discrete time-steps. Our framework supports both qualitative and quantitative on-line monitoring of STL specifications, and thus it terminates whenever a property is satisfied and/or violated by a finite prefix of the trajectory, and it can also provide the bounds of the quantitative satisfaction/violation w.r.t. the remaining execution. Notably, for the so-called piece-wise linear NSSs against affine STL formulas, our approach is exact. On top of it, a prototype tool is implemented, and is experimentally evaluated. The results demonstrate the feasibility of the presented runtime verification approach. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Model checking

来源：评论

学校读者我要写书评

暂无评论

Role of Blockchain in Tele-Health and Tele-Medicine 9

Role of Blockchain in Tele-Health and Tele-Medicine

引用

9th IEEE International Conference for Convergence in technology, I2CT 2024

作者： Kushwaha, Ankit Chauhan, Rahul Rawat, Ruchira Aluvala, Srinivas Singh, Rahul Graphic Era Hill University Computer Science And Engineering Uttarakhand Dehradun India Graphic Era Deemed To Be University Computer Science And Engineering Uttarakhand Dehradun India Sr University School of Computer Science & Artificial Intelligence Warangal India Chitkara University Institute of Engineering And Technology Chitkara University Punjab India

ISBN: (纸本)9798350394474

Systems for telehealth and telemedicine provide medical care remotely in an effort to impede the COVID-19 pandemic. Additionally, they can aid in the management of the limited healthcare resources needed to alleviate the heavy load that COVID-19 patients experience in hospitals. By offering a safe, open, and decentralized platform for exchanging and preserving private patient data, blockchain technology in telemedicine and telehealth aims to alter the way healthcare services are *** patient outcomes is one of the blockchains in telemedicine's other goals. Healthcare providers can access accurate and current information about their patients, enabling them to make educated decisions about their care, by offering a transparent and secure platform for storing patient data. Patients may experience better health outcomes as a result, and there may be fewer medical errors and higher standards of care overall. By enabling smart contracts and decentralized apps, blockchain technology can potentially streamline hospital processes. Smart contracts automate the payment process, lowering administrative expenses and increasing payment efficiency. Smart contracts are self-executing contracts. Remote consultations can be facilitated through decentralized applications, allowing patients to obtain care from any location in the world. To sum up, the purpose of blockchain in telemedicine and telehealth is to offer a safe, open, and decentralized platform for storing and exchanging private patient data. Healthcare providers can increase data privacy, lower fraud, improve patient outcomes, and streamline administrative processes by utilizing blockchain technology. © 2024 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

DESIGN OF RF FEEDING NETWORK [1:8] USING UNEQUAL AMPLITUDE HYBRID COUPLER FOR LOW SLL X-BAND RADAR APPLICATIONS

引用

Telecommunications and Radio engineering (English translation of Elektrosvyaz and Radiotekhnika) 2025年第5期84卷 1-19页

作者： Kothapudi, Venkata Kishore Sunayana, Lella Divya, Shaik Kumar, Vijay Pappula, Lakshman Gottapu, Srinivasa Kiran Guntur District Andhra Pradesh Vadlamudi522213 India Department of Communication Engineering School of Electronics Engineering Vellore Institute of Technology Tamil Nadu Vellore632014 India Department of Electrical Electronics and Communication Engineering GITAM School of Technology GITAM University Andhra Pradesh Visakhapatnam530045 India School of Science and Engineering Engineering and Computer Science Department Benedict College 1600 Harden St. ColumbiaSC29204 United States

The design simulation and manufacturing of an x-band frequency uneven amplitude 90° hybrid coupler are described in this paper. This hybrid coupler is used to create a feeder network with eight output ports operating at 9.3 GHz. The overall goal is to design and analyze an uneven power feeding network (1:8) for low SLL x-band radar applications employing a hybrid coupler. The specific goal is to create a hybrid coupler with equal amplitude, a hybrid coupler with uneven amplitude [Taylor’s amplitude = –17 dB], and a feeding network using hybrid couplers. The goal of this research is to improve the ability of a single transmitter to provide power to more than one antenna, all at a time either equally or unequally, and this can be achieved by designing a desired number of hybrid couplers and connecting them to the specific number of antennas at the output end and to the single transmitter at the input end. © 2025 by Begell House, Inc.

关键词： Transmitters

来源：评论

学校读者我要写书评

暂无评论

Exploring Deep Learning Models for Cinnamon Plant Disease Characterization: Discriminating Rough Bark from Stripe Canker

Exploring Deep Learning Models for Cinnamon Plant Disease Ch...

引用

2024 Asia Pacific Conference on Innovation in technology, APCIT 2024

作者： Shandilya, Gunjan Anand, Vatsala Chauhan, Rahul Pokhariya, Hemant Singh Gupta, Sheifali Sunil, G. Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Graphic Era Hill University Computer Science and Engineering Uttarakhand Dehradun India Graphic Era Deemed to Be University Computer Science and Engineering Uttarakhand Dehradun India SR University School of Computer Science & Artificial Intelligence Warangal India

ISBN: (纸本)9798350361537

The world market for spices is dominated by the important spice crop, cinnamon. Achieving excellent yields and production standards in the cultivation of cinnamon depends on the accurate classification of diseases affecting the plant, such as rough bark and stripe canker. To minimize yield loss and maintain healthy yields of crops, early recognition of plant disease is crucial for prompt action. Deep learning approaches for automated classification make it easier to identify sick plants quickly and take appropriate action. Convolutional Neural Networks (CNNs), one of the deep learning techniques, have greatly improved automated diagnosis of plant diseases. In this work, a CNN-based method has been utilized to classify two common diseases in cinnamon plants: rough bark and stripe canker. This study uses a carefully selected dataset of 1600 high-resolution photos of impacted cinnamon plants. After a great deal of testing and optimization, the suggested CNN architecture performs admirably, with an astounding accuracy of 94.99% and a negligible loss of 0.93 with precision and recall of approx 96.5%. Enhancing agricultural productivity, early disease diagnosis, affordable treatments, agricultural precision, global food security, research and development are all areas where this sort of classification is important. In addition to addressing current issues in agriculture, this study advances more general goals like sustainability, food safety, and agricultural technology innovation. © 2024 IEEE.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

A Vision-Based Method for UAV Autonomous Landing Area Detection 6th

A Vision-Based Method for UAV Autonomous Landing Area Detect...

引用

6th IFIP TC 12 International Conference on Intelligence science, ICIS 2024

作者： Zhang, Qiutong Xia, Qingyuan Wei, Lisheng Deng, Bohai School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China National Key Laboratory of Rotorcraft Aeromechanics Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9783031712524

Automatic identification of the landing area is crucial for UAV (Unmanned Aerial Vehicles) to land correctly and safely. Using passive vision sensors to achieve this objective is a very promising avenue due to their low cost and the potential they provide for performing simultaneous terrain analysis. In this paper, a computer vision method is proposed using an improved U-Net based architecture on UAV imagery to assess the safe landing area. Contrary to past methods, which little attention has been paid to the whole landing process with multiple descending altitude, experiment involves evaluating the landing area by analyzing visual images obtained from different descending heights. In the initial stage of landing, separation was made between water and land, guiding the flight to the land. As descending, classification was applied on images captured near ground into safe/unsafe landing areas and then mapped to the safety score for selection. Experiments on public datasets have shown promising results. © IFIP International Federation for Information Processing 2025.

关键词： Unmanned aerial vehicles (UAV)

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：