检索结果-内蒙古大学图书馆

Evasive attacks against autoencoder-based cyberattack detection systems in power systems

Energy and AI 2024年第3期17卷 126-135页

作者： Yew Meng Khaw Amir Abiri Jahromi Mohammadreza F.M.Arani Deepa Kundur Department of Electrical and Computer Engineering University of TorontoTorontoON M5S 3G4Canada School of Electronic and Electrical Engineering University of LeedsLeedsLS29JTUnited Kingdom Department of Electrical Computer&Biomedical EngineeringToronto Metropolitan University(formerly Ryerson University)TorontoON M5B 2K3Canada

The digital transformation process of power systems towards smart grids is resulting in improved reliability, efficiency and situational awareness at the expense of increased cybersecurity vulnerabilities. Given the availability of large volumes of smart grid data, machine learning-based methods are considered an effective way to improve cybersecurity posture. Despite the unquestionable merits of machine learning approaches for cybersecurity enhancement, they represent a component of the cyberattack surface that is vulnerable, in particular, to adversarial attacks. In this paper, we examine the robustness of autoencoder-based cyberattack detection systems in smart grids to adversarial attacks. A novel iterative-based method is first proposed to craft adversarial attack samples. Then, it is demonstrated that an attacker with white-box access to the autoencoder-based cyberattack detection systems can successfully craft evasive samples using the proposed method. The results indicate that naive initial adversarial seeds cannot be employed to craft successful adversarial attacks shedding insight on the complexity of designing adversarial attacks against autoencoder-based cyberattack detection systems in smart grids.

关键词： Cybersecurity Adversarial attacks Anomaly detection Iterative-based methods Substati on automati on

来源：评论

学校读者我要写书评

暂无评论

Enhanced healing of critical-sized bone defects using degradable scaffolds with tailored composition through immunomodulation and angiogenesis

引用

Bioactive Materials 2025年第2期44卷 371-388页

作者： Juncen Zhou Negar Akrami Hanbo Wang Liang Fang Jie Shen Cunjiang Yu Ben Zhang Donghui Zhu Department of Biomedical Engineering University of Stony Brook100 Nicolls RdStony BrookNY11794USA Department of Orthopaedic Surgery Washington UniversitySt.LouisMO63110USA Department of Electrical&Computer Engineering University of Illinois Urbana-ChampaignUrbanaIL61801USA

The impact of orthopedic scaffolds on bone defect healing,particularly the late-stage bone remodeling process,is pivotal for the therapeutic *** study applies fadditively manufactured scaffolds composed of hydroxyapatite-doped poly(lactide-co-glycolide)-b-poly(ethylene glycol)-b-poly(lactide-co-glycolide)(HAPELGA)with varying properties to treat rat calvarial defects,elucidating their significant role in bone remodeling by modulating physiological *** engineered two scaffolds with different polylactic acid(PLA)to polyglycolic acid(PGA)ratio(9/1 and 18/1)to vary in hydrophobicity,degradation rate,mechanical properties,and structural *** variations influenced physiological responses,including osteogenesis,angiogen-esis,and immune reactions,thereby guiding bone *** findings show that the HA-PELGA(18/1)scaffold,with a slower degradation rate,supported bulk bone formation due to a stable ***,the HA-PELGA(9/1)scaffold,with a faster degradation rate and more active interfaces,facilitated the formation of a thin bone layer and higher bone *** study demonstrates these degradable scaffolds help to promote bone healing and reveals how scaffold properties influence the bone remodeling process,offering a potential strategy to optimize scaffold design aiming at late-stage bone defect healing.

关键词： Additive manufacturing Polymer scaffolds Biodegradable Bone defect healing Bone remodeling

来源：评论

学校读者我要写书评

暂无评论

Compact Model Build Upon Dynamic Weighting Artificial Neural Network Approach for Complementary Field Effect Transistors

引用

IEEE Transactions on Electron Devices 2024年第1期71卷 246-253页

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation The Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program The Institute of Communications Engineering the Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan

In this work, a dynamic weighting-artificial neural network (DW-ANN) methodology is presented for quick and automated compact model (CM) generation. It takes advantage of both TCAD simulations for high accuracy and SPICE simulations for cost-effectiveness. This methodology is developed for gate-all-around (GAA) silicon (Si) nanosheet (NS) complementary field effect transistor (CFET), a potential candidate for future CMOS technology due to its innate properties. The critical process variation (PV) sources that severely degrade the CFET performance are estimated using DW-ANN. It reduces the computation cost and predicts the effects of PV sources with less than 1% error. Furthermore, a compact DW-ANN-based Verilog-A model has been developed that captures the dc as well as transient behavior accurately for circuit-level analysis. CFET-based circuits such as inverter, 6T-static random access memory (SRAM), and ring oscillator (RO) are characterized and implemented using DW-ANN-based CM. The overall average error of the model is reported as less than 2%. Therefore, the proposed device and circuit modeling approach provides a feasible solution for the rapid compact modeling of new emerging devices with good convergence and high accuracy. © 1963-2012 IEEE.

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

Intelligent ADHD Detection Using Explainable Multimodal Fusion Model 4

Intelligent ADHD Detection Using Explainable Multimodal Fusi...

引用

4th IEEE International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2024

作者： Tsai, Ho-Jung Wu, Hsiao-Kuang Chen, Chun-Chuan Yeh, Chen-Hsin Chu, Tzu-Yueh Yeh, Shih-Ching National Central University Department of Computer Science and Information Engineering Taiwan National Central University Department of Biomedical Sciences and Engineering Taiwan Hunan University College of Computer Science and Electrical Engineering China

ISBN: (纸本)9798350363586

Deep learning has been proved to diagnose Attention Deficit/Hyperactivity Disorder (ADHD) accurately, but it has raised concerns about trustworthiness because of the lack of explainability. Fortunately, the development of explainable artificial intelligence (XAI) offers a solution to this problem. In this study, we employed a VR-based GO/NOGO task with distractions, capturing participants' eye movement, head movement, and electroencephalography (EEG) data. We used the collected data to train an explainable multimodal fusion model. Besides classifying between ADHD and normal children, the proposed model also generates explanation heatmaps. The heatmaps provide the importance of specific variables and timestamps in the EEG data to help us analyze the patterns captured by the model. According to our observations, the model identified specific time intervals that related to specific event-related potentials (ERPs) components. The heatmaps also demonstrate that the impacts of distractions vary between not only the GO and NOGO events but also ADHD and normal children. © 2024 IEEE.

关键词： Eye movements

来源：评论

学校读者我要写书评

暂无评论

Role of Deep Learning Models in Intelligent Classification of Various Date Fruit Bunches 17

Role of Deep Learning Models in Intelligent Classification o...

引用

17th International Conference on Developments in eSystems engineering, DeSE 2024

作者： Abuowda, Zainab Salam, Nour Ramadan, Shorouk Hassan, Taimur Ghazal, Mohammed Almajali, Eqab Hussain, Abir Jafar Yousaf, Jawad Electrical Computer and Biomedical Engineering Department Abu Dhabi University Abu Dhabi United Arab Emirates Department of Electrical Engineering University of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9798350368697

This study presents a performance comparison of different deep machine learning models for the intelligent segregation of date fruit bunches of numerous varieties. The shape, size, and color of the various types of dates with different maturity conditions require experienced farmers to estimate the accrual class. This study has used a transfer learning approach on various machine learning models (VGG-19, MobileNetV2, DenseNet, and NASNet) to classify five different kinds of date bunches (Barhi, Khalas, Menifi, Nabout saif, and Sullaj). Each model is trained on a dataset of 11,944 images of five different date classes. The comparison deduces that DenseNet produces the best accuracy, precision, and recall when compared with the performance of other models. The maximum achieved accuracy of the trained DenseNet model is 100% for the validation dataset and 98.4% for the test dataset. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Enhancing Wildlife Protection: Poacher Detection Using Machine Learning Models 17

Enhancing Wildlife Protection: Poacher Detection Using Machi...

引用

17th International Conference on Developments in eSystems engineering, DeSE 2024

作者： Gad, Omar Mohamed Elbatanouny, Hagar Almajali, Eqab Yousaf, Jawad Hussain, Abir Department of Electrical Engineering University of Sharjah Sharjah United Arab Emirates Electrical Computer and Biomedical Engineering Department Abu Dhabi University Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350368697

Wildlife conservation is a pressing global concern, with illegal poaching posing a severe threat to many endangered species. In recent years, advanced technologies like machine learning and digital signal processing have shown significant potential in supporting conservation efforts by detecting and preventing illegal poaching. This work explores the integration of these technologies into wildlife conservation strategies, focusing on their role in identifying and combating poachers. Two datasets are utilized:"Poacher Detection 3 Classes" and"Illegal Poacher Detection". Several machine learning models including Support Vector Machines (SVM), Random Forest (RF), Decision Trees (DT), and Convolutional Neural Networks (CNN) are applied to detect illegal activities in these datasets. For the first dataset, the SVM model achieved the best accuracy of 93%, while the CNN model performed best on the second dataset, achieving accuracy of 75%. In the final phase, both datasets were combined, and augmented images were introduced to increase data diversity. On the combined dataset, the Random Forest model achieved the highest accuracy of 83%. These results demonstrate the effectiveness of machine learning in improving wildlife conservation efforts. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Hand-Powered Point-of-Care: Centrifugal Microfluidic Platform for Urine Routine Examination (μCUREX)

引用

Langmuir 2023年第5期39卷 1897-1904页

作者： Kuo, Shao-Hsuan Peraro, Alberto Lin, Hsiu-Pen Chang, Chun-Hao Li, Bor-Ran Institute of Biomedical Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu300 Taiwan Department of Biomedical Engineering University of Padua Padova35122 Italy Center for Emergent Functional Matter Science National Yang Ming Chiao Tung University Hsinchu300 Taiwan Department of Electrical and Computer Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu300 Taiwan

Urinalysis is one of the simplest and most common medical tests in modern cities. With the assistance of professional technicians and equipment, people in metropolitan areas can effortlessly acquire information about their physiological conditions from traditional clinical laboratories. However, the threshold, including precise benchtop equipment and well-trained personnel, still remains a considerable dilemma for residents in healthcare-poor areas. Hence, it is a crucial and urgent topic to develop a smart and affordable widget to address this challenge. To improve the healthcare rights of residents, we proposed a disposable centrifugal microfluidic urine routine examination platform (named μCUREX) actuated with a modified hand-powered fan. Two parts of urinalysis (sediment test and chemical strip test) were integrated into the μCUREX disc. The influence on sedimentation by variant hand-powered manipulation was simulated using COMSOL. As a result, more than 70% of the sediment can be collected. Moreover, the color change of chemical strip papers (indicators for glucose, pH, protein, and occult blood) was recorded with a 3D-printed studio and analyzed after reaction with chemical-spiked and pH-adjusted artificial and human urine specimens. The whole process can be completed within 10 min, with only 200 μL of urine needed. In conclusion, we successfully constructed an ultra-low-cost point-of-care platform for urinalysis in extremely resource-poor settings. The handy size, high affordability, and user-friendliness of the μCUREX disc provide strong potential and feasibility in solving problems in resource-poor settings. Furthermore, we highly expect the μCUREX platform to improve the level of healthcare in resource-limited areas. © 2023 American Chemical Society.

关键词： Microfluidics

来源：评论

学校读者我要写书评

暂无评论

Microwave Sensors: Novel Techniques, Topologies, and Manufacturing Technologies 16

Microwave Sensors: Novel Techniques, Topologies, and Manufac...

引用

16th International Conference on Advanced Technologies, Systems and Services in Telecommunications, TELSIKS 2023

作者： Delmonte, Nicolo Silvestri, Lorenzo Masoumabad, Mehdi Alipour Perregrini, Luca Bozzi, Maurizio University of Pavia Department of Electrical Computer and Biomedical Engineering Pavia27100 Italy

ISBN: (纸本)9798350347029

This paper presents an overview of the recent advances we made in the field of microwave sensors. Sensors for different physical quantities are presented, ranging from structures for the retrieval of the electric and magnetic characteristics of materials, to devices for the determination of position and angular rotation. These sensors are based on various fabrication technologies, including planar structures, additive manufacturing, and hybrid solutions, which take advantage of the best features of different technologies. © 2023 IEEE.

关键词： 3D printing

来源：评论

学校读者我要写书评

暂无评论

A soft,high-density neuroelectronic array

引用

npj Flexible Electronics 2023年第1期7卷 131-138页

作者： Kyung Jin Seo Mackenna Hill Jaehyeon Ryu Chia-Han Chiang Iakov Rachinskiy Yi Qiang Dongyeol Jang Michael Trumpis Charles Wang Jonathan Viventi Hui Fang Thayer School of Engineering Dartmouth CollegeHanoverNH 03755USA Department of Biomedical Engineering Duke UniversityDurhamNC 27708USA Department of Electrical and Computer Engineering Northeastern UniversityBostonMA 02115USA

Techniques to study brain activities have evolved dramatically,yet tremendous challenges remain in acquiring high-throughput electrophysiological recordings minimally ***,we develop an integrated neuroelectronic array that is filamentary,highdensity and ***,with a design of single-transistor multiplexing and current sensing,the total 256 neuroelectrodes achieve only a 2.3×0.3mm^(2)area,unprecedentedly on a flexible substrate.A single-transistor multiplexing acquisition circuit further reduces noise from the electrodes,decreases the footprint of each pixel,and potentially increases the device’s *** filamentary neuroelectronic array also integrates with a rollable contact pad design,allowing the device to be injected through a syringe,enabling potential minimally invasive array *** acute auditory experiments in rats validate the ability of the array to record neural signals with high tone decoding ***,these results establish soft,high-density neuroelectronic arrays as promising devices for neuroscience research and clinical applications.

关键词： electronic high Together

来源：评论

学校读者我要写书评

暂无评论

Granger Causality Pattern Learning Equipped with Noise Invalidation Soft Thresholding 31

Granger Causality Pattern Learning Equipped with Noise Inval...

引用

31st European Signal Processing Conference, EUSIPCO 2023

作者： Bayati, Khashayar Umapathy, Karthikeyan Beheshti, Soosan Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University Toronto Canada

ISBN: (纸本)9789464593600

This paper concentrates on pattern learning of Granger causality. In this context, the entities of the Granger causality matrix estimation derived from the state-space model indicate directional dependencies of the observations. Existing methods propose different forms of thresholding to eliminate insignificant entities from this matrix. These approaches do not exploit the difference in statistical characteristics of insignificant entities compared to the Granger causality itself. In this work, Noise Invalidation Soft Thresholding is chosen as the thresholding method to discard null relations in the Granger causality matrix pattern learning. Unlike existing approaches, the proposed method benefits from the statistical properties of insignificant entities. The simulation results demonstrate the advantages and superiority of the proposed method in the sense of accuracy and robustness for both randomly generated datasets with causal footprints as well as simulated electroencephalogram datasets. © 2023 European Signal Processing Conference, EUSIPCO. All rights reserved.

关键词： Statistical tests

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：