检索结果-内蒙古大学图书馆

11th IEEE Global Conference on Consumer Electronics, GCCE 2022

作者： Chen, Zhi-Sheng Pulungan, Reza Li, Yung-Hui Raswa, Farchan Hakim Harjoko, Agus Wang, Jia-Ching Kinarta, Indra Yusuf Lee, Chung-Ting Providence University Department of Computer Science and Information Engineering Taiwan Universitas Gadjah Mada Department of Computer Science and Electronics Indonesia AI Research Center Hon Hai Research Institute Taiwan National Central University Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9781665492324

Fingerprint recognition is commonly used to verify a user's identity. However, the fingerprint recognition systems in use today can be vulnerable to attacks. For example, some artificial fingerprints can spoof fingerprint recognition systems and use identity information to obtain personal information. For security reasons, fingerprint liveness detectors should be robust to attacks using various materials. As a result, we propose a fingerprint recognition method that uses multi-radius local binary pattern (Multi-radius LBP) and local phase quantization (LPQ) as local texture descriptors and wavelet transforms to remove noise. Classification results are obtained using a multi-layer perceptron (MLP) classifier. This study confirms that the proposed method is useful to improve the average fingerprint liveness detection tasks. On LivDet 2015 dataset, the proposed method achieves 6.73% Average Error Rate(AER). © 2022 IEEE.

关键词： Local binary pattern

来源：评论

学校读者我要写书评

暂无评论

Adversarial Neural network Classifiers for COVID-19 Diagnosis in Ultrasound Images

引用

computers, Materials & Continua 2022年第1期70卷 1683-1697页

作者： Mohamed Esmail Karar Marwa Ahmed Shouman Claire Chalopin Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering(FEE)Menoufia UniversityMenouf32952Egypt Department of Computer Engineering and Networks College of Computing and Information TechnologyShaqra UniversityShaqra11961Saudi Arabia Department of Computer Science and Engineering Faculty of Electronic Engineering(FEE)Menoufia UniversityMenouf32952Egypt Innovation Center for Computer Assisted Surgery(ICCAS) Universit鋞LeipzigLeipzig04103Germany

The novel Coronavirus disease 2019(COVID-19)pandemic has begun in China and is still affecting thousands of patient livesworldwide *** X-ray and Computed Tomography are the gold standardmedical imaging modalities for diagnosing potentially infected COVID-19 cases,applying Ultrasound(US)imaging technique to accomplish this crucial diagnosing task has attracted many physicians *** this article,we propose two modified deep learning classifiers to identify COVID-19 and pneumonia diseases in US images,based on generative adversarial neural networks(GANs).The proposed image classifiers are a semi-supervised GAN and a modifiedGANwith auxiliary *** one includes a modified discriminator to identify the class of the US image using semi-supervised learning technique,keeping its main function of defining the“realness”of tested *** tests have been successfully conducted on public dataset of US images acquired with a convex US *** study demonstrated the feasibility of using chest US images with two GAN classifiers as a new radiological tool for clinical check of COVID-19 *** results of our proposed GAN models showed that high accuracy values above 91.0%were obtained under different sizes of limited training data,outperforming other deep learning-based methods,such as transfer learning models in the recent ***,the clinical implementation of our computer-aided diagnosis of US-COVID-19 is the future work of this study.

关键词： COVID-19 medical imaging machine learning applications adversarial neural networks ultrasound

来源：评论

学校读者我要写书评

暂无评论

FIN: A Deep Multi-task Model for Face information Detection

FIN: A Deep Multi-task Model for Face Information Detection

引用

2023 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2023

作者： Lai, Yi-Shan Chen, Yi Fu, Li-Chen Hsiao, Pei-Yung Wang, Yu-Chieh National Taiwan University Department of Computer Science and Information Engineering Taiwan National University of Kaohsiung Department of Electrical Engineering Taiwan Automotive Research and Testing Center Taiwan Taiwan

ISBN: (纸本)9798350382204

In recent years, with the development of autonomous driving technology, designing a driver monitoring system that can run on vehicles has become increasingly important. The driving system analyzes various factors such as head pose, gaze direction, and eye state to determine the driver's attentiveness and aid the system in evaluating the driver's capability to control the vehicle. In this paper, we present a lightweight multi-task deep learning model that utilizes full-face images to detect head pose, gaze direction, and eye state simultaneously. We propose a task-based cross-dimensional attention module (TCAM) that selectively filters and enhances relevant features for each specific task. Additionally, to tackle the lack of diverse head pose angles in the eye state dataset, we introduce a data augmentation technique to generate eye state data under different head poses, enhancing the model's robustness in detecting eye states under varying head poses. We demonstrate the results of our work on the 300WLP, AFLW2000, BIWI, Gaze360, and MRL datasets. Extensive experiments show that our method can obtain competitive results with lower parameter costs. Furthermore, we establish a baseline for eye state detection using full-face images as the input on the CEW datasets. © 2023 IEEE.

关键词： Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

CPIMAC: MEC-assisted Message Dissemination Based on Traffic Prediction at Intersections 10

CPIMAC: MEC-assisted Message Dissemination Based on Traffic ...

引用

10th IEEE Smart World Congress, SWC 2024

作者： Liu, Bingyi Shao, Xun Zhao, Haoxiang Wang, Enshu Liu, Zhi Wuhan University of Technology Sanya Science and Education Innovation Park Sanya China Toyohashi University of Technology Department of Electrical and Electronic Information Engineering Aichi Japan Wuhan University School of Cyber Science and Engineering Wuhan China The University of Electro-Communications Department of Computer and Network Engineering Tokyo Japan

ISBN: (纸本)9798331520861

The Internet of Vehicles (IoV) is gaining increasing attention for its ability to improve traffic safety and efficiency by providing situational awareness and detecting potential hazards beyond the visual range. Time division multiple access (TDMA) based communication protocol effectively prevents transmission collisions in IoV. However, road intersections pose challenges for the implementation of TDMA-based MAC protocols, as vehicles converge from different directions, leading to severe communication access and merging collisions. To address this issue, we propose a distributed MAC protocol named slot collisions prediction based MAC at intersection (CPIMAC). Specifically, We combine mobile edge computing (MEC) with a CNN-BiLSTM-Attention neural network model to predict potential transmission collisions and propose corresponding collision avoidance algorithms. In addition, we design the head-tail beacon (HTB) algorithm to reduce slot collisions during vehicle waiting periods at intersections by adjusting beacon frequency. Finally, we conduct extensive experiments to evaluate the proposed protocol. The results show that transmission collisions can be reduced by 58.1 % compared to the existing protocols. © 2024 IEEE.

关键词： Time division multiple access

来源：评论

学校读者我要写书评

暂无评论

A Novel Krill Herd Based Random Forest Algorithm for Monitoring Patient Health

引用

computers, Materials & Continua 2023年第5期75卷 4553-4571页

作者： Md.Moddassir Alam Md Mottahir Alam Muhammad Moinuddin Mohammad Tauheed Ahmad Jabir Hakami Anis Ahmad Chaudhary Asif Irshad Khan Tauheed Khan Mohd Department of Health Information Management and Technology University of Hafr Al-BatinSaudi Arabia Department of Electrical and Computer Engineering Faculty of EngineeringKing AbdulazizJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems King Abdul Aziz UniversityJeddahSaudi Arabia College of Medicine King Khalid UniversityAbhaSaudi Arabia Department of Physics College of ScienceJazan UniversityP.O.Box.114Jazan45142Saudi Arabia Department of Biology College of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11623Saudi Arabia Computer Science Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Math and Computer Science Augustana CollegeIL61201United States

Artificial Intelligence(AI)is finding increasing application in healthcare *** learning systems are utilized for monitoring patient health through the use of IoT sensor,which keep track of the physiological state by way of various health ***,early detection of any disease or derangement can aid doctors in saving patients’***,there are some challenges associated with predicting health status using the common algorithms,such as time requirements,chances of errors,and improper *** propose an Artificial Krill Herd based on the Random Forest(AKHRF)technique for monitoring patients’health and eliciting an optimal prescription based on their health *** begin with,various patient datasets were collected and trained into the system using IoT *** a result,the framework developed includes four processes:preprocessing,feature extraction,classification,and result ***,preprocessing removes errors,noise,and missing values from the dataset,whereas feature extraction extracts the relevant ***,in the classification layer,we updated the fitness function of the krill herd to classify the patient’s health status and also generate a *** found that the results fromthe proposed framework are comparable to the results from other state-of-the-art techniques in terms of sensitivity,specificity,Area under the Curve(AUC),accuracy,precision,recall,and F-measure.

关键词： Healthcare system health monitoring clinical decision support internet of things artificial intelligence machine learning diagnosis

来源：评论

学校读者我要写书评

暂无评论

Interdisciplinary perspectives on privacy awareness in lifelogging technology development

引用

Journal of Ambient Intelligence and Humanized Computing 2023年第3期14卷 2291-2312页

作者： Wilkowska, Wiktoria Offermann, Julia Colonna, Liane Florez-Revuelta, Francisco Climent-Pérez, Pau Mihailidis, Alex Poli, Angelica Spinsante, Susanna Ziefle, Martina Human-Computer Interaction Center RWTH Aachen University Aachen Germany Swedish Law and Informatics Research Institute Stockholm University Stockholm Sweden Department of Computer Technology University of Alicante Alicante Spain Department of Occupational Science and Occupational Therapy University of Toronto Toronto Canada Department of Information Engineering Marche Polytechnic University Ancona Italy

Population aging resulting from demographic changes requires some challenging decisions and necessary steps to be taken by different stakeholders to manage current and future demand for assistance and support. The consequences of population aging can be mitigated to some extent by assisting technologies that can support the autonomous living of older individuals and persons in need of care in their private environments as long as possible. A variety of technical solutions are already available on the market, but privacy protection is a serious, often neglected, issue when using such (assisting) technology. Thus, privacy needs to be thoroughly taken under consideration in this context. In a three-year project PAAL (‘Privacy-Aware and Acceptable Lifelogging Services for Older and Frail People’), researchers from different disciplines, such as law, rehabilitation, human-computer interaction, and computer science, investigated the phenomenon of privacy when using assistive lifelogging technologies. In concrete terms, the concept of Privacy by Design was realized using two exemplary lifelogging applications in private and professional environments. A user-centered empirical approach was applied to the lifelogging technologies, investigating the perceptions and attitudes of (older) users with different health-related and biographical profiles. The knowledge gained through the interdisciplinary collaboration can improve the implementation and optimization of assistive applications. In this paper, partners of the PAAL project present insights gained from their cross-national, interdisciplinary work regarding privacy-aware and acceptable lifelogging technologies. © 2022, The Author(s).

关键词： Human computer interaction

来源：评论

学校读者我要写书评

暂无评论

A Global Best-guided Firefly Algorithm for engineering Problems

引用

Journal of Bionic engineering 2023年第5期20卷 2359-2388页

作者： Mohsen Zare Mojtaba Ghasemi Amir Zahedi Keyvan Golalipour Soleiman Kadkhoda Mohammadi Seyedali Mirjalili Laith Abualigah Department of Electrical Engineering Faculty of EngineeringJahrom UniversityJahrom***FrasIran Department of Electronics and Electrical Engineering Shiraz University of TechnologyShiraz***Iran Department of Electrical and Computer Engineering Tarbiat Modares UniversityTehran***Iran Department of Computer Engineering Sari BranchIslamic Azad UniversitySari***Iran Department of Electrical Engineering Urmia BranchIslamic Azad UniversityUrmia571696896Iran Centre for Artificial Intelligence Research and Optimisation Torrens University AustraliaBrisbaneQLD4006Australia Yonsei Frontier Lab Yonsei UniversitySeoul03722South Korea Computer Science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl Al-Bayt UniversityMafraq25113Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan Faculty of Information Technology Middle East UniversityAmman11831Jordan School of Computer Sciences Universiti Sains Malaysia11800George TownPulau PinangMalaysia University Research and Innovation Center Obuda University1034BudapestHungary School of Engineering and Technology Sunway University MalaysiaPetaling Jaya27500Malaysia Applied science research center Applied science private universityAmman11931Jordan

The Firefly Algorithm(FA)is a highly efficient population-based optimization technique developed by mimicking the flashing behavior of fireflies when *** article proposes a method based on Differential Evolution(DE)/current-to-best/1 for enhancing the FA's movement *** proposed modification increases the global search ability and the convergence rates while maintaining a balance between exploration and exploitation by deploying the global best ***,employing the best solution can lead to premature algorithm convergence,but this study handles this issue using a loop adjacent to the algorithm's main ***,the suggested algorithm’s sensitivity to the alpha parameter is reduced compared to the original *** GbFA surpasses both the original and five-version of enhanced FAs in finding the optimal solution to 30 CEC2014 real parameter benchmark problems with all selected alpha ***,the CEC 2017 benchmark functions and the eight engineering optimization challenges are also utilized to evaluate GbFA’s efficacy and robustness on real-world problems against several enhanced *** all cases,GbFA provides the optimal result compared to other *** that the source code of the GbFA algorithm is publicly available at https://***/projects/gbfa.

关键词： Firefly algorithm New movement vector Global best-guided firefly algorithm Global optimization engineering design

来源：评论

学校读者我要写书评

暂无评论

Applications of Machine Learning in Medicine: Current Trends and Prospects 6

Applications of Machine Learning in Medicine: Current Trends...

引用

6th Global Conference on Wireless and Optical Technologies, GCWOT 2023

作者： Aamir, Muhammad Bazai, Sibghatullah Bhatti, Uzair Aslam Dayo, Zaheer Ahmed Liu, Jing Zhang, Kun Huanggang Normal Univeristy College of Computer Science Huanggang China Balochistan University of Information Technology Engineering and Management Sciences Department of Computer Engineering Quetta Pakistan Hainan University School of Information and Communication Engineering Haikou China Zhejiang Lab Research Center for Healthcare Data Science Hangzhou China

ISBN: (纸本)9798350333718

With the continuous development of information technology and medical data information, more and more clinicians recognize artificial intelligence or will completely change medical practice by using advanced machine learning methods. The potential of using machine learning and predictive analysis to customize specific treatments for individuals is currently under research. Machine learning can learn a large number of medical data and explore the dependencies in data concentration, forming a corresponding medical model that can quickly and accurately predict new data, which is conducive to the early diagnosis of diseases and assisted clinical decisions. Clinical medicine faces the status quo of the relative shortage of medical resources and the identification and rapid diagnosis and treatment of critically ill emergency patients. In the era of big data, clinical demand is driven by clinical needs, and intelligent medical care provided by machines is the key to tackling the aforementioned issues. © 2023 IEEE.

关键词： Patient treatment

来源：评论

学校读者我要写书评

暂无评论

Active terahertz beam steering based on mechanical deformation of liquid crystal elastomer metasurface

引用

Light(science & Applications) 2023年第1期12卷 118-127页

作者： Xiaolin Zhuang Wei Zhang Kemeng Wang Yangfan Gu Youwen An Xueqian Zhang Jianqiang Gu Dan Luo Jiaguang Han Weili Zhang Center for Terahertz Waves and College of Precision Instrument and Optoelectronics Engineering Key Laboratory of Optoelectronic Information TechnologyMinistry of EducationTianjin University300072 TianjinChina Department of Electrical and Electronic Engineering Southern University of Science and Technology518055 ShenzhenChina School of Electrical and Computer Engineering Oklahoma State UniversityStillwaterOK 74078USA

Active metasurfaces are emerging as the core of next-generation optical devices with their tunable optical responses and flat-compact *** for the terahertz band,active metasurfaces have been developed as fascinating devices for optical chopping and compressive sensing ***,performance regulation by changing the dielectric parameters of the integrated functional materials exhibits severe limitations and parasitic ***,we introduce a C-shape-split-ring-based phase discontinuity metasurface with liquid crystal elastomer as the substrate for infrared modulation of terahertz ***-focused infrared light is applied to manipulate the deflection of the liquid crystal elastomer substrate,enabling controllable and broadband wavefront steering with a maximum output angle change of 22°at *** as another control method is also investigated and compared with infrared *** further demonstrate the performance of liquid crystal elastomer metasurface as a beam steerer,frequency modulator,and tunable beam splitter,which are highly desired in terahertz wireless communication and imaging *** proposed scheme demonstrates the promising prospects of mechanically deformable metasurfaces,thereby paving the path for the development of reconfigurable metasurfaces.

关键词： tunable modulator beam

来源：评论

学校读者我要写书评

暂无评论

Efficient survivable mapping algorithm for logical topology in IP-over-WDM optical networks against node failure

引用

Journal of Supercomputing 2023年第5期79卷 5037-5063页

作者： Cheng, Dun-Wei Chang, Jo-Yi Lin, Chen-Yen Lin, Limei Huang, Yanze Thulasiraman, Krishnaiyan Hsieh, Sun-Yuan Department of Computer Science and Information Engineering National Yunlin University of Science and Technology 123 University Road Yunlin64002 Taiwan Department of Computer Science and Information Engineering National Cheng Kung University No. 1 University Road Tainan701 Taiwan College of Mathematics and Informatics and the Key Laboratory of Network Security and Cryptology Fujian Normal University Fujian Fuzhou350117 China Fujian Provincial Key Laboratory of Big Data Mining and Applications School of Mathematics and Physics Fujian University of Technology Fujian Fuzhou350118 China Department of Computer Science University of Oklahoma 660 Parrington Oval NormanOK73019 United States Department of Computer Science and Information Engineering National Chi Nan University No. 1 Daxue Rd Nantou County Puli Township54561 Taiwan

The survivable mapping problem in an IP-over-WDM network with a logical graph and physical graph is the problem of finding a mapping of a logical network in a physical layer so that any failure in physical topology does not break the logical topology’s connection. Determining whether a survivable mapping against failure exists is an NP-complete problem, and therefore many heuristic algorithms have been proposed in the literature. In this paper, a heuristic mapping design strategy is proposed to enable the lightpaths to more efficiently endure a node failure. We individually consider the logical topology by building a Hamiltonian cycle and then deal with the mapping problem for disjoint physical paths. Experimental results demonstrate that the proposed algorithm can provide efficient survivable mapping in IP-over-WDM networks. The simulation shows that the survivability of previous methods (SNF and SMART-Node) is around 60–80%, but our proposed algorithm can build survivable mapping in all kinds of situations. © 2022, The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature.

关键词： Heuristic algorithms

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：