检索结果-内蒙古大学图书馆

11th International Symposium on Telecommunication, IST 2024

作者： Safari, Rahebeh Mojtahedi Rahmani, Amir Masoud Alizaeh, Sasan H. Islamic Azad University Lahijan Branch Department of Computer Engineering Lahijan Iran National Yunlin University of Science and Technology Future Technology Research Center 123 University Road Section3 Douliou Yunlin64002 Taiwan Faculty of Information Technology Tehran Iran

ISBN: (纸本)9798350356250

Nowadays, retweeting behavior is considered a substantial behavior to analyze information diffusion in the microblogging network. To understand the underlying mechanism of information diffusion and analyze the evolution of the diffusion corresponding to a given original microblog, user retweeting behavior prediction has recently gained considerable attention. In this paper firstly, we introduce the most influential factors which affect user retweeting behavior and propose an effective measurement based on the random walk model to measure the social influence. Secondly, by incorporating our defined influential factors into a logistic regression classifier model, we predict the future activated user set concerning the diffusion of a given original microblog at the next time point. Unlike other comparative models, our prediction model can illustrate the evolution of diffusion and predict the retweeting behavior of all potential users through the diffusion of any original microblog in the microblogging network. Finally, based on the real Twitter microblogging dataset, the experimental results show by the contribution of our defined influential factors and presenting an effective measure of the social influence factor, we can obtain more accurate predictions in comparison to other baseline methods. © 2024 IEEE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

ViWise: Fusing Visual and Wireless Sensing Data for Trajectory Relationship Recognition

引用

ACM Transactions on Internet of Things 2023年第4期4卷 1-29页

作者： Wu, Fang-Jing Lai, Sheng-Wun Sou, Sok-Ian TU Dortmund University Otto-Hahn-Str. 6 Dortmund44227 Germany Department of Computer Science and Information Engineering National Taiwan University No. 1 Section 4 Roosevelt Rd Da’an District Taipei10617 Taiwan Department of Electrical Engineering National Cheng Kung University No. 1 Daxue Rd. East Dist. Tainan701401 Taiwan

People usually form a social structure (e.g., a leader-follower, companion, or independent group) for better interactions among them and thus share similar perceptions of visible scenes and invisible wireless signals encountered while moving. Many mobility-driven applications have paid much attention to recognizing trajectory relationships among people. This work models visual and wireless data to quantify the trajectory similarity between a pair of users. We design a visual and wireless sensor fusion system, called ViWise, which incorporates the first-person video frames collected by a wearable visual device and the wireless packets broadcast by a personal mobile device for recognizing finer-grained trajectory relationships within a mobility group. When people take similar trajectories, they usually share similar visual scenes. Their wireless packets observed by ambient wireless base stations (called wireless scanners in this work) usually contain similar patterns. We model the visual characteristics of physical objects seen by a user from two perspectives: micro-scale image structure with pixel-wise features and macro-scale semantic context. However, we model characteristics of wireless packets based on the encountered wireless scanners along the user’s trajectory. Given two users’ trajectories, their trajectory characteristics behind the visible video frames and invisible wireless packets are fused together to compute the visual-wireless data similarity that quantifies the correlation between trajectories taken by them. We exploit modeled visual-wireless data similarity to recognize the social structure within user trajectories. Comprehensive experimental results in indoor and outdoor environments show that the proposed ViWise is robust in trajectory relationship recognition with an accuracy of above 90%. © 2023 Copyright held by the owner/author(s)

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Biphoton spectral quantum interference for information processing and delay metrology 3

Biphoton spectral quantum interference for information proce...

引用

Quantum Computing, Communication, and Simulation III 2023

作者： Seshadri, Suparna Lu, Hsuan-Hao Lukens, Joseph M. Weiner, Andrew M. School of Electrical and Computer Engineering Purdue Quantum Science and Engineering Institute Purdue University West LafayetteIN47907 United States Quantum Information Science Section Oak Ridge National Laboratory Oak RidgeTN37831 United States Research Technology Office Arizona State University TempeAZ85287 United States

ISBN: (纸本)9781510659971

Broadband time-energy entangled photons feature strong temporal correlations with potential for precision delay metrology, but previous work has leveraged only time-of-flight information ultimately limited by the detection jitter and resolution of the time-tagging electronics. Firstly, our work pushes the entanglement-based nonlocal delay metrology from the conventional time-of-flight measurement to a new direction—two-photon interferometry with subpicosecond sensitivity independent of detection resolution. Next, we show the selective sensitivity of frequency-bin encoded Bell states to the sum and difference of biphoton-delays by using a novel reconfigurable setup capable of switching between the Bell states by successively employing single and dual spectral-line pumps. © 2023 SPIE.

关键词： Photons

来源：评论

学校读者我要写书评

暂无评论

A Novel Explainable CNN Model for Screening COVID-19 on X-ray Images

引用

computer Systems science & engineering 2023年第8期46卷 1789-1809页

作者： Hicham Moujahid Bouchaib Cherradi Oussama El Gannour Wamda Nagmeldin Abdelzahir Abdelmaboud Mohammed Al-Sarem Lhoussain Bahatti Faisal Saeed Mohammed Hadwan EEIS Laboratory ENSET of MohammediaHassan II University of CasablancaMohammedia28820Morocco STIE Team CRMEF Casablanca-SettatThe Provincial Section of El JadidaEl Jadida24000Morocco Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Information Systems King Khalid UniversityMuhayel Aseer61913Saudi Arabia College of Computer Science and Engineering Taibah UniversityMedina42353Saudi Arabia Department of Computer Science University of Sheba RegionMarib14400Yemen DAAI Research Group Department of Computing and Data ScienceSchool of Computing and Digital TechnologyBirmingham City UniversityBirminghamB47XGUK Department of Information Technology College of ComputerQassim UniversityBuraydah 51452Saudi Arabia Department of Computer Science College of Applied SciencesTaiz UniversityTaiz6803Yemen

Due to the rapid propagation characteristic of the Coronavirus(COVID-19)disease,manual diagnostic methods cannot handle the large number of infected individuals to prevent the spread of ***,new automated diagnostic methods have been brought on board,particularly methods based on artificial intelligence using different medical data such as X-ray *** imaging,for example,produces several image types that can be processed and analyzed by machine and deep learning methods.X-ray imaging materials widely exist in most hospitals and health institutes since they are affordable compared to other imaging *** this paper,we propose a novel Convolutional Neural Network(CNN)model(COV2Net)that can detect COVID-19 virus by analyzing the X-ray images of suspected *** model is trained on a dataset containing thousands of X-ray images collected from different *** model was tested and evaluated on an independent *** order to approve the performance of the proposed model,three CNN models namely Mobile-Net,Residential Energy Services Network(Res-Net),and Visual Geometry Group 16(VGG-16)have been implemented using transfer learning *** experiment consists of a multi-label classification task based on X-ray images for normal patients,patients infected by COVID-19 virus and other patients infected with *** proposed model is empowered with Gradient-weighted Class Activation Mapping(Grad-CAM)and Grad-Cam++techniques for a visual explanation and methodology debugging *** finding results show that the proposed model COV2Net outperforms the state-of-the-art methods.

关键词： Artificial intelligence intelligent diagnostic systems decisionmaking COVID-19 convolutional neural network

来源：评论

学校读者我要写书评

暂无评论

A Machine Learning-Based Model for the Detection of Skin Cancer Using YOLOv10

A Machine Learning-Based Model for the Detection of Skin Can...

引用

IEEE International Conference on Signal and Image Processing Applications (ICSIPA)

作者： Bushra Shaukat Ali Haidawati Nasir Akbar Khan Muhammad Ashraf Syed Muhammad Akbar Department of Computer Science University of Information Technology Engineering and Management Sciences (BUITEMS) Quetta Pakistan Computer Engineering section Malaysian Institute of Technology Kuala Lumpur Malaysia Department of Computer Engineering University of Information Technology Engineering and Management Sciences (BUITEMS) Quetta Pakistan

ISBN: (数字)9798350352368

ISBN: (纸本)9798350352375

Melanoma, the most dangerous form of skin cancer originates in pigment cells (melanocytes) and poses a significant threat to patients. Therefore, individuals must have any suspicious lesions or moles promptly evaluated for early detection to improve survival rates. The following study presents a Machine learning-based model for detecting skin cancer using YOLOv10 technology. The process involves preprocessing, augmentation, and training on two datasets: the ISIC 2017 dataset (with classes melanoma, nevus, and seborrheic keratosis) annotated based on YOLOv8 versions via Roboflow; and another dataset from Roboflow containing three classes-malignant tumors, benign growths, and healthy skin. Preprocessing techniques were utilized alongside augmentation methods to enhance the model's performance before fine-tuning the pre-trained YOLOv10 model as per requirements. This approach yielded promising results with achieved precision of 1, recall of 0.88, and $mAP50$ of 0.94 on the ISIC2017 dataset; precision of 1, recall of 0.95, mAP50 of 0.79, and F-score score of 82% on the Skin Detection Dataset respectively.

关键词： Training Industries Image processing Object detection Melanoma Medical services Pigments

来源：评论

学校读者我要写书评

暂无评论

Parkinson’s Detection Using RNN-Graph-LSTM with Optimization Based on Speech Signals

引用

computers, Materials & Continua 2022年第7期72卷 871-886页

作者： Ahmed S.Almasoud Taiseer Abdalla Elfadil Eisa Fahd N.Al-Wesabi Abubakar Elsafi Mesfer Al Duhayyim Ishfaq Yaseen Manar Ahmed Hamza Abdelwahed Motwakel Department of Information Systems College of Computer and Information SciencesPrince Sultan UniversityMahayil62529Saudi Arabia Department of Information Systems-Girls Section King Khalid UniversityMahayil62529Saudi Arabia Department of Computer Science College of Science and Artsat MahayilKing Khalid UniversityMahayil62529Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahSaudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversityMahayil62529Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj62529Saudi Arabia

Early detection of Parkinson’s Disease(PD)using the PD patients’voice changes would avoid the intervention before the identification of physical *** machine learning algorithms were developed to detect PD ***,these ML methods are lack in generalization and reduced classification performance due to subject *** overcome these issues,this proposed work apply graph long short term memory(GLSTM)model to classify the dynamic features of the PD patient speech *** proposed classification model has been further improved by implementing the recurrent neural network(RNN)in batch normalization layer of GLSTM and optimized with adaptive moment estimation(ADAM)on network hidden *** consider the importance of feature engineering,this proposed system use Linear Discriminant analysis(LDA)for dimensionality reduction and SparseAuto-Encoder(SAE)for extracting the dynamic speech *** on the computation of energy content transited from unvoiced to voice(onset)and voice to voiceless(offset),dynamic features are *** PD datasets is evaluated under 10 fold cross validation without sample *** proposed smart PD detection method called RNN-GLSTM-ADAM is numerically experimented with persistent phonations in terms of accuracy,sensitivity,and specificity andMatthew correlation *** evaluated result of RNN-GLSTM-ADAM extremely improves the PD detection accuracy than static feature based conventional ML and DL approaches.

关键词： Dimensionality reduction LDA feature extraction auto encoder classification recurrent neural network LSTM and optimization

来源：评论

学校读者我要写书评

暂无评论

Heuristic computing with sequential quadratic programming for solving a nonlinear hepatitis B virus model

引用

Mathematics and computers in Simulation 2023年第1期212卷 234-248页

作者： Umar, Muhammad Sabir, Zulqurnain Raja, Muhammad Asif Zahoor Baskonus, Haci Mehmet Ali, Mohamed R. Shah, Nehad Ali Department of Mathematics and Statistics Hazara University Mansehra Pakistan Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Douliou Yunlin64002 Taiwan Faculty of Education Harran University Sanliurfa Turkey Department of Mathematics Benha Faculty of Engineering Benha University Egypt Faculty of Engineering and Technology Future University Cairo Egypt Department of Mechanical Engineering Sejong University Seoul05006 Korea Republic of Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon

This current study presents a nonlinear system of the hepatitis B virus infection by using the strength of artificial neural network (ANN) together with the competences of global and local search efficiencies of genetic algorithm (GA) and sequential quadratic programming scheme (SQPS), i.e., ANN-GA-SQPS. An error function is designed to use the mathematical form of the hepatitis B virus differential model and its initial conditions. The optimization of the error function is performed by using the hybridization efficiency of the GA-SQPS for the hepatitis B virus infection disease model. For the competence of ANN-GA-SQPS, the matching of obtained and the Adams numerical solutions has been observed. The absolute error is found in good measures for solving a nonlinear hepatitis B virus infection disease model. Moreover, statistical measures using different indices for 50 independent executions and 30 variables have been performed to check constancy, reliability, and effectiveness of the ANN-GA-SQPS. © 2023 International Association for Mathematics and computers in Simulation (IMACS)

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Energy efficient virtual machine migration approach with SLA conservation in cloud computing

引用

Journal of Central South University 2021年第3期28卷 760-770页

作者： GARG Vaneet JINDAL Balkrishan Computer Science and Engineering Section Punjabi UniversityPatiala 147002India Computer Engineering Section Yadvindra College of EngineeringPunjabi UniversityGuru Kashi CampusTalwandi Sabo 151302India

In the age of online workload explosion,cloud users are increasing ***,large scale data centers are required in cloud environment that leads to high energy ***,optimal resource utilization is essential to improve energy efficiency of cloud data ***,most of the existing literature focuses on virtual machine(VM)consolidation for increasing energy efficiency at the cost of service level agreement *** order to improve the existing approaches,load aware three-gear THReshold(LATHR)as well as modified best fit decreasing(MBFD)algorithm is proposed for minimizing total energy consumption while improving the quality of service in terms of *** offers promising results under dynamic workload and variable number of VMs(1-290)allocated on individual *** outcomes of the proposed work are measured in terms of SLA,energy consumption,instruction energy ratio(IER)and the number of migrations against the varied numbers of *** experimental results it has been concluded that the proposed technique reduced the SLA violations(55%,26%and 39%)and energy consumption(17%,12%and 6%)as compared to median absolute deviation(MAD),inter quartile range(IQR)and double threshold(THR)overload detection policies,respectively.

关键词： cloud computing energy efficiency three-gear threshold resource allocation service level agreement

来源：评论

学校读者我要写书评

暂无评论

Enhanced pruning algorithm for improving visual quality in MPEG immersive video

Enhanced pruning algorithm for improving visual quality in M...

引用

作者： Shin, Hong-Chang Jeong, Jun-Young Lee, Gwangsoon Kakli, Muhammad Umer Yun, Junyoung Seo, Jeongil Realistic-Media Research Section Electronics and Telecommunications Research Institute Daejeon Korea Republic of Department of Computer Science College of Engineering Hanyang University Seoul Korea Republic of

The moving picture experts group (MPEG) immersive video (MIV) technology has been actively developed and standardized to efficiently deliver immersive video to viewers in order for them to experience immersion and realism in various realistic and virtual environments. Such services are provided by MIV technology, which uses multiview videos as input. The pruning process, which is an important component of MIV technology, reduces interview redundancy in multiviews videos. The primary aim of the pruning process is to reduce the amount of data that available video codec must handle. In this study, two approaches are presented to improve the existing pruning algorithm. The first method determines the order in which images are pruned. The amount of overlapping region between the source views is then used to determine the pruning order. The second method considers global region-wise color similarity to minimize matching ambiguity when determining the pruning area. The proposed methods are evaluated under common test condition of MIV, and the results show that incorporating the proposed methods can improve both objective and subjective quality. 1225-6463/$ © 2021 ETRI

关键词： Virtual reality

来源：评论

学校读者我要写书评

暂无评论

Novel nonlinear fractional order Parkinson's disease model for brain electrical activity rhythms: Intelligent adaptive Bayesian networks

引用

Chaos, Solitons and Fractals 2024年 180卷

作者： Mukhtar, Roshana Chang, Chuan-Yu Raja, Muhammad Asif Zahoor Chaudhary, Naveed Ishtiaq Shu, Chi-Min Graduate School of Engineering Science and Technology National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan Department of Computer Science and Information Engineering National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan Department of Safety Health and Environmental Engineering National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan

In this study, a novel investigation in developing intelligent adaptive Bayesian networks (IABN) is carried out to solve the fractional order Parkinson's disease model (FOPDM) represented with a system of three fractional differential equations reflecting the brain's electrical activity rhythms at different cerebral cortex positions. The IABN are developed by using the competency of the multi-layer architecture of neural networks with backpropagation through Bayesian regularization optimization scheme. The reference dataset for IABN is created through Grunwald-Letnikov fractional derivative-based numerical solver for FOPDM in case of varying sensor locations on the cerebral cortex, as well as, considering different fractional orders in FOPDM. The proposed IABN is applied to the created datasets arbitrarily partitioned into training and testing sets by optimizing the fitness criterion based on mean square error (MSE) metric. The detailed analyses of the proposed IABN through extensive simulations and comparison with the reference numerical solutions of FOPDM in terms of MSE training/testing plots, absolute error, training/testing regression plots, and error histogram results, endorse the worth of the proposed intelligent scheme for different fractional orders. © 2024 Elsevier Ltd

关键词： Bayesian networks

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：