检索结果-内蒙古大学图书馆

13th International Conference on Information and Knowledge Technology, IKT 2022

作者： Adib, Sara Zamani, Bahman Mdse Research Group University of Isfahan Faculty of Computer Engineering Isfahan Iran

ISBN: (纸本)9798350320626

Developing mobile applications in general, and Android tourism applications in particular, is a laborious and challenging task. This problem has roots in 1) the required domain knowledge and 2) the diversity and fast emerging requirements of a tourism app. To address these issues, in this paper, we propose a novel approach based on model-driven engineering (MDE) principles. To make the approach practical, it is supported by three contributions: a domain-specific modeling language (DSML), a graphical editor, and a transformation engine. To build an app using our approach, the developer must first design the model of the app using the graphical editor, and then generate the app code, automatically using the transformation engine. To evaluate the proposed approach, we built a tourism app as a case study and showed that the proposed approach expedites the development process 8 times compared to the traditional programming. © 2022 IEEE.

关键词： Modeling languages

来源：评论

学校读者我要写书评

暂无评论

Publication performance and trends in virtual reality research in education fields: a bibliometric analysis

引用

Multimedia Tools and Applications 2025年第10期84卷 6999-7026页

作者： Elaish, Monther M. Yadegaridehkordi, Elaheh Ho, Yuh-Shan Computer Science Department Information Technology Faculty University of Benghazi Benghazi Libya College of Information and Communications Technology School of Engineering and Technology CQUniversity Sydney Australia Trend Research Centre Asia University No. 500 Lioufeng Road Taichung41354 Taiwan

Virtual Reality (VR) technology has the potential to enhance education by providing immersive and engaging learning experiences that can improve teaching and learning outcomes. While there is a growing interest in utilizing VR in education settings, further research is needed to understand its pedagogical effectiveness and address associated considerations and challenges. This bibliometric study comprehensively analyzes 1,157 relevant articles from the Social Science Citation Index (SSCI) and the Science Citation Index Expanded (SCI-EPANDED) to gain insights into the current state of VR integration in education. The analysis revealed variation in VR adoption and research output across countries and institutions, underscoring the importance of collaboration and knowledge-sharing in the field. Key research areas and trends, such as the use of VR for skill development and training, were identified. Additionally, the study highlighted the need for more research on the pedagogical effectiveness of VR. The findings carry practical implications for guiding future research shaping policy decisions and advocating for a concerted effort to harness VR’s capabilities in education. This study serves as a practical roadmap, promoting the implementation and improvement of VR technology and fostering equitable and inclusive educational practices. © The Author(s) 2024.

关键词： Virtual reality

来源：评论

学校读者我要写书评

暂无评论

An efficient computational procedure to solve the biological nonlinear Leptospirosis model using the genetic algorithms

引用

Soft Computing 2024年第1期28卷 607-625页

作者： Sabir, Zulqurnain Ali, Mohamed R. Raja, Muhammad Asif Zahoor Sadat, R. Department of Mathematics and Statistics Hazara University Mansehra Pakistan Faculty of Engineering and Technology Future University in Egypt New Cairo11835 Egypt Basic Engineering Science Department Benha Faculty of Engineering Benha University Banha Egypt Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan Department of Mathematics Zagazig Faculty of Engineering Zagazig University Zagazig Egypt Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon

The purpose of this work is to present the numerical solutions of the nonlinear mathematical Leptospirosis disease (LD) model using the computational performances of the artificial neural networks (ANNs) along with the optimization procedures based on the global search genetic algorithm (GA) and local search active-set algorithm (ASA) scheme, i.e., ANNs-GA-ASA. LD is a zoonotic disease that is occurring in the whole world, obtained by rodents that become the reason of death in the people. The LD model based on the susceptible-infected-recovered, i.e., SIR, is used to solve the mechanisms of disease spread. The optimization of an error-based fitness function, which is constructed through the differential mathematical system using the hybrid computing proficiencies of the ANNs-GA-ASA for solving the LD model. The stochastic ANNs-GA-ASA procedures are applied to the LD model to authenticate the precision, exactness, reliability and competence of the ANNs-GA-ASA. The obtained results using the ANNs-GA-ASA of the LD model will be compared using the Runge–Kutta scheme, which authenticate the importance of the ANNs-GA-ASA. Furthermore, statistical analysis through different actions for the LD model approve the convergence and precision of the ANNs-GA-ASA. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

Performance of Gradient-Based Optimizer for Optimum Wind Cube Design

引用

computers, Materials & Continua 2022年第4期71卷 339-353页

作者： Alaa A.K.Ismaeel Essam H.Houssein Amir Y.Hassan Mokhtar Said Faculty of Computer Studies(FCS) Arab Open University(AOU)Muscat130Sultanate of Oman Faculty of Science Minia UniversityMiniaEgypt Faculty of Computers and Information Minia UniversityMiniaEgypt Electronics Research Institute GizaEgypt Electrical Engineering Department Faculty of EngineeringFayoum UniversityFayoumEgypt

Renewable energy is a safe and limitless energy source that can be utilized for heating,cooling,and other *** energy is one of the most important renewable energy *** fluctuation of wind turbines occurs due to variation of wind velocity.A wind cube is used to decrease power fluctuation and increase the wind turbine’s *** optimum design for a wind cube is the main contribution of this *** decisive design parameters used to optimize the wind cube are its inner and outer radius,the roughness factor,and the height of the wind turbine hub.A Gradient-Based Optimizer(GBO)is used as a new metaheuristic algorithm in this *** objective function of this research includes two parts:the first part is to minimize the probability of generated energy loss,and the second is to minimize the cost of the wind turbine and wind *** Gradient-Based Optimizer(GBO)is applied to optimize the variables of two wind turbine types and the design of the wind *** metrological data of the Red Sea governorate of Egypt is used as a case study for this *** on the results,the optimum design of a wind cube is achieved,and an improvement in energy produced from the wind turbine with a wind cube will be compared with energy generated without a wind *** energy generated from a wind turbine with the optimized cube is more than 20 times that of a wind turbine without a wind cube for all cases studied.

关键词： Wind turbine wind cube gradient-based optimizer metaheuristics energy source

来源：评论

学校读者我要写书评

暂无评论

Imitation Learning from Purified Demonstrations 41

Imitation Learning from Purified Demonstrations

引用

41st International Conference on Machine Learning, ICML 2024

作者： Wang, Yunke Dong, Minjing Zhao, Yukun Du, Bo Xu, Chang School of Computer Science National Engineering Research Center for Multimedia Software Institute of Artificial Intelligence Wuhan Institute of Data Intelligence Wuhan University China Department of Computer Science City University of Hong Kong Hong Kong School of Computer Science Faculty of Engineering The University of Sydney Australia

Imitation learning has emerged as a promising approach for addressing sequential decision-making problems, with the assumption that expert demonstrations are optimal. However, in real-world scenarios, most demonstrations are often imperfect, leading to challenges in the effectiveness of imitation learning. While existing research has focused on optimizing with imperfect demonstrations, the training typically requires a certain proportion of optimal demonstrations to guarantee performance. To tackle these problems, we propose to purify the potential noises in imperfect demonstrations first, and subsequently conduct imitation learning from these purified demonstrations. Motivated by the success of diffusion model, we introduce a two-step purification via diffusion process. In the first step, we apply a forward diffusion process to smooth potential noises in imperfect demonstrations by introducing additional noise. Subsequently, a reverse generative process is utilized to recover the optimal demonstration from the diffused ones. We provide theoretical evidence supporting our approach, demonstrating that the distance between the purified and optimal demonstration can be bounded. Empirical results on MuJoCo and RoboSuite demonstrate the effectiveness of our method from different aspects. Copyright 2024 by the author(s)

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Physical Layer Authentication Using Ensemble Learning Technique in Wireless Communications

引用

computers, Materials & Continua 2022年第12期73卷 4489-4499页

作者： Muhammad Waqas Shehr Bano Fatima Hassan Shanshan Tu Ghulam Abbas Ziaul Haq Abbas Engineering Research Center of Intelligent Perception and Autonomous Control Faculty of Information TechnologyBeijing University of TechnologyBeijing100124China Faculty of Computer Science and Engineering GIK Institute of Engineering Sciences and TechnologyTopi23460Pakistan School of Engineering Edith Cowan UniversityJoondalup Perth6027WA Australia Faculty of Electrical Engineering GIK Institute of Engineering Sciences and TechnologyTopi23460Pakistan

Cyber-physical wireless systems have surfaced as an important data communication and networking research *** is an emerging discipline that allows effective monitoring and efficient real-time communication between the cyber and physical worlds by embedding computer software and integrating communication and networking *** to their high reliability,sensitivity and connectivity,their security requirements are more comparable to the Internet as they are prone to various security threats such as eavesdropping,spoofing,botnets,man-in-the-middle attack,denial of service(DoS)and distributed denial of service(DDoS)and *** methods use physical layer authentication(PLA),themost promising solution to detect ***,the cyber-physical systems(CPS)have relatively large computational requirements and require more communication resources,thus making it impossible to achieve a low latency *** methods perform well but only in stationary *** have extracted the relevant features from the channel matrices using discrete wavelet transformation to improve the computational time required for data processing by considering mobile *** features are fed to ensemble learning algorithms,such as AdaBoost,LogitBoost and Gentle Boost,to classify *** authentication of the received signal is considered a binary classification *** transmitted data is labeled as legitimate information,and spoofing data is illegitimate ***,this paper proposes a threshold-free PLA approach that uses machine learning algorithms to protect critical data from spoofing *** detects the malicious data packets in stationary scenarios and detects them with high accuracy when receivers are *** proposed model achieves better performance than the existing approaches in terms of accuracy and computational time by decreasing the processing time.

关键词： Physical layer authentication machine learning cyber-physical systems security

来源：评论

学校读者我要写书评

暂无评论

Information Centric Networking Based Cooperative Caching Framework for 5G Communication Systems

引用

computers, Materials & Continua 2024年第9期80卷 3945-3966页

作者： R.Mahaveerakannan Thanarajan Tamilvizhi Sonia Jenifer Rayen Osamah Ibrahim Khalaf Habib Hamam Department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai602105India Department of Computer Science and Engineering Panimalar Engineering CollegeChennai600123India Department of Computer Science and Engineering Sathyabama Institute of Science and TechnologyChennai600119India Department of Solar Energy Al-Nahrain Research Center for Renewable EnergyAl-Nahrain UniversityJadriyaBaghdad64074Iraq Faculty of Engineering Universitéde MonctonNew BrunswickE1A3E9Canada Hodmas University College Mogadishu521376Somalia Bridges for Academic Excellence Tunis1002Tunisia School of Electrical Engineering University of JohannesburgAuckland ParkJohannesburg2006South Africa

The demands on conventional communication networks are increasing rapidly because of the exponential expansion of connected multimedia *** light of the data-centric aspect of contemporary communication,the information-centric network(ICN)paradigm offers hope for a solution by emphasizing content retrieval by name instead of *** 5G networks are to meet the expected data demand surge from expanded connectivity and Internet of Things(IoT)devices,then effective caching solutions will be required tomaximize network throughput andminimize the use of ***,an ICN-based Cooperative Caching(ICN-CoC)technique has been used to select a cache by considering cache position,content attractiveness,and rate *** findings show that utilizing our suggested approach improves caching regarding the Cache Hit Ratio(CHR)of 84.3%,Average Hop Minimization Ratio(AHMR)of 89.5%,and Mean Access Latency(MAL)of 0.4 *** a framework,it suggests improved caching strategies to handle the difficulty of effectively controlling data consumption in 5G *** improvements aim to make the network run more smoothly by enhancing content delivery,decreasing latency,and relieving *** improving 5G communication systems’capacity tomanage the demands faced by modern data-centric applications,the research ultimately aids in advancement.

关键词： Information-centric networking caching schemes 5G communication non-negative matrix factorization(NMF) weighted clustering algorithm

来源：评论

学校读者我要写书评

暂无评论

High efficiency of Brillouin scattering behavior in single-mode Ge–As–Se–Te fibers at 2μm

引用

Chinese Physics B 2023年第5期32卷 449-456页

作者：付悦戴世勋徐路路方耀俊王莹莹焦凯王训四 Laboratory of Infrared Materials and Devices The Research Institute of Advanced TechnologiesNingbo UniversityNingbo 315211China Key Laboratory of Photoelectric Materials and Devices of Zhejiang Province Ningbo 315211China Engineering Research Center for Advanced Infrared Photoelectric Materials and Devices of Zhejiang Province Ningbo 315211China Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China

The Brillouin characteristics of step-index Ge–As–Se–Te(GAST)fibers at 2μm are designed and simulated on the basis of optical and acoustic *** refractive indexes of Ge_(20)As_(20)Se_(45)Te_(15)glass and Ge_(20)As_(20)Se_(43)Te_(17)glass serving as fiber core and cladding are 3.20 and 3.18 at 2μm,and their acoustic velocities are 2200 m/s and 2300 m/s,*** results indicate that the stimulated Brillouin scattering(SBS)efficiency is 248 m^(-1)·W^(-1),and the Brillouin threshold power is 66 m W when the core diameter of the 2-m-long GAST fiber is 4μm at 2-μm *** optic–acoustic coupling factor,the Brillouin frequency shift,and the Brillouin gain coefficient are 0.98,7.02 GHz,and 3.81×10^(-9)m/W,*** SBS effect of GAST fibers simulated for the first time provides a new promising approach to selecting gain medium based on 2-μm-wavelength fiber laser.

关键词： stimulated Brillouin scattering chalcogenide fiber nonlinear effect optical–acoustic coupling

来源：评论

学校读者我要写书评

暂无评论

Hierarchical Transfer Multi-task Learning Approach for Scene Classification 27th

Hierarchical Transfer Multi-task Learning Approach for Scen...

引用

27th International Conference on Pattern Recognition, ICPR 2024

作者： Khoshkangini, Reza Tajgardan, Mohsen Jamali, Mahtab Ljungqvist, Martin Georg Mihailescu, Radu-Casian Davidsson, Paul Internet of Things and People Research Center Department of Computer Science and Media Technology Malmö University Malmö Sweden Faculty of Electrical and Computer Engineering Qom University of Technology Qom Iran Axis Communications AB Lund Sweden

ISBN: (纸本)9783031781063

This paper presents a novel Hierarchical Transfer and Multi-task Learning (HTMTL) approach designed to substantially improve the performance of scene classification networks by leveraging the collective influence of diverse scene types. HTMTL is distinguished by its ability to capture the interaction between various scene types, recognizing how context information from one scene category can enhance the classification performance of another. Our method, when applied to the Places365 dataset, demonstrates a significant improvement in the network’s ability to accurately identify scene types. By exploiting these inter-scene interactions, HTMTL significantly enhances scene classification performance, making it a potent tool for advancing scene understanding and classification. Additionally, this study explores the contribution of individual tasks and task groupings on the performance of other tasks. To further validate the generality of HTMTL, we applied it to the Cityscapes dataset, where the results also show promise. This indicates the broad applicability and effectiveness of our approach across different datasets and scene types. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Automatic classification of fatty acid amide hydrolase polymorphism genotype based on EEG signal: Automatic classification of fatty acid amide hydrolase polymorphism…: Reza Javanshir et al.

引用

Soft Computing 2024年第21期28卷 12575-12585页

作者： Javanshir, Reza Sedghi, Mohammadreza Esmaeili, Mahdad Charsouei, Saeid Anvar, Leila Hosseinzadeh Ahmadalipour, Ali Department of Medical Bioengineering Faculty of Advanced Medical Sciences Tabriz University of Medical Sciences Tabriz Iran School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Department of Neurology Faculty of Medicine Tabriz University of Medical Sciences Tabriz Iran Student Research Committee Tabriz University of Medical Sciences Tabriz Iran Research Center of Psychiatry and Behavioral Sciences Tabriz University of Medical Sciences Tabriz Iran Aging Research Institute Tabriz University of Medical Sciences Tabriz Iran

Epilepsy is a brain abnormality neurological disorder and is life-threatening, affecting the behavior and lifestyle of many people worldwide. Neurologists commonly use an electroencephalogram (EEG) to manually interpret the brain's electrical activity. Some patients respond differently to drugs as the effective doses will be ineffective in some patients or cause adverse drug reactions in others and genetic factors seem to be involved in variable responses in some cases. On the other hand, performing genetic tests to detect the genotype of patients is usually invasive, expensive, and time-consuming. Estimating the patient's genotype using data such as information obtained from EEG, can be considered a significant achievement. Genes involved in the functioning of the endocannabinoid system are known to be a critical element in the physiological function the brain and nerves perform, and the defects in the activity of this system have been confirmed in the pathobiology of diseases such as epilepsy. Levels of endocannabinoids can be influenced by gene polymorphisms such as fatty acid amide hydrolase (FAAH) gene single nucleotide polymorphism. Because the FAAH controls the endocannabinoids levels by hydrolyzing and terminating the activity of the anandamide within the central nervous system (CNS) and also the origin of seizures which is the electrical storm of brain neurons, it is thought that there can be a relation between the FAAH enzyme and the brain oscillations. Identifying genotypes that are related to EEG variation in epilepsy is crucial for clinical epilepsy monitoring and controlling brain oscillations. In this paper, we show the FAAH rs2295633 polymorphism can be detected (classified) using EEG signals (as a common diagnostic tool) following the convolutional neural network (CNN) classification method. The multichannel time series data of EEG collected through a sliding window technique was given as input into a deep CNN model to find a probable relationship b

关键词： Electroencephalography

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：