检索结果-内蒙古大学图书馆

Virtual Laboratory Learning Experience in engineering: An Extended Technology Acceptance Model (TAM) 3

Virtual Laboratory Learning Experience in Engineering: An Ex...

3rd IEEE International Maghreb Meeting of the Conference on sciences and Techniques of Automatic Control and computer engineering, MI-STA 2023

作者： Ahmed Alnagrat, Ahmed Jamah Ahmed, Khamiss M. S. Alkhallas, Muhannad Ismail Almakhzoom, Osama Abulaqasim Ibrahim Syed Idrus, Syed Zulkarnain Che Ismail, Rizalafande Higher Institute of Science and Technology Wadi Al-Shati Department of Computer Science and Information Technology Wadi al-Shati Fezzan Libya Sebha University Faculty of Information Technology Department of Computer Science Sebha Libya Faculty of Engineering Technology in Zuwarah Department of Software Engineering Zuwarah Libya Department of Communication Perlis Kangar01000 Malaysia Arau02600 Malaysia

ISBN: (纸本)9798350319897

This research presents an enhanced version of the Technology Acceptance Model (TAM), which integrates usability and learning objectives to evaluate the effect of adopting virtual laboratories on student performance. Data from 97 participants, gathered via a survey, was used to examine the correlation between perceived usefulness (PU), perceived ease of use (PEOU), and intention to use (IU) concerning their experiences and outcomes with a simulation-based virtual laboratory. A custom questionnaire was designed to assess TAM components, namely PU, PEOU, and IU, specifically in the context of virtual laboratory learning environments. Findings indicate that the integration of specific laboratory learning objectives fosters the creation of a more credible and authentic simulation tool. This, in turn, optimizes the learning process and enhances students' learning outcomes. The refined TAM model provides valuable insights into the determinants of user acceptance of virtual laboratories and offers practical guidance for educators and instructional designers to construct more effective and efficient virtual laboratory environments in educational contexts. © 2023 IEEE.

关键词： Virtual reality

来源：评论

学校读者我要写书评

暂无评论

Voice Enabled Intelligent Programming Assistant 4

Voice Enabled Intelligent Programming Assistant

引用

4th International Conference on Advancements in Computing, ICAC 2022

作者： Wataketiya, Ravindu Chandrasiri, Navinda Kithsiri, Ramesh Malwatta, Hirush Nadeeshani, Madhuka Siriwardana, Samanthi Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

In modern era where software development is of vital importance, software developers are challenged with conditions like Repetitive Strain Injury (RSI) which hinders their ability to work effectively. Furthermore, people with difficulties with using their hands also find it challenging to program in the traditional manner. As a solution, coding with one's voice has been experimented with, but current solutions lack interactivity and are harder to use and setup leaving much room for improvement in this domain. In this research work, by using input classifier models with accuracies over 90%, intent classifiers with accuracies over 70%, code parsing and various human computer interaction techniques, we developed a conversationally interactive, programming language agnostic, easy to setup and easy to use Voice Coding Assistant. This will potentially help a global audience of programmers to achieve their goals and improve productivity and lead a healthier life. We have named the system thus developed, "Venic". © 2022 IEEE.

关键词： Human computer interaction

来源：评论

学校读者我要写书评

暂无评论

Development of Low Resource Machine Learning Models for Child Cognitive Ability Assessments 4

Development of Low Resource Machine Learning Models for Chil...

引用

4th International Conference on Advancements in Computing, ICAC 2022

作者： Kahawanugoda, Adithya Gnanarathna, Kulanika Meegoda, Nilan Monarawila, Randika Samarasinghe, Pradeepa Lindamulage, Asiri Gawesha Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

Automated cognitive assessment tools are state-of-the-art in assessing cognition development. Due to the low availability of resources, building automated cognitive ability evaluation tools is challenging. This study focuses on developing machine learning models using a limited amount of data to assess Reasoning IQ, Knowledge IQ, Mental Chronometry and Attention-levels of Sinhala-speaking children between the age of 7 to 9 years. Our solution includes Sinhala speech recognition systems, image classification models, gaze estimation, blink count detection and facial expression recognition models to evaluate the above four cognitive ability measuring factors. Open domain speech recognition has been used to evaluate complex Sinhala child verbal responses and limited vocabulary responses were assessed using an end-to-end speech recognition system, respectively achieving 40.1% WER and 97.14% accuracy. Additionally, the image classification models for handwritten Sinhala letter recognition and two shape recognition models have gained 97%, 89% and 99% accuracy. The linear regression model for attention level evaluation that utilizes the inputs from a combination of eye-gaze estimation, facial expression recognition and blink rate detection models has gained 85% accuracy. © 2022 IEEE.

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

Smart UML - Assignment Management Tool for UML Diagrams 4

Smart UML - Assignment Management Tool for UML Diagrams

引用

4th International Conference on Advancements in Computing, ICAC 2022

作者： Weerasinghe, D.N.H. Thiwanka, K.A.T. Jayasith, H.B.C. Onella Natalie, P.A.D. Samantha Rajapaksha, U.U. Karunasena, Anuradha Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

The great majority of manual processes have been automated in the current day. Nonetheless, there is no reliable approach for evaluating UML diagrams for plagiarism and correctness. Unified Modeling Language (UML) provides the basis for UML diagrams. UML Diagrams are typically used to graphically express a system's stakeholders, activities, objects, and classes to get a deep knowledge of a particular system. UML diagrams are widely used by industry experts as well as beginners. Class diagrams and use case diagrams are the most commonly used diagrams in UML. Though most computer science-related students get assessed in UML modelling, diagram plagiarism isn't considered in most exams since it's a tedious task to perform. The proposed system automates capturing details in UML diagram components and generating a model answer from the given question scenario to compare the diagrams and calculate the plagiarism percentage with the correction percentage. © 2022 IEEE.

关键词： Unified Modeling Language

来源：评论

学校读者我要写书评

暂无评论

Towards combating frequency simplicity-biased learning for domain generalization 24

Towards combating frequency simplicity-biased learning for d...

引用

Proceedings of the 38th International Conference on Neural information Processing Systems

作者： Xilin He Jingyu Hu Qinliang Lin Cheng Luo Weicheng Xie Siyang Song Muhammad Haris Khan Linlin Shen Computer Vision Institute School of Computer Science & Software Engineering Shenzhen University Computer Vision Institute School of Computer Science & Software Engineering Shenzhen University and Shenzhen Institute of Artificial Intelligence and Robotics for Society and Guangdong Provincial Key Laboratory of Intelligent Information Processing University of Exeter Mohamed bin Zayed University of Artificial Intelligence

ISBN: (纸本)9798331314385

Domain generalization methods aim to learn transferable knowledge from source domains that can generalize well to unseen target domains. Recent studies show that neural networks frequently suffer from a simplicity-biased learning behavior which leads to over-reliance on specific frequency sets, namely as frequency shortcuts, instead of semantic information, resulting in poor generalization performance. Despite previous data augmentation techniques successfully enhancing generalization performances, they intend to apply more frequency shortcuts, thereby causing hallucinations of generalization improvement. In this paper, we aim to prevent such learning behavior of applying frequency shortcuts from a data-driven perspective. Given the theoretical justification of models' biased learning behavior on different spatial frequency components, which is based on the dataset frequency properties, we argue that the learning behavior on various frequency components could be manipulated by changing the dataset statistical structure in the Fourier domain. Intuitively, as frequency shortcuts are hidden in the dominant and highly dependent frequencies of dataset structure, dynamically perturbating the over-reliance frequency components could prevent the application of frequency shortcuts. To this end, we propose two effective data augmentation modules designed to collaboratively and adaptively adjust the frequency characteristic of the dataset, aiming to dynamically influence the learning behavior of the model and ultimately serving as a strategy to mitigate shortcut learning. Code is available at https://***/C0notSilly/AdvFrequency.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Cloud Security Service for Identifying Unauthorized User Behaviour

引用

computers, Materials & Continua 2022年第2期70卷 2581-2600页

作者： D.Stalin David Mamoona Anam Chandraprabha Kaliappan S.Arun Mozhi Selvi Dilip Kumar Sharma Pankaj Dadheech Sudhakar Sengan Department of Computer Science and Engineering IFET College of EngineeringVillupuram605108Tamil NaduIndia Department of Computer Sciences and Software Engineering Faculty of Basic and Applied SciencesInternational Islamic UniversityIslamabadPakistan Department of Information Technology Bannari Amman Institute of TechnologySathyamangalam638401Tamil NaduIndia Department of Computer Science Engineering DMI St.John the Baptist UniversityMangochiLilongweMalawi Department of Mathematics Jaypee University of Engineering and TechnologyGuna473226Madhya PradeshIndia Department of Computer Science and Engineering Swami Keshvanand Institute of TechnologyManagement and Gramothan(SKIT)Jaipur302017RajasthanIndia Department of Computer Science and Engineering PSN College of Engineering and TechnologyTirunelveli627152Tamil NaduIndia

Recently,an innovative trend like cloud computing has progressed quickly in *** a background of distributed networks,the extensive sprawl of internet resources on the Web and the increasing number of service providers helped cloud computing technologies grow into a substantial scaled information Technology service *** cloud computing environment extracts the execution details of services and systems from end-users and ***,through the system’s virtualization accomplished using resource pooling,cloud computing resources become more *** attempt to design and develop a solution that assures reliable and protected authentication and authorization service in such cloud environments is described in this *** the help of multi-agents,we attempt to represent Open-Identity(ID)design to find a solution that would offer trustworthy and secured authentication and authorization services to software services based on the *** research aims to determine how authentication and authorization services were provided in an agreeable and preventive *** on attack-oriented threat model security,the evaluation *** considering security for both authentication and authorization systems,possible security threats are analyzed by the proposed security systems.

关键词： Cloud computing user behaviour access control security model

来源：评论

学校读者我要写书评

暂无评论

Self-adaptive Bat Algorithm With Genetic Operations

引用

IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1284-1294页

作者： Jing Bi Haitao Yuan Jiahui Zhai MengChu Zhou H.Vincent Poor School of Software Engineering Faculty of Information TechnologyBeijing University of TechnologyBeijing 100124China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewark NJ 07102 USA School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China Department of Electrical Engineering Princeton UniversityPrinceton NJ 08544 USA IEEE

Swarm intelligence in a bat algorithm(BA)provides social *** operations for reproducing individuals in a genetic algorithm(GA)offer global search ability in solving complex optimization *** integration provides an opportunity for improved search ***,existing studies adopt only one genetic operation of GA,or design hybrid algorithms that divide the overall population into multiple subpopulations that evolve in parallel with limited interactions *** from them,this work proposes an improved self-adaptive bat algorithm with genetic operations(SBAGO)where GA and BA are combined in a highly integrated ***,SBAGO performs their genetic operations of GA on previous search information of BA solutions to produce new exemplars that are of high-diversity and *** by these exemplars,SBAGO improves both BA’s efficiency and global search *** evaluate this approach by using 29 widely-adopted problems from four test *** is also evaluated by a real-life optimization problem in mobile edge computing *** results show that SBAGO outperforms its widely-used and recently proposed peers in terms of effectiveness,search accuracy,local optima avoidance,and robustness.

关键词： Bat algorithm(BA) genetic algorithm(GA) hybrid algorithm learning mechanism meta-heuristic optimization algorithms

来源：评论

学校读者我要写书评

暂无评论

Brain Tumor Segmentation in Multimodal MRI Using U-Net Layered Structure

引用

computers, Materials & Continua 2023年第3期74卷 5267-5281页

作者： Muhammad Javaid Iqbal Muhammad Waseem Iqbal Muhammad Anwar Muhammad Murad Khan Abd Jabar Nazimi Mohammad Nazir Ahmad Department of Information Technology The Superior UniversityLahorePakistan Department of Software Engineering The Superior UniversityLahorePakistan Department of Information Sciences Division of Science and TechnologyUniversity of EducationLahorePakistan Department of Computer Science Government College UniversityFaisalabadPakistan Deptment of Oral and Maxillofacial Surgery Faculty of DentistryUniversiti Kebangsaan MalaysiaKuala LumpurMalaysia Institute of IR4.0 Universiti Kebangsaan MalaysiaBangiSelangorMalaysia

The brain tumour is the mass where some tissues become old or damaged,but they do not die or not leave their *** brain tumour masses occur due to malignant *** tissues must die so that new tissues are allowed to be born and take their *** segmentation is a complex and time-taking problem due to the tumour’s size,shape,and appearance *** finding such masses in the brain by analyzing Magnetic Resonance Images(MRI)is a crucial task for experts and *** could not work for large volume images simultaneously,and many errors occurred due to overwhelming image *** main objective of this research study is the segmentation of tumors in brain MRI images with the help of digital image processing and deep learning *** research study proposed an automatic model for tumor segmentation in MRI *** proposed model has a few significant steps,which first apply the pre-processing method for the whole dataset to convert Neuroimaging Informatics Technology Initiative(NIFTI)volumes into the 3D NumPy *** the second step,the proposed model adopts U-Net deep learning segmentation algorithm with an improved layered structure and sets the updated *** the third step,the proposed model uses state-of-the-art Medical Image Computing and computer-Assisted Intervention(MICCAI)BRATS 2018 dataset withMRI modalities such as T1,T1Gd,T2,and Fluidattenuated inversion recovery(FLAIR).Tumour types in MRI images are classified according to the tumour *** of these masses carried by state-of-the-art approaches such that the first is enhancing tumour(label 4),edema(label 2),necrotic and non-enhancing tumour core(label 1),and the remaining region is label 0 such that edema(whole tumour),necrosis and *** proposed model is evaluated and gets the Dice Coefficient(DSC)value for High-grade glioma(HGG)volumes for their test set-a,test set-b,and test set-c 0.9795, 0.9855 and 0.9793, respectively.

关键词： Brain tumour segmentation magnetic resonance images modalities dice coefficient low-grade glioma U-Net

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based Model for Detection of Brinjal Weed in the Era of Precision Agriculture

引用

computers, Materials & Continua 2023年第10期77卷 1281-1301页

作者： Jigna Patel Anand Ruparelia Sudeep Tanwar Fayez Alqahtani Amr Tolba Ravi Sharma Maria Simona Raboaca Bogdan Constantin Neagu Department of Computer Science and Engineering Institute of TechnologyNirma UniversityAhmedabad382481India Software Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh12372Saudi Arabia Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Centre for Inter-Disciplinary Research and Innovation University of Petroleum and Energy StudiesDehradun248001India Doctoral School University Politehnica of BucharestBucharest060042Romania National Research and Development Institute for Cryogenic and Isotopic Technologies-ICSI Rm ValceaRamnicu Valcea240050Romania Power Engineering Department Gheorghe Asachi Technical University of IasiIasi700050Romania

The overgrowth of weeds growing along with the primary crop in the fields reduces crop *** solutions like hand weeding are labor-intensive,costly,and time-consuming;farmers have used *** application of herbicide is effective but causes environmental and health ***,Precision Agriculture(PA)suggests the variable spraying of herbicides so that herbicide chemicals do not affect the primary *** by the gap above,we proposed a Deep Learning(DL)based model for detecting Eggplant(Brinjal)weed in this *** key objective of this study is to detect plant and non-plant(weed)parts from crop *** the help of object detection,the precise location of weeds from images can be *** dataset is collected manually from a private farm in Gandhinagar,Gujarat,*** combined approach of classification and object detection is applied in the proposed *** Convolutional Neural Network(CNN)model is used to classify weed and non-weed images;further DL models are applied for object *** have compared DL models based on accuracy,memory usage,and Intersection over Union(IoU).ResNet-18,YOLOv3,CenterNet,and Faster RCNN are used in the proposed *** outperforms all other models in terms of accuracy,i.e.,88%.Compared to other models,YOLOv3 is the least memory-intensive,utilizing 4.78 GB to evaluate the data.

关键词： Precision Agriculture Deep Learning brinjal weed detection ResNet-18 YOLOv3 CenterNet Faster RCNN

来源：评论

学校读者我要写书评

暂无评论

Safeguarding Privacy in Real-Time Trajectory Releases for AI-Driven Consumer Applications

引用

IEEE Transactions on Consumer Electronics 2025年

作者： Cai, Sujin Tian, Wei Lv, Taizhi Wang, Xiangchen Li, Xin Jiangsu Maritime Institute School of Information and Engineering Nanjing211106 China Guizhou University of Commerce College of Computer and Information engineering Guiyang550014 China Southern University of Science and Technology College of Computer Science Shenzhen518055 China Hohai University College of Computer Science and Software Engineering Nanjing211106 China

Intelligent consumer applications optimize product recommendations by analyzing users' real-time trajectory information and mobility patterns to gain insights into their consumption preferences. However, privacy concerns often cause individuals to hesitate when sharing their locations. This paper introduces a real-time trajectory release scheme called Dynamic Trajectory Releasing based on Geo-indistinguishability (DTRG) that ensures client-side data protection. A significant contribution of this work is the introduction of a novel concept, w-event Geo-indistinguishability, which extends the measurement of privacy for real-time trajectories. Building upon the theoretical foundation of w-event Geo-indistinguishability, we design a dynamic privacy budget allocation strategy that doesn't require pre-setting trajectory length. This strategy recycles unused privacy budgets and progressively reallocating them in a backward cumulative manner, enhancing the utilization efficiency of the privacy budget. By incorporating users' travel information for prediction, DTRG adaptively perturbs real locations based on prediction results. Through the collaborative operation of the Prediction Mechanism (PM), Detection Mechanism (DM) and Noisy Mechanism (NM), this approach further optimizes the utility of the budget. Experimental results demonstrate that DTRG significantly improves data availability, achieving up to a 36% increase compared to some competing algorithms while maintaining the desired level of privacy. © 1975-2011 IEEE.

关键词： Differential privacy

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：