检索结果-内蒙古大学图书馆

Joint of the BIR 2024 Workshops and Doctoral Consortium, BIR-WS 2024

作者： Lace, Ksenija Kirikova, Marite Institute of Applied Computer Systems Faculty of Computer Science and Information Technology Riga Technical University 6A Kipsalas Street RigaLV-1048 Latvia

The transition from structured coursework to independent research poses significant challenges for students, particularly in mastering the design science method required for thesis work. To address this issue, the paper proposes implementing gamified learning strategies within a Requirements Engineering course to enhance student readiness for thesis projects. A detailed course outline is provided, demonstrating how gamification, storytelling, and the design science method can be effectively embedded in the curriculum. By integrating these multifaceted teaching methods, the course aims to manage the complexity of preparing students for independent research and thesis writing. The course design refers to Bloom's taxonomy to ensure comprehensive learning outcomes across multiple cognitive levels, thereby fostering a deeper understanding and application of the design science method in engineering education. © 2024 Copyright for this paper by its authors.

关键词： Requirements engineering

来源：评论

学校读者我要写书评

暂无评论

CNN-Based Multi-Output and Multi-Task Regression for Supershape Reconstruction from 3D Point Clouds

Informatica (Slovenia)

引用

Informatica (Slovenia) 2025年第5期49卷 37-48页

作者： Remmach, Hassnae Razak, Siti Fatimah Abdul Ullah, Arif Yogarayan, Sumendra Sayeed, Md Shohel Mrhari, Amine Computer Systems Engineering Laboratory Cadi Ayyad University Marrakesh40000 Morocco Faculty of Information Science and Technology Multimedia University Ayer Keroh75450 Malaysia Research in Computer Science Laboratory Faculty of Sciences Ibn Tofail University Kenitra Morocco

In a number of industries, including computer graphics, robotics, and medical imaging, three-dimensional reconstruction is essential. In this research, a CNN-based Multi-output and Multi-Task Regressor with deep learning capabilities is proposed for three-dimensional object reconstruction from 3D point cloud. Our approach is grounded in the original Point Net architecture, which addresses the difficulties associated with convolution when applied to point clouds. Firstly, this paper is modified using a Multi-Output Regressor to accurately recreate Super forms from 3D point clouds. Using this method, we first extract features from the 3D point cloud using Point Net. After that, a Multi-Output Regressor receives these data and uses them to anticipate the Super shape parameters needed to reconstruct the shape. Taking in the data, the Multi-Output Regressor retrieved characteristics from Point Net and simultaneously predicts several outcomes. Second, a Multi-Task Regressor is used to modify the Point Net. The network gains from the capacity to transfer knowledge from one task to another, improving the model's overall performance. The model would forecast the ten parameters needed to create the shape in the case of rebuilding Super shapes. The test findings were better than expected;they are intriguing in terms of prediction accuracy and cost, and they update the result by 80%, which is a good accomplishment for the study. © 2025 Slovene Society Informatika. All rights reserved.

关键词： 3D reconstruction

来源：评论

学校读者我要写书评

暂无评论

Facial Image-Based Autism Detection:A Comparative Study of Deep Neural Network Classifiers

引用

computers, Materials & Continua 2024年第1期78卷 105-126页

作者： Tayyaba Farhat Sheeraz Akram Hatoon SAlSagri Zulfiqar Ali Awais Ahmad Arfan Jaffar Faculty of Computer Science and Information Technology The Superior UniversityLahore54600Pakistan Intelligent Data Visual Computing Research(IDVCR) Faculty of Computer Science and Information TechnologyThe Superior UniversityLahore54600Pakistan Information Systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh12571Saudi Arabia School of Computer Science and Electronic Engineering(CSEE) University of EssexWivenhoe ParkColchesterCO43SQUK

Autism Spectrum Disorder(ASD)is a neurodevelopmental condition characterized by significant challenges in social interaction,communication,and repetitive *** and precise ASD detection is crucial,particularly in regions with limited diagnostic resources like *** study aims to conduct an extensive comparative analysis of various machine learning classifiers for ASD detection using facial images to identify an accurate and cost-effective solution tailored to the local *** research involves experimentation with VGG16 and MobileNet models,exploring different batch sizes,optimizers,and learning rate *** addition,the“Orange”machine learning tool is employed to evaluate classifier performance and automated image processing capabilities are utilized within the *** findings unequivocally establish VGG16 as the most effective classifier with a 5-fold cross-validation ***,VGG16,with a batch size of 2 and the Adam optimizer,trained for 100 epochs,achieves a remarkable validation accuracy of 99% and a testing accuracy of 87%.Furthermore,the model achieves an F1 score of 88%,precision of 85%,and recall of 90% on test *** validate the practical applicability of the VGG16 model with 5-fold cross-validation,the study conducts further testing on a dataset sourced fromautism centers in Pakistan,resulting in an accuracy rate of 85%.This reaffirms the model’s suitability for real-world ASD *** research offers valuable insights into classifier performance,emphasizing the potential of machine learning to deliver precise and accessible ASD diagnoses via facial image analysis.

关键词： Autism Autism Spectrum Disorder(ASD) disease segmentation features optimization deep learning models facial images classification

来源：评论

学校读者我要写书评

暂无评论

Responding to platform owner moves: A 14-year qualitative study of four enterprise software complementors

Responding to platform owner moves: A 14-year qualitative st...

引用

作者： Kude, Thomas Huber, Thomas L. Faculty of Information Systems and Applied Computer Sciences University of Bamberg Germany Department of Information Systems Decision Sciences and Statistics ESSEC Business School Cergy France

Integrating the competition and the cooperation perspectives on value co-creation in platform ecosystems, this study explores complementor responses to platform owner moves that adversely affect the complementor's positioning. Our primary focus is to discern dynamic patterns of complementor responses and to understand their role in the process of re-stabilising the complementor's positioning. To this end, we conducted a 14-year longitudinal study, analysing 21 move-response instances across four platform partnerships. Our findings reveal three distinct complementor response archetypes: insist, pivot, and detach. Over time, complementors combine these archetypes into three unique response patterns. Through progressive diverging, complementors sidestep platform owner moves by diversifying their offer beyond the focal ecosystem. Although this can entail substantial multi-homing costs, it reduces dependence on the platform owner and bolsters resilience against future moves. Through adaptive oscillating, complementors use platform owner moves as opportunities to gradually diversify their offer within the focal ecosystem. This stepwise market expansion makes them resilient against future moves, while mitigating costs and efforts related to multi-homing. Through persistent insisting, complementors can re-establish their previous positioning, but at the cost of increased dependence on the platform owner, leaving the complementor vulnerable to future moves. We synthesise these findings in our process model of complementor positioning. Emphasising the importance of complementor responses in fostering resilient software ecosystems, this model bears important implications for research on platform governance and platform-dependent entrepreneurship. © 2024 The Authors. information systems Journal published by John Wiley & Sons Ltd.

关键词： Ecosystems

来源：评论

学校读者我要写书评

暂无评论

Energy and QoS-aware virtual machine placement approach for IaaS cloud datacenter

引用

Neural Computing and Applications 2025年第4期37卷 2211-2237页

作者： Elsedimy, E.I. Herajy, Mostafa Abohashish, Sara M. M. Department of Information Technology Management Faculty of Management Technology and Information Systems Port Said University Port Said Egypt Department of Mathematics and Computer Science Faculty of Science Port Said University Port Said Egypt Cyber Secuirty Department Faculty of Science Al-Esraa University College Baghdad Iraq

Virtualization technology enables cloud providers to abstract, hide, and manage the underlying physical resources of cloud data centers in a flexible and scalable manner. It allows placing multiple independent virtual machines (VMs) on a single server in order to improve resource utilization and energy efficiency. However, determining the optimal VM placement is crucial as it directly impacts load balancing, energy consumption, and performance degradation within the data center. Furthermore, deciding on VM placement based on a single factor is usually insufficient to improve data center performance because many factors must be considered, and ignoring them may be too expensive. This paper improves a new multi-objective VM placement (MVMP) algorithm using a quantum particle swarm optimization (QPSO) technique. We call it QPSO-MOVMP, and its objective is to find the Pareto optimal solution for the VM placement problem by balancing different goals. This algorithm generates Pareto optimal solutions that save power by minimizing the number of running physical machines, avoid performance degradation by maintaining service level agreement (SLA), and improve load balancing by keeping server loads at optimal utilization. The experimental results show that QPSO-MOVMP had superior performance in terms of power consumption and performance degradation compared to three other multi-objective algorithms and three conventional single-objective algorithms. Simulation results show that the proposed QPSO-MOVMP achieves a consumption of 2.4 × 104 watts in power. Furthermore, it outperformed the others, achieving a minimum of 12% SLA breaches while experiencing a significant surge in requests from VMs. Moreover, the proposed model generated Pareto solutions that had a better distribution than those derived from a comparative method. © The Author(s) 2025.

关键词： Particle swarm optimization (PSO)

来源：评论

学校读者我要写书评

暂无评论

Work in Progress: Supporting Distributed Practice with a Gamified E-Learning Course 27th

Work in Progress: Supporting Distributed Practice with a ...

引用

27th International Conference on Interactive Collaborative Learning, ICL 2024

作者： John, Isabel Hess, Anne Fertig, Tobias Faculty of Computer Science and Business Information Systems Technical University of Applied Sciences Würzburg-Schweinfurt Sanderheinrichsleitenweg 20 Würzburg97074 Germany

ISBN: (纸本)9783031835193

For the teaching of agile methods in an IT undergraduate course we developed a gamified blended learning course. We created the course with gamification elements such as videos, quizzes, badges, and points in the learning management system Moodle. In this paper, we first share our experiences with distributed practice in this course and how gamification supported our flipped classroom approach. We also briefly present results of a survey study that investigated intrinsic motivation with an earlier version of the course and that revealed mixed results, i.e., an increase of intrinsic motivation for some factors, but not for all factors. The evaluation results and observations motivated a future research agenda aimed at further improving and continuously evaluating the impact of gamification on intrinsic motivation to ultimately promote distributed practice as well as sustained learning combined with fun for the students. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Hybrid Feature Selection Method for Predicting Alzheimer’s Disease Using Gene Expression Data

引用

computers, Materials & Continua 2023年第3期74卷 5559-5572页

作者： Aliaa El-Gawady BenBella S.Tawfik Mohamed A.Makhlouf Department of Information Systems Faculty of Computers and InformaticsSuez Canal UniversityIsmailia41522Egypt Faculty of Computer Science Nahda UniversityBeni SuefEgypt

Gene expression(GE)classification is a research trend as it has been used to diagnose and prognosis many *** machine learning(ML)in the prediction of many diseases based on GE data has been a flourishing research ***,some diseases,like Alzheimer’s disease(AD),have not received considerable attention,probably owing to data scarcity *** this work,we shed light on the prediction of AD from GE data accurately using *** approach consists of four phases:preprocessing,gene selection(GS),classification,and performance *** the preprocessing phase,gene columns are preprocessed *** the GS phase,a hybrid filtering method and embedded method are *** the classification phase,three ML models are implemented using the bare minimum of the chosen genes obtained from the previous *** final phase is to validate the performance of these classifiers using different *** crux of this article is to select the most informative genes from the hybrid method,and the best ML technique to predict AD using this minimal set of *** different datasets are used to achieve our *** predict AD with impressive values forMultiLayer Perceptron(MLP)classifier which has the best performance metrics in four datasets,and the Support Vector Machine(SVM)achieves the highest performance values in only one *** assessed the classifiers using sevenmetrics;and received impressive results,allowing for a credible performance *** metrics values we obtain in our study lie in the range[.97,.99]for the accuracy(Acc),[.97,.99]for F1-score,[.94,.98]for kappa index,[.97,.99]for area under curve(AUC),[.95,1]for precision,[.98,.99]for sensitivity(recall),and[.98,1]for *** these results,the proposed approach outperforms recent interesting *** these results,the proposed approach outperforms recent interesting results.

关键词： Gene expression gene selection machine learning classification Alzheimer’s disease

来源：评论

学校读者我要写书评

暂无评论

A class of elliptic system in non reflexive Orlicz-Sobolev spaces

引用

Annali dell'Universita di Ferrara 2025年第1期71卷 1-23页

作者： El-Houari, Hamza University Moulay Ismail Faculty of Sciences and Techniques Research Laboratory “Applied Mathematics Computer Science and Systems” Errachidia Morocco

This paper aims to show that there exists a weak solution to the following quasilinear system driven by the M-Laplacian (Formula presented.) where Ω is a bounded open subset in RN and (-Δm) is the M-Laplacian operat... 详细信息

This paper aims to show that there exists a weak solution to the following quasilinear system driven by the M-Laplacian (Formula presented.) where Ω is a bounded open subset in R^N and (-Δ_m) is the M-Laplacian operator. Here we consider the non-reflexive case taking into account the Orlicz and Orlicz-Sobolev Space. The non-reflexive case occurs when the N-function M¯ does not verify the Δ₂-condition. We consider an approximated quasilinear elliptic problem driven by the M_ϵ-Laplacian and using the Mountain Pass Theorem to obtain the existence of a nontrivial and nonnegative solution for the above system in reflexive case. By tending ϵ→0 we get the solution in the non-reflexive case. © The Author(s) under exclusive license to Università degli Studi di Ferrara 2024.

关键词： Elliptic system M-Laplacian operator Orlicz-Sobolev spaces Variational problem

来源：评论

学校读者我要写书评

暂无评论

Competing with autonomous model vehicles:a software stack for driving in smart city environments

引用

Autonomous Intelligent systems 2024年第1期4卷 166-178页

作者： Julius Bächle Jakob Häringer Noah Köhler Kadir-KaanÖzer Markus Enzweiler Reiner Marchthaler Institute for Intelligent Systems Faculty of Computer Science and EngineeringEsslingen University of Applied SciencesFlandernstraße 101Esslingen am Neckar73732Germany

This article introduces an open-source software stack designed for autonomous 1:10 scale model *** developed for the Bosch Future Mobility Challenge(BFMC)student competition,this versatile software stack is applicable to a variety of autonomous driving *** stack comprises perception,planning,and control modules,each essential for precise and reliable scene understanding in complex environments such as a miniature smart city in the context of *** the limited computing power of model vehicles and the necessity for low-latency real-time applications,the stack is implemented in C++,employs YOLO Version 5 s for environmental perception,and leverages the state-of-the-art Robot Operating System(ROS)for inter-process *** believe that this article and the accompanying open-source software will be a valuable resource for future teams participating in autonomous driving student *** work can serve as a foundational tool for novice teams and a reference for more experienced *** code and data are publicly available on GitHub.

关键词： Autonomous model vehicle Software architecture Embedded real-time systems Bosch Future Mobility Challenge Autonomous driving

来源：评论

学校读者我要写书评

暂无评论

Exploring the Role of Sleep Quality, Obsessive–Compulsive Disorder, Fear of Missing Out, and Psychological Resilience on Problematic Instagram Use

引用

Journal of Technology in Behavioral science 2024年 1-11页

作者： Yilmaz, Ramazan Avci, Ummuhan Karaoglan Yilmaz, Fatma Gizem Department of Computer Technology & Information Systems Faculty of Science Bartin University Bartin Turkey Department of Management Information Systems Faculty of Economics and Administrative Sciences Bartin University Bartin Turkey

This study addresses a gap in the literature regarding the relationships between sleep quality, obsessive–compulsive disorder (OCD), fear of missing out (FoMO), psychological resilience, and problematic Instagram use (PIU) among university students. By examining these interrelated factors, the research aims to clarify the mechanisms behind Instagram addiction, support effective interventions, and contribute to academic knowledge. This study examined university students’ sleep quality, PIU, OCD, FoMO, and psychological resilience, as well as the structural relationships between these variables. The study encompassed a sample of 407 Turkish university students with an average age of 21.78. The age range of the participants was between 18 and 35 years;43% of them were female, and 57% were male. This study was conducted according to the correlational research method, and pathway analysis was used to conduct the research. Research findings show that OCD and FoMO positively affect PIU. In other words, as OCD and FoMO increase, Instagram addiction also increases. Psychological resilience has an indirect effect on PIU. OCD plays a mediating role between psychological resilience and PIU and between psychological resilience and FoMO. Therefore, as psychological resilience increases, PIU and FoMO decrease. A positive correlation was found between OCD and FoMO. As the OCD level increases, the FoMO level of the individuals also increases. Another study finding was that OCD, FoMO, psychological resilience, and PIU did not significantly affect sleep quality. Future research may focus on exploring cause-effect relationships among these variables alongside implementing school-based programs to enhance students’ psychological resilience through training, planning, and follow-up studies. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Fear of missing out (FoMO) Obsessive–compulsive disorder Problematic Instagram use Psychological resilience Sleep quality

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：