检索结果-内蒙古大学图书馆

International Conference on Wavelet Active Media Technology and Information Processing (ICWAMTIP)

作者： Imtiaz Ahmed Butt Li Bo Muhammad Hassaan Farooq Butt Megabiaw Tewodros Tassew Muhammad Usama Bin Akhtar Khan School of Electronics and Information Northwestern Polytechnical University Xi'an Shaanxi China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Software Northwestern Polytechnical University Xi'an Shaanxi China Department of Computing Comsats University Islamabad Wah Campus Wah Pakistan

In the domain of hyperspectral imaging classification (HSIC) for remote sensing, recent advancements in deep learning have proven transformative. Convolutional neural networks have demonstrated immense potential in resolving these issues of HSIC, including insufficient labeled data, redundant spatial and spectral features, and overfitting. Traditional convolutional neural networks (CNNs) have effectively extracted spectral and spatial features, but 2D CNNs are limited in spatial modeling, while 3D CNNs alone struggle to distinguish spectral and spatial characteristics. Given that the accuracy of HSIC hinges on both spatial and spectral information, we proposed a hybrid-CNN model designed to mitigate the constraints of 2D and 3D CNNs. Our approach involves leveraging hybrid CNNs with spatial and channel attention (CA) mechanisms to address challenges like overfitting and model complexity. The proposed framework also improves generalization performance compared to 2D or 3D CNNs alone. Experiments were conducted on open datasets from Pavia University, Indian Pines, and Salinas to validate the proposed approach. The results demonstrate the efficacy of the hybrid CNN model with spatial and CA in consistently producing excellent classification results through thorough analyses with different deep-learning models.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Multi-aspects Intelligent Requirements Prioritization Technique for Value Based software Systems 2nd

Multi-aspects Intelligent Requirements Prioritization Techni...

引用

2nd International Conference on Intelligent Technologies and Applications, INTAP 2019

作者： Sher, Falak Jawawi, Dayang N. A. Mohammad, Radziah Babar, Muhammad Imran Kazmi, Rafaqat Shah, Muhammad Arif Faculty of Engineering School of Computing Department of Software Engineering UTM Johor81310 Malaysia Army Public College of Management and Sciences Rawalpindi Pakistan Department of Computer Science & IT The Islamia University of Bahawalpur Bahawalpur Pakistan

ISBN: (纸本)9789811552311

Requirements engineering (RE) is an important phase of software engineering. During this phase, an important set of activities are carried out to manage requirements elicitation, verification, prioritization and validation. Dimension and dynamics of software development are changing with the passage of time. Economic growth in different sectors is increasing the demand for software development. This enhancement has introduced the concept of Value Base software (VBS) development. Requirements prioritization is playing a vital role in ordering requirements to support the release planning of the software. A prioritization process is considered as highly complex process and depends on the nature and size of requirements. VBS systems are entirely different from typical software development, and prioritization process for VBS is also very challenging. A need arises from the provision of prioritization techniques to support the technical and business aspects-based prioritization. Existing techniques are not qualified to meet the expectation of the industry for VBS development. Therefore, this research contribution is an effort made, based on an intelligent decision support system for requirements prioritization in the domain of VBS system. Aspects based requirements prioritization is applied to many requirements and results are produced in two clusters. Results are claimed as a prioritized list of requirements for traditional as well as value-based system. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Requirements engineering

来源：评论

学校读者我要写书评

暂无评论

Dual-View Pyramid Pooling in Deep Neural Networks for Improved Medical Image Classification and Confidence Calibration

arXiv

引用

arXiv 2024年

作者： Zhang, Xiaoqing Nie, Qiushi Xiao, Zunjie Zhao, Jilu Wu, Xiao Guo, Pengxin Li, Runzhi Liu, Jin Wei, Yanjie Pan, Yi Center for High Performance Computing Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen518055 China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Department of Statistics and Actuarial Science The University of Hong Kong 999077 Hong Kong Cooperative Innovation Center of Internet Healthcare Zhengzhou University Zhengzhou450001 China Hunan Provincial Key Lab on Bioinformatics School of Computer Science and Engineering Central South University Changsha410083 China Xinjiang Engineering Research Center of Big Data and Intelligent Software School of software Xinjiang University Wulumuqi830046 China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen China

Spatial pooling (SP) and cross-channel pooling (CCP) operators have been applied to aggregate spatial features and pixel-wise features from feature maps in deep neural networks (DNNs), respectively. Their main goal is to reduce computation and memory overhead without visibly weakening the performance of DNNs. However, SP often faces the problem of losing the subtle feature representations, while CCP has a high possibility of ignoring salient feature representations, which may lead to both miscalibration of confidence issues and suboptimal medical classification results. To address these problems, we propose a novel dual-view framework, the first to systematically investigate the relative roles of SP and CCP by analyzing the difference between spatial features and pixel-wise features. Based on this framework, we propose a new pooling method, termed dual-view pyramid pooling (DVPP), to aggregate multi-scale dual-view features. DVPP aims to boost both medical image classification and confidence calibration performance by fully leveraging the merits of SP and CCP operators from a dual-axis perspective. Additionally, we discuss how to fulfill DVPP with five parameter-free implementations. Extensive experiments on six 2D/3D medical image classification tasks show that our DVPP surpasses state-of-the-art pooling methods in terms of medical image classification results and confidence calibration across different DNNs. © 2024, CC BY.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

CLDG: Contrastive Learning on Dynamic Graphs

CLDG: Contrastive Learning on Dynamic Graphs

引用

International Conference on Data engineering

作者： Yiming Xu Bin Shi Teng Ma Bo Dong Haoyi Zhou Qinghua Zheng Department of Computer Science and Technology Xi’an Jiaotong University China Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering Xi’an Jiaotong University China Department of Distance Education Xi’an Jiaotong University China School of Software Beihang University China Advanced Innovation Center for Big Data and Brain Computing Beihang University China

The graph with complex annotations is the most potent data type, whose constantly evolving motivates further exploration of the unsupervised dynamic graph representation. One of the representative paradigms is graph contrastive learning. It constructs self-supervised signals by maximizing the mutual information between the statistic graph’s augmentation views. However, the semantics and labels may change within the augmentation process, causing a significant performance drop in downstream tasks. This drawback becomes greatly magnified on dynamic graphs. To address this problem, we designed a simple yet effective framework named CLDG. Firstly, we elaborate that dynamic graphs have temporal translation invariance at different levels. Then, we proposed a sampling layer to extract the temporally-persistent signals. It will encourage the node to maintain consistent local and global representations, i.e., temporal translation invariance under the timespan views. The extensive experiments demonstrate the effectiveness and efficiency of the method on seven datasets by outperforming eight unsupervised state-of-the-art baselines and showing competitiveness against four semi-supervised methods. Compared with the existing dynamic graph method, the number of model parameters and training time is reduced by an average of 2,001.86 times and 130.31 times on seven datasets, respectively. The code and data are available at: https://***/yimingxu24/CLDG.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Comparison on Blockchain-based Intrusion Detection Systems for Internet of Things

Comparison on Blockchain-based Intrusion Detection Systems f...

引用

Knowledge engineering and Communication Systems (ICKECS), International Conference on

作者： Daniel Mago Vistro Muhammad Kamran Abid Mughees Ahmad Mubashir Ali Jawad Hassan Akhlaq Younas School of Computing Asia Pacific University of Technology and Innovation Kuala lumpur Malaysia Department of Computer Science NFC Institute of Engineering and Technology Multan Pakistan Department of Computer Science University College of Zhob (BUITEMS) Zhob Pakistan Department of Software Engineering Lahore Garrison University Lahore Pakistan Department of Computer Science and Engineering Air University Multan Campus Multan Pakistan

The Internet of Things (IoT) is a cutting-edge concept that unites the Internet with actual physical objects from a variety of industries, such as home automation, manufacturing, human health, and environmental monitoring. Users are now able to use gadgets with Internet access for routine tasks. Along with many advantages, IoT also presents a number of security-related difficulties. The security of the IoT network has grown in importance as the popularity of the Internet of Things increases daily. An IoT network is more secure thanks to encryption and authentication, yet it can be challenging to defend IoT devices from online threats. Cyberattacks on the Internet of Things system not only result in data loss, but they also have the potential to bring the entire system to a standstill. The performance of the network can be negatively impacted by hostile activities, which are easily detected by intrusion detection systems (IDS). To safeguard IoT systems, an efficient intrusion detection system (IDS) is required. Another cutting-edge technology that helps security systems counter the most recent threats is blockchain. In this post, we analysed state-of-the-art blockchain-based intrusion detection methods for Internet of Things devices. New advancements to alleviate security threats are also listed in a table. Finally, we list the major questions brought on by the current restrictions.

关键词： Performance evaluation Knowledge engineering Industries Home automation Intrusion detection Manufacturing Internet of Things

来源：评论

学校读者我要写书评

暂无评论

Panel Session: A Vision for the Next 15 Years of computing Education

Panel Session: A Vision for the Next 15 Years of Computing E...

引用

Frontiers in Education (FIE) Conference

作者： Adrienne Decker Monica M. McGill Briana Morrison Manuel A. Pérez-Quiñones Aman Yadav Department of Engineering Education University at Buffalo Buffalo NY USA Institute for Advancing Computing Education Peoria IL USA Computer Science University of Virginia Charlottesville VA USA Software and Information Systems University of North Carolina Charlotte Charlotte NC USA College of Education and College of Natural Science Michigan State University East Lansing MI USA

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

The session will present the final report of an NSF sponsored workshop tasked with creating a vision for computing education for the next 15 years. Within several broad themes identified, the panelists were asked to probe further into where the field should be heading and what difficult questions we need to tackle. We will use the final report as a basis for discussion with the attendees and ask them the same hard questions we asked ourselves when writing this report to see how these questions shape their views of where computing education needs to be in the next 15 years.

关键词： Shape Conferences Education Writing Probes

来源：评论

学校读者我要写书评

暂无评论

Smart Health Monitoring System with Wireless Networks to Detect Kidney Diseases

引用

Computational Intelligence and Neuroscience 2022年第0期2022卷 3564482页

作者： Dhanke, Jyoti Rathee, Naveen Vinmathi, M.S. Janu Priya, S. Abidin, Shafiqul Tesfamariam, Mikiale Bharati Vidyapeeth's College of Engineering Lavale Maharashtra Pune412115 India Department of Electronics and Communication Engineering IIMT College of Engineering Uttar Pradesh Greater Noida201310 India Department of CSE Panimalar Engineering College Bangalore Trunk Road Nazarethpet Poonamallee Tamilnadu Chennai600123 India Department of Electronics and Communication Engineering K. Ramakrishnan College of Engineering Samayapuram Tamilnadu Tiruchirappalli621112 India Department of Computer Science Aligarh Muslim University Uttar Pradesh Aligarh202002 India Department of Software Engineering College of Computing and Informatics Haramaya University Dire Dawa Ethiopia

It is essential to change health services from a hospital to a patient-centric platform since medical costs are steadily growing and new illnesses are emerging on a worldwide scale. This study provides an optimal decision support system based on the cloud and Internet of Things (IoT) for identifying Chronic Kidney Disease (CKD) to provide patients with efficient remote healthcare services. To identify the presence of medical data for CKD, the proposed technique uses an algorithm named Improved Simulated Annealing-Root Mean Square -Logistic Regression (ISA-RMS-LR). The four subprocesses that make up the proposed model are a collection of data, preprocessing, feature selection, and classification. The incorporation of Simulated Annealing (SA) during Feature Selection (FS) enhances the ISA-RMS-LR model's classifier outputs. Using the CKD benchmark dataset, the ISA-RMS-LR model's efficacy has been verified. According to the experimental findings, the proposed ISA-RMS-LR model effectively classifies patients with CKD, with high sensitivity at 99.46%, accuracy at 99.26%, Specificity at 98%, F-score at 99.63%, and kappa value at 98.29%. The proposed system has many benefits including the fast transmission of medical data to the medical personnel, real-time tracking, and registration condition of the patient through a medical record. Potential enhancement of the performance measures the provider system's hospital capacity and monitoring of a significant number of patients with a concentrated average delay. © 2022 Jyoti Dhanke et al.

关键词： Simulated annealing

来源：评论

学校读者我要写书评

暂无评论

The impact of feature importance methods on the interpretation of defect classifiers

arXiv

引用

arXiv 2022年

作者： Rajbahadur, Gopi Krishnan Wang, Shaowei Oliva, Gustavo A. Kamei, Yasutaka Hassan, Ahmed E. The Centre for Software Excellence Huawei Canada School of Computing Queen’s University Canada The department of computer science University of Manitoba Canada Lab Graduate School and Faulty of Information Science and Electrical Engineering Kyushu University Japan

Classifier specific (CS) and classifier agnostic (CA) feature importance methods are widely used (often interchangeably) by prior studies to derive feature importance ranks from a defect classifier. However, different feature importance methods are likely to compute different feature importance ranks even for the same dataset and classifier. Hence such interchangeable use of feature importance methods can lead to conclusion instabilities unless there is a strong agreement among different methods. Therefore, in this paper, we evaluate the agreement between the feature importance ranks associated with the studied classifiers through a case study of 18 software projects and six commonly used classifiers. We find that: 1) The computed feature importance ranks by CA and CS methods do not always strongly agree with each other. 2) The computed feature importance ranks by the studied CA methods exhibit a strong agreement including the features reported at top-1 and top-3 ranks for a given dataset and classifier, while even the commonly used CS methods yield vastly different feature importance ranks. Such findings raise concerns about the stability of conclusions across replicated studies. We further observe that the commonly used defect datasets are rife with feature interactions and these feature interactions impact the computed feature importance ranks of the CS methods (not the CA methods). We demonstrate that removing these feature interactions, even with simple methods like CFS improves agreement between the computed feature importance ranks of CA and CS methods. In light of our findings, we provide guidelines for stakeholders and practitioners when performing model interpretation and directions for future research, e.g., future research is needed to investigate the impact of advanced feature interaction removal methods on computed feature importance ranks of different CS methods. © 2022, CC BY-NC-ND.

关键词： Defects

来源：评论

学校读者我要写书评

暂无评论

SCALABLE EDGE BLOCKING ALGORITHMS FOR DEFENDING ACTIVE DIRECTORY STYLE ATTACK GRAPHS :A PREPRINT

arXiv

引用

arXiv 2022年

作者： Guo, Mingyu Ward, Max Neumann, Aneta Neumann, Frank Nguyen, Hung School of Computer Science University of Adelaide Australia School of Physics Maths and Computing Computer Science and Software Engineering University of Western Australia Australia Department of Molecular and Cellular Biology Harvard University CambridgeMA United States

Active Directory (AD) is the default security management system for Windows domain networks. An AD environment naturally describes an attack graph where nodes represent computers/accounts/security groups, and edges represent existing accesses/known exploits that allow the attacker to gain access from one node to another. Motivated by practical AD use cases, we study a Stackelberg game between one attacker and one defender. There are multiple entry nodes for the attacker to choose from and there is a single target (Domain Admin). Every edge has a failure rate. The attacker chooses the attack path with the maximum success rate. The defender can block a limited number of edges (i.e., revoke accesses) from a set of blockable edges, limited by budget. The defender’s aim is to minimize the attacker’s success rate. We exploit the tree-likeness of practical AD graphs to design scalable algorithms. We propose two novel methods that combine theoretical fixed parameter analysis and practical optimisation techniques. For graphs with small tree widths, we propose a tree decomposition based dynamic program. We then propose a general method for converting tree decomposition based dynamic programs to reinforcement learning environments, which leads to an anytime algorithm that scales better, but loses the optimality guarantee. For graphs with small numbers of non-splitting paths (a parameter we invent specifically for AD graphs), we propose a kernelization technique that significantly downsizes the model, which is then solved via mixed-integer programming. Experimentally, our algorithms scale to handle synthetic AD graphs with tens of thousands of nodes. Copyright © 2022, The Authors. All rights reserved.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Systematic Literature Review on Global software Development Risks in Agile Methodology 8

Systematic Literature Review on Global Software Development ...

引用

8th International Conference on Information Technology and Multimedia, ICIMU 2020

作者： Podari, Zuriyaninatasa Arbain, Adila Firdaus Ibrahim, Noraini Abang Jawawi, Dayang Norhayati Nasir Wan Kadir, Wan Mohd Fahmi, Azim Muhammad Universiti Tun Hussein Onn Malaysia Software Engineering Department Parit Raja86400 Malaysia School of Computing Universiti Teknologi Malaysia Skudai81310 Malaysia

ISBN: (纸本)9781728173108

Background: The word 'Global software Development' can be described as the development of software, with development teams spread across different geographical locations. Problem statement: The issues arise when there are gaps in information, workflows or processes, policies and others in the world. Objective: This paper aims to build an understanding of the risk in Global software Development. Then, to identify category risk in Global software Development and how Agile can reduce or mitigate their challenges. Method: This review paper using the standard systematic literature review method by Kitchehamm by reviewing and analyzing the relevant state-of -art techniques and approaches in the journal libraries based on the research questions. Results: The findings show that communication in Agile Global software development is the main risk challenge. Contribution: The contributions of this paper may support the academician to propose and validate an enhanced approach to solve the issues if risk management in Agile GSD environment and assist the practitioners in choosing the most suitable and relevant method based on the requirement of Agile GSD project. This review paper is also focusing on the contribution to the software engineering Management and software engineering Models and Methods Knowledge Area. © 2020 IEEE.

关键词： Risk management

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：