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Global software development and collaboration: Barriers and solutions

ACM Inroads 2010年第3期1卷 66-78页

作者： Noll, John Beecham, Sarah Richardson, Ita Lero the Irish Software Engineering Centre Department of Computer Science and Information Systems University of Limerick Limerick Ireland

While organisations recognise the advantages offered by global software development, many socio-technical barriers affect successful collaboration in this inter-cultural environment. In this paper, we present a review of the global software development literature where we highlight collaboration problems experienced by a cross-section of organisations in twenty-six studies. We also look at the literature to answer how organisations are overcoming these barriers in practice. We build on our previous study on global software development where we define collaboration as four practices related to agreeing, allocating, and planning goals, objectives, and tasks among distributed teams. We found that the key barriers to collaboration are geographic, temporal, cultural, and linguistic distance;the primary solutions to overcoming these barriers include site visits, synchronous communication technology, and knowledge sharing infrastructure to capture implicit knowledge and make it explicit. © 2010 ACM.

关键词： software design

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An Intelligent Privacy Protection Scheme for Efficient Edge Computation Offloading in IoV

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Chinese Journal of Electronics 2024年第4期33卷 910-919页

作者： Liang YAO Xiaolong XU Wanchun DOU Muhammad Bilal School of Software Nanjing University of Information Science and Technology State Key Laboratory for Novel Software Technology Nanjing University Department of Computer and Electronics Systems Engineering Hankuk University of Foreign Studies

As a pivotal enabler of intelligent transportation system(ITS), Internet of vehicles(Io V) has aroused extensive attention from academia and industry. The exponential growth of computation-intensive, latency-sensitive,and privacy-aware vehicular applications in Io V result in the transformation from cloud computing to edge computing,which enables tasks to be offloaded to edge nodes(ENs) closer to vehicles for efficient execution. In ITS environment,however, due to dynamic and stochastic computation offloading requests, it is challenging to efficiently orchestrate offloading decisions for application requirements. How to accomplish complex computation offloading of vehicles while ensuring data privacy remains challenging. In this paper, we propose an intelligent computation offloading with privacy protection scheme, named COPP. In particular, an Advanced Encryption Standard-based encryption method is utilized to implement privacy protection. Furthermore, an online offloading scheme is proposed to find optimal offloading policies. Finally, experimental results demonstrate that COPP significantly outperforms benchmark schemes in the performance of both delay and energy consumption.

关键词： Industries Privacy Energy consumption Transportation Computational efficiency Encryption Protection

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Domain adaptive person re-identification via homogeneous hierarchical progressive adaptation and multi-view consistency

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Advanced engineering Informatics 2025年 67卷

作者： Zhengyang Wang Xiufen Ye Xue Shang Shuxiang Guo College of Intelligent Systems Science and Engineering Harbin Engineering University Harbin 150001 China Department of Electrical Computer and Software Engineering University of Auckland Auckland 1142 New Zealand Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen 518055 China

Domain adaptive person re-identification (Re-ID) encounters significant challenges when models trained on one dataset are deployed in new environments. It is particularly critical in engineering applications where surveillance infrastructure must be rapidly adapted to new environments without compromising security system reliability. The problem represents a knowledge-intensive engineering task that requires sophisticated knowledge representation and transfer mechanisms to support automated system reconfiguration decisions. These challenges include preserving fine-grained visual details, handling camera-specific variations, generating reliable pseudo-labels, maintaining consistency across multiple camera views, and managing varying difficulty levels in domain transfer. To address these issues, we propose a novel framework that separates adaptation into intra-domain and cross-domain learning phases. Our approach introduces several key innovations: an adaptive fine-grained network that preserves spatial details while ensuring domain invariance, a memory-guided learning method for stable feature representation, and a hierarchical adaptation strategy for reliable intra-domain learning. Additionally, we incorporate a progressive learning strategy for gradual domain adaptation and a consistency reinforcement mechanism to resolve cross-camera identity conflicts. Experiments on the Market-1501, DukeMTMC-reID, and MSMT17 datasets across four domain adaptation tasks show that our method outperforms state-of-the-art approaches, significantly improving both mAP and CMC accuracy. This work contributes to engineering informatics by providing a reliable solution for automating knowledge-intensive tasks across diverse engineering domains, while also laying the foundation for advancements in intelligent surveillance systems and automated decision-making in engineering infrastructures.

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Artificial intelligence for modelling infectious disease epidemics

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Nature 2025年第8051期638卷 623-635页

作者： Kraemer, Moritz U. G. Tsui, Joseph L.-H. Chang, Serina Y. Lytras, Spyros Khurana, Mark P. Vanderslott, Samantha Bajaj, Sumali Scheidwasser, Neil Curran-Sebastian, Jacob Liam Semenova, Elizaveta Zhang, Mengyan Unwin, H. Juliette T. Watson, Oliver J. Mills, Cathal Dasgupta, Abhishek Ferretti, Luca Scarpino, Samuel V. Koua, Etien Morgan, Oliver Tegally, Houriiyah Paquet, Ulrich Moutsianas, Loukas Fraser, Christophe Ferguson, Neil M. Topol, Eric J. Duchêne, David A. Stadler, Tanja Kingori, Patricia Parker, Michael J. Dominici, Francesca Shadbolt, Nigel Suchard, Marc A. Ratmann, Oliver Flaxman, Seth Holmes, Edward C. Gomez-Rodriguez, Manuel Schölkopf, Bernhard Donnelly, Christl A. Pybus, Oliver G. Cauchemez, Simon Bhatt, Samir Pandemic Sciences Institute University of Oxford Oxford United Kingdom Department of Biology University of Oxford Oxford United Kingdom Department of Electrical Engineering and Computer Science University of California Berkeley Berkeley CA United States UCSF UC Berkeley Joint Program in Computational Precision Health Berkeley CA United States Division of Systems Virology Department of Microbiology and Immunology The Institute of Medical Science The University of Tokyo Tokyo Japan Section of Epidemiology Department of Public Health University of Copenhagen Copenhagen Denmark Oxford Vaccine Group University of Oxford and NIHR Oxford Biomedical Research Centre Oxford United Kingdom Department of Epidemiology and Biostatistics Imperial College London London United Kingdom Department of Computer Science University of Oxford Oxford United Kingdom School of Mathematics University of Bristol Bristol United Kingdom MRC Centre for Global Infectious Disease Analysis School of Public Health Imperial College London London United Kingdom Department of Statistics University of Oxford Oxford United Kingdom Doctoral Training Centre University of Oxford Oxford United Kingdom Institute for Experiential AI Northeastern University MA Boston Thailand Santa Fe Institute Santa Fe NM United States World Health Organization Regional Office for Africa Brazzaville Congo WHO Hub for Pandemic and Epidemic Intelligence Health Emergencies Programme World Health Organization Berlin Germany Centre for Epidemic Response and Innovation (CERI) School for Data Science and Computational Thinking Stellenbosch University Stellenbosch South Africa African Institute for Mathematical Sciences (AIMS) South Africa Muizenberg Cape Town South Africa Genomics England London United Kingdom Scripps Research La Jolla CA United States Department of Biosystems Science and Engineering ETH Zürich Basel Switzerland Swiss Institute of Bioinformatics Lausanne Switzerland The Ethox Centre Nuffield

Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Artificial intelligence (AI) and related technologies, which are already supporting human decision making in economics, medicine and social science, have the potential to transform the scope and power of infectious disease epidemiology. Here we consider the application to infectious disease modelling of AI systems that combine machine learning, computational statistics, information retrieval and data science. We first outline how recent advances in AI can accelerate breakthroughs in answering key epidemiological questions and we discuss specific AI methods that can be applied to routinely collected infectious disease surveillance data. Second, we elaborate on the social context of AI for infectious disease epidemiology, including issues such as explainability, safety, accountability and ethics. Finally, we summarize some limitations of AI applications in this field and provide recommendations for how infectious disease epidemiology can harness most effectively current and future developments in AI. © Springer Nature Limited 2025.

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Emerging case oriented agents for sustaining educational institutions going green towards environmental responsibility

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Journal of systems and Information Technology 2019年第2期21卷 186-214页

作者： Anthony Jnr, Bokolo Abdul Majid, Mazlina Romli, Awanis Department of Computer Science Norwegian University of Science and Technology NTNU Trondheim Norway Universiti Malaysia Pahang Faculty of Computer Systems and Software Engineering Kuantan Malaysia

Purpose: The purpose of this paper is to design a system deployment model that integrates case-based agent technique to develop an eco-responsibility decision support tool for greening educational institutions toward environmental responsibility. Design/methodology/approach: Data were collected through questionnaires distributed among a statistical population that comprised practitioners across educational institutions in Malaysia that implement green practices. The questionnaire measured the feasibility of the developed tool based on factors derived from the literature. Accordingly, descriptive, exploratory and factor analysis approach using statistical package for social sciences (SPSS) was used to test the feasibility of the developed tool. Findings: Results from descriptive analysis confirm the tool is feasible based on mean values that range from 4.1619 to 3.6508 on a five-point scale, indicating that the tool is effective in sustaining educational institutions going green. Besides, results from exploratory analysis verify the reliability of the tool based on the acceptable Cronbach’s alpha reliability coefficient score higher than 0.7 and Kaiser–Meyer–Olkin value being above 0.5. Finally, results from factor analysis reveal that the developed tool is usable, efficient, helpful, flexible and credible and supports educational institutions in going green at 88.44 per cent of the total variance, suggesting that the respondents are satisfied with the tool. Research limitations/implications: The sample population in this study comprises only practitioners from educational institutions in Malaysia. Theoretically, this research provides feasibility factors and associated items that can be used in evaluating developed information systems. Practical implications: Practically, this study develops an eco-responsibility decision support tool to facilitate green strategies and provides information on how practitioners in educational institutions can improve green growth. So

关键词： Sustainable development

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Empirical topological investigation of practical supply chains based on complex networks

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Chinese Physics B 2017年第11期26卷 144-150页

作者：廖好沈婧吴兴桐陈博奎周明洋 National Engineering Laboratory for Big Data Computing Systems Guangdong Province Key Laboratory of Popular High Performance ComputersCollege of Computer Science and Software Engineering Shenzhen University Department of Computer Science School of Computing National University of Singapore

The industrial supply chain networks basically capture the circulation of social resource, dominating the stability and efficiency of the industrial system. In this paper, we provide an empirical study of the topology of smartphone supply chain network. The supply chain network is constructed using open online data. Our experimental results show that the smartphone supply chain network has small-world feature with scale-free degree distribution, in which a few high degree nodes play a key role in the function and can effectively reduce the communication cost. We also detect the community structure to find the basic functional unit. It shows that information communication between nodes is crucial to improve the resource utilization. We should pay attention to the global resource configuration for such electronic production management.

关键词： China supply chain networks complex networks data science network science

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A Machine Learning Approach for Expression Detection in Healthcare Monitoring systems

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computers, Materials & Continua 2021年第5期67卷 2123-2139页

作者： Muhammad Kashif Ayyaz Hussain Asim Munir Abdul Basit Siddiqui AaqifAfzaal Abbasi Muhammad Aakif Arif Jamal Malik Fayez Eid Alazemi Oh-Young Song Department of Computer Science&Software Engineering International Islamic UniversityIslamabad44000Pakistan Department of Computer Science Quaid-i-Azam UniversityIslamabad44000Pakistan Department of Computer Science Capital University of Science&TechnologyIslamabad44000Pakistan Department of Software Engineering Foundation UniversityIslamabad44000Pakistan Department of Computer Science Abdul Wali Khan UniversityMardan23200Pakistan Department of Computer Science and Information Systems College of Business StudiesPAAET12062Kuwait Department of Software Sejong UniversitySeoul05006Korea

Expression detection plays a vital role to determine the patient’s condition in healthcare *** helps the monitoring teams to respond swiftly in case of *** to the lack of suitable methods,results are often compromised in an unconstrained environment because of pose,scale,occlusion and illumination variations in the image of the face of the patient.A novel patch-based multiple local binary patterns(LBP)feature extraction technique is proposed for analyzing human behavior using facial expression *** consists of three-patch[TPLBP]and four-patch LBPs[FPLBP]based feature engineering *** representation is encoded from local patch statistics using these *** and FPLBP capture information that is encoded to find likenesses between adjacent patches of pixels by using short bit strings contrary to pixel-based *** images are transformed into the frequency domain using a discrete cosine transform(DCT).Most discriminant features extracted from coded DCT images are combined to generate a feature *** vector machine(SVM),k-nearest neighbor(KNN),and Naïve Bayes(NB)are used for the classification of facial expressions using selected *** experimentation is performed to analyze human behavior by considering standard extended Cohn Kanade(CK+)and Oulu–CASIA *** demonstrate that the proposed methodology outperforms the other techniques used for comparison.

关键词： Detection expressions gestures analytics pain patch-based local binary descriptor discrete cosine transform healthcare

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A Generalized Binary Tree Mechanism for Differentially Private Approximation of All-Pair Distances

arXiv

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arXiv 2025年

作者： Dinitz, Michael Fan, Chenglin Liu, Jingcheng Upadhyay, Jalaj Zou, Zongrui Department of Computer Science Johns Hopkins University United States Department of Computer Science and Engineering Seoul National University Korea Republic of State Key Laboratory for Novel Software Technology New Cornerstone Science Laboratory Nanjing University China Management Science & Information Systems Department Rutgers University United States

We study the problem of approximating all-pair distances in a weighted undirected graph with differential privacy, introduced by Sealfon [Sea16]. Given a publicly known undirected graph, we treat the weights of edges as sensitive information, and two graphs are neighbors if their edge weights differ in one edge by at most one. We obtain efficient algorithms with significantly improved bounds on a broad class of graphs which we refer to as recursively separable. In particular, for any n-vertex Kh-minor-free graph, our algorithm achieve an additive error of Õ(h(nW)1/3), where W represents the maximum edge weight;For grid graphs, the same algorithmic scheme achieve additive error of Õ(n1/4√W). Our approach can be seen as a generalization of the celebrated binary tree mechanism for range queries, as releasing range queries is equivalent to computing all-pair distances on a path graph. In essence, our approach is based on generalizing the binary tree mechanism to graphs that are recursively separable. Copyright © 2025, The Authors. All rights reserved.

关键词： Binary trees

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Collaborative creativity: From hand drawn sketches to formal domain specific models and back again

Collaborative creativity: From hand drawn sketches to formal...

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Workshop on Models and Their Role in Collaboration, MoRoCo 2013 - Co-located with the 13th European Conference on computer Supported Cooperative Work, ECSCW 2013

作者： Bartelt, Christian Vogel, Martin Warnecke, Tim Software Systems Engineering Department for Computer Science University of Clausthal Germany

Most of the time developers make extensive use of software tools in a software development process to support them in their day-to-day work. One of the first and most important phases is the design phase. Here tools are missing which support the creative and collaborative workflow (parallel/distributed). At the moment software designers uses classic whiteboards in team meetings to express their ideas. Subsequently a coworker uses a mobile phone or a camera to take photos of the work and remodel the picture with a modeling tool. That process is very inconvenient, error-prone and hinders a creative modeling cycle. For overcoming this ineffective process this paper shows a new approach to use digital whiteboards to transform free hand sketches in formal models and back again while modeling in a distributed team. The approach is completely independent from a pre-defined modeling language. It provides an interactive training mode to learn new graphical syntax elements and map these elements to formal metamodel entities. Based on the approach a collaborative sketch and modeling infrastructure was implemented. Copyright © 2013 for the individual papers by the papers' authors.

关键词： Modeling languages

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Data model extension for security event notification with dynamic risk assessment purpose

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science China(Information sciences) 2013年第11期56卷 36-44页

作者： David LOPEZ Oscar PASTOR Luis Javier GARCIA VILLALBA Group of Analysis Security and Systems (GASS) Department of Software Engineering and Artificial Intelligence (DISIA) School of Computer Science Universidad Complutense Madrid 28040 Spain

Dynamic risk assessment refers to a risk management framework where frequent updates of risk evaluation information are used to evaluate risk exposure,as close as possible to *** this paper,we present the incident object description exchange format extended model for dynamic risk *** format attempts to overcome the absence of integration and real-time communication between security systems and risk assessment *** model is based on the incident object definition exchange format,which is commonly used in the computer security incident response teams *** data model aims to facilitate a global vision of information systems risk by supplying real-time security events data to risk assessment tools based on renowned *** present a proof-of-concept scenario to demonstrate the usefulness of this integration and the proposed data model,and discuss the expected improvements.

关键词： dynamic risk assessment risk management DRA IODEF-DRA IODEF.

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