Journal articles: 'Collaborative and social computing'

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Alonso, Ricardo S., Javier Prieto, Óscar García, and Juan M. Corchado. "Collaborative learning via social computing." Frontiers of Information Technology & Electronic Engineering 20, no. 2 (February 2019): 265–82. http://dx.doi.org/10.1631/fitee.1700840.

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Vlachopoulou, Olympia. "Social Computing for Collaborative Learning in Higher Education." Journal of Digital Art & Humanities 3, no. 2 (December 27, 2022): 24–33. http://dx.doi.org/10.33847/2712-8148.3.2_2.

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This study aims to investigate the use of the specific social computing tool (Wiki) for collaborative learning, and study students’ perceptions in higher education. The participants of the study were a higher education student cohort in Bahrain. The data was collected through questionnaire and interviews. To demonstrate the intricacy of the investigation topic, a mixed methods data collection method was employed. Wiki as a social computing tool significantly enhances student collaboration, according to the preliminary questionnaire results and interviews with selected respondents. As a social computing tool, a Wiki has the potential to play a significant role in the future of learning settings, according to the study's findings.

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Moreno, Nathalie, Alejandro Pérez-Vereda, and Antonio Vallecillo. "Managing Reputation in Collaborative Social Computing Applications." Journal of Object Technology 21, no. 3 (2022): 3:1. http://dx.doi.org/10.5381/jot.2022.21.3.a1.

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Huang, Chenn-Jung, Heng-Ming Chen, Shun-Chih Chang, and Sheng-Yuan Chien. "Application of Social Computing to Collaborative Web Search." Open Journal of Social Sciences 03, no. 09 (2015): 28–33. http://dx.doi.org/10.4236/jss.2015.39005.

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Gonzalez, Patricia. "Anthropological Research and Collaborative Computing." Social Science Computer Review 14, no. 1 (April 1996): 21–23. http://dx.doi.org/10.1177/089443939601400106.

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Bin Zamanhuri, Mohd Afiq, Zalilah Abd Aziz, Rose Hafsah Abd Rauf, Elly Johana Johan, and Noratikah Shamsudin. "A review on various methods of collaborative computing." Indonesian Journal of Electrical Engineering and Computer Science 16, no. 2 (November 1, 2019): 1002. http://dx.doi.org/10.11591/ijeecs.v16.i2.pp1002-1008.

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Currently, mosques in Malaysia distribute their lecture schedules either on paper-based form or by uploading the schedule on their social media platform. This has some disadvantages such as paper schedules are susceptible to damages and information on social media platform is often not updated to current changes. Collaborative Computing is a system that enable individuals to work together remotely by making use of the reach ability of the internet. In order to utilise the Internet’s obvious advantages over paper-based and rapid information distribution and asynchronous communication, a review is conducted to study the available methods of collaborative computing, further analyse current research papers. Result shows that Centralized Computing method is the most suitable method for developing collaborative mobile application for Islamic Lectures schedule.

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Li, Yafei, Rui Chen, Jianliang Xu, Qiao Huang, Haibo Hu, and Byron Choi. "Geo-Social K-Cover Group Queries for Collaborative Spatial Computing." IEEE Transactions on Knowledge and Data Engineering 27, no. 10 (October 1, 2015): 2729–42. http://dx.doi.org/10.1109/tkde.2015.2419663.

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Huang, Lin Na, and Chun Li Liu. "Construction of Collaborative Learning Environment Supported by Cloud-Computing." Applied Mechanics and Materials 543-547 (March 2014): 3581–85. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.3581.

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In the field of education, cloud computing, as a basic environment and platform for the future network learning, will bring positive effect on construction of the learners' personal learning environment, on construction of school resources, on development of the educational information system. Based on the analysis of the cloud-computing influence on collaborative learning, this paper puts forward the construction strategy of collaborative learning environment supported by cloud-computing and the specific application case, which will provide reference for cloud-computing application in education informatization and social network learning.

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Ortegat, Guillaume, Donatien Grolaux, Etienne Riviere, and Jean Vanderdonckt. "Engineering the Transition of Interactive Collaborative Software from Cloud Computing to Edge Computing." Proceedings of the ACM on Human-Computer Interaction 6, EICS (June 14, 2022): 1–31. http://dx.doi.org/10.1145/3532210.

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The "Software as a Service" (SaaS) model of cloud computing popularized online multiuser collaborative software. Two famous examples of this class of software are Office 365 from Microsoft and Google Workspace. Cloud technology removes the need to install and update the software on end users' computers and provides the necessary underlying infrastructure for online collaboration. However, to provide a good end-user experience, cloud services require an infrastructure able to scale up to the task and allow low-latency interactions with a variety of users worldwide. This is a limiting factor for actors that do not possess such infrastructure. Unlike cloud computing which forgets the computational and interactional capabilities of end users' devices, the edge computing paradigm promises to exploit them as much as possible. To investigate the potential of edge computing over cloud computing, this paper presents a method for engineering interactive collaborative software supported by edge devices for the replacement of cloud computing resources. Our method is able to handle user interface aspects such as connection, execution, migration, and disconnection differently depending on the available technology. We exemplify our approach by developing a distributed Pictionary game deployed in two scenarios: a nonshared scenario where each participant interacts only with their own device and a shared scenario where participants also share a common device, including a TV. After a theoretical comparative study of edge vs. cloud computing, an experiment compares the two implementations to determine their effect on the end user's perceived experience and latency vs. real latency.

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Liu, Xun. "Blockchain-Enabled Collaborative Edge Computing for Intelligent Education Systems Using Social IoT." International Journal of Distributed Systems and Technologies 13, no. 7 (July 12, 2022): 1–19. http://dx.doi.org/10.4018/ijdst.307958.

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As new technologies such as the internet of things, big data analysis, artificial intelligence, and cloud computing are widely used, intelligent learning platforms and web-based educational platforms are gaining popularity. Social internet of things (SIoT) uses mobile edge computing and interpersonal interactions among SIoT users to take advantage of the benefits that collaborative edge computing (CEC) offers, even while posing new challenges. The communication efficiency and the security of intelligent education systems must be considerably developed to ensure real-time services. Therefore, this work deliberates an advanced structural framework for a blockchain-enabled 6G communication network (BC-6GCN) for the intelligent education system. Schools must analyze massive data volumes to provide intelligent education services, leaving the data open to manipulation by malicious hackers. The challenges discussed can lead to the potential advancement of protected, reliable, and smart SIoT frameworks.

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Patel, Ahmed, Mona Taghavi, Joaquim Celestino Júnior, Rodziah Latih, and Abdullah Mohd Zin. "Safety Measures for Social Computing in Wiki Learning Environment." International Journal of Information Security and Privacy 6, no. 2 (April 2012): 1–15. http://dx.doi.org/10.4018/jisp.2012040101.

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Wikis are social networking systems that allow users to freely intermingle at different levels of communication such as collaborative learning, chatting, and group communications. Although a great idea and goal, it’s particularly vulnerable due to its features of open medium and lack of clear plan of defense. Personal data can be misused for virtual insulting, resulting in misuse of personal information for financial gains or creating misuses. Wikis are an example of social computing of collaborative learning, joint editing, brain storming, and virtual socializing, which is a ripe environment for hacking, deception, abuse, and misuse. Thus, wiki needs comprehensive security measures which include privacy, trust, security, audit, and digital forensics to protect users and system resources. This paper identifies and explores the needs of secure social computing and supporting information systems as places for interaction, data collection, and manipulation for wikis. It does this by reviewing the literature and related works in proposing a safety measure framework for a secure and trustworthy medium together with privacy, audit, and digital forensic investigative functions in wiki environments. These then can aid design and usage in social computing environments with the proviso to give comfort and confidence to users without worrying about abuse and cybercrime perpetrated activities.

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Ai, Yutong, Li Wang, Zhu Han, Ping Zhang, and Lajos Hanzo. "Social Networking and Caching Aided Collaborative Computing for the Internet of Things." IEEE Communications Magazine 56, no. 12 (December 2018): 149–55. http://dx.doi.org/10.1109/mcom.2018.1701089.

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Arinze, Bay. "E-Research Collaboration in Academia and Industry." International Journal of e-Collaboration 8, no. 2 (April 2012): 1–13. http://dx.doi.org/10.4018/jec.2012040101.

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E-Collaboration has come of age in the last decade, with industry and academia using the latest web-based collaborative software to bring together groups of workers to work on common tasks. Research is a $370 billion industry in the United States and is conducted in every sector of the economy. It has collaboration at its core. Most innovations result from collaborative efforts between groups of workers who are often geographically dispersed. Academic leaders now seek the synergies that result from collaboration between their research faculty and others. Web 2.0-based research portals have emerged that allow knowledge sharing and lowering of social barriers between researchers. Another important development is cloud computing, which has dramatically reduced computing costs for organizations. These tools allow researchers in both industry and academia to extend their range and reach, gain synergies between dispersed groups, and increase research efficiency and effectiveness. This paper examines the use of e-research collaboration tools in industry and academia. It describes a framework that matches an organization’s e-research collaboration needs to e-research collaboration solutions across several critical dimensions. The proposed framework will help to improve the understanding of available options for e-collaboration infrastructures, particularly in the sub-area of e-research. It will also help to identify the fit between these infrastructures and organizational e-research collaboration needs.

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Cheng, Yong, Jie Du, Yonggang Yang, Zhibao Ma, Ning Li, Jia Zhao, and Di Wu. "Designing Collaborative Edge Computing for Electricity Heterogeneous Data Based on Social IoT Systems." International Journal of Distributed Systems and Technologies 13, no. 7 (July 12, 2022): 1–22. http://dx.doi.org/10.4018/ijdst.307955.

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Power generation, transmission, maintenance costs, and electricity prices are heavily influenced by accurate load forecasts at energy suppliers' operation centers. Every aspect of our life has been transformed by the social internet of things (SIoT). Collaborative edge computing (CEC) has emerged as a new paradigm for meeting the demands of the internet of things by alleviating resource congestion (IoT). Remote devices can connect to CEC's processing, storage, and network resources. About short-term electrical load forecasting, this study explores the application of feed-forward deep neurological networking (FF-DNN) and recurrent deep neuronal networking (R-DNN) methods and analyzes their accuracy and computing performance. A dynamic prediction system using a deep neural network (DPS-DNN) is proposed in this research. The recently unveiled smartgrid with the results shows the higher performance of the proposed DPS-DNN model than the existing models with an enhancement of 93.15% based on collaborative edge networks based on SIoT.

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Zhou, Chuan, Suying Gui, Yan Liu, Junpeng Ma, and Hao Wang. "Perspectives of Collaborative Governance: Integration of Social and Cognitive Computing with Complex Networks." Mobile Information Systems 2023 (June 2, 2023): 1–6. http://dx.doi.org/10.1155/2023/2162076.

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In the current era, big data play a very important role in various government organizations. Therefore, it is necessary to connect government big data with the national modern governance system since it is a crucial resource, asset, technology, and service support facility for government departments. The government information system requires complex system engineering. The collaborative governance of government data by integrating cognitive computing and complex networks is conducive to eliminating the contradiction and tension between policies and policy subjects. It can reduce the cross and overlap of functions between different departments and form a collaborative mechanism of other governance subjects. The suggested mechanism enhanced the government governance content integrity and system synergy. The modernization of the system is also boosted by governance capacity.

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Pulimood, S. Monisha, Kim Pearson, and Diane Bates. "Encouraging CS students to compute for social good through collaborative, community-engaged projects." ACM SIGCAS Computers and Society 49, no. 1 (January 22, 2021): 21–22. http://dx.doi.org/10.1145/3447892.3447900.

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Which pedagogical techniques better engage computer science (CS) students in computing for social good? We examine this question with students enrolled in classes using the Collaborating Across Boundaries to Engage Undergraduates in Computational Thinking (CABECT) pedagogical model, that pairs CS and non-CS courses with a community partner to propose solutions to a local problem. Pre- and post-tests of self-assessed concerns about civic responsibility, global responsibility, and local civic efficacy were administered to the students in a three-year long pedagogical experiment, which paired five CS courses with five journalism courses. While CS students were not statistically different from their journalism peers in pre-test measures of social and global responsibility, they lagged behind in local efficacy. In the posttest, CS students had significantly increased their sense of local efficacy to the extent that they were statistically indistinguishable from journalism students. Community-engaged learning projects, such as the one in the CABECT model, show great potential for attracting students to computing for social good.

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Zhang, Qiansha, and Gang Li. "Innovative Knowledge Automation Framework in DM and Collaborative Edge Computing Social IoT Systems." International Journal of Distributed Systems and Technologies 13, no. 7 (July 12, 2022): 1–23. http://dx.doi.org/10.4018/ijdst.307953.

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Digital marketing-based innovative knowledge management helps people inspire creativity and cultural changes required to advance the organization and satisfy changing business requirements. Knowledge workers can respond more rapidly when they have quicker access to resources and information across the company. A knowledge-based approach views innovation as a process characterized by the knowledge needed to understand how the innovation was created. The term “digital marketing automation” (DMA) refers to software platforms and technologies built for marketing departments and enterprises to sell online and automate tedious tasks more effectively. Digital marketing encompasses all forms of advertising that take place online, including but not limited to websites, search engines, social media, email, and mobile apps. An entirely new approach to big data processing has emerged because of the rise of edge computing in the internet of things environment. As a result of these findings, a distributed neural network cloud-edge computing paradigm is presented.

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Hu, Shaopeng. "Physical Education Teaching Quality Evaluation Method Using Collaborative Edge Computing and Social Internet of Things." International Journal of Distributed Systems and Technologies 13, no. 7 (July 12, 2022): 1–23. http://dx.doi.org/10.4018/ijdst.307951.

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A quality assessment technique for physical education and digital hybrid learning application of mobile edge devices is presented to improve physical education and evaluation hybrid instruction. As a result, the primary goal of this study is to showcase the rapid gains of social internet of things (SIoT) materials for applications and to provide various challenges and opportunities for future cases with collaborative edge computing (CEC). This work creates the quality assessment indicator system of mixed physical and digital evaluation based on aim, index, the value of the index, and assessment standard. Collaborative edge computing and social internet of things in the classroom for research into the use of SIoT and its implementations in underdeveloped nations is strongly encouraged, according to the findings of this study by increasing 28.1% enhancement. The fuzzy extensive analysis methodology is employed to successfully achieve the hybrid physical training quality assessment and digital evaluation method.

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Sandí Delgado, Juan Carlos, and Patricia Bazán. "Educational Serious Games as a Service: Challenges and Solutions." Journal of Computer Science and Technology 19, no. 01 (April 17, 2019): e07. http://dx.doi.org/10.24215/16666038.19.e07.

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Cloud computing is a distributed computing technology that facilitates access to resources in a dynamic and scalable way which is highly available. One of the service models is SaaS (Software as a Service) which allows executing Web applications flexible and elastically while offering collaborative characteristics. The integration of SaaS in educational environments promotes academic performance and facilitates knowledge management, allowing for storage, exchange, access, and synchronization of information. On the other hand, serious educational games promote among the people involved: collaboration, communication, social abilities, critical thinking, and problems solving. The present work analyzes the challenges that SaaS, with its collaborative and Multi-Tenant characteristics, offer to the execution of serious educational games, this is named JSEaaS –Serious Educational Games as a Service. The analysis was developed based on an exhaustive and systematic bibliographic revision with a qualitative methodological focus, which generated investigation questions, search strategies, keywords and inclusion and exclusion criteria that were applied to identify articles in different sources. This work allowed for the development of a list of the functional characteristics that the serious educational games will acquire when used as software as a service.

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Chapelle, Carol A. "LANGUAGE LEARNING THROUGH SOCIAL COMPUTING: OCCASIONAL PAPERS OF THE APPLIED LINGUISTICS ASSOCIATION OF AUSTRALIA, 16.Robert Debski, June Gassin, and Mike Smith (Eds.). Melbourne: ALAA & The Horwood Language Centre, 1997. Pp. viii + 224. A$12.00 paper." Studies in Second Language Acquisition 21, no. 3 (September 1999): 502–3. http://dx.doi.org/10.1017/s0272263199283076.

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The papers in Language learning through social computing introduce the classroom practices and philosophical underpinnings of computer-assisted language learning (CALL), which builds on collaborative approaches to L2 teaching and learning. The majority of the essays address general issues in collaborative learning through CALL, describing the authors' experience and reflections on L2 activities designed to engage learners in interesting discussions and projects, many of which rely on target language materials from the Internet.

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Ning, Zhaolong, Meng Chu Zhou, Yong Yuan, Edith C. H. Ngai, and Ricky Yu-Kwong Kwok. "Guest Editorial Special Issue on Collaborative Edge Computing for Social Internet of Things Systems." IEEE Transactions on Computational Social Systems 9, no. 1 (February 2022): 59–63. http://dx.doi.org/10.1109/tcss.2022.3145152.

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Wang, Tao, Qingpeng Zhang, Zhong Liu, Wenli Liu, and Ding Wen. "On social computing research collaboration patterns: a social network perspective." Frontiers of Computer Science 6, no. 1 (January 27, 2012): 122–30. http://dx.doi.org/10.1007/s11704-011-1173-9.

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Polli, Andrea. "A Walk in the Woods: Investigating Ethical Design, Ubiquitous Computing and Social Media." Leonardo 47, no. 5 (October 2014): 504–5. http://dx.doi.org/10.1162/leon_a_00824.

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This paper will examine what has been learned through three years of research by an interdisciplinary university laboratory investigating ethical design and media. The University of New Mexico’s Social Media Workgroup (SMW) is an environment in which faculty, undergraduate and graduate students, and outside experts work in interdisciplinary collaborative teams to design and develop a wide variety of media tools, assets and events including the large-scale projection work Particle Falls visualizing real-time air quality in San Jose, California, and a permanent public work at the University of Utah, E-Oculus.

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Xu, Min, Mei Qi Fang, Pan Pan Yang, and Yu Chen. "Research on Personalized Learning Service Based on Collaborative Filtering Method." Advanced Materials Research 159 (December 2010): 252–57. http://dx.doi.org/10.4028/www.scientific.net/amr.159.252.

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In this paper, we discussed various personalized learning recommendation service and their advantages and disadvantages. On the basis of these methods, we proposed the similarity degree computing algorithm and user community discover algorithm. After verifying, analyzing and evaluating these algorithms and the recommendation model, we applied it as a recommendation service in SGCL (Social Group Collaborative Learning) System. Using the model in SGCL system, the system can recommend user personalized information and practical data proves that it can improve the learning quality effectively.

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Chandra, Ramesh, Reethika S. Iyer, and Ramakrishnan Raman. "Enabling organizations to implement smarter, customized social computing platforms by leveraging knowledge flow patterns." Journal of Knowledge Management 19, no. 1 (February 9, 2015): 95–107. http://dx.doi.org/10.1108/jkm-11-2014-0455.

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Purpose – The purpose of this study was to understand the knowledge sharing in projects based on knowledge flow patterns. The impact of attrition, thereby leading to a loss of tacit knowledge, inability to capture and reuse knowledge and inability to understand the knowledge flow patterns, which leads to lack of structured workspace collaboration, are frequently faced challenges in organizations. The change in knowledge sourcing behaviors by the current generation workforce has a high reaching impact in driving collaboration among employees. Design/methodology/approach – This paper attempts to study this impact and identify means to improve the effectiveness of collective knowledge sharing via social computing platforms. As part of this study, customized solutions are devised based on knowledge flow patterns prevalent in teams. Knowledge network analysis (KNA), a socio-metric analysis, is performed to understand knowledge flow patterns among employees in a team which helps understand the relationships between team members with respect to knowledge sharing. KNA helps in understanding ties and interactions between human and system resources. Findings – Significant changes were observed in knowledge sourcing and sharing behaviors. Capture of the tacit knowledge of employees further resulted in reducing the impact of knowledge attrition. For instance, targeted communities of practice (CoPs) based on the presence of cliques within teams enabled teams to complete projects effectively and efficiently. Practical implications – The results are used to identify push and pull networks to enable effective knowledge management (KM). Results of this study reveal that analyzing knowledge flow patterns in a team and deploying a customized social computing platform that is tailored to address the needs of specific knowledge flow patterns within that team, significantly enhances collaborative sharing as opposed to a standardized “one-size-fits-all” platform. Originality/value – This paper is an original creation after research by the authors for a continuous assessment of KM within the organization.

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Chaudhary, Sunil, Eleni Berki, Linfeng Li, and Juri Valtanen. "Time Up for Phishing with Effective Anti-Phishing Research Strategies." International Journal of Human Capital and Information Technology Professionals 6, no. 2 (April 2015): 49–64. http://dx.doi.org/10.4018/ijhcitp.2015040104.

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Public awareness is a significant factor in the battle against online identity theft (phishing). Advancing public readiness can be a strategic protection mechanism for citizens' vulnerability and privacy. Further, an effective research strategy against phishing is the combination of increased social awareness with software quality and social computing. The latter will decrease phishing victims and will improve information systems quality. First, the authors discuss recent research results on software quality criteria used for the design of anti-phishing technologies. Second, it is argued that the dynamics of social surroundings affect citizens' trust and can compromise social security. Third, the authors outline basic research needs and strategic steps to be taken for timely citizens' protection. Last, the authors propose strategic research directions for improving information systems total quality management through international collaborative research and by focusing on: i) increasing social awareness; ii) predicting information phishing attempts; iii) adopting social computing approaches.

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Yadav, Poonam, Ioannis Charalampidis, Jeremy Cohen, John Darlington, and Francois Grey. "A Collaborative Citizen Science Platform for Real-Time Volunteer Computing and Games." IEEE Transactions on Computational Social Systems 5, no. 1 (March 2018): 9–19. http://dx.doi.org/10.1109/tcss.2017.2771479.

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SENGUPTA, BIKRAM, ANSHU JAIN, KAMAL BHATTACHARYA, HONG-LINH TRUONG, and SCHAHRAM DUSTDAR. "COLLECTIVE PROBLEM SOLVING USING SOCIAL COMPUTE UNITS." International Journal of Cooperative Information Systems 22, no. 04 (December 2013): 1341002. http://dx.doi.org/10.1142/s0218843013410025.

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Service process orchestration using workflow technologies has led to significant improvements in generating predicable outcomes by automating tedious manual tasks but suffer from challenges related to the flexibility required in work especially when humans are involved. Recently emerging trends in enterprises to explore social computing concepts have realized value in more agile work process orchestrations but tend to be less predictable with respect to outcomes. In this paper, we use IT services management, specifically, incident management for large scale systems, to investigate the interplay of workflow systems and social computing. We apply a recently introduced concept of social compute units (SCU), and flexible teams sourced based on various parameters such as skills, availability, incident urgency, etc. in the context of resolution of incidents in an IT service provider organization. Results from simulation-based experiments indicate that the combination of SCUs and workflow based processes can lead to significant improvement in key service delivery outcomes, with average resolution time per incident and number of SLO violations being at times as low as 53.7% and 38.1%, respectively of the corresponding values for pure workflow based incident management. Moreover, significant benefits may also be obtained through cross-skilling of practitioners via exposure to new skills in the context of collaborative work.

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Yuan, Jie, Erxia Li, Chaoqun Kang, Fangyuan Chang, and Xiaoyong Li. "Review of the D2D Trusted Cooperative Mechanism in Mobile Edge Computing." Information 10, no. 8 (August 15, 2019): 259. http://dx.doi.org/10.3390/info10080259.

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Mobile edge computing (MEC) effectively integrates wireless network and Internet technologies and adds computing, storage, and processing functions to the edge of cellular networks. This new network architecture model can deliver services directly from the cloud to the very edge of the network while providing the best efficiency in mobile networks. However, due to the dynamic, open, and collaborative nature of MEC network environments, network security issues have become increasingly complex. Devices cannot easily ensure obtaining satisfactory and safe services because of the numerous, dynamic, and collaborative character of MEC devices and the lack of trust between devices. The trusted cooperative mechanism can help solve this problem. In this paper, we analyze the MEC network structure and device-to-device (D2D) trusted cooperative mechanism and their challenging issues and then discuss and compare different ways to establish the D2D trusted cooperative relationship in MEC, such as social trust, reputation, authentication techniques, and intrusion detection. All these ways focus on enhancing the efficiency, stability, and security of MEC services in presenting trustworthy services.

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Jiang, Jielin, Xing Zhang, and Shengjun Li. "A Task Offloading Method with Edge for 5G-Envisioned Cyber-Physical-Social Systems." Security and Communication Networks 2020 (August 7, 2020): 1–9. http://dx.doi.org/10.1155/2020/8867094.

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Recently, Cyber-Physical-Social Systems (CPSS) have been introduced as a new information physics system, which enables personnel organizations to control physical entities in a reliable, real-time, secure, and collaborative manner through cyberspace. Moreover, with the maturity of edge computing technology, the data generated by physical entities in CPSS are usually sent to edge computing nodes for effective processing. Nevertheless, it remains a challenge to ensure that edge nodes maintain load balance while minimizing the completion time in the event of the edge node outage. Given these problems, a Unique Task Offloading Method (UTOM) for CPSS is designed in this paper. Technically, the system model is constructed firstly and then a multi-objective problem is defined. Afterward, Improving the Strength Pareto Evolutionary Algorithm (SPEA2) is utilized to generate the feasible solutions of the above problem, whose aims are optimizing the propagation time and achieving load balance. Furthermore, the normalization method has been leveraged to produce standard data and select the global optimal solution. Finally, several necessary experiments of UTOM are introduced in detail.

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Neagu, Ioan-Mădălin. "Sustainable Smart Cities: A Fog Computing Framework for a Smart Urban Transport Network." Studia Universitatis „Vasile Goldis” Arad – Economics Series 28, no. 4 (December 1, 2018): 68–80. http://dx.doi.org/10.2478/sues-2018-0021.

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Abstract In the present paper, a fog computing framework for smart urban transport is developed. The proposed framework is adapted to the smart city concept. It uses a collaborative multitude of end-user clients to carry out a substantial amount of communication and computation. It can be adapted for specific situations of smart cities in Romania, such as: Cluj-Napoca, Timișoara, Iași or Bucharest. Economic and social implications as well as available European funding sources are presented.

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McDowell, James. "A Black Swan in a Sea of White Noise: Using Technology-Enhanced Learning to Afford Educational Inclusivity for Learners with Asperger’s Syndrome." Social Inclusion 3, no. 6 (December 28, 2015): 7–15. http://dx.doi.org/10.17645/si.v3i6.428.

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Against a backdrop of increasingly vocation-focussed course provision within higher education, of widening participation initiatives intended to promote greater inclusion for learners affected by learning difficulties, and of moves towards greater use of social and collaborative forms of learning, this paper discusses the case of an undergraduate Computing student affected by Asperger’s Syndrome (AS).While there is recognition in the literature of problems associated with face-to-face dialogue for persons affected by AS, there is a paucity of research both into the experience of students in higher education, and around the issue of participation in group-work activities increasingly found in creative aspects of computing. This paper highlights a tension between moves towards collaborative learning and UK disabilities legislation in relation to learners with AS. Employing a qualitative case-study methodology, the investigation revealed how a technology-enhanced learning intervention afforded an AS-diagnosed learner greater opportunities to participate in group-work in a higher education context. The findings suggest that not only can computer-mediated communications afford AS-diagnosed learners opportunities to participate meaningfully in group-work, but also that the learner demonstrated higher levels of collective-inclusive versus individual-exclusive phraseology than neurotypical peers, thereby challenging assumptions around participation in collaborative learning activities and assimilation of peer-feedback.

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Pater, Jessica, and Raquel Oliveira Prates. "Editorial Introduction - Supporting Group Work." Proceedings of the ACM on Human-Computer Interaction 7, GROUP (December 29, 2022): 1. http://dx.doi.org/10.1145/3567551.

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Explorations into groupwork research have expanded over the years to encompass broader themes like human-centered computing, human-computer interaction, social computing, and human- centered data science, and other related contexts. Like the previous PACM:HCI volumes for Group Work (volumes 5 and 6), this volume contains the tradition of design fictions in addition to short- form and long-from research articles. The work presented in this issue spans a wide range of disciplines, methods, and theoretical foundations. Paper topics range from perceptions of justice and participation to using AI to increase inclusivity and participation to safety. Application domains were varied ranging from social media norms to internet safety to robotics to collaborative programming and beyond. Specific communities were also the focus of the research, including specific gender and ethnic groups to non-profits and other community groups.

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Liu, Danqing, and Luqun Liu. "Collaborative Edge Computing Advances in Children's Behavior Observation for Social Internet of Things Systems in Preschool Education." International Journal of Distributed Systems and Technologies 13, no. 7 (July 12, 2022): 1–21. http://dx.doi.org/10.4018/ijdst.307952.

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Teachers who observe and analyze children's conduct can learn more about children and the reasons for their behavior. Promoting the fusion of adult and preschool vision through discussion is a basic competency of preschool teachers.Social Internet of Things (SIoT) uses recent advances in collaborativeand social relationships among SIoT users to take advantage of the network's strengths while posing new challenges.With the help of the theory of development, behavioral cues, and individual circumstances, a thorough and holistic interpretation can be made of children's behavior.There is a brief introduction to the concepts of collaborative edge computing and data storage in addition to examples of various socially-minded solutions; for long last, a list of research obstacles is provided. When measured numerically, the ECBO has a positive impact on student accomplishment (97.9%), developmental progress (95.3%), interpersonal interaction (94.6%), parental participation (98.5%), and attention ratio (98%).

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Hao, Fei, Doo-Soon Park, Jungho Kang, and Geyong Min. "2L-MC 3: A Two-Layer Multi-Community-Cloud/Cloudlet Social Collaborative Paradigm for Mobile Edge Computing." IEEE Internet of Things Journal 6, no. 3 (June 2019): 4764–73. http://dx.doi.org/10.1109/jiot.2018.2867351.

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Shinohara, Kristen, Murtaza Tamjeed, Michael McQuaid, and Dymen A. Barkins. "Usability, Accessibility and Social Entanglements in Advanced Tool Use by Vision Impaired Graduate Students." Proceedings of the ACM on Human-Computer Interaction 6, CSCW2 (November 7, 2022): 1–21. http://dx.doi.org/10.1145/3555609.

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Despite increasing work investigating the accessibility of research tools, most accessibility research has traditionally focused on popular, mainstream, or web technologies. We investigated barriers and workarounds blind and low vision doctoral students in computing-intensive disciplines experienced and engaged, respectively, when using advanced technical tools for research tasks. We conducted an observation and interview study with eight current and former Ph.D. students, closely analyzing the accessibility of specific tasks. Our findings contextualize how inaccessible tools complicate research tasks, adding time and effort, and exacerbating social entanglements in collaborative relationships. This work contributes empirical data that extricates how in/accessibility of advanced technical tools used in research influences productivity and collegial efforts.

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Konomi, Shin'ichi, and Chang S. Nam. "Supporting Collaborative Privacy-Observant Information Sharing Using RFID-Tagged Objects." Advances in Human-Computer Interaction 2009 (2009): 1–13. http://dx.doi.org/10.1155/2009/713516.

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RFID technology provides an economically feasible means to embed computing and communication capabilities in numerous physical objects around us, thereby allowing anyone to effortlessly announce and expose varieties of information anywhere at any time. As the technology is increasingly used in everyday environments, there is a heightening tension in the design and shaping of social boundaries in the digitally enhanced real world. Our experiments of RFID-triggered information sharing have identified usability, deployment, and privacy issues of physically based information systems. We discuss awareness issues and cognitive costs in regulating RFID-triggered information flows and propose a framework for privacy-observant RFID applications. The proposed framework supports users' in situ privacy boundary control by allowing users to (1) see how their information is socially disclosed and viewed by others, (2) dynamically negotiate their privacy boundaries, and (3) automate certain information disclosure processes.

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Costa, Carlos, José Oliveira, and Eriksson Melício Monteiro. "A Cloud Architecture for Teleradiology-as-a-Service." Methods of Information in Medicine 55, no. 03 (2016): 203–14. http://dx.doi.org/10.3414/me14-01-0052.

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SummaryBackground: Telemedicine has been promoted by healthcare professionals as an efficient way to obtain remote assistance from specialised centres, to get a second opinion about complex diagnosis or even to share knowledge among practitioners. The current economic restrictions in many countries are increasing the demand for these solutions even more, in order to optimize processes and reduce costs. However, despite some technological solutions already in place, their adoption has been hindered by the lack of usability, especially in the set-up process. Objectives: In this article we propose a tele-medicine platform that relies on a cloud computing infrastructure and social media principles to simplify the creation of dynamic user-based groups, opening up opportunities for the establishment of teleradiology trust domains.Methods: The collaborative platform is provided as a Software-as-a-Service solution, supporting real time and asynchronous collaboration between users. To evaluate the solution, we have deployed the platform in a private cloud infrastructure. The system is made up of three main components – the collaborative framework, the Medical Management Information System (MMIS) and the HTML5 (Hyper Text Markup Language) Web client application – connected by a message-oriented middleware.Results: The solution allows physicians to create easily dynamic network groups for synchronous or asynchronous cooperation. The network created improves dataflow between colleagues and also knowledge sharing and cooperation through social media tools. The platform was implemented and it has already been used in two distinct scena -rios: teaching of radiology and tele-reporting.Conclusions: Collaborative systems can simplify the establishment of telemedicine expert groups with tools that enable physicians to improve their clinical practice. Stream -lining the usage of this kind of systems through the adoption of Web technologies that are common in social media will increase the quality of current solutions, facilitating the sharing of clinical information, medical imaging studies and patient diagnostics among collaborators.

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Martinez-Pabon, Francisco, Juan Camilo Ospina-Quintero, Gustavo Ramirez-Gonzalez, and Mario Munoz-Organero. "Recommending Ads from Trustworthy Relationships in Pervasive Environments." Mobile Information Systems 2016 (2016): 1–18. http://dx.doi.org/10.1155/2016/8593173.

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The use of pervasive computing technologies for advertising purposes is an interesting emergent field for large, medium, and small companies. Although recommender systems have been a traditional solution to decrease users’ cognitive effort to find good and personalized items, the classic collaborative filtering needs to include contextual information to be more effective. The inclusion of users’ social context information in the recommendation algorithm, specifically trust in other users, may be a mechanism for obtaining ads’ influence from other users in their closest social circle. However, there is no consensus about the variables to use during the trust inference process, and its integration into a classic collaborative filtering recommender system deserves a deeper research. On the other hand, the pervasive advertising domain demands a recommender system evaluation from a novelty/precision perspective. The improvement of the precision/novelty balance is not only a matter related to the recommendation algorithm itself but also a better recommendations’ display strategy. In this paper, we propose a novel approach for a collaborative filtering recommender system based on trust, which was tested throughout a digital signage prototype using a multiscreen scheme for recommendations delivery to evaluate our proposal using a novelty/precision approach.

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Valverde, Jose A. "Healthcare through social computing: a case for public private collaboration." International Journal of Management and Network Economics 1, no. 3 (2009): 343. http://dx.doi.org/10.1504/ijmne.2009.030596.

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Karuna, Prakruthi, Mohammad Rana, and Hemant Purohit. "CitizenHelper: A Streaming Analytics System to Mine Citizen and Web Data for Humanitarian Organizations." Proceedings of the International AAAI Conference on Web and Social Media 11, no. 1 (May 3, 2017): 729–30. http://dx.doi.org/10.1609/icwsm.v11i1.14863.

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Vast information available on social media through citizen sensing, complemented by diverse Web sources such as blogs, and news present an unprecedented opportunity for organizations to improve their work practices using such data. We will demo a novel, scalable and interactive streaming analytics system with a collaborative visual dashboard. The proposed system mines heterogeneous information streams from social and web platforms for analyzing real world events in humanitarian domain, along dimensions of information source demographics, time, location, and content summaries. Specific use-cases of gender-based violence and global displacements will be presented to demonstrate contrasting analyses of diverse data sources, unlike existing social computing systems with single data source, in humanitarian domain.

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He, Wang, and Huang Xiang. "Research on Collaborative Innovation Strategy of Smart Supply Chain in the Big Data Era." E3S Web of Conferences 235 (2021): 03073. http://dx.doi.org/10.1051/e3sconf/202123503073.

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With the continuous emergence of new technologies such as Artificial intelligence, big data, Cloud computing and IOT, technology accelerates integration and innovation, and data dividends have continued to emerge. At the same time, China’s “Internet Action Plan”, “Made in China 2025”, “Digital China” and other national strategies have been implemented in depth, China’s social and economic development has entered the era of big data. As the basic industry of the national economy. The logistics industry will also accelerate changes, and it has become a development trend for companies to use new technologies to realize smart supply chain collaborative innovation. The paper analyzes the development opportunities of smart supply chain in the Big Data Era, summarizes the problems encountered in the application of big data in the smart supply chain at this stage, and finally puts forward the collaborative innovation strategy for smart supply chain in the Big Data Era, Providing reference for collaborative innovation development of enterprise supply chain.

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Liu, Xiaozhen, Zuozhi Wang, Shengquan Ni, Sadeem Alsudais, Yicong Huang, Avinash Kumar, and Chen Li. "Demonstration of collaborative and interactive workflow-based data analytics in texera." Proceedings of the VLDB Endowment 15, no. 12 (August 2022): 3738–41. http://dx.doi.org/10.14778/3554821.3554888.

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Collaborative data analytics is becoming increasingly important due to the higher complexity of data science, more diverse skills from different disciplines, more common asynchronous schedules of team members, and the global trend of working remotely. In this demo we will show how Texera supports this emerging computing paradigm to achieve high productivity among collaborators with various backgrounds. Based on our active joint projects on the system, we use a scenario of social media analysis to show how a data science task can be conducted on a user friendly yet powerful platform by a multi-disciplinary team including domain scientists with limited coding skills and experienced machine learning experts. We will present how to do collaborative editing of a workflow and collaborative execution of the workflow in Texera. We will focus on data-centric features such as synchronization of operator schemas among the users during the construction phase, and monitoring and controlling the shared runtime during the execution phase.

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Rohanifar, Yasaman, Sharifa Sultana, Shaid Hasan, Priyank Chandra, and Syed Ishtiaque Ahmed. ""Kabootar": Towards Informal, Trustworthy, and Community-Based FinTech for Marginalized Immigrants." Proceedings of the ACM on Human-Computer Interaction 6, CSCW2 (November 7, 2022): 1–32. http://dx.doi.org/10.1145/3555109.

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Financial technology (FinTech) platforms often exclude certain countries from their services due to global political conflicts. As a result, immigrants from these neglected countries struggle with transferring money to and from their homeland through formal mechanisms. Instead, they get involved in informal transnational transactions that, while flexible, are often risky and full of hassles. We looked into this issue through an online survey (n=127) and engaged with multiple stakeholders (n=16), including the Iranian immigrant community in Canada, to co-design an application called ?Kabootar' that matches senders and receivers of money across borders. In this application, a sender-receiver pair is matched with a pertinent pair sending money in the opposite direction. By facilitating two intra-national transactions in local currencies instead of two relatively complicated inter-national transactions, the need for money to cross borders is eliminated while staying within the boundaries of the law. Our user study (n=13) revealed several tensions in users trusting such informal transnational transactions. This work contributes to CSCW, HCI, and social computing's growing scholarship in personalized and collaborative computing technologies by advocating for a novel design approach based on collaboration and informality and extends their scope to the domain of FinTech for politically marginalized communities.

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Shen, Xuehao, Yuezhong Wu, Shuhong Chen, and Xueming Luo. "An Intelligent Garbage Sorting System Based on Edge Computing and Visual Understanding of Social Internet of Vehicles." Mobile Information Systems 2021 (August 30, 2021): 1–12. http://dx.doi.org/10.1155/2021/5231092.

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In order to enable Social Internet of Vehicles devices to achieve the purpose of intelligent and autonomous garbage classification in a public environment, while avoiding network congestion caused by a large amount of data accessing the cloud at the same time, it is therefore considered to combine mobile edge computing with Social Internet of Vehicles to give full play to mobile edge computing features of high bandwidth and low latency. At the same time, based on cutting-edge technologies such as deep learning, knowledge graph, and 5G transmission, the paper builds an intelligent garbage sorting system based on edge computing and visual understanding of Social Internet of Vehicles. First of all, for the massive multisource heterogeneous Social Internet of Vehicles big data in the public environment, different item modal data adopts different processing methods, aiming to obtain a visual understanding model. Secondly, using the 5G network, the model is deployed on the edge device and the cloud for cloud-side collaborative management, aiming to avoid the waste of edge node resources, while ensuring the data privacy of the edge node. Finally, the Social Internet of Vehicles devices is used to make intelligent decision-making on the big data of the items. First, the items are judged as garbage, and then the category is judged, and finally the task of grabbing and sorting is realized. The experimental results show that the system proposed in this paper can efficiently process the big data of Social Internet of Vehicles and make valuable intelligent decisions. At the same time, it also has a certain role in promoting the promotion of Social Internet of Vehicles devices.

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Ran, Maoli, and Xiangyu Bai. "Vehicle Cooperative Network Model Based on Hypergraph in Vehicular Fog Computing." Sensors 20, no. 8 (April 16, 2020): 2269. http://dx.doi.org/10.3390/s20082269.

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In this paper, we propose an optimization framework of vehicular fog computing and a cooperation vehicular network model. We aim to improve the performance of vehicular fog computing and solve the problem that the data of the vehicle collaborative network is difficult to obtain. This paper applies the hypergraph theory to study the underlying structure, considering the social characteristics of the vehicles and vehicle communication. Since the vehicles join the network in accordance with the Poisson process law, the model is analyzed by using Poisson stochastic process and mean field theory. This paper uses MATLAB to simulate the evolution process of cooperative networks. The results show that the vehicle’s super-degree in vehicular fog computing has scale-free characteristics. Through this model, the vehicle cooperation situation can be analyzed, and the vehicle dynamics can be accurately predicted to further improve the performance of vehicular fog computing. The model can be transformed into some complex network models by adjusting the parameters. It has strong universality and has certain reference significance for the research on the related characteristics of VANETs and the theoretical research of the cooperative network.

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Elnaffar, Said, Zakaria Maamar, and Quan Z. Sheng. "When Clouds Start Socializing." International Journal of E-Business Research 9, no. 2 (April 2013): 1–7. http://dx.doi.org/10.4018/jebr.2013040101.

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This paper discusses the possible blend between social computing and cloud computing. The result of this blend is the Sky model in which several clouds engaged in different types of social relations like collaboration and competition. Challenges and opportunities associated with the Sky model are reported in this work.

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Li, Yanpeng, Huaiyu Wu, Tariku Sinshaw Tamir, Zhen Shen, Sheng Liu, Bin Hu, and Gang Xiong. "An Efficient Product-Customization Framework Based on Multimodal Data under the Social Manufacturing Paradigm." Machines 11, no. 2 (January 26, 2023): 170. http://dx.doi.org/10.3390/machines11020170.

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With improvements in social productivity and technology, along with the popularity of the Internet, consumer demands are becoming increasingly personalized and diversified, promoting the transformation from mass customization to social manufacturing (SM). How to achieve efficient product customization remains a challenge. Massive multi-modal data, such as text and images, are generated during the manufacturing process. Based on the data, we can use large-scale pre-trained deep learning models and neural radiation field (NeRF) techniques to generate user-friendly 3D contents for 3D Printing. Furthermore, by the cloud computing technology, we can achieve more efficient SM operations. In this paper, we propose an efficient product-customization framework that can provide new ideas for the design, implementation, and optimization of collaborative production, and can provide insights for the upgrading of manufacturing industries.

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Wang, Mian, and Lijuan Li. "Research and Implementation of Distributed Computing Management System for College Students’ Sports Health Based on Integrated Regional Collaborative Medical Care." Occupational Therapy International 2022 (May 18, 2022): 1–11. http://dx.doi.org/10.1155/2022/9306200.

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This paper constructs and applies a university student sports health management system through the theory of integrated regional collaborative medical care and distributed computing technology. Firstly, it analyzes the current situation and problems of cross-regional medical care, the root causes, and the corresponding business scenarios, reflecting the development trend of cross-regional medical care, in the light of the current practical needs of cross-regional medical care. In response to the strong demand for cross-regional medical care, this paper gives the overall design of the distributed computing system, for the deployment and architecture of the cross-regional platform; the registration of cross-regional patients, regional platforms, and health events and documents; and data exchange, service integration, and process integration, etc. The corresponding design is given. The research was conducted on several medical institutions to refine the functional requirements for the construction of the regional collaborative medical platform, and the requirements were analyzed to present the research results of the collaborative medical project. Based on this, requirements were made for the preparation of the project construction data center and medical institutions, and the remote consultation and two-way referral modules of the distributed collaborative medical platform were designed, which are processed and analyzed through a system composed of multiple servers. The results are returned to the user, and the design results were tested for functionality, compatibility, security, and other usability tests. The necessity and feasibility of the college physical health test data platform were analyzed. Students have various needs for physical test data management, the necessity of designing the college physical health test data platform, and the feasibility of the college physical health test data platform in terms of technical means, theoretical basis, and social environment.

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Menendez-Blanco, Maria, Matthieu Tixier, and Donghee Yvette Wohn. "PACMHCI V8, GROUP, January 2024 Editorial." Proceedings of the ACM on Human-Computer Interaction 8, GROUP (February 16, 2024): 1. http://dx.doi.org/10.1145/3633066.

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It is our great pleasure to introduce this issue of the Proceedings of the ACM on Human-Computer Interaction, which focuses on contributions from the research community on Supporting Group Work (GROUP). This thriving community is home to researchers within CSCW, HCI for practice-centered computing, sociotechnical studies, and interdisciplinary groups who provide theoretical, methodological, and/or conceptual contributions on collaborative technologies and practices. GROUP's research community vividly raises the awareness of dimensions of growing importance in our highly connected life, as exemplified by the papers included in this issue. Information sharing and moderation in and across groups and formal organisations continue to call for complex research questions. Collaborative practices that have been the object of concern in GROUP become revisited through the lenses of new technologies, as illustrated by the papers investigating recommender systems and conversational agents in collaborative contexts. More than ever, the Internet is acknowledged as a space for social relationships, see for instance the case of dating apps or mom's chat group in this issue. Reflecting on our densely computing supported practices, ethics for research and design become an essential topic for consideration. The editorial board worked hard to organize this first submission round. The call for papers for this issue on GROUP attracted a total of 31 submissions from all over the world, of which 8 papers (25.8 %) were accepted. This issue results from the dedicated volunteer effort of 23 members of the community who served as Associate Chairs (ACs). They all lent their expertise and time to provide insightful feedback to all authors. The Editorial Board can be found on GROUP's track page. As Track Chairs, we are grateful for the community's collective efforts to continue shaping and sharing GROUP's contributions.

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Journal articles on the topic 'Collaborative and social computing'

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