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      A Systematic Literature Review on Service Composition for People with Disabilities: Taxonomies, Solutions, and Open Research Challenges

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          Abstract

          Integrating smart heterogeneous objects, IoT devices, data sources, and software services to produce new business processes and functionalities continues to attract considerable attention from the research community due to its unraveled advantages, including reusability, adaptation, distribution, and pervasiveness. However, the exploitation of service-oriented computing technologies (e.g., SOC, SOA, and microservice architectures) by people with special needs is underexplored and often overlooked. Furthermore, the existing challenges in this area are yet to be identified clearly. This research study presents a rigorous literature survey of the recent advances in service-oriented composition approaches and solutions for disabled people, their domains of application, and the major challenges, covering studies published between January 2010 and October 2022. To this end, we applied the systematic literature review (SLR) methodology to retrieve and collate only the articles presenting and discussing service composition solutions tailored to produce digitally accessible services for consumption by people who suffer from an impairment or loss of some physical or mental functions. We searched six renowned bibliographic databases, particularly IEEE Xplore, Web of Science, Springer Link, ACM Library, ScienceDirect, and Google Scholar, to synthesize a final pool of 38 related articles. Our survey contributes a comprehensive taxonomy of service composition solutions, techniques, and practices that are utilized to create assistive technologies and services. The seven-facet taxonomy helps researchers and practitioners to quickly understand and analyze the fundamental conceptualizations and characteristics of accessible service composition for people with disabilities. Key findings showed that services are fused to assist disabled persons to carry out their daily activities, mainly in smart homes and ambient intelligent environments. Despite the emergence of immersive technologies (e.g., wearable computing), user-service interactions are enabled primarily through tactile and speech modalities. Service descriptions mainly incorporate functional features (e.g., performance, latency, and cost) of service quality, largely ignoring accessibility features. Moreover, the outstanding research problems revolve around (1) the unavailability of assistive services datasets, (2) the underspecification of accessibility aspects of disabilities, (3) the weak adoption of accessible and universal design practices, (4) the abstraction of service composition approaches, and (5) the rare experimental testing of composition approaches with disabled users. We conclude our survey with a set of guidelines to realize effective assistive service composition in IoT and cloud environments. Researchers and practitioners are advised to create assistive services that support the social relationships of disabled users and model their accessibility needs as part of the quality of service (QoS). Moreover, they should exploit AI/ML models to address the evolving requirements of disabled users in their unique environments. Furthermore, weaknesses of service composition solutions and research challenges are exposed as notable opportunities for future research.

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          Understanding the barriers to setting up a healthcare quality improvement process in resource-limited settings: a situational analysis at the Medical Department of Kamuzu Central Hospital in Lilongwe, Malawi

          Background Knowledge regarding the best approaches to improving the quality of healthcare and their implementation is lacking in many resource-limited settings. The Medical Department of Kamuzu Central Hospital in Malawi set out to improve the quality of care provided to its patients and establish itself as a recognized centre in teaching, operations research and supervision of district hospitals. Efforts in the past to achieve these objectives were short-lived, and largely unsuccessful. Against this background, a situational analysis was performed to aid the Medical Department to define and prioritize its quality improvement activities. Methods A mix of quantitative and qualitative methods was applied using checklists for observed practice, review of registers, key informant interviews and structured patient interviews. The mixed methods comprised triangulation by including the perspectives of the clients, healthcare providers from within and outside the department, and the field researcher’s perspectives by means of document review and participatory observation. Results Human resource shortages, staff attitudes and shortage of equipment were identified as major constraints to patient care, and the running of the Medical Department. Processes, including documentation in registers and files and communication within and across cadres of staff were also found to be insufficient and thus undermining the effort of staff and management in establishing a sustained high quality culture. Depending on their past experience and knowledge, the stakeholder interviewees revealed different perspectives and expectations of quality healthcare and the intended quality improvement process. Conclusions Establishing a quality improvement process in resource-limited settings is an enormous task, considering the host of challenges that these facilities face. The steps towards changing the status quo for improved quality care require critical self-assessment, the willingness to change as well as determined commitment and contributions from clients, staff and management.
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            Guidelines for conducting systematic mapping studies in software engineering: An update

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              Cloud computing service composition: A systematic literature review

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                Author and article information

                Contributors
                Journal
                Comput Intell Neurosci
                Comput Intell Neurosci
                cin
                Computational Intelligence and Neuroscience
                Hindawi
                1687-5265
                1687-5273
                2023
                8 March 2023
                : 2023
                : 5934548
                Affiliations
                1Faculty of Computer and Information Systems, Islamic University of Madinah, Madinah 42351, Saudi Arabia
                2School of Digital Science, Faculty of Science, Universiti Brunei Darussalam, BE1410, Bandar Seri Begawan, Brunei Darussalam
                Author notes

                Academic Editor: Asif Irshad Khan

                Author information
                https://orcid.org/0000-0002-7050-0532
                https://orcid.org/0000-0003-4871-4080
                https://orcid.org/0000-0002-9989-6163
                https://orcid.org/0000-0002-4540-3650
                https://orcid.org/0000-0002-6080-5236
                Article
                10.1155/2023/5934548
                10017225
                36936667
                a98d4aac-105d-451e-94df-279a21fd1cbf
                Copyright © 2023 Abdallah Namoun et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 17 October 2022
                : 16 January 2023
                : 21 January 2023
                Funding
                Funded by: Ministry of Education – Kingdom of Saudi Arabia
                Award ID: 13/20
                Categories
                Research Article

                Neurosciences
                Neurosciences

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