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Deadline for Submissions: 30 March 2025 |
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Special Issue Editors |
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Guest Editor |
Dr. Shah Nazir |
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Affiliation |
Department of Computer Science, University of Swabi, Swabi, Pakistan |
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Interests |
Component-based software engineering, Software Birthmark, Systematic Literature Review, Big Data and Decision Making |
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Guest Editor |
Dr. Habib Ullah Khan |
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Affiliation |
Department of Accounting & Information Systems, College of Business & Economics, Qatar University, Qatar |
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Interests |
IT security, online behavior, IT adoption in supply chain management, Internet addiction, mobile commerce |
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Special Issue Information |
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With the growing of information technology and increase in use of smart devices such as sensor, actuator, wearable, and other devices have produced massive amount of data. This data is available in various shapes such as healthcare, medical records, data warehouses, and many others. This increase of information can yield to research issues and challenges as extracting useful information become a challenging task for research. The useful insights once drawn in a successful way can ultimately be used for different purposes including analysis of data, managing the data, patient care, and so on which will provide effective solution in the area. Big data is the data which need to be shaped for its volume, size, and shape in order to extract meaningful information for an explicit purpose. Data is ever playing a significant role in organization and industry for its daily activities to smoothly functional. Keeping in view the importance of data and to extract significant information, the data need to be shaped in a structure way to mine the information and useful insights for the useful use of research and practice. Diverse approaches, methods, and mechanisms are in practice to tackle the issues of big data and its analytics. Scientific programming is considered as a key tool and plays a major role in facilitating solutions to the current and future issues exist in the managing of large-scale data, such as by supporting in the processing of huge data volumes, complex system modelling, and sourcing derivations from data and its simulations. Programming tools, such as Tableau, Apache Hadoop, and Informatica PowerCenter, analyze and manage the data efficiently and allow the visualization of expressive comprehensions extracted from data. Scientific Programming facilitates research forums for elaborating research results in, and practical experiences with, analyzing, programming tools, programming languages, and experienced models of computation in data science aimed specifically at supporting scientific research in the domain of data science. This Special Issue invites original research articles and review articles that discover the incorporation of technologies in data science based on scientific programming and its applications in the domain. Studies and research that considers technological and computational barriers to data science management is particularly welcome. Potential topics include but are not limited to the following: • Scientific computation for data science • Tools and its applications in big data • Scientific computation for data science visualization • Deep learning and machine learning algorithms for data analytics • Evaluation of data science • Data warehouse and knowledge representation of big data technologies • Data mining and optimizations in IoT • Probabilistic computing for managing data science • Data science and decision support system • Data and its impact on science mining • Data science and software engineering
Manuscripts could be submitted via our online system: https://ojs.wiserpub.com/index.php/CM/about/submissions. Please visit the Instructions for Authors page before submitting a manuscript.
For any queries, please feel free to contact the CM Special Issue Coodinator (wayne@wiserpub.com).
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Published Papers |
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This special issue is now open for submission. |
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