Journal of Systems and Information Technology, Volume 16, Issue 3
ebook ∣ Journal of Systems and Information Technology
By Craig Standing

Sign up to save your library
With an OverDrive account, you can save your favorite libraries for at-a-glance information about availability. Find out more about OverDrive accounts.
Find this title in Libby, the library reading app by OverDrive.

Search for a digital library with this title
Title found at these libraries:
Library Name | Distance |
---|---|
Loading... |
The articles in this issue were submitted to last year's International Conference on Integrated Information.
The paper on Provision of an Integrated Data Analysis Platform for Computational Neuroscience Experiments by a team at the University of the West of England (Munir et al) provides a base in order to facilitate computational neuroscience experiments. An integrated e-science environment of computational neuroimaging could enhance the prospects, speed and utility of the data analysis process for neurodegenerative diseases. A user-led approach is proposed to provide access to the integrated neuroscience data and to enable the analyses demanded by the biomedical research community.
Two separate papers on the impact of the risk reduction strategies in online shopping through the perspective of buyer's trust, and the association of Lack of Awareness and Human factors, and the association of Lack of Awareness and important attacks that threat computer security in Higher Education. The first study (Vos et al) investigates how trust is affecting the consumers' engagement to e-commerce and revealed that three e-quality dimensions namely, ease of use, customization and assurance, e-scape and responsiveness have significant positive effects on e-loyalty and e-satisfaction. Regarding e-trust, only customization and assurance exerts a significant positive effect. In the second study (Metalidou et al.) five human factors and nine attacks are considered, in order to investigate their relationship. Considering the relationship of Lack of Awareness to human factors, all five human factors used are significantly and positively correlated with Lack of Awareness. The paper extends understanding of the relationship of the human factors, the Lack of Awareness, and information security.
Dynamic Simulation Models of IS are often used to create effective plans of Strategic Leadership, and supporting mechanisms to Strategic Management of an organization. In their research Damianos Sakas, Dimitrios Vlachos, and Dimitrios Nasiopoulos focus on the significant role that the IS function plays in the complete Strategic Management, and based on the requirements of the IS strategic role, they identify the major factors to evolve a Dynamic Simulation Model of IS. Their paper proposes an effective framework on Modelling Strategic Management for the Development of Competitive Advantage, based on Technology.
Kutsikos et al. further discuss the increasingly close link between IS and strategic management in the realm of service ecosystems; i.e. business networks that are comprised of a multitude of service providers collaborating for value creation. In such an environment, interoperability at IS, operational and strategy layers is a key challenge. By adopting a Service Science viewpoint (service value co-creation, value-in-use), the authors describe a holistic approach for building collaboration capabilities: a) at the enterprise level, it pertains to decision making mechanisms for service provision; b) at the ecosystem level, it pertains to a software platform for managing common collaboration tasks.
There are six universal basic emotions plus neutral emotion, that is: happiness, surprise, fear, sadness, anger, disgust and neutral. The scope of the current research, by Anagnostopoulos and Skourlas, is to understand the emotional state of a human being by capturing the speech utterances that uses during a common conversion. It is proved that given enough acoustic evidence the emotional state of a person can be classified by an ensemble majority voting classifier. The proposed ensemble classifier is constructed over three base classifiers: kNN, C4.5 and SVM Polynomial Kernel.