Fuzzy Techniques for Decision Making 2018

Zadeh's fuzzy set theory incorporates the impreciseness of data and evaluations, by imputting the degrees by which each object belongs to a set. Its success fostered theories that codify the subjectivity, uncertainty, imprecision, or roughness of the evaluations. Their rationale is to produce new flexible methodologies in order to model a variety of concrete decision problems more realistically. This Special Issue garners contributions addressing novel tools, techniques and methodologies for decision making (inclusive of both individual and group, single- or multi-criteria decision making) in the context of these theories. It contains 38 research articles that contribute to a variety of setups that combine fuzziness, hesitancy, roughness, covering sets, and linguistic approaches. Their ranges vary from fundamental or technical to applied approaches

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

Model za praćenje usklađenosti između bezbednosnih standarda i prioritizaciju zahteva u kritičnim infrastruktirama

This thesis presents research in the field of information security. We present a model that uniformly represents the building blocks of the security requirements that are defined in various standards, security guidelines, and regulations for Critical Infrastructure. We analyze the structure of the requirements in the most commonly used standards for this purpose. We have extended the model with components to prioritize and track the implementation and compliance of similar requirements selected from different security publications. We define prioritization criteria for selecting the requirements for implementation that rely on four factors: risk assessment results, essence levels of the requirements set that is analyzed, dependency graph of the social actors involved in the implementation, and the domain affiliation of the requirement. We also define a framework with a set of activities that follow the elements of the proposed model to demonstrate its practical applicability

INQUIRIES IN INTELLIGENT INFORMATION SYSTEMS: NEW TRAJECTORIES AND PARADIGMS

Rapid Digital transformation drives organizations to continually revitalize their business models so organizations can excel in such aggressive global competition. Intelligent Information Systems (IIS) have enabled organizations to achieve many strategic and market leverages. Despite the increasing intelligence competencies offered by IIS, they are still limited in many cognitive functions. Elevating the cognitive competencies offered by IIS would impact the organizational strategic positions. With the advent of Deep Learning (DL), IoT, and Edge Computing, IISs has witnessed a leap in their intelligence competencies. DL has been applied to many business areas and many industries such as real estate and manufacturing. Moreover, despite the complexity of DL models, many research dedicated efforts to apply DL to limited computational devices, such as IoTs. Applying deep learning for IoTs will turn everyday devices into intelligent interactive assistants. IISs suffer from many challenges that affect their service quality, process quality, and information quality. These challenges affected, in turn, user acceptance in terms of satisfaction, use, and trust. Moreover, Information Systems (IS) has conducted very little research on IIS development and the foreseeable contribution for the new paradigms to address IIS challenges. Therefore, this research aims to investigate how the employment of new AI paradigms would enhance the overall quality and consequently user acceptance of IIS. This research employs different AI paradigms to develop two different IIS. The first system uses deep learning, edge computing, and IoT to develop scene-aware ridesharing mentoring. The first developed system enhances the efficiency, privacy, and responsiveness of current ridesharing monitoring solutions. The second system aims to enhance the real estate searching process by formulating the search problem as a Multi-criteria decision. The system also allows users to filter properties based on their degree of damage, where a deep learning network allocates damages in 12 each real estate image. The system enhances real-estate website service quality by enhancing flexibility, relevancy, and efficiency. The research contributes to the Information Systems research by developing two Design Science artifacts. Both artifacts are adding to the IS knowledge base in terms of integrating different components, measurements, and techniques coherently and logically to effectively address important issues in IIS. The research also adds to the IS environment by addressing important business requirements that current methodologies and paradigms are not fulfilled. The research also highlights that most IIS overlook important design guidelines due to the lack of relevant evaluation metrics for different business problems

New Fundamental Technologies in Data Mining

The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining

Cognitive Models and Computational Approaches for improving Situation Awareness Systems

2016 - 2017The world of Internet of Things is pervaded by complex environments with smart services available every time and everywhere. In such a context, a serious open issue is the capability of information systems to support adaptive and collaborative decision processes in perceiving and elaborating huge amounts of data. This requires the design and realization of novel socio-technical systems based on the “human-in-the-loop” paradigm. The presence of both humans and software in such systems demands for adequate levels of Situation Awareness (SA). To achieve and maintain proper levels of SA is a daunting task due to the intrinsic technical characteristics of systems and the limitations of human cognitive mechanisms. In the scientific literature, such issues hindering the SA formation process are defined as SA demons. The objective of this research is to contribute to the resolution of the SA demons by means of the identification of information processing paradigms for an original support to the SA and the definition of new theoretical and practical approaches based on cognitive models and computational techniques. The research work starts with an in-depth analysis and some preliminary verifications of methods, techniques, and systems of SA. A major outcome of this analysis is that there is only a limited use of the Granular Computing paradigm (GrC) in the SA field, despite the fact that SA and GrC share many concepts and principles. The research work continues with the definition of contributions and original results for the resolution of significant SA demons, exploiting some of the approaches identified in the analysis phase (i.e., ontologies, data mining, and GrC). The first contribution addresses the issues related to the bad perception of data by users. We propose a semantic approach for the quality-aware sensor data management which uses a data imputation technique based on association rule mining. The second contribution proposes an original ontological approach to situation management, namely the Adaptive Goal-driven Situation Management. The approach uses the ontological modeling of goals and situations and a mechanism that suggests the most relevant goals to the users at a given moment. Lastly, the adoption of the GrC paradigm allows the definition of a novel model for representing and reasoning on situations based on a set theoretical framework. This model has been instantiated using the rough sets theory. The proposed approaches and models have been implemented in prototypical systems. Their capabilities in improving SA in real applications have been evaluated with typical methodologies used for SA systems. [edited by Author]XXX cicl

The Role of Occupational Therapy in Pressure Ulcer Care: An Educational Program for Therapy Practitioners

Occupational therapists play an important role in wound prevention and management. They provide a unique perspective focused on holistic and client-centered care centered around meaningful occupations. Pressure ulcers are a common occurrence within hospital facilities, creating costly expenses for the facility and poor outcomes for the patients who develop them. More than 2.5 million patients per year will develop a pressure injury, and 60,000 of those patients will die because of their pressure injury. Over 25 billion dollars will be spent by hospital systems for the treatment of pressure injuries. This capstone project aims to develop a personalized quality improvement program for therapy staff at the site to equip them with the necessary skills to improve the quality of care provided and inform them of current evidence-based practices. This project is developed under the Ecology of Human Performance (EHP) model and the Health Belief Model (HBM). Detailed exploration into areas of wound prevention and management takes place as a literature review. Needs assessment interviews are conducted, inventory is tracked, and a staff survey is administered. Based on these results, an educational program is developed, and a pretest/posttest is completed to check for staff improvement. The results of the pretest/posttest indicate a statistically significant increase in pressure ulcer prevention and management after participation in the program. There is a great need for therapists to have a more active role in wound management and prevention. Practitioners have an in-depth understanding of these areas and can provide innovative treatment and education to improve the quality of life for patients. This capstone project demonstrated improved awareness of the role of occupational therapy as a part of the multidisciplinary team

Mind the Gap: Developments in Autonomous Driving Research and the Sustainability Challenge

Scientific knowledge on autonomous-driving technology is expanding at a faster-than-ever pace. As a result, the likelihood of incurring information overload is particularly notable for researchers, who can struggle to overcome the gap between information processing requirements and information processing capacity. We address this issue by adopting a multi-granulation approach to latent knowledge discovery and synthesis in large-scale research domains. The proposed methodology combines citation-based community detection methods and topic modeling techniques to give a concise but comprehensive overview of how the autonomous vehicle (AV) research field is conceptually structured. Thirteen core thematic areas are extracted and presented by mining the large data-rich environments resulting from 50 years of AV research. The analysis demonstrates that this research field is strongly oriented towards examining the technological developments needed to enable the widespread rollout of AVs, whereas it largely overlooks the wide-ranging sustainability implications of this sociotechnical transition. On account of these findings, we call for a broader engagement of AV researchers with the sustainability concept and we invite them to increase their commitment to conducting systematic investigations into the sustainability of AV deployment. Sustainability research is urgently required to produce an evidence-based understanding of what new sociotechnical arrangements are needed to ensure that the systemic technological change introduced by AV-based transport systems can fulfill societal functions while meeting the urgent need for more sustainable transport solutions

Time Orientation, Rational Choice and Deterrence: an Information Systems Perspective

The present study examines General Deterrence Theory (GDT) and its parent, Rational Choice Theory (RCT), in an information security setting, assessing the behavioral intent to violate organizational policy under varying levels of certainty, severity and celerity of negative sanction. Also assessed is the individual computer user\u27s time orientation, as measured by the Consideration of Future Consequences (CFC) instrument (Strathman et. al, 1994). How does rational consideration of violation rewards influence the impact of sanctions on individuals? How does time orientation impact intent to violate security policy? How do these operate in an IS context? These questions are examined by assessing the responses of university students (N = 443) to experimental manipulations of sanctions and rewards. Answering vignettes with the factorial survey method, intent to violate is assessed in a setting of Internet piracy of electronic textbooks while being monitored by computer security systems. Findings show that, although traditional GDT variables and reward impact intent to violate, CFC does not cause the hypothesized moderating effect on these variables. However, post-hoc analysis reveals a direct effect of time orientation on behavioral intent, as well as a weak moderating effect opposite of the hypotheses, indicating increased time orientation positively moderates, rather than negatively moderates, the impact of reward on intent to violate. Implications for theory and practice, and future research directions, are discussed