Towards a framework for terrain attribute selection in environmental studies

Abstract:Expert systems in medicine are frequently restricted to assisting the physician to derive a patient-specific diagnosis and therapy proposal. In many cases, however, there is a clinical need to use these patient data for other purposes as well. The intention of this paper is to show how and to what extent patient data in expert systems can additionally be used to create clinical registries and for statistical data analysis. At first, the pitfalls of goal-oriented mechanisms for the multiple usability of data are shown by means of an example. Then a data acquisition and inference mechanism is proposed, which includes a procedure for controlling selection bias, the so-called knowledge-based attribute selection. The functional view and the architectural view of expert systems suitable for the multiple usability of patient data is outlined in general and then by means of an application example. Finally, the ideas presented are discussed and compared with related approaches.

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OPTIMIZATION OF ATTRIBUTE SELECTION MODEL USING BIO-INSPIRED ALGORITHMS

Journal of Information and Communication Technology ◽

10.32890/jict2019.18.1.3 ◽

2019 ◽

Vol 18 (1) ◽

pp. 35-55

Author(s):

Mohammad Aizat Basir ◽

Yuhanis Yusof ◽

Mohamed Saifullah Hussin

Keyword(s):

Selection Model ◽

Attribute Selection

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Environmental Studies and Ethnic Studies

Explorations in Ethnic Studies ◽

10.1525/esr.2020.43.2.9 ◽

2020 ◽

Vol 43 (2) ◽

pp. 9-16

Author(s):

David N. Pellow

Keyword(s):

Case Studies ◽

Multiple Scales ◽

Ethnic Studies ◽

Environmental Studies ◽

Potential Value

This article offers insights into conceptual, pedagogical, and programmatic crossings and conflicts between the fields of Environmental Studies and Ethnic Studies. It highlights both the important intersections between the two fields and their potential value, while also addressing the challenges posed in the development of programmatic collaborations. Utilizing case studies drawn from the author’s own experiences, the article’s focus is on harnessing the strengths and limitations of both fields to promote transformative knowledge and action at multiple scales.

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Journal of The Institute of Environmental Studies

10.15336/jies. ◽

2016 ◽

Keyword(s):

Environmental Studies

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Attribute Selection for the Early Diagnosis of Alzheimers Disease from Magnetic Resonance Images

International Journal of Computer Sciences and Engineering ◽

10.26438/ijcse/v6i6.13211326 ◽

2018 ◽

Vol 6 (6) ◽

pp. 1321-1326

Author(s):

C.S. Sandeep ◽

A. Sukesh Kumar

Keyword(s):

Magnetic Resonance ◽

Early Diagnosis ◽

Magnetic Resonance Images ◽

Attribute Selection ◽

Alzheimers Disease ◽

Selection For

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Long Island Sound environmental studies

Open-File Report ◽

10.3133/ofr98502 ◽

1998 ◽

Cited By ~ 1

Author(s):

Lawrence J. Poppe ◽

Chris F. Polloni

Keyword(s):

Long Island ◽

Environmental Studies ◽

Long Island Sound ◽

Island Sound

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Recognizing Job Apathy Patterns of Iraqi Higher Education Employees Using Data Mining Techniques

Journal of Southwest Jiaotong University ◽

10.35741/issn.0258-2724.54.4.30 ◽

2019 ◽

Vol 54 (4) ◽

Author(s):

Mustafa S. Abd ◽

Suhad Faisal Behadili

Keyword(s):

Higher Education ◽

Data Mining ◽

Psychiatric Patients ◽

Human Life ◽

A Priori ◽

Psychological Research ◽

Attribute Selection ◽

Specific Class ◽

Data Mining Techniques ◽

Using Data

Psychological research centers help indirectly contact professionals from the fields of human life, job environment, family life, and psychological infrastructure for psychiatric patients. This research aims to detect job apathy patterns from the behavior of employee groups in the University of Baghdad and the Iraqi Ministry of Higher Education and Scientific Research. This investigation presents an approach using data mining techniques to acquire new knowledge and differs from statistical studies in terms of supporting the researchers’ evolving needs. These techniques manipulate redundant or irrelevant attributes to discover interesting patterns. The principal issue identifies several important and affective questions taken from a questionnaire, and the psychiatric researchers recommend these questions. Useless questions are pruned using the attribute selection method. Moreover, pieces of information gained through these questions are measured according to a specific class and ranked accordingly. Association and a priori algorithms are used to detect the most influential and interrelated questions in the questionnaire. Consequently, the decisive parameters that may lead to job apathy are determined.

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