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11.
Editorial
Miroljub Kljajić, Gerhard-Wilhelm Weber, 2012, preface, afterword

Keywords: education, research, systems, modeling, group decision making
Published: 29.11.2017; Views: 457; Downloads: 61
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12.
A statistical model for shutdowns due to air quality control for a copper production decision support system
Khalid Aboura, 2015, original scientific article

Abstract: Background: In the mid-1990s, a decision support system for copper production was developed for one of the largest mining companies in Australia. The research was conducted by scientists from the largest Australian research center and involved the use of simulation to analyze options to increase production of a copper production facility. Objectives: We describe a statistical model for shutdowns due to air quality control and some of the data analysis conducted during the simulation project. We point to the fact that the simulation was a sophisticated exercise that consisted of many modules and the statistical model for shutdowns was essential for valid simulation runs. Method: The statistical model made use of a full year of data on daily downtimes and used a combination of techniques to generate replications of the data. Results: The study was conducted with a high level of cooperation between the scientists and the mining company. This contributed to the development of accurate estimates for input into a support system with an EXCEL based interface. Conclusion: The environmental conditions affected greatly the operations of the production facility. A good statistical model was essential for the successful simulation and the high budget expansion decision that ensued.
Keywords: decision support system, simulation, statistical modelling
Published: 28.11.2017; Views: 440; Downloads: 258
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13.
System dynamic models as decision-making tools in agritourism
Tadeja Jere Lazanski, 2016, original scientific article

Abstract: Agritourism as a type of niche tourism is a complex and softly defined phaenomenon. The demands for fast and integrated decision regarding agritourism and its interconnections with environment, economy (investments, traffic) and social factors (tourists) is urgent. Many different methodologies and methods master softly structured questions and dilemmas with global and local properties. Here we present methods of systems thinking and system dynamics, which were first brought into force in the educational and training area in the form of different computer simulations and later as tools for decision-making and organisational re-engineering. We develop system dynamics models in order to present accuracy of methodology. These models are essentially simple and can serve only as describers of the activity of basic mutual influences among variables. We will pay the attention to the methodology for parameter model values determination and the so-called mental model. This one is the basis of causal connections among model variables. At the end, we restore a connection between qualitative and quantitative models in frame of system dynamics.
Keywords: agritourism, multi-criteria decision-making, modelling, system dynamics
Published: 14.11.2017; Views: 547; Downloads: 96
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14.
New perspectives for computer-aided discrimination of Parkinson's disease and essential tremor
Petra Povalej Bržan, J.A. Gallego, J. P. Romero, Vojko Glaser, E. Rocon, Julián Benito-León, Félix Bermejo-Pareja, Ignacio Posada, Aleš Holobar, 2017, original scientific article

Abstract: Pathological tremor is a common but highly complex movement disorder, affecting ~5% of population older than 65 years. Different methodologies have been proposed for its quantification. Nevertheless, the discrimination between Parkinson's disease tremor and essential tremor remains a daunting clinical challenge, greatly impacting patient treatment and basic research. Here, we propose and compare several movement-based and electromyography-based tremor quantification metrics. For the latter, we identified individual motor unit discharge patterns from high-density surface electromyograms and characterized the neural drive to a single muscle and how it relates to other affected muscles in 27 Parkinson's disease and 27 essential tremor patients. We also computed several metrics from the literature. The most discriminative metrics were the symmetry of the neural drive to muscles, motor unit synchronization, and the mean log power of the tremor harmonics in movement recordings. Noteworthily, the first two most discriminative metrics were proposed in this study. We then used decision tree modelling to find the most discriminative combinations of individual metrics, which increased the accuracy of tremor type discrimination to 94%. In summary, the proposed neural drive-based metrics were the most accurate at discriminating and characterizing the two most common pathological tremor types.
Keywords: Parkinson's disease, essential tremor, electromyography, wrist movements, motor units, muscular excitation, decision tree
Published: 03.11.2017; Views: 827; Downloads: 310
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15.
Implementation aspects of a BDD package supporting general decision diagrams
Robert Meolic, 2016, invited lecture at foreign university

Abstract: General decision diagram is a loose term for a superset of different types of decision diagrams - we are interested in joining BDDs, FDDs, and different types of suppressed DDs, e.g. ZBDDs. I will present: The current state of our BDD package Biddy (functionalities and details about the original implementation aspects). Our ideas for efficient implementation of ZBDDs (which could be used for all types of suppressed DDs).New type od decision diagrams called ZFDD (somehow symmetric to ZBDD). A rough draft about the implementation of a package supporting general decision diagrams.
Keywords: Binary Decision Diagram, Zero-suppressed Binary Decision Diagram, Boolean function, Algorithm, BDD package, Biddy
Published: 26.10.2017; Views: 1604; Downloads: 59
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16.
Pomen poznavanja dejanskega stanja hidravličnega olja kot osnova za strateška odločanja
Darko Lovrec, Vito Tič, published scientific conference contribution

Abstract: Običajna hidravlična olja na mineralni osnovi in turbinska olja, katera se uporabljajo na strojih in napravah imajo različno dolgo uporabno dobo. Ta je odvisna od vrste različnih faktorjev: od pravilnega vzdrževanja in uporabljen vrste nadzora in aktivnosti in od skrbne izbire vrste olja. Mehanizmi staranja hidravličnih olj in pa vzroki, zakaj jih je potrebno zamenjati so sicer zelo dobro znani uporabnikom, manj poznano pa je dejstvo, da so med posameznimi vrstami olj velike razlike glede njihove vzdržljivosti, ko so le ta izpostavljena delovnim pogojem stroja. Vsako podaljšanje uporabne dobe hidravličnega ali turbinskega olja ponuja tako finančne kot okoljske prednosti, a predpostavlja poznavanje dejanskega stanja olja. Za namene ocene preostale uporabne dobe olja, je v prispevku predstavljena nova metoda za primerna za on-line nadzor stanja in za testiranje vzdržljivosti oz. oksidacijske odpornosti različnih hidravličnih olj. Rezultati takšnega testiranja uporabniku nudijo možnost strateškega odločanja pri postopku nabave najprimernejšega olja z dolgo uporabno dobo.
Keywords: hydraulic oil, aging, on-line monitoring, testing, strategical decision-making
Published: 10.10.2017; Views: 514; Downloads: 42
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17.
Organizational learning supported by machine learning models coupled with general explanation methods
Marko Bohanec, Marko Robnik Šikonja, Mirjana Kljajić Borštnar, 2017, original scientific article

Abstract: Background and Purpose: The process of business to business (B2B) sales forecasting is a complex decision-making process. There are many approaches to support this process, but mainly it is still based on the subjective judgment of a decision-maker. The problem of B2B sales forecasting can be modeled as a classification problem. However, top performing machine learning (ML) models are black boxes and do not support transparent reasoning. The purpose of this research is to develop an organizational model using ML model coupled with general explanation methods. The goal is to support the decision-maker in the process of B2B sales forecasting. Design/Methodology/Approach: Participatory approach of action design research was used to promote acceptance of the model among users. ML model was built following CRISP-DM methodology and utilizes R software environment. Results: ML model was developed in several design cycles involving users. It was evaluated in the company for several months. Results suggest that based on the explanations of the ML model predictions the users’ forecasts improved. Furthermore, when the users embrace the proposed ML model and its explanations, they change their initial beliefs, make more accurate B2B sales predictions and detect other features of the process, not included in the ML model. Conclusions: The proposed model promotes understanding, foster debate and validation of existing beliefs, and thus contributes to single and double-loop learning. Active participation of the users in the process of development, validation, and implementation has shown to be beneficial in creating trust and promotes acceptance in practice.
Keywords: decision support, organizational learning, machine learning, explanations
Published: 01.09.2017; Views: 855; Downloads: 133
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18.
Deficiency areas in decision making in undergraduate medical students
Zalika Klemenc-Ketiš, Janko Kersnik, 2014, original scientific article

Abstract: Background: In family medicine, decisions can be difficult due to the early presentation of often poorly developed symptoms or the presentation of undifferentiated conditions that require competencies unique to family medicine, such as; primary care management, specific problem-solving skills, and a comprehensive and holistic approach to be taught to medical students. Purpose: The aim of this study was to assess the decision-making process covering all theoretical aspects of family practice consultation and to recognize possible areas of deficiency in undergraduate medical students. Materials and methods: This was a cross-sectional, observational study performed at the Medical School of the University of Maribor in Slovenia. The study population consisted of 159 fourth-year medical students attending a family medicine class. The main outcome measure was the scores of the students' written reports on solving the virtual clinical case. An assessment tool consisted of ten items that could be graded on a 5-point Likert scale. Results: The final sample consisted of 147 (92.5%) student reports. There were 95 (64.6%) female students in the sample. The mean total score on the assessment scale was 35.1+-7.0 points of a maximum 50 points. Students scored higher in the initial assessment items and lower in the patient education/involvement items. Female students scored significantly higher in terms of total assessment score and in terms of initial assessment and patient education/involvement. Conclusion: Undergraduate medical education should devote more time to teaching a comprehensive approach to consultation, especially modification of the health behavior of patients and opportunistic health promotion to patients. Possible sex differences in students' performance should be further evaluated.
Keywords: assessment, family medicine, undergraduate medical education, decision making
Published: 03.08.2017; Views: 513; Downloads: 291
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19.
Considering interactions among multiple criteria for the server selection
Vesna Čančer, 2010, original scientific article

Abstract: Decision-making about server selection is one of the multi-criteria decision-making (MCDM) processes where interactions among criteria should be considered. The paper introduces and develops some solutions for considering interactions among criteria in the MCDM problems. In the frame procedure for MCDM by using the group of methods, based on assigning weights, special attention is given to the synthesis of the local alternatives' values into the aggregate values where the mutual preferential independence between two criteria is not assumed. Firstly, we delineate how to complete the additive model into the multiplicative one with synergic and redundancy elements in the case that criteria are structured in one level and in two levels. Furthermore, we adapted the concept of the fuzzy Choquet integral to the multi-attribute value theory. Studying and comparing the results of the example case of the server selection obtained by both aggregation approaches, the paper highlights the advantages of the first one since it does not require from decision makers to determine the weights of all possible combinations of the criteria and it enables the further use of the most preferred MCDM methods.
Keywords: interaction, multi-criteria decision-making, preferential dependence, server
Published: 03.08.2017; Views: 519; Downloads: 72
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20.
Decision making under conditions of uncertainty in agriculture
Karmen Pažek, Črtomir Rozman, 2009, review article

Abstract: In decision under uncertainty individual decision makers (farmers) have to choose one of a set number of alternatives with complete information about their outcomes but in the absence of any information or data about the probabilities of the various state of nature. This paper examines a decision making under uncertainty in agriculture. The classical approaches of Wald’s, Hurwicz’s, Maximax, Savage’s and Laplace’s are discussed and compared in case study of oil pumpkin production and selling of pumpkin oil. The computational complexity and usefulness of the criterion are further presented. The article is concluded with aggregate the results of all observed criteria and business alternatives in the conditions of uncertainty, where the business alternative 1 is suggested.
Keywords: uncertainty, Wald’s, Hurwicz’s, Maximax, Savage’s and Laplace’s criterion, decision support system, agriculture, oil crops
Published: 20.07.2017; Views: 500; Downloads: 76
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