• Journal of Korean Society of Industrial and Systems Engineering
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• v.10 no.16
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• pp.39-51
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• 1987

This paper deals with the case analysis of second order processes under sampled-data. Proportional Integral-Derivative(PID) control, and development of Decision Support Systems(DSS) for such processes. In this paper three techniques were described for identifying the dynamics of closed loop stable processes. The first, called pulse testing is a frequency-domain method, which yields the frequency response diagram of an open loop process. The second is a time-domain method which yields the gain and time constants of the process model. The third technique is based on step response and gives the parameters of PID controllers. The development of DSS design programs consisting of above three techniques will provide very powerful tools in the microcomputer based process control.

• Perspectives in Nursing Science
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• v.5 no.1
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• pp.17-31
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• 2008

Purpose: The purpose of this study was to evaluate the usability of a prototype personal digital assistant (PDA)-based decision support system for the management of obesity through usability testing with end-users (Advanced Practice Nurses [APNs]) prior to its implementation in clinical settings. Methods: This descriptive study used observational and think aloud techniques to address the research question: what usability problems are perceived by end-users? Five APNs were provided with the scenarios and the list of tasks to evaluate the application. Their verbalizations were recorded through Morae usabil ity software. Data analysis was based on the data captured through Morae, transcriptions, notes, and the end-user survey. Results: End-users completed all the required tasks without encountering a severe usability problem, and agreed that the system was easy to use. clear, concise, and useful. Usability issues that were unrecognized by the developer or usability experts were identified by APNs. The usability problems were categorized according to positive characteristics, negative characteristics, and recommendations. The usability issues were discussed with the project team members, and solutions were suggested to improve the user interface of the PDA-based decision support system before the final implementation. Conclusions: This approach had an important impact on making the system easier to use and more useful from the perspective of design and content. The results of this evaluation provided iterative feedback regarding the design and implementation of the PDA-based decision support system for the management of obesity.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.1
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• pp.80-93
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• 2024

This study attempted to analyze the factors that influence the participation of beneficiary companies in the government's defense industry promotion support project. To this end, experimental data were analyzed by constructing a prediction model consisting of highly important variables in beneficiary company decisions among various company information using the decision tree model, one of the data mining techniques. In addition, various rules were derived to determine the beneficiary companies of the government's support project using the analysis results expressed as decision trees. Three policy measures were presented based on the important rules that repeatedly appear in different predictive models to increase the effect of the government's industrial development. Using the analysis methods presented in this study and the determinants of the beneficiary companies of the government support project will help create a sustainable future defense industry growth environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.248-268
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• 2018

The performance of smartphone applications are usually constrained in user interactions due to resource limitation and it promises great opportunities to improve the performance by exploring the smartphone built-in and embedded sensing techniques. However, heterogeneity in techniques, semantic gap between sensor data and usable context, and complexity of contextual situations keep the techniques from seamless integration. Relevant studies mainly focus on feasibility demonstration of emerging sensing techniques, which rarely address both general architectures and comprehensive technical solutions. Based on a proposed functional model, this investigation provides a general architecture to deal with the dynamic context for context-aware automation and decision support. In order to take advantage of the built-in sensors to improve the performance of mobile applications, an ontology-based method is employed for context modelling, linguistic variables are used for heterogeneous context presentation, and semantic distance-based rule matching is employed to customise functions to the contextual situations. A case study on mobile application authentication is conducted with smartphone built-in hardware modules. The results demonstrate the feasibility of the proposed solutions and their effectiveness in improving operational efficiency.

• Information Systems Review
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• v.9 no.3
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• pp.45-65
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• 2007

As digital economy era and knowledge society advent, division of the industry has been indistinctive and complex. This change of business environment has leaded todifficulty in operations of firms consisted of continuous decision making. To develop effective SDSS needs systematic strategic decision making process, efficient problem solving techniques, information of good quality, efficiently information system, and analysis ability of problem solver. This research develop SDSS framework combined strategic decision making process with various problem solving techniques for designing SDSS. Finally, this paper developed the technique recommendation system by selected the criterions of technique assortment.

• Journal of Integrative Natural Science
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• v.4 no.1
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• pp.31-37
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• 2011

Various algorithms and system development are being required to support the advanced decision making of navigation information support system because of a serious loss of lives and property accidents by officer's error like as carelessness and decision faults. Much of researchers have introduced the techniques about the systems, but they hardly consider environmental factors. In this paper, We collect the context information in order to assess the risk, which is considered the various factor of the sailing ship, then extract the features of knowledge context, which is to apply the weight of correlation coefficients among data in context information. We decide the risk after the extract features through the classification and prediction of context information, and compare the value accuracy of proposed method in order to compare efficiency of the weighted value with the non-weighted value. As a result of experience, we know that the method of weight properties effectively reflect the marine environment because the weight accurate better than the non-weighted.

• Journal of Information Technology Services
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• v.11 no.sup
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• pp.139-152
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• 2012

In the medical web forum, people share medical experience and information as patients and patents' families. Some people search medical information written in non-expert language and some people offer words of comport to who are suffering from diseases. Medical web forums play a role of the informative support and the emotional support. We propose the automatic classification model of articles in the medical web forum into the information support and emotional support. We extract text features of articles in web forum using text mining techniques from the perspective of linguistics and then perform supervised learning to classify texts into the information support and the emotional support types. We adopt the Support Vector Machine (SVM), Naive-Bayesian, decision tree for automatic classification. We apply the proposed model to the HealthBoards forum, which is also one of the largest and most dynamic medical web forum.

• Asia pacific journal of information systems
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• v.10 no.3
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• pp.105-120
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• 2000

The objective of this paper is to show how team study can be advanced with the aid of a current computer technology, that is distributed Artificial Intelligence(DAI). Studying distributed problem solving by using groups of artificial agents, DAI can provide important ideas and techniques for the study of team behaviors like team decision making. To demonstrate the usefulness of DAI models as team research tools, a DAI model called 'Team-Soar' was built and a simulation experiment done with the model was introduced, Here, Team-Soar models a naval command and control team consisting of four members whose mission was to identify the threat level of aircraft. The simulation experiment was performed to examine the relationships of team decision scheme and member incompetence with team performance. Generally, the results of the Team-Soar simulation met expectations and confirmed previous findings in the literature. For example, the results support the existence of main and interaction effects of team decision scheme and member competence on team performance. Certain results of the Team-Soar simulation provide new insights about team decision making, which can be tested against human subjects or empirical data.

• The Journal of Korean Institute of Information Technology
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• v.17 no.5
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• pp.47-55
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• 2019

As the damage caused by GPS jamming has been increased, researches for detecting and preventing GPS jamming is being actively studied. This paper deals with a GPS jamming detection method using multiple GPS receiving channels and three-types machine learning techniques. Proposed multiple GPS channels consist of commercial GPS receiver with no anti-jamming function, receiver with just anti-noise jamming function and receiver with anti-noise and anti-spoofing jamming function. This system enables user to identify the characteristics of the jamming signals by comparing the coordinates received at each receiver. In this paper, The five types of jamming signals with different signal characteristics were entered to the system and three kinds of machine learning methods(AB: Adaptive Boosting, SVM: Support Vector Machine, DT: Decision Tree) were applied to perform jamming detection test. The results showed that the DT technique has the best performance with a detection rate of 96.9% when the single machine learning technique was applied. And it is confirmed that DT technique is more effective for GPS jamming detection than the binary classifier techniques because it has low ambiguity and simple hardware. It was also confirmed that SVM could be used only if additional solutions to ambiguity problem are applied.

• Journal of Information Processing Systems
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• v.18 no.5
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• pp.637-649
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• 2022

Investors aim to increase their profitability by investing in the stock market. An adroit strategy for minimizing related risk lies through diversifying portfolio operationalization. In this paper, we propose a six-step stocks portfolio selection model. This model is based on data mining clustering techniques that reflect the ensuing impact of the political, economic, legal, and corporate governance in Mongolia. As a dataset, we have selected stock exchange trading price, financial statements, and operational reports of top-20 highly capitalized stocks that were traded at the Mongolian Stock Exchange from 2013 to 2017. In order to cluster the stock returns and risks, we have used k-means clustering techniques. We have combined both k-means clustering with Markowitz's portfolio theory to create an optimal and efficient portfolio. We constructed an efficient frontier, creating 15 portfolios, and computed the weight of stocks in each portfolio. From these portfolio options, the investor is given a choice to choose any one option.