• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.28-31
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• 1998

This paper describes the differences of the information system's success factors to improve the end-user's performance according to the job characteristics. A modified model of DeLone and McLean's IS success model is proposed with the two added variables of the top management concern and the IS department support. The model is validated using data collected from a field study of 3872 users on 3 Korean companies. ANOVA, correlation analysis, and stepwise regression are used to test research hypotheses. The results of the study indicate the following implications. First the top management concern and the IS department support have the significant relation with the system usage and the user satisfaction. Second, the system quality has an influence on the user satisfaction more than on the system usage. And the information quality has an influence on the system usage more than on the user satisfaction. Third, the system usage has more relations to the user's performance in the logistics function and R&D function. The user satisfaction has more relations to the user's performance in the sales and the A/S function. Therefore information system strategy to increase the user's performance must be differentiated according to job characteristics.

• Journal of Sensor Science and Technology
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• v.25 no.6
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• pp.431-434
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• 2016

Currently, the radial basis function network (RBFN) and various other neural networks are employed to classify gases using chemical sensors arrays, and their performance is steadily improving. In particular, the identification performance of the RBFN algorithm is being improved by optimizing parameters such as the center, width, and weight, and improved algorithms such as the radial basis function network-stochastic gradient (RBFN-SG) and radial basis function network-normalized stochastic gradient (RBFN-NSG) have been announced. In this study, we optimized the number of centers, which is one of the parameters of the RBFN-NSG algorithm, and observed the change in the identification performance. For the experiment, repeated measurement data of 8 samples were used, and the elbow method was applied to determine the optimal number of centers for each sample of input data. The experiment was carried out in two cases(the only one center per sample and the optimal number of centers obtained by elbow method), and the experimental results were compared using the mean square error (MSE). From the results of the experiments, we observed that the case having an optimal number of centers, obtained using the elbow method, showed a better identification performance than that without any optimization.

• Korea Trade Review
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• v.46 no.6
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• pp.191-209
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• 2021

In this paper, various time series analysis models and machine learning models are presented for long-term prediction of export growth rate, and the prediction performance is compared and reviewed by RMSE and MAE. Export growth rate is one of the major economic indicators to evaluate the economic status. And It is also used to predict economic forecast. The export growth rate may have a negative (-) value as well as a positive (+) value. Therefore, Instead of using the ReLU function, which is often used for time series prediction of deep learning models, the PReLU function, which can have a negative (-) value as an output value, was used as the activation function of deep learning models. The time series prediction performance of each model for three types of data was compared and reviewed. The forecast data of long-term prediction of export growth rate was deduced by three forecast methods such as a fixed forecast method, a recursive forecast method and a rolling forecast method. As a result of the forecast, the traditional time series analysis model, ARDL, showed excellent performance, but as the time period of learning data increases, the performance of machine learning models including LSTM was relatively improved.

• The Journal of Information Systems
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• v.13 no.2
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• pp.225-240
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• 2004

The most critical problem of MIS evaluation is the lack of the systematic framework to cover various factors and viewpoints. To solve this problem, this study takes the multi-level and contingent approach to performance evaluation, composed of three levels: evaluating the contribution of MIS to an organization [strategy level]; evaluating the activities of MIS department or MIS function as an organizational sub-function through the overall MIS lifecycle [function level]; and evaluating the quality or productivity of the application systems as MIS outputs [system level]. Ideal MIS evaluation should include all three levels of the hierarchy with balanced importance. However, MIS evaluationcanbedividedintothreetypes,suchasstrategy-oriented, function-oriented and system-oriented evaluation, depending on the focus and emphasis of evaluation. The usage pattern of each evaluation type is analyzed according to contingent variables of MIS evaluation such as MIS maturity, information intensity and firm size, and top management's intent. It is also found that the firms of higher MIS maturity and top management's intent use the strategy-oriented evaluation type, and the firms with strategy-oriented evaluation type show a higher MIS performance. Further, MIS maturity and top management's intent show contingent effects between evaluation type and MIS performance. Some managerial implications can be drawn based on the results of the study. First, strategy-oriented evaluation of MIS is more important as many firms more often use information technology as a strategic weapon. Second, MIS performance varies with evaluation type. Therefore, the design of MIS evaluation framework should be done carefully in the strategic and managerial contexts. Third, firms are recommend to use a different evaluation type according to organizational characteristics such as MIS maturity and information intensity.

• Journal of Korean Academy of Medicine & Therapy Science
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• v.10 no.2
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• pp.59-71
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• 2018

Objective: The purpose of this study is to compare the effects of the CO-OP program using cognitive strategy on the satisfaction and high-level cognitive function of chronic stroke patients with cognitive impairment with the existing task-oriented approach training method. Method: The group randomly selects the experimental group and control group from 30 patients who suffer cognitive damage due to brain damage, and then randomly presents the Cognitive Orientation to daily Occupative Performance (CO-OP) Results: The results of the study showed a significant increase in patient performance and satisfaction, task performance, and high-level cognitive functions in comparison to those before training (p<).05) There was no significant difference in CNT testing in controls; Although there were no significant differences in overall CNT testing between the two groups, the COPM, AMPS tests showed a significant increase in the experimental group compared to the comparators (p <.05). Conclusion: The Cognitive Orientation to Daily Occupative Performance (CO-OP) Intervention Act, which uses meta-in strategies, was previously used. We were able to confirm that it could be a more effective intervention in task performance and high-level cognitive function than in the Meaningful Task-Specific Training Program (MTST).

• Journal of Industrial Convergence
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• v.21 no.10
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• pp.159-166
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• 2023

This study is a descriptive research study to confirm the mediating effect of Problem-Solving Skills in the relationship between Confidence in Performing Core Nursing Skills and Clinical Performance of nursing college students. Participants included 211 nursing college students from S university in D city. Data was collected from August 14 to August 18, 2023 using a self-report questionnaires. The collected data were analyzed by descriptive statistics, Pearson's correlation coefficient, sem function and sobel function using the R.4.2.2 program. In this study, it was found that there was a significant positive correlation between the Confidence in Performing Core Nursing Skills, Problem-Solving Skills, and Clinical Performance, and it was confirmed that Problem-Solving Skills partially mediated the relationship between onfidence in Performing Core Nursing Skills and Clinical Performance. Therefore, it is suggested that Performing Core Nursing Skills and Problem-Solving Skills should be improved in order to improve the Clinical Performance of nursing college students.

• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.57-64
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• 2005

LBL(Layer-By-Layer) algorithms have been proposed to accelerate the training speed of MLPs(Multilayer Perceptrons). In this LBL algorithms, each layer needs a error function for optimization. Especially, error function for hidden layer has a great effect to achieve good performance. In this sense, this paper proposes a new hidden layer error function for improving the performance of LBL algorithm for MLPs. The hidden layer error function is derived from the mean squared error of output layer. Effectiveness of the proposed error function was demonstrated for a handwritten digit recognition and an isolated-word recognition tasks and very fast learning convergence was obtained.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.131-137
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• 2016

In this paper, the peak finding algorithms corresponding to the Autocorrelation Function (ACF), which are widely exploited for detecting the pitch of voiced signal, are proposed. According to various researchers, it is well known fact that the estimation of fundamental frequency (F0) in speech signal is not only very important task but quite difficult mission. The proposed algorithms, presented in this paper, are implemented by using many characteristics - such as monotonic increasing function - of ACF function. Thus, the proposed algorithms may be able to estimate both reliable and correct the fundamental frequency as long as the autocorrelation function of speech signal is accurate. Since the proposed algorithms may reduce the computational complexity it can be applied to the real-time processing. The speech data, is composed of Korean emotion expressed words, is used for evaluation of their performance. The pitches are measured to compare the performance of proposed algorithms.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.138-145
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• 2003

Performance assessment was introduced to improvement of self-directed learning and method of assessment for differenced learning as the seventh educational curriculum is enforced. Performance assessment is overcoming limitation about problem solving ability and higher thinking abilities assessment that is problem of a written examination and get into the spotlight by way for quality of class and school normalization. But, performance assessment has problems about possibilities of assessment fault by appraisal, fairness, reliability, and validity of grading, ambiguity of grading standard, difficulty about objectivity security etc. This study proposes fuzzy performance assessment system to solve problem of the conventional performance assessment. This paper presented an objective and reliable performance assessment method through fuzzy reasoning, design fuzzy membership function and define fuzzy rule analyzing factor that influence in each sacred ground of performance assessment to account principle subject. Also, performance assessment item divides by formation estimation and subject estimation and designed membership function in proposed performance assessment method. Performance assessment result that is worked through fuzzy performance assessment system can pare down burden about appraisal's fault and provide fair and reliable assessment result through grading that have correct standard and consistency to students.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.176-180
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• 2011

Even though algorithms for watermark embedding and extraction step are important issue for digital watermarking, watermark selection and post-processing can give us an opportunity to improve our algorithms and achieve higher performance. For this reason, we summarized the possibilities of improvements for digital watermarking by referring to the watermark merging techniques rather than embedding and extraction algorithms in this paper. We chose Cox's function as main embedding and extraction algorithm, and multiple barcode watermarks as a watermark. Each bit of the multiple copies of barcode watermark was embedded into a gray-scale image with Cox's embedding function. After extracting the numbers of watermark, we applied the watermark merging techniques; including the simple merging, N-step iterated merging, recover merging and combination of iterated-recover merging. Main consequence of our paper was the fact of finding out how multiple barcode watermarks and merging techniques can give us opportunities to improve the performance of algorithm.