• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.303-311
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• 2012

In this study, we introduce a dynamic process model as well as the design methodology of optimized fuzzy controller for its efficient application to vacuum production system to produce a semiconductor, solar module and display and so on. In a vacuum control field, PID control method is widely used from the viewpoint of simple structure and preferred performance. But, PID control method is very sensitive to the change of environment of control system as well as the change of control parameters. Therefore, it's difficult to get a preferred performance results from target system which has a complicated structure and lots of nonlinear factors. To solve such problem, we propose the design methodology of an optimized fuzzy PID controller through a following series of steps. First a dynamic characteristic of the target system is analyzed through a series of experiments. Second the process model is built up and its characteristic is compared with real process. Third, the optimized fuzzy PID controller is designed using genetic algorithms. Finally, the fuzzy controller is applied to target system and then its performance is compared with that of other conventional controllers(PID, PI, and Fuzzy PI controller). The performance of the proposed fuzzy controller is evaluated in terms of auto-tuned control parameters and output responses considered by ITAE index, overshoot, rise time and steady state time.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.273-283
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• 2000

In this paper we suggest an optimal design method of Fuzzy-Neural Networks(FNN) model for complex and nonlinear systems. The FNNs use the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. And we use a HCM(Hard C-Means) Clustering Algorithm to find initial parameters of the membership function. The parameters such as parameters of membership functions learning rates and momentum weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. According to selection and adjustment of a weighting factor of an aggregate objective function which depends on the number of data and a certain degree of nonlinearity (distribution of I/O data we show that it is available and effective to design and optimal FNN model structure with a mutual balance and dependency between approximation and generalization abilities. This methodology sheds light on the role and impact of different parameters of the model on its performance (especially the mapping and predicting capabilities of the rule based computing). To evaluate the performance of the proposed model we use the time series data for gas furnace the data of sewage treatment process and traffic route choice process.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1986-1995
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• 2018

In this paper, a novel neutral-point voltage balancing scheme for NPC three-level inverters using carrier-based sinusoidal pulse width modulation (SPWM) method is developed. The new modulation approach, based on the obtained expressions of zero sequence voltage in all six sectors, can significantly suppress the low-frequency voltage oscillation in the neutral point at high modulation index and achieve a fast voltage-balancing dynamic performance. The implementation of the proposed method is very simple. Another attractive feature is that the scheme can stably control any voltage difference between the two dc-link capacitors within a certain range without using any extra hardware. Furthermore, the presented scheme is also applicable to the single-phase NPC three-level inverter. It can maintain the neutral-point voltage balance at full modulation index and improve the voltage-balancing dynamic performance of the single-phase NPC three-level inverter. The performance of the proposed strategy and its benefits over other previous techniques are verified experimentally.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.145-156
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• 2021

The research purpose of this paper is to empirically examine the effects of technological readiness and innovation on logistics performance. To build up and maintain an important role in global supply chains, nowadays it is obvious that countries and logistics providers need to achieve competitive advantage in terms of digitalization. However, there is a lack of empirical studies about the impacts of information technologies and innovation potential on the logistics efficiency of countries. Hence, the study analyzes whether the corresponding pillars of the Global Competitiveness Index (GCI) matter for the Logistics Performance Index (LPI) and its dimensions. For determining the effects, the pooled regression approach is applied. The results show that technological readiness and innovation are positively and statistically significantly correlated with logistics performance: competence and quality of logistics services, efficiency of customs clearance processes, ability to track and trace consignments, frequency with which shipments reach consignee within scheduled or expected time, and ease of arranging competitively priced shipments. The findings of this study suggest that investments in innovations and technology progress improve countries' logistics efficiency, which is an important prerequisite for enabling Logistics 4.0 and thus, Industry 4.0 and the digital transformation of the economy and society.

• Journal of Chest Surgery
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• v.23 no.1
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• pp.22-32
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• 1990

Postoperative cardiac performance of cyanotic congenital heart disease is somewhat different from that of other cardiac diseases. For the evaluation of postoperative cardiac performance in the cyanotic congenital heart disease we measured cardiac output by thermodilution technique at 1, 4, 8, 12, 16, 20, 24, 36, 48 postoperative hours in 14 patients operated from Feb. 1989 to Nov. 1989 in The Department of Thoracic and Cardiovascular Surgery, Seoul National University Children`s Hospital. At the same time, we checked left atrial pressure [LAP], central venous pressure [CUP], and mixed venous oxygen saturation [SvO2] to detect correlation between them. Immediate postoperative cardiac index was 3.585 $\pm$ 0.945 L/min/m2, and it decreased maximally to 3.322$\pm$1.007 L/min/m2 at postoperative 16 hours. After then it increased and stabilized from 36 hours after operation, and its value was 4.426$\pm$1.358 L/min/m2. There were no correlations between cardiac index and left atrial pressure or central venous pressure. Between mixed venous oxygen saturation and cardiac index, there was no correlation in the early postoperative period but after postoperative 16 hours, there was significant correlation between them and correlation coefficients were 0.573 [16hrs], 0.743 [20hrs], 0.436 [24hrs], 0.560 [36hrs], 0.636 [48hrs], respectively. From these results, we concluded that in the corrective surgery of cyanotic congenital heart disease, cardiac performance was depressed in the early postoperative period. It improved from postoperative 16 hours, and stabilized from 36 hours after operation. During early postoperative period, mixed venous oxygen saturation should not be used as a predictor of cardiac performance but it could be used as a predictor of cardiac performance from 16 hours after operation.

• Journal of the Korean Society for information Management
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• v.28 no.2
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• pp.177-193
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• 2011

This study constructed an ontology targeting journal articles and evaluated its performance. Also, the performance of a triple structure ontology was compared with the knowledge base of an inverted index file designed for a simple keyword search engine. The coverage was three years of articles published in the Journal of the Korean Society for Information Management from 2007 to 2009. Protege was used to construct an ontology, whilst utilizing an inverted index file to compare performance. The concept ontology was manually established, and the bibliography ontology was automatically constructed to produce an OWL concept ontology and an OWL bibliography ontology, respectively. This study compared the performance of the knowledge base of the ontology, using the Jena search engine with the performance of an inverted index file using the Lucene search engine. As a result, The Lucene showed higher precision rate, but Jena showed higher recall rate.

• The Journal of Asian Finance, Economics and Business
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• v.4 no.2
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• pp.19-23
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• 2017

It is undisputable that crude oil and its price fluctuations are major components that affect most of the countries' economies. Recent studies have demonstrated that beside the impact that crude oil price fluctuations have on common macroeconomic indicators like gross domestic product (GDP), inflation rates, exchange rates, unemployment rate, etc., it also has a strong influence on stock markets and their performance. This relationship has been examined in a number of settings, but it is yet to be unraveled in the Omani context. Accordingly, the main purpose of this study is to examine the possible effect of the oil price fluctuations on stock price movements. The study applies Toda and Yamamoto's (1995) Granger non-causality test on the daily Oman stock index (Muscat Securities Market Index) and oil prices between the period of 2 January 2003 and 13 March 2016. The results indicated that the oil price fluctuations have a significant impact on stock index movements. However, the stock price movements do not have a significant impact on oil prices. These findings have significant implications not only for the Omani economy but also for the economy of similar countries, particularly in the Gulf Cooperation Council (GCC) countries. The latter should carefully consider their policies and strategies regarding crude oil production and the generated income allocation as it might potentially affect the financial markets performance in these countries.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.250-258
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• 2019

Due to the problems associated with the aging of industrial complexes, research on the decline of industrial complexes is being conducted. In the case of decline, it is necessary to not respond immediately, but with a crisis, it is necessary to minimize the impact on the industrial complex through preemptive responses to the external environment and internal changes. Therefore, it is necessary to develop a crisis index that can systematically predict and evaluate changes in the industrial complex. In this research, a method for extracting the crisis index of an industrial complex is developed. We derive performance measures for developing the crisis index, deriving the relative importance of performance measures based on the analytical hierarchy process. Because units of performance measurement are different, a normalization method is developed to sensitively reflect change. Based on the relative importance and normalized values of the performance measures, the crisis index of the industrial complex is developed and applied to a national industrial complex in order to verify its applicability.

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.305-312
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• 2001

Recently, high-dimensional index structures have been required for similarity search in such database applications s multimedia database and data warehousing. In this paper, we propose a new cell-based signature tree, called CS-tree, which supports efficient storage and retrieval on high-dimensional feature vectors. The proposed CS-tree partitions a high-dimensional feature space into a group of cells and represents a feature vector as its corresponding cell signature. By using cell signatures rather than real feature vectors, it is possible to reduce the height of our CS-tree, leading to efficient retrieval performance. In addition, we present a similarity search algorithm for efficiently pruning the search space based on cells. Finally, we compare the performance of our CS-tree with that of the X-tree being considered as an efficient high-dimensional index structure, in terms of insertion time, retrieval time for a k-nearest neighbor query, and storage overhead. It is shown from experimental results that our CS-tree is better on retrieval performance than the X-tree.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.7
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• pp.1815-1830
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• 2012

Existing R-tree that is based on a variety of outdoor-based techniques to manage moving objects have been investigated. Due to the different characteristics of the indoor and outdoor, it is difficult to management of moving object using existed methods in indoor setting. We propose a new index structure called ACII(adaptive Cell-based index for Indoor moving objects) for Indoor moving objects. ACII is Cell-based access structure adopting an overlapping technique. The ACII refines cells adaptively to handle indoor regional data, which may change its locations over time. The ACII consumed at most 30% of the space required by R-tree based methods, and achieved higher query performance compared with r-tree based methods.