• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.147-147
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• 2021

A partition of water distribution network (WDN) into district metered areas (DMAs) brings the efficiency and efficacy for water network operation and management (O&M), especially in monitoring pressure and leakage. Traditionally, the DMA configurations (i.e., number, shape, and size of DMAs) are permanent and cannot be changed occasionally. This leads to changes in water quality and reduced network redundancy lowering network resilience against abnormal conditions such as water demand variability and mechanical failures. This study proposes a framework to automatically divide a WDN into dynamic DMA configurations, in which the DMA layouts can self-adapt in response to abnormal scenarios. To that aim, a complex graph theory is adopted to sectorize a WDN into multiscale DMA layouts. Then, different failure-based scenarios are investigated on the existing DMA layouts. Here, an optimization-based model is proposed to convert existing DMA layouts into dynamic layouts by considering existing valves and possibly placing new valves. The objective is to minimize the alteration of flow paths (i.e., flow direction and velocity in the pipes) while preserving the hydraulic performance of the network. The proposed method is tested on a real complex WDN for demonstration and validation of the approach.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.177-189
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• 2020

To newly discover the placeness of Xita Koreatown in Shenyang, this study establishes the conceptual structure of urban inclusivity based on the actor-network theory and the main discourse of inclusive cities. It then applies a framework to the relevant space for analysis. We conduct the case study by first identifying a historical timeline by dividing the age from the founding of New China to the present into sprouting and developing stages of Xita Koreatown, extracting major actors out of time, and finally creating a network graph for each of the six periods representing changes in the region. Throughout this process, we not only analyze the aspect of transition in the urban inclusivity of Xita Koreatown but also prospect the feasibility of an inclusive city for the area. The results of this study are as follows. First, the number and type of actors constituting Xita Koreatown have constantly increased significantly since the establishment of diplomatic relations between China and South Korea. The related actor-networks have also continued to expand in all indicators of urban inclusivity. Secondly, the agency of human actors such as Korean-Chinese, locals, and both South and North Koreans, representing the specificity of Xita Koreatown, has continuously improved. Lastly, due to the increase of cultural exchanges and related policy actors, the actor-network in this region has achieved an unprecedented leap forward. In conclusion, the urban inclusivity of Xita Koreatown in Shenyang shows significant growth in quality, with expectations of further improvement.

• Journal of the Economic Geographical Society of Korea
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• v.17 no.4
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• pp.718-742
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• 2014

The capitalist economic process of glocalization and development of transportation and communication technology have led us to the significance of network city as well as concepts of global city, megacity region, etc. Network city theory pursues development of both individual cities and of the region of those cities through strengthening of mutual connectivity among them with specialized industries. On the basis of network city theory, this paper is to analyze specialized industries of cities and connectivity among them in the Youngnam region in S. Korea. It uses the methods of locational quotient, locational Gini coefficient, and shift-share method to analyze specialized industries of cities, and correspondence analysis, global and local Moran's I to examine connectivity among cities. As results, it can be identified that each city in the Youngnam region has its own specialized industries different from each others, but it seems not easy to grasp the overall extent of connectivity among them, partly because of the limitations of applied analysis methods and partly because of a lack of connectivity among cities themselves.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.2
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• pp.81-86
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• 2013

In this paper, the parameter identification for localization scheme for the optics-based micro sensor node is conducted. We analyzed short measurement range problem which can be occurred in optical based micro sensor node localization method using a time of flight. And we set up the theory for distance and maximum reflected laser power to overcome the problem by identifying hardware parameters like laser power, effective area of MEMS CCR, sensitivity of photodetector, and so on. Experimental results of measurement of maximum reflected laser power were compared with results of the theory. By using the theory, we can identify hardware parameters of localization scheme to measure particular position of the optics-based micro sensor node.

• Journal of Contemporary Eastern Asia
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• v.12 no.2
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• pp.89-97
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• 2013

This paper explores the influences of the traditional Chinese culture on social relations in China. It provides an introduction to the concept of Guanxi, the notion that social connections are based on socially situated reciprocity. This is different from social interaction in Western society that is based on self-interest and equity. Guanxi represents the foundation of social networks in many Eastern countries. As such, the study of social networks in China requires scholars to examine Guanxi networks. The paper demonstrates how a Guanxi perspective might be added to the examination of various theories that comprise structural (network) theory, including social capital theory, social exchange theory, cognitive and contagion theories, and the role of homophily for the study of Chinese society and its social organizations.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.2
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• pp.82-88
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• 1999

In this paper, we propose a new structure optimization method of multilayer neural networks which begin and carry out learning from a bigger network. This method redundant links and neurons according to the rough set theory. In order to find redundant links, we analyze the variations of all weights and output errors in every step of the learning process, and then make the decision table from their variation of weights and output errors. We can find the redundant links from the initial structure by analyzing the decision table using the rough set theory. This enables us to build a structure as compact as possible, and also enables mapping between input and output. We show the validity and effectiveness of the proposed algorithm by applying it to the XOR problem.

• Journal of Korean Society of Rural Planning
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• v.6 no.2 s.12
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• pp.12-19
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• 2000

Irrigation pipeline networks consist mainly of buried pipes and are therefore relatively free from topographic constraints. Installation of irrigation pipeline systems is increasing since the systems have several advantages compared to open channel systems. To achieve economic design of pipeline networks, the layout should meet several conditions such as shortest path, maximum flow, and least cost. Graph theory is mathematical tool which enable to find out optimum layout for complicated network systems. In this study, applicability of graph theory to figure out optimum layout of irrigation pipeline networks was evaluated.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.549-555
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• 2003

The technology of machine condition monitoring is used effectively to detect the machine faults at an early stage using different machine quantities, such as current, voltage, temperature and vibration. Induction motors are most widely used to drive pumps, compressors and fans in industrial drives. This paper presents approach to data fusion using Dempster-Shafer theory because only one technique has uncertainty. So we can obtain advanced accuracy of the machine fault diagnosis. Vibration and current quantities are applied to diagnose three-phase induction motor.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1489-1502
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• 2019

This work introduces a novel unweighted combination method (UCSS) for business failure perdition (BFP). With considering features of BFP in the age of big data, UCSS integrates the quantitative and qualitative analysis by utilizing soft set theory (SS). We adopt the conventional expert system (ES) as the basic qualitative classifier, the logistic regression model (LR) and the support vector machine (SVM) as basic quantitative classifiers. Unlike other traditional combination methods, we employ soft set theory to integrate the results of each basic classifier without weighting. In this way, UCSS inherits the advantages of ES, LR, SVM, and SS. To verify the performance of UCSS, it is applied to real datasets. We adopt ES, LR, SVM, combination models utilizing the equal weight approach (CMEW), neural network algorithm (CMNN), rough set and D-S evidence theory (CMRD), and the receiver operating characteristic curve (ROC) and SS (CFBSS) as benchmarks. The superior performance of UCSS has been verified by the empirical experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.8
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• pp.1454-1463
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• 2008

Blind source separation by independent component analysis (ICA) has applied in signal processing, telecommunication, and image processing to recover unknown original source signals from mutually independent observation signals. Neural networks are learned to estimate the original signals by unsupervised learning algorithm. Because the outputs of the neural networks which yield original source signals are mutually independent, then mutual information is zero. This is equivalent to minimizing the Kullback-Leibler convergence between probability density function and the corresponding factorial distribution of the output in neural networks. In this paper, we present a learning algorithm using information theory and higher order statistics to solve problem of blind source separation. For computer simulation two deterministic signals and a Gaussian noise are used as original source signals. We also test the proposed algorithm by applying it to several discrete images.