• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.205-208
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• 2002

When establishing the submarine optical fiber table between international and domestic, marine survey in advance it grasps the submarine geological features which is accurate and a depth of water condition. And the route which is safe for selecting and submarine optical fiber cable laying it is a work which secures an ease one location. If also, the PLGR the submarine of optical fiber table root the sea contamination material (rope, wire and net) it removes in advance and if the submarine of the optical fiber cable ease it does to arrive safely. And it is a work the Plough and ROV laying work hour laying work efficiency improvement and laying equipment it will be able to protect. So, This paper presents the monitoring system of ship information management and operation for marine survey and PLGR work in submarine optical fiber table construction enterprise. In order to achieve these purpose, overall serial multi-port communication modulo of configuration, realtime processing for management and operation of receiving data, realtime graph and a printout are described.

• The Transactions of the Korea Information Processing Society
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• v.4 no.2
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• pp.628-638
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• 1997

This paper describes an implementation of fault simulator that can switch level fault models such as transistor stuck-open and stuck-closed faults as well as stuck-at faults. It overcomes the limitation when only stuck-at faults are used in VLSI circuits. Signal flow of a transistor switch is bidirectional in its nature, but most of signal flows in a switch level circuits, about 95%, are in one direction. This fault simulator focuses on the way which changes a switch level circuit into a graph model with two directed edges. Two paths from Vdd to ground and from ground to directions. Logic simulation is performed along dominant signal flows. The switch level fault simulation estimates the dominant path by injecting switch-level fualts, and pattern vectors are used for faults simulation. Experimental results are shown to demonstrate correctness of the fault simulator.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.5
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• pp.179-186
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• 2014

Current networks such as social network, web page link, traffic network are big data which have the large numbers of nodes and edges. Many applications such as social network services and navigation systems use these networks. Since big networks are not fit into the memory, existing in-memory based analysis techniques cannot provide high performance. Frontier-Expansion-Merge (FEM) framework for graph search operations using three corresponding operators in the relational database (RDB) context. FEM exploits an index table that stores pre-computed partial paths for efficient shortest path discovery. However, the index table of FEM has low hit ratio because the indices are determined by distances of indices rather than the possibility of containing a shortest path. In this paper, we propose an method that construct index table using high degree nodes having high hit ratio for efficient shortest path discovery. We experimentally verify that our index technique can support shortest path discovery efficiently in real-world datasets.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.787-794
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• 2018

The various natural disasters such as floods and localized heavy rains are increasing due to the global warming. If a natural disaster can be detected and analyzed in advance and more effectively, it can prevent enormous damage of natural disasters. Recent development in visual sensor technologies has encouraged various studies on monitoring environments including rivers. In this paper, we propose a method to detect water regions from river images which can be exploited for river surveillance systems using video sensor networks. In the proposed method, we first segment a river image finely using the minimum spanning tree algorithm. Then, the seed regions for the river region and the background region are set by using the preliminary information, and each seed region is expanded by merging similar regions to segment the water region from the image. Experimental results show that the proposed method separates the water region from a river image easier and accurately.

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.6
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• pp.1241-1246
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• 2009

It has been suggested that Tae-Eum peoples are prone to obesity. Although extensive clinical observations have shown this tendency in Sasang Constitutional Medicine (SCM), no scientific hypothesis has been proposed to delineate its mechanism. According to SCM theory, Tae-Eum peoples have a hypoactive lung system and a hyperactive liver system. In this paper we propose a new hypothesis explaining the tendency of obesity in Tae-Eum people in the viewpoint of cell physiology. The hypoactive lung system might imply an attenuated 'respiration' at the cell/subcell level, namely mitochondrial oxygen consumption. Because a functional weakness in mitochondria energy metabolism indicates intrinsic hypo-activity in the consumption (or production) of metabolic energy, we deduced that the tendency can easily induce body weight gain via an increase in anabolism. This relation is also introduced in the graph of cellular metabolic power against body weight. To test this hypothesis, we analyzed the clinical data with 863 subjects. Statistical analysis of the data showed that Tae-Eum peoples had relatively a lower cellular metabolic power, and that the percentage of peoples with BMI>25 was significantly higher than that of the other constitutional types.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.10
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• pp.477-482
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• 2016

As being the advanced analytics indispensable on big data for agile decision-making and tactical planning in enterprises, distributed processing platforms, such as Hadoop and Spark which distribute and handle the large volume of data on multiple nodes, receive great attention in the field. In Spark platform stack, Spark SQL unveiled recently to make Spark able to support distributed processing framework based on SQL. However, Spark SQL cannot effectively handle advanced analytics that involves machine learning and graph processing in terms of iterative tasks and task allocations. Motivated by these issues, this paper proposes the design of SQL-based big data optimal processing engine and processing framework to support advanced analytics in Spark environments. Big data optimal processing engines copes with complex SQL queries that involves multiple parameters and join, aggregation and sorting operations in distributed/parallel manner and the proposing framework optimizes machine learning process in terms of relational operations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.603-607
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• 2004

The vision-based driver fatigue detection is one of the most prospective commercial applications of facial expression recognition technology. The facial feature tracking is the primary technique issue in it. Current facial tracking technology faces three challenges: (1) detection failure of some or all of features due to a variety of lighting conditions and head motions; (2) multiple and non-rigid object tracking and (3) features occlusion when the head is in oblique angles. In this paper, we propose a new active approach. First, the active IR sensor is used to robustly detect pupils under variable lighting conditions. The detected pupils are then used to predict the head motion. Furthermore, face movement is assumed to be locally smooth so that a facial feature can be tracked with a Kalman filter. The simultaneous use of the pupil constraint and the Kalman filtering greatly increases the prediction accuracy for each feature position. Feature detection is accomplished in the Gabor space with respect to the vicinity of predicted location. Local graphs consisting of identified features are extracted and used to capture the spatial relationship among detected features. Finally, a graph-based reliability propagation is proposed to tackle the occlusion problem and verify the tracking results. The experimental results show validity of our active approach to real-life facial tracking under variable lighting conditions, head orientations, and facial expressions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.821-826
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• 2010

The door-lock switch is one of the most important part in the front-load washer. As an safety system, it keeps the door locked while the front-load washer or the dish washer is working and generating heat and spin. The door of front-load washer needs the emotionality as well as the safety because the consumers always get feels when using it. In this paper, We study about emotional factors in the door of front-load washer and analyze the difference of emotionality as the structure of the door-lock switch changed. For this, we analyze the force graph by using the software and the jig which can measure the force while the door is opened or closed.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.549-554
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• 2016

ConceptNet is a common sense knowledge base which is formed in a semantic graph whose nodes represent concepts and edges show relationships between concepts. As it is difficult to make knowledge base integrity, a knowledge base often suffers from incompleteness problem. Therefore the quality of reasoning performed over such knowledge bases is sometimes unreliable. This work presents neural tensor networks which can alleviate the problem of knowledge bases incompleteness by reasoning new assertions and adding them into ConceptNet. The neural tensor networks are trained with a collection of assertions extracted from ConceptNet. The input of the networks is two concepts, and the output is the confidence score, telling how possible the connection between two concepts is under a specified relationship. The neural tensor networks can expand the usefulness of ConceptNet by increasing the degree of nodes. The accuracy of the neural tensor networks is 87.7% on testing data set. Also the neural tensor networks can predict a new assertion which does not exist in ConceptNet with an accuracy 85.01%.

• Tunnel and Underground Space
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• v.27 no.3
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• pp.121-131
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• 2017

We studied the time-dependent behaviors of rock and concrete materials by conducting the static and dynamic long-term strength tests. In particular, acoustic emission(AE) signals generated while the tests were analyzed and used for the long-term stability evaluation. In the static subcritical crack growth test, the long-term behavior and AE characteristics of Mode I and Mode II were investigated. In the dynamic long-term strength test, the fatigue limit and characteristics of generation of AE were analyzed through cyclic four points bending test. The graph of the cumulative AE hits versus time showed a shape similar to that of the creep curve with the first, second and third stages. The possibility for evaluating the static and dynamic long-term stability of rock and concrete is presented from the log - log relationship between the slope of the secondary stage of cumulative AE hits curve and the delayed failure time.