• Journal of Preventive Medicine and Public Health
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• v.37 no.4
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• pp.366-372
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• 2004

Objectives : This study was conducted to propose a new transmission/disequilibrium test(TDT) to test the linkage between genetic markers and disease-susceptibility genes based on haplotypes. Simulation studies were performed to compare the proposed method with that of Zhao et al. in terms of type I error probability and powers. Methods : We estimated the haplotype frequencies using the expectation-maximization(EM) algorithm with parents genotypes taken from a trio dataset, and then constructed a two-way contingency table containing estimated frequencies to all possible pairs of parents haplotypes. We proposed a score test based on differences between column marginals and their corresponding row marginals. The test also involved a covariance structure of marginal differences and their variances. In simulation, we considered a coalescent model with three genetic markers of biallele to investigate the performance of the proposed test under six different configurations. Results : The haplotype-based TDT statistics, our test and Zhao et al.'s test satisfied a type I error probability, but the TDT test based on single locus showed a conservative trend. As expected, the tests based on haplotypes also had better powers than those based on single locus. Our test and that of Zhao et al. were comparable in powers. Conclusion : We proposed a TDT statistic based on haplotypes and showed through simulations that our test was more powerful than the single locus-based test. We will extend our method to multiplex data with affected and/or unaffected sibling(s) or simplex data having only one parent s genotype.

• Journal of Digital Contents Society
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• v.16 no.1
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• pp.157-164
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• 2015

The existing input device is limited to keyboard and mouse. However, recently new type of input device has been developed in response to requests from users. To reflect this trend we propose the new type of input device that gives instruction as analyzing the hand motion of image without special device. After binarizing the skin color area using Cam-Shift method and tracking, it recognizes the hand motion by inputting the finger areas and the angles from the palm center point, which are separated through labeling, into four cardinal directions and counting them. In cases when specific background was not set and without gloves, the recognition rate remained approximately at 75 percent. However, when specific background was set and the person wore red gloves, the recognition rate increased to 90.2 percent due to reduction in noise.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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• pp.59-69
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• 2018

The up-to-date business environment for Korean manufacturers is very complex and rapidly changing. Especially, the companies have faced with various changes derived from small quantity batch production, diversification of customer demands, and short life cycles of products. Consequently, the Korean manufacturing companies are in need of more efficient production planning and scheduling techniques. In this paper, the research trend of scheduling techniques is investigated to provide relevant information to researchers in this field. Furthermore, some implications for future researches are presented regarding literatures published in Korea over the last 10 years. This paper presents an entire investigation into Korean research works on scheduling (2,569 papers) that are published from 2007 to 2016. Especially, detailed analysis was carried out in the following three industry : 1) semiconductor, 2) shipbuilding and 3) automobile. In this paper, approaches to scheduling presented in the literature are categorized into the following three categories : 1) application, 2) algorithm, and 3) simulation modeling. First, in the semiconductor industry, scheduling techniques related to semiconductor cleaning processes, photolithography processes, chemical processes, transport and transport equipment have been found to be dominant. Second, the shipbuilding industry is focused on assembly processes, transporter, crane and various existing production management system. On the other hand, the scheduling research of the automobile industry is mainly focused on the vehicle movement routing and procurement supply-chain planning algorithm in terms of logistics. The conclusion of this study are expected to provide many implications for various types of academic and practical follow-up studies related to scheduling in consideration of main characteristics of semiconductor, shipbuilding and automobile industries.

• Journal of KIISE:Information Networking
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• v.30 no.2
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• pp.143-154
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• 2003

There is a growing trend in developing system for distributed mobile system that supports services - job flow management, video conference, replicated data management and resource allocation. Supporting these services, applications have to use causally ordered message delivery. Previous proposals that provide causally ordered message delivery have problems such as communication overhead, message delaying, scalability, computing overload of mobile host. In this paper, we proposed efficient protocol for causally ordered message delivery using the methods that MSS maintains dependency information matrix between MSS and MH, Piggybacking dependency information about each immediate predecessor message. Proposed algorithm, when compared with previous proposals, provides a low message overhead, and low probability of unnecessary inhibition in delivering messages. Also, it consider resource restriction of MH and low bandwidth of wireless communication by computing most of algorithm at MSS, and reduce processing delay by executing causally ordered message delivery a unit of MH.

• Korean Institute of Interior Design Journal
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• v.26 no.6
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• pp.163-171
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• 2017

Brick is not only aesthetically beautiful and emotional material, but also eco-friendly and good building commodity for human health. Nonetheless, the use of brick has declined, due to the difficulty of building high-rise buildings and the limitation of the free form implementation. However, modern society is increasingly interested in environmentally friendly finishing materials for solving environmental problems. From this point of view, the brick architecture is being reexamined as a material to improve the living environment and to provide comfort without destroying nature. In addition, the development of digital technology enables the implementation of various types of masonry method and curved forms. Parametric design is one of the ways to realize the curved forms and various architectural expressions for brick architecture. In this background, the purpose of this study is to develop algorithms that can easily generate curved brick walls through parametric design, enable various pattern designs, and respond to real-time feedback. The details of the study are as follows. First of all, we examine organic architecture, the trend of brick architecture, and the concept of parametric design. Secondly, In order to generate curved surface with complex curvature, major planning factors affecting form generation are examined. Finally, we develop a parametric design method that consists of generating a curved surface for brick arrangement, implementing a parametric algorithm, and generating a curved form using bricks. Consequentially, we propose an algorithm that can maximize the use of ready-made bricks without using cut bricks to design curved walls and present efficient and economical design alternatives.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.269-276
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• 2015

Recently, with the activation of the industry related to the big data, the global security companies have expanded their scopes from structured to unstructured data for the intelligent security threat monitoring and prevention, and they show the trend to utilize the technique of user's tendency analysis for security prevention. This is because the information scope that can be deducted from the existing structured data(Quantify existing available data) analysis is limited. This study is to utilize the analysis of security tendency(Items classified purpose distinction, positive, negative judgment, key analysis of keyword relevance) applying the machine learning algorithm($Na{\ddot{i}}ve$ Bayes, Decision Tree, K-nearest neighbor, Apriori) in the big data environment. Upon the capability analysis, it was confirmed that the security items and specific indexes for the decision of security tendency could be extracted from structured and unstructured data.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.113-121
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• 2005

Face detection in real-time video constitutes one of the major trend in face recognition. In this paper, we propose a face detection algorithm using the skin color and Haar-like feature in real-time video. The proposed algorithm is followed by three sequences; First, moving objects are detected by difference-method in YCbCr coordinates, and then by using Haar-like features, face candidate regions of the moving objects is selected. Finally we extract the most possible face candidates by comparing the pixel values of face candidates with the skin color. In order to prevent a mistake. we use similar features or skin color to detect a face by selecting a adaptive ROI and improve the processing speed in real-time video. The computer simulation shows the validity of the proposed method that the processing speed is improved by 30% than previous works and the detection success rate is 96.8%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.219-222
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• 2011

There are number of methods that track the movement of an object or the change of state, such as Kalman filter, particle filter, dynamic clustering, and so on. Amongst these method, dynamic clustering method is an useful way to track cluster across multiple data frames and analyze their trend. In this paper we suggest the similarity-based dynamic clustering method, and verifies it's performance by simulation. Proposed dynamic clustering method is how to determine the same clusters for each continuative frame. The same clusters have similar characteristics across adjacent frames. The change pattern of cluster's characteristics in each time frame is throughly studied. Clusters in each time frames are matched against each others to see their similarity. Mamdani fuzzy model is used to determine similarity based matching algorithm. The proposed algorithm is applied to radar reflectivity data over time domain. We were able to observe time dependent characteristic of the clusters.

• The Transactions of the Korean Institute of Power Electronics
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• v.11 no.4
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• pp.302-306
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• 2006

The improvement of load following operation of the thermal power plant is influenced to the electrical quality. Analysis of boiler, turbine, and governor system, and the study of control algorithm are necessarily preceded. The thermal power plant is operated by various control systems. In the case of faulty governor system, it takes long days to solve the problem and impossible to repair the mechanism without outage. A non-planned outage is taken into consideration because of economical power production. The paper introduces the followings; In case of system-frequency drop during long term, at 500MW thermal power plant, the generator output was drop. To clear this problem, the control logic is modified with analysis of trend and control algorithm. As a result system frequency drop is prevented during the long tenn and the electric grid operation is improved.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.1
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• pp.11-20
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• 2012

Stream data shows a sequence of values changing continuously over time. Due to the nature of stream data, its trend is continuously changing according to various time intervals. Therefore the prediction of stream data must be carried out simultaneously with respect to multiple intervals, i.e. Continuous Multiple Prediction(CMP). In this paper, we propose a Continuous Integrated Hierarchical Temporal Memory (CIHTM) network for CMP based on the Hierarchical Temporal Memory (HTM) model which is a neocortex leraning algorithm. To develop the CIHTM network, we created three kinds of new modules: Shift Vector Senor, Spatio-Temporal Classifier and Multiple Integrator. And also we developed learning and inferencing algorithm of CIHTM network.