• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.715-717
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• 2005

Support vector machine(SVM)은 최근 각광받는 기계학습 방법 중 하나로서, kernel function 이라는 사상(mapping)을 이용하여 입력 공간의 벡터를 classification이 용이한 특징 (feature) 공간의 벡터로 변환하는 것을 근간으로 한다. SVM은 이러한 특징 공간에서 두 클래스를 구분 짓는 hyperplane을 일련의 최적화 방법론을 사용하여 찾아내며, 주어진 문제가 convex problem 인 경우 항상 global optimal solution 을 보장하는 등의 장점을 지닌다. 한편 bioinformatics 연구에서 주로 사용되는 데이터는 측정 오류 등 일련의 오류를 포함하고 있으며, 이러한 오류는 기계학습 방법론이 어떤 decision boundary를 찾아내는가에 영향을 끼치게 된다. 특히 SVM의 경우 이러한 오류는 특징 공간 벡터간의 관계를 나타내는 Gram matrix를 변화로 나타나게 된다. 본 연구에서는 입력 공간에 오류가 발생할 때 그것이 SVM 의 decision boundary를 어떻게 변화시키는가를 대표적인 두 가지 kernel function, 즉 linear kernel과 Gaussian kernel에 대해 분석하였다. Wisconsin대학의 유방암(breast cancer) 데이터에 대해 실험한 결과, 데이터의 오류에 따른 SVM 의 classification 성능 변화 양상을 관찰하여 커널의 종류에 따라 SVM이 어떠한 특성을 보이는가를 밝혀낼 수 있었다. 또 흥미롭게도 어떤 조건 하에서는 오류가 크더라도 오히려 SVM 의 성능이 향상되는 것을 발견했는데, 이것은 바꾸어 생각하면 Gram matrix 의 일부를 변경하여 SVM 의 성능 향상을 꾀할 수 있음을 나타낸다.

• English Language & Literature Teaching
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• v.16 no.4
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• pp.153-184
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• 2010

On the bases of the 5 principles and the 4 criteria for designing and developing of the listening and the reading test of National English Ability Test (NEAT), this study presents Item-Types Decision-Making Model as a blueprint for designing and constructing the two tests. It sets up the criteria for validating item types, designs a modular type of test specifications, constructs an item-types bank, and specifies a complementary type of test specifications of the two tests. To gather all these threads up, it constructs Item-Types Decision-Making Model which consists of such components as the item-type pool, the validity criteria and the procedures of testing item types, the item-types bank, the modular and the complementary type test specification. Thus, it shows how the Model works in developing and constructing the two level-differentiated listening and reading tests (the 2nd and the 3rd rank) of NEAT. Finally, it discusses some implications and applications of the Model to the two level-differentiated tests (the A and the B type) of 2014 CSAT (College Scholastic Ability Test) systems, National Assessment of Educational Achievement (NAEA), and classroom testing. In conclusion, Item-Types Decision-Making Model functions as a testing template in an item development system and as a matrix in an item-types bank system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.5
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• pp.467-476
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• 2010

For the very light jet aircraft design, the design baseline configuration has been selected using the logical decision making process, and the design optimization problem is formulated by considering the airworthiness regulations as design constraints. Airworthiness regulations are the minimum requirements for the safe aircraft flight and must be considered from the conceptual design stage. After carefully selecting the airworthiness constraints and the user specified requirements, a series of design making models including the affinity diagram, nested column diagram, quality function deployment (QFD), Pugh concept selection matrix, are used to find and evaluate alternative configuration baselines. From the feasible design space searching process, the best altenative design, which satisfies the airworthiness constraints while excluding the user subjective decisions as much as possible, has been successfully derived.

• Journal of the Korea Institute of Building Construction
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• v.16 no.4
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• pp.331-339
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• 2016

According to high-rise, complexation, and enlargement of buildings, various construction methods are being developed, and the significance of construction method selection about main work types has emerged as a major interest. However, it has been pointed out that hand-on workers cannot consider project characteristics carefully, and they lack an objective standard or reference for main construction method selection. Hence, the selection is being made depending on hand-on workers' experience and intuition. To solve this problem, various studies have proceeded for construction method selection of main work types using Artificial Intelligence like Fuzzy, AHP and Case-based reasoning. It is difficult to apply many different kinds of construction method selection to every main work type with consideration for characteristics of work types and condition of a construction site when selecting construction method in the field. Accordingly, this study proposed the decision-making model which can apply to fields easily. Using matrix analysis and liner transformation, this study verified consistency of study models applied in the process of soil retaining selection with a case study.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.1C
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• pp.82-91
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• 2005

This paper introduces an efficient affine projection algorithm(APA) using iterative hyperplane projection. Among various fast converging adaptation algorithms, APA has been preferred to be employed for various applications due to its inherent effectiveness against the rank deficient problem. However, the amount of complexity of the conventional APA could not be negligible because of the accomplishment of sample matrix inversion(SMI). Moreover, the 'shifting invariance property' usually exploited in single channel case does not hold for the application of space-time decision-directed equalizer(STDE) deployed in single-input-multi-output(SIMO) systems. Thus, it is impossible to utilize the fast adaptation schemes such as fast transversal filter(FlF) having low-complexity. To accomplish such tasks, this paper introduces the low-complexity APA by employing hyperplane projection algorithm, which shows the excellent tracking capability as well as the fast convergence. In order to confirm th validity of the proposed method, its performance is evaluated under wireless SIMO channel in respect to bit error rate(BER) behavior and computational complexity.

• Journal of Korean Society for Quality Management
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• v.41 no.3
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• pp.465-474
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• 2013

Purpose: To provide a variety of stable military supplies, risk should be avoided or removed. This paper aims to provide an objective method of risk assesment for risk matrix to evaluate risk level. Methods: According to previous results of risk assesment through risk matrix, some parameters and probability density functions, which include characteristics of military supplies, are selected and Risk matrix is modelled based on that. Results: Results show that a proposed method can evaluate objectively risk level through the stochastic modelling and provide well-balanced risk assessments by categorizing into 3 levels such as high, middle and low level risk. Conclusion: A current risk assessment method includes substantial subjectivity of risk assessment and as a problem about military supplies comes up, we can not show any appropriate evidences for decision of risk assessment. We propose an objective scheme employing stochastic modelling with parameters and probability density functions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.12C
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• pp.1167-1174
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• 2005

In this paper, we propose a priority method on same co-occurrence count in adaptive rank-based reindexing scheme for lossless indexed image compression. The priority on same co-occurrence count in co-occurrence count matrix depends on a front count value on each raw of co-occurrence count matrix, a count value around diagonal line on each raw of the matrix, and a count value around large co-occurrence count on each raw of the matrix. Experimental results show that our proposed method can be reduced up to 1.71 bpp comparing with Zeng's and Pinho's method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1036-1057
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• 2013

Wireless body area network (WBAN) is a promising candidate for future health monitoring system. Nevertheless, the path to mature solutions is still facing a lot of challenges that need to be overcome. Energy efficient scheduling is one of these challenges given the scarcity of available energy of biosensors and the lack of portability. Therefore, researchers from academia, industry and health sectors are working together to realize practical solutions for these challenges. The main difficulty in WBAN is the uncertainty in the state of the monitored system. Intelligent learning approaches such as a Markov Decision Process (MDP) were proposed to tackle this issue. A Markov Decision Process (MDP) is a form of Markov Chain in which the transition matrix depends on the action taken by the decision maker (agent) at each time step. The agent receives a reward, which depends on the action and the state. The goal is to find a function, called a policy, which specifies which action to take in each state, so as to maximize some utility functions (e.g., the mean or expected discounted sum) of the sequence of rewards. A partially Observable Markov Decision Processes (POMDP) is a generalization of Markov decision processes that allows for the incomplete information regarding the state of the system. In this case, the state is not visible to the agent. This has many applications in operations research and artificial intelligence. Due to incomplete knowledge of the system, this uncertainty makes formulating and solving POMDP models mathematically complex and computationally expensive. Limited progress has been made in terms of applying POMPD to real applications. In this paper, we surveyed the existing methods and algorithms for solving POMDP in the general domain and in particular in Wireless body area network (WBAN). In addition, the papers discussed recent real implementation of POMDP on practical problems of WBAN. We believe that this work will provide valuable insights for the newcomers who would like to pursue related research in the domain of WBAN.

• The Journal of the Acoustical Society of Korea
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• v.20 no.6
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• pp.87-93
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• 2001

As a new type of a linear decorrelating receiver, the Pseudo-Decorrelator was presented for asynchronous code division multiple access systems by the author. In this paper, the concept of the Pseudo-Decorrelator is extended to derive a receiver for WCDMA uplink systems over an additive white Gaussian noise channel. Starting with the analysis of the multiple access components of the decision statistics, a non-square cross-correlation matrix for each bit is obtained. This cross-correlation matrix is then inverted, and the inverted matrix is applied to the decision statistics obtained from a conventional receiver. In this receiver, the detection process can be started after the first three consecutive bits are received. Simulation results are presented for K-user systems over an additive white Gaussian noise channel under the circumstances in which synchronization errors, including time delay errors and carrier phase errors exist. It is shown that the proposed receiver performs better than a conventional receiver and parallel interference canceller.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.11
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• pp.1237-1242
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• 2007

In this paper, we study STBC(Space Time Block Code) detection scheme in time varying Rayleigh fading channel. When the channel is varying during the time duration of STBC, the channel matrix of orthogonal STBC is not orthogonal. To get the optimum reception performance in this channel, joint ML detection scheme may be used, however this scheme requires high computation complexity. Decision feedback scheme is proposed to reduce the computation complexity with less reception performance. In this paper, we propose a novel STBC detection algorithm using double decision feedback which is less complex than the joint ML scheme and outperforms the conventional decision feedback scheme.