• Journal of IKEEE
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• v.12 no.1
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• pp.65-74
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• 2008

One of the popular methods used for pattern classification is the MBR (Memory-Based Reasoning) algorithm. Since it simply computes distances between a test pattern and training patterns or hyperplanes stored in memory, and then assigns the class of the nearest training pattern, it is notorious for memory usage and can't learn additional information from new data. In order to overcome this problem, we propose an incremental learning algorithm (iMPA). iMPA divides the entire pattern space into fixed number partitions, and generates representatives from each partition. Also, due to the fact that it can not learn additional information from new data, we present iMPA which can learn additional information from new data and not require access to the original data, used to train. Proposed methods have been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory using benchmark data sets from UCI Machine Learning Repository.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.88-88
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• 2011

수자원에서 일강수량 모의기법은 다양한 목적으로 활용되고 있으며 기본적으로 수공구조물 설계 및 수자원계획을 수립하기 위한 입력 자료로서 이용된다. 수자원계획은 장기적인 목적을 가지고 수행되는 것이 일반적이며 우리가 목표로 하는 장기간의 일강수량자료의 획득이 어렵기 때문에 단기간의 일강수량자료를 장기 모의하여 이용하게 된다. 일강수량을 모의하는데 있어서 강수계열의 단기간의 기억(memory)을 활용한 Markov Chain 모형이 가장 일반적이며, 기존 Markov Chain 모형을 통한 일강수량 모의에서 발생하는 가장 큰 문제점은 극치강수량을 재현하기 어렵다는 점이다. 이러한 문제점으로 인해 수자원 계획을 수립하는데 있어서 불확실성을 가중시키고 있다. 특히 일강수량 모의기법을 통해서 추정되는 빈도강수량의 과소추정으로 인해 수공구조물 설계 시에 신뢰성을 확보하는 데 문제점이 있다. 이러한 점에서 본 연구에서는 기존 Markov Chain 모형에서 일강수량에 평균적인 특성과 극치특성을 동시에 재현할 수 있도록 불연속 Kernel-Pareto Distribution 기반에 일강수량모의기법을 개발하였다. 한강유역의 3개 강수지점에 대해서 기존 Markov Chain 모형과 본 연구에서 제안한 방법을 적용한 결과 여름의 일강수량 모의 시 1차모멘트인 평균과 2-3차 모멘트 모두 효과적으로 재현하지 못하는 문제점이 나타났다. 그러나 본 연구에서 제안한 불연속 Kernel-Pareto 분포형 기반 Markov Chain 모형은 여름의 일강수량 모의 시 강수계열의 평균적인 특성뿐만 아니라 표준편차 및 왜곡도의 경우에도 관측치의 통계특성을 매우 효과적으로 재현하는 것으로 나타났다. 본 연구에서 제시한 방법론은 전체적으로 기존 Markov Chain 모형에 비해 극치강수량을 재현하는데 유리한 기법으로 판단되며, 또한 극치강수량을 일반강수량으로부터 분리하여 모의함으로서 평균 및 중간값 등 낮은 차수에 모멘트 등 일강수량에 전체적인 분포특성을 더욱 효과적으로 모의할 수 장점을 확인하였다.

• Design Convergence Study
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• v.18 no.4
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• pp.1-15
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• 2019

As the game industry is steadily becoming the spotlight industry, the importance of user experience design in game industry is increasing. This study tried to approach game from the viewpoint of user experience design and aimed to analyze the onboarding process focusing on user accessibility and retention in an online game. First, through literature review, onboarding process was devided into three stages. Then each stages were analyzed into experience design, game design elements to derive the key UX factors. Second, based on the UX elements, the game experience and cognitive element analysis frame was presented. With this frame, five domestic online games were qualitatively analyzed and cognitive elements of each game's onboarding process were derived. Key cognitive factors in each stages were, selective attention in the discovery stage, working memory and active learning in the learning stage, and participation and motivation in the immersion stage. Finally, improvement direction were presented, focusing on the key cognitive factors. These studies highlight the importance of the user entry process in online games and suggests improvements to lower entry barriers.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.3
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• pp.356-363
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• 2000

Java programming language is designed to run effectively on internet and distributed network environments. However, because it has a deficit to be executed by the interpreter method on each platform, to execute Java programs efficiently the code generation system which transforms Bytecode into SPARC code as target machine code must be developed. In this paper, we implement a code generation system which translates Bytecode into SPARC code using the retargetable code generating techniques. For the sake of code expander, we wrote a Bytecode table describing a rule of SPARC code generation from Bytecode, and implemented the information extractor transforming Bytecode to suitable form during expanding of source code from class file. The information extractor determines constant pool entry of each Bytecode instruction operand and then the code expander translates the Bytecode into SPARC code accoring to the Bytecode table. Also, the retargetable code generation system can be systematically reconfigured to generate code for a variety of distinct target computers.

• Journal of Korea Game Society
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• v.14 no.4
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• pp.45-52
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• 2014

We cannot load the entire data for high-resolution terrain model to the GPU memory since its size is too big. Out-of-core approaches are commonly used to solve the problem. However, due to limited bandwidth of the secondary storage, it is difficult to render the terrain in real-time. A method that compresses the DEM data with wavelet transform on GPU, and renders the decoded data is suggested. However, it is inefficient since it has to sample the values from textures, convert them to vertices, and generate a mesh periodically. We propose a method to store the approximation coefficients of wavelet compression as vertex attributes and render the terrain by decoding the data on geometric shader. It can reduce the amount of transferring terrain texture since approximation coefficients are given as an attribute of the vertex. Also, it generate meshes without additional upload of terrain texture.

• Journal of Practical Engineering Education
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• v.12 no.1
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• pp.41-47
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• 2020

This study aims to investigate effects of brain-based learning. 27 primary studies were selected through rigorous search process and analyzed through meta-analytic methods. Research findings are as follows. First, the total effect size was .67. Second, the effect of dependent variables was academic achievement, cognitive domain, and affective domain in order. Third, with respect to types of cognitive domain, the effect was self-regulation, creativity, competence, communication, and research ability in order. Fourth, the effect of affective domains was sociality, learning interest, and subject attitude in order. Fifth, regarding development of cognitive ability, the effect size was combined, brain training, learning environments, and right brain activities in order. Sixth, the effect of learning activities was memory improvement and attention enhancement in order.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.4
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• pp.595-599
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• 2013

Alzheimer's disease is a progressive neurodegenerative disorder characterized by a gradual decline in memory associated with shrinkage of brain tissue, with a localized loss of neurons mainly in the hippocampus and basal forebrain. This study investigated the neuroprotective effect of Gastrodia elata aqueous extracts against scopolamine-induced neurotoxicity in the hippocampus of male Sprague-Dawley rats. The animals (n=25) were divided into five different groups with five animals per each group. The normal group (Nor) was administered with saline, while the control (Con) group was administered saline after scopolamine treatment. The experimental group (Exp) was administered Gastrodia elata aqueous extracts (200 mg/kg body weight) for 20 or 30 days after scopolamine treatment. From a light microscopy study, the nuclei of neurons in the hippocampus were more shrunken or condensed in the 20 or 30 day control groups compared to experimental groups. The densities of neurons from the CA1 and CA3 area of the hippocampus in the Exp increased compared with the Con. Amyloid ${\beta}$ protein, containing PAS-positive materials, was lower in the Exp compared with the Con. The present study demonstrates that Gastrodia elata aqueous extracts possess neuroprotective potential, thus validating its use in alleviating the toxic effects of scopolamine.

• Sleep Medicine and Psychophysiology
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• v.11 no.1
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• pp.44-49
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• 2004

Objectives: The purpose of this study was to investigate whether longitudinal changes in positive and negative symptoms affect cognitive functioning in chronic schizophrenia. Methods: Sixty-eight patients diagnosed with DSM-IV schizophrenia were examined on two occasions over 6 months for symptoms and cognitive changes. Symptoms were measured by PANSS. Cognitive functions were examined for sustained attention, executive function, concentration and attention, and verbal memory and learning using Degraded Stimulus Continuous Performance Test, Wisconsin Card Sorting Test, Digit Span, and Rey Auditory Verbal Learning Test, respectively. Twenty control subjects were assessed to compare the cognitive scores of remitted schizophrenic patients. Results: Patients showed significant improvement in symptoms and all cognitive tests after 6 months treatments. Significant improvements in positive and negative symptoms did not predict improvements in any aspect of cognitive functioning measured. Normal controls performed significantly better than remitted schizophrenic patients on all cognitive tests. The results show no relationship between change in symptoms and change in cognition in chronic schizophrenia. Conclusion: We suggest that symptomatic and cognitive impairment may be a distinct construct. These findings highlight the importance of treating cognitive impairment in addition to the clinical symptoms of schizophrenia.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.11
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• pp.622-633
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• 2002

Authentication and Key Agreement using password provide convenience and amenity, but what human can remember has extremely low entropy. To overcome its defects, AMP(Authentiration and key agreement via Memorable Password) which performs authentication and key agreement securely via low entropy password are presented. AMP uses Diffie-Hellman problem that depends on discrete logarithm problem. Otherwise, this thesis applies elliptic curve cryptosystem to AMP for further efficiency That is, this thesis presents EC-AMP(Elliptic Curve-AMP) protocol based on elliptic curve discrete logarithm problem instead of discrete logarithm problem, and shows its high performance through the implementation. EC-AMP secures against various attacks in the random oracle model just as AMP Thus, we nay supply EC-AMP to the network environment that requires authentication and key agreement to get both convenience and security from elliptic curve discrete logarithm problem.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.6
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• pp.558-571
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• 1992

In this paper, we propose an improved method of state exploration called the extended circular exploration (ECE) for the efficiency of state exploration and the reduction of explosively growing state. The ECE does not need to explore all the reachable global states, and It can be applied to JV($\boxDr$$\geq$ 2) -party protocol with alternative routes, i.e., it is applicable to the protocol In which adaptiverouting mechanism can be performed. The ECE eliminates a restriction of topology of the conventional circular exploration(CE) by exploring only those global states which are reachable, provided that the participant processes of any group of transitions proceed at the same speed, and that they can be formed as a cycle. Thus the state space explored if not exhaustive. The algorithm presented can detect deadlock error and unspecified reception error It requires storage space and /or execution time much less than those of the conventional perturbation(CP) . It might be used for a solution of the N-process collision and the interference mechanism.