• Journal of The Korean Association For Science Education
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• v.40 no.6
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• pp.595-609
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• 2020

The purpose of this study is to analyze the experiences of teachers who participated in the development of online science class videos in the context of covid-19, their perception of online science class, and the characteristics of the online science class content developed by teachers. A survey and interviews were conducted with ten elementary school teachers who made online science class videos themselves. Also the characteristics of the online science class were investigated by analyzing the online science class video produced by the participants. As a result, participants in the study recognized the lack of production time, difficulty in filming and editing, concerns over misconceptions, the problem of solving copyrights for existing materials, and the burden of external disclosure. Although it was a teacher who had experience producing online science class video contents, no research participants actively answered the merits of online science class. On the other hand, the study participants cited that the shortcomings of online science classes were that students had fewer opportunities for inquiry and lack of communication or interaction. In particular, these shortcomings were thought to have a great influence on the quality of online science classes, especially in making inquiry classes difficult. Some teachers took a negative view that online science classes could not completely replace face-to-face classes. However, if multiple teachers are presented with supplementary teaching activities that complement the content-based online teaching method, the method of combining online science classes and face-to-face classes is not. Through the analysis of the contents of the online science class, the introduction and arrangement steps of the online science class were similar to the process of the face-to-face science class, but the inquiry step and the conceptual explanation step showed a big difference from the face-to-face science class.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.5
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• pp.31-36
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• 2011

In this paper, Mel-Frequency Cepstral Coefficient (MFCC), Decorrelated Filter Bank (DFB), Octave-based Spectral Contrast (OSC), Zero-Crossing Rate (ZCR), and Spectral Contract/Roll-Off are combined as a set of multiple feature-vectors for the music genre classification system based on the Support Vector Machine (SVM) classifier. In the conventional system, feature vectors for the entire genre classes are normalized for the SVM model training and classification. However, in this paper, selected feature vectors that are compared based on the One-Against-One (OAO) SVM classifier are only used for normalization. Using OSC as a single feature-vector and the multiple feature-vectors, we obtain the genre classification rates of 60.8% and 77.4%, respectively, with the conventional normalization method. Using the proposed normalization method, we obtain the increased classification rates by 8.2% and 3.3% for OSC and the multiple feature-vectors, respectively.

• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1136-1146
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• 2005

Fingerprint classification is useful in an automated fingerprint identification system (AFIS) to reduce the matching time by categorizing fingerprints. Based on Henry system that classifies fingerprints into S classes, various techniques such as neural networks and support vector machines (SVMs) have been widely used to classify fingerprints. Especially, SVMs of high classification performance have been actively investigated. Since the SVM is binary classifier, we propose a novel classifier-combination model, multiple decision templates (MuDTs), to classily fingerprints. The method extracts several clusters of different characteristics from samples of a class and constructs a suitable combination model to overcome the restriction of the single model, which may be subject to the ambiguous images. With the experimental results of the proposed on the FingerCodes extracted from NIST Database4 for the five-class and four-class problems, we have achieved a classification accuracy of $90.4\%\;and\;94.9\%\;with\;1.8\%$ rejection, respectively.

• Journal of KIISE:Software and Applications
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• v.26 no.12
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• pp.1468-1481
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• 1999

didates.본 논문은 절차 중심 소프트웨어를 객체 지향 소프트웨어로 재/역공학하기 위한 다단계 절차중 첫 절차인 객체 추출 절차에 대하여 기술한다. 사용한 객체 추출 방법은 전처리, 기본 분할 및 결합, 정제 결합, 결정 및 통합의 다섯 단계로 이루어진다 : 1) 전처리 과정에서는 객체 추출을 위한 FTV(Function, Type, Variable) 그래프를 생성/분할 및 클러스터링하고, 2) 기본 분할 및 결합 단계에서는 다중 객체 추출을 위한 그래프를 생성하고 생성된 그래프의 정적 객체를 추출하며, 3) 정제 결합 단계에서는 동적 객체를 추출하며, 4) 결정 단계에서는 영역 모델링과 다중 객체 후보군과의 유사도를 측정하여 영역 전문가가 하나의 최적합 후보를 선택할 수 있는 측정 결과를 제시하며, 5) 통합 단계에서는 전처리 과정에서 분리된 그래프가 여러 개 존재할 경우 각각의 처리된 그래프를 통합한다. 본 논문에서는 클러스터링 순서가 고정된 결정론적 방법을 사용하였으며, 가능한 경우의 수에 따른 다중 객체 후보, 객관적이고 의미가 있는 객체 추출 방법으로의 정제와 결정, 영역 모델링을 통한 의미적 관점에 기초한 방법 등을 사용한다. 이러한 방법을 사용함으로써 전문가는 객체 추출 단계에서 좀더 다양하고 객관적인 선택을 할 수 있다.Abstract This paper presents an object extraction process, which is the first phase of a methodology to transform procedural software to object-oriented software. The process consists of five steps: the preliminary, basic clustering & inclusion, refinement, decision and integration. In the preliminary step, FTV(Function, Type, Variable) graph for object extraction is created, divided and clustered. In the clustering & inclusion step, multiple graphs for static object candidate groups are generated. In the refinement step, each graph is refined to determine dynamic object candidate groups. In the decision step, the best candidate group is determined based on the highest similarity to class group modeled from domain engineering. In the final step, the best group is integrated with the domain model. The paper presents a new clustering method based on static clustering steps, possible object candidate grouping cases based on abstraction concept, a new refinement algorithm, a similarity algorithm for multiple n object and m classes, etc. This process provides reengineering experts an comprehensive and integrated environment to select the best or optimal object candidates.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.6
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• pp.75-82
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• 2005

The robust feature vector selection method for the multiple frontal face detection is proposed in this paper. The proposed feature vector for the training and classification are integrated by means, amplitude projections, and its 1D Harr wavelet of the input image. And the statistical modeling is performed both for face and nonface classes. Finally, the estimated probability density functions (PDFs) are applied for the detection of multiple frontal faces in the still image. The proposed method can handle multiple faces, partially occluded faces, and slightly posed-angle faces. And also the proposed method is very effective for low quality face images. Experimental results show that detection rate of the propose method is $98.3\%$ with three false detections on the testing data, SET3 which have 227 faces in 80 images.

• Structural Engineering and Mechanics
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• v.11 no.3
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• pp.259-272
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• 2001

The impact behavior of a multigirder concrete bridge under single and multiple moving vehicles is studied based on correlated road surface characteristics. The bridge structure is modeled as grillage beam system. A 3D nonlinear vehicle model with eleven degrees of freedom is utilized according to the HS20-44 truck design loading in the American Association of State Highway and Transportation Officials (AASHTO) specifications. A triangle correlation model is introduced to generate four classes of longitudinal road surface roughness as multi-correlated random processes along deck transverse direction. On the basis of a correlation length of approximately half the bridge width, the upper limits of impact factors obtained under confidence level of 95 percent and side-by-side three-truck loading provide probability-based evidence for the evaluation of AASHTO specifications. The analytical results indicate that a better transverse correlation among road surface roughness generally leads to slightly higher impact factors. Suggestions are made for the routine maintenance of this type of highway bridges.

• Journal of the Korean Society of School Health
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• v.30 no.2
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• pp.174-180
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• 2017

Purpose: This study examined depression, ego-resilience and health behaviors of high school student in order to understand the relationship among these variables. Methods: The study used raw data from the Korean Children and Youth Panel Survey conducted in 2015. Data was analyzed using SPSS 21.0 for descriptive statistics, t-test, $x^2$ test, Pearson's correlation coefficients, and multiple regression analysis. Results: Gender, school performance, economic status, subjective health status, drinking behavior and ego-resilience had significant effects on depression. Moreover, school performance, subjective health status, smoking behavior, duration of exercise during physical education classes, and depression had significant effects on ego-resilience. Conclusion: Based on these findings, we need to develop the interventions for depression and ego-resilience for adolescents, considering the related factors to health status and behaviors.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.2
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• pp.41-61
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• 2005

The concept of revenue management (RM) has been used widely in the air-transportation industry, and proven as a good system for managing perishable assets. While the airlines are the oldest and most sophisticated users of RM, these practices have been an enormously important innovation in other service industries such as the travel, the railway, the internet and the manufacturing industries. In this paper, reviewing several studies on RM, we introduce the fundamental concepts and the major models of RM covering seat allocation with multiple fare classes and overbooking. Future research directions also are suggested.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10b
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• pp.1481-1484
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• 2001

Most implementations of HTTP servers do not distinguish among requests for hypermedia data from different clients. Commercialization of Web site is becoming increasingly common. Therefore providing quality of service with members paying to the site is often an important issue for the hosts. For some uses, such as web prefetching or multiple priority schemes, different levels of service are desirable. We propose server-side TCP connection management mechanisms to provide two different levels of Web service, high and regular levels by setting different timeout for inactive connection. Therefore this mechanism can effectively provide different service classes even in the absence of operating system and network support.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.117-135
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• 2016

Performance enhancement is one of the most important issues in high performance distributed computing systems. In such computing systems, online users submit their jobs anytime and anywhere to a set of dynamic resources. Jobs arrival and processes execution times are stochastic. The performance of a distributed computing system can be improved by using an effective load balancing strategy to redistribute the user tasks among computing resources for efficient utilization. This paper presents a multi-class load balancing strategy that balances different classes of user tasks on multiple heterogeneous computing nodes to minimize the per-class mean response time. For a wide range of system parameters, the performance of the proposed multi-class load balancing strategy is compared with that of the random distribution load balancing, and uniform distribution load balancing strategies using simulation. The results show that, the proposed strategy outperforms the other two studied strategies in terms of average task response time, and average computing nodes utilization.