• Journal of The Korean Association For Science Education
• /
• v.28 no.4
• /
• pp.331-339
• /
• 2008

The aim of this study was to compare the effectiveness of microcomputer-based laboratory (MBL) with the traditional laboratory experiment on science classes in middle school. MBL tools were developed and applied for five experiment subjects chosen from middle school science textbook for MBL experiment classes, while usual experiment methods suggested in the textbook were used in traditional experiment classes. In order to evaluate the effects of MBL experiment class, achievement, graphic ability, science process skills, affective aspect related to science were tested before and after applying the MBL experiment. The result revealed that MBL experiment class was more effective than traditional experiment class in improving student's science achievement, science process skills, and graphic ability. The result also indicated that there was a significant difference between experiment and control group with regards to the effect on affective aspect related to science. From the above result, we can find the positive implication of applicability of MBL experiment as a new experiment tool at the early stage of introduction in a real context.

• Science of Emotion and Sensibility
• /
• v.11 no.4
• /
• pp.541-552
• /
• 2008

We cannot express emotions correctly with only speech because it is hard to estimate the kind, size, amount of emotions. Hamlet who is a protagonist in 'Hamlet' of Shakespeare has emotions which cannot be expressed within only speech because he is in various dramatic situations. So we supposed an artificial emotion, instead of expressing emotion with speech, expressing and visualizing current emotions with color and location. And we visualized emotions of characters in 'Hamlet' with the artificial emotion. We designed the artificial emotion to four steps considering peculiarities of emotion. First, the artificial emotion analyzes inputted emotional stimulus as relationship between causes and effects and analyzes its kinds and amounts. Second, we suppose Emotion Graph Unit to express generating, maintaining, decaying of analyzed one emotional stimuli which is outputted by first step, according to characteristic. Third, using Emotion Graph Unit, we suppose Emotion Graph that expresses continual same emotional stimulus. And we make Emotion Graph at each emotions, managing generation and decay of emotion individually. Last, we suppose Emotion Field can express current combined value of Emotion Graph according to co-relation of various emotions, and visualize current emotion by a color and a location in Emotion Field. We adjusted the artificial emotion to the play 'Hamlet' to test and visualize changes of emotion of Hamlet and his mother, Gertrude.

• Journal of KIISE:Software and Applications
• /
• v.35 no.9
• /
• pp.572-587
• /
• 2008

The Self-organizing Feature Map(SOFM) that is one of unsupervised neural networks is a very powerful tool for data clustering and visualization in high-dimensional data sets. Although the SOFM has been applied in many engineering problems, it needs to cluster similar weights into one class on the trained SOFM as a post-processing, which is manually performed in many cases. The traditional clustering algorithms, such as t-means, on the trained SOFM however do not yield satisfactory results, especially when clusters have arbitrary shapes. This paper proposes automatic clustering on trained SOFM, which can deal with arbitrary cluster shapes and be globally optimized by graph cuts. When using the graph cuts, the graph must have two additional vertices, called terminals, and weights between the terminals and vertices of the graph are generally set based on data manually obtained by users. The Proposed method automatically sets the weights based on mode-seeking on a distance matrix. Experimental results demonstrated the effectiveness of the proposed method in texture segmentation. In the experimental results, the proposed method improved precision rates compared with previous traditional clustering algorithm, as the method can deal with arbitrary cluster shapes based on the graph-theoretic clustering.

• Journal of Korean Society of Archives and Records Management
• /
• v.21 no.3
• /
• pp.61-78
• /
• 2021

Records on Japanese "Comfort Women" have been individually managed by private sectors or institutions, and some are provided as digital archives on the Internet. However, records of digital archives differ in the composition and representation of metadata by individual institutions. Meanwhile, there is a lack of a consistent structure to describe the relationships between and among these records, leading to their fragmentation and disconnectedness. This paper proposes a knowledge model for interlinking the digital archival resources and builds a knowledge graph by integrating the records from distributed digital archives. It derives common elements by analyzing metadata from the diverse digital archives and expresses them in standard vocabularies to semantically describe multiple entities and relationships of the digital archival resources. In particular, the study includes the refinement of collected data to search and thread dispersed records and the enrichment of external data to provide significant contextual information of records. An evaluation of the knowledge graph is performed via a query measuring the (dis)connectivity between the distributed records. As a result, the knowledge graph is capable of interlinking and retrieving fragmented records, providing substantial contextual information on the records with external data enrichment, and searching accurately to match the user's intentions through semantic-based queries.

• Proceedings of the Korean Information Science Society Conference
• /
• 2005.11a
• /
• pp.529-531
• /
• 2005

본 논문은 한국을 비롯하여 미국, 러시아 중국 등 4개국을 연결하는 글로벌 과학기술협업연구망인 글로리아드의 활용도를 측정하여 망의 유지, 보수 및 관리를 도와주며 망의 사용국가, 사용성격 등을 분석하는데 유용하게 사용할 수 있도록 하기 위하여 한국과학기술정보연구원에서 수행하고 있는 글로벌 과학기술협업연구망 구축사업의 일환인 글로리아드-한국 링크 활용도 모니터링 시스템 (GMON-KR) 개발 연구를 소개한다. GMON-KR은 넷플로우(Netflow) 기반의 트래픽 모니터링 시스템으로써 넷플로우 데이터를 분석하여 웹페이지 기반의 테이블과 그래프로 결과를 보여주며 10분을 주기로 결과 값을 자동으로 갱신한다. 또한, 분석 결과 값을 데이터베이스에 저장하므로 추후에 원하는 정보를 추출해낼 수 있다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2013.05a
• /
• pp.250-253
• /
• 2013

최근 카메라 영상을 이용한 제스처 인식 관련 연구가 활발히 진행되고 있다. 카메라 영상을 이용한 제스처 인식에서 많이 사용되는 학습 알고리즘에는 확률 그래프 모델인 HMM과 CRF 등이 있다. 이 학습 알고리즘들은 다차원의 연속된 실수 데이터를 가지고 모델을 학습하면 계산량이 많아진다. 본 논문에서는 팔 관절 위치 데이터를 k-평균 군집화 과정을 거쳐 1차원의 시계열 데이터로 변환 후, 제스처별로 HMM 모델을 학습하는 방법을 제안한다. 키넥트 센서를 통해 얻은 팔 관절 위치 데이터에 k-평균 군집화를 적용하여 1차원 시계열 데이터를 생성하고, 이를 HMM의 학습 및 인식에 사용한다. 본 논문에서 제안하는 방법의 성능을 분석하기 위하여, 다른 시계열 학습 알고리즘인 AP+DTW를 이용한 방법과의 비교 실험을 포함해 다양한 실험들을 수행하였다.

• Journal of KIISE:Software and Applications
• /
• v.27 no.5
• /
• pp.551-562
• /
• 2000

Content-based image retrieval system retrieves an image from a database using visual features. Among approaches to express visual aspects in queries, 'query by sketch' is most convenient and expressive. However, every 'query by sketch' system has the query imperfectness problem. GContent-based image retrieval system retrieves an image from a database using visual features. Among approaches to express visual aspects in queries, 'query by sketch' is most convenient and expressive. However, every 'query by sketch' system has the query imperfectness problem. Generally, the query image produced by a user is different from the intended target image. To overcome this problem, many image retrieval systems use the spatial relationships of the objects, instead of pixel coordinates of the objects. In this paper, a query-converting algorithm for an image retrieval system, which uses the spatial relationship of every two objects as an image feature, is proposed. The proposed algorithm converts the query image into a graph that has the minimum number of edges, by eliminating every transitive edge. Since each edge in the graph represents the spatial relationship of two objects, the elimination of unnecessary edges makes the retrieval process more efficient. Experimental results show that the proposed algorithm leads the smaller number of comparison in searching process as compared with other algorithms that do not guarantee the minimum number of edges.

• Journal of KIISE:Computer Systems and Theory
• /
• v.29 no.7
• /
• pp.411-421
• /
• 2002

In this Paper we propose a new Image analysis algorithm for microarray processing and a method to locate the position of the grid cell using the topology of the grid spots. Microarray is a device which enables a parallel experiment of 10 to 100 thousands of test genes in order to measure the gene expression. Because of the huge data obtained by a experiment automated image analysis is needed. The final output of this microarray experiment is a set of 16-bit gray level image files which consist of grid-structured spots. In this paper we propose one algorithm which located the address of spots (spot indices) using graph structure from image data and a method which determines the precise location and shape of each spot by measuring the inclination of grid structure. Several experiments are given from real data sets.

• Journal of KIISE
• /
• v.41 no.12
• /
• pp.1117-1125
• /
• 2014

Folksonomy data, which is derived from social tagging systems, is a useful source for understanding a user's intention and interest. Using the folksonomy data, it is possible to create an accurate user profile which can be utilized to build a personalized search system. However there are limitations in some of the traditional methods such as Vector Space Model(VSM) for user profiling and similarity computation. This paper suggests a novel method with graph-based user and document profile which uses the proximity information of query terms to improve personalized search. We demonstrate the performance of the suggested method by comparing its performance with several state-of-the-art VSM based personalization models in two different folksonomy datasets. The results show that the proposed model constantly outperforms the other state-of-the-art personalization models. Furthermore, the parameter sensitivity results show that the proposed model is parameter-free in that it is not affected by the idiosyncratic nature of datasets.

• Journal of KIISE:Information Networking
• /
• v.28 no.3
• /
• pp.447-453
• /
• 2001

In this paper, we consider the scheduling of SE(switching element)-disjoint multicasting in photonic Banyan-type switching networks constructed with directional couplers. This ensures that at most, one connection holds each SE in a given time thus, neither crosstalk nor blocking will arise in the network. Such multicasting usually takes several routing rounds hence, it is desirable to keep the number of rounds(i.e., scheduling length) to a minimum. We first present the necessary and sufficient condition for connections to pass through a common SE(i.e., make crosstalk) in the photonic Banyan-type networks capable of supporting one-to-many connections. With definition of uniquely splitting a multicast connection into distinct subconnections, the crosstalk relationship of a set of connections is represented by a graph model. In order to analyze the worst case crosstalk we characterize the upper bound on the degree of the graph. The successor paper(Part II)[14] is devoted to the scheduling algorithm and the upper bound on the scheduling length. Comparison with related results is made in detail.