• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.46-48
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• 2005

이동 컴퓨팅 환경에서 다수의 이동 클라이언트들에게 데이터를 전달할 때는 클라이언트들의 동시 데이터 접근을 지원하는 브로드캐스트 기법을 사용하면 무선 채널 대역폭의 협소함과 클라이언트 측의 에너지 제약과 같은 단점을 해결할 수 있다. 기존 기법들은 클라이언트의 데이터에 대한 접근빈도(access frequencies)와 클라이언트의 에너지 효율(energy efficiency)을 동시에 고려하지 않았다. 따라서 원하는 데이터가 올 때까지 계속해서 채널을 들어야 함으로 인해 에너지 소비를 많이 하거나, 데이터를 얻을 때까지 추가한 많은 양의 정보에 따른 지연이 발생하는 단점이 있다. 본 논문에서는 클라이언트의 에너지 절약을 위한 tuning time을 최소화하고 실제 데이터를 얻을 때까지 소요되는 access time의 효율을 높이기 위해 데이터의 접근빈도와 에너지 효율을 동시에 고려하는 HIDAF: Hybrid Index considering Data Access Frequencies 기법을 제한한다. 제안하는 기법은 트리기반 기법과 해싱기반 기법을 함께 적용하여 구성한 인덱스를 브로드캐스트 주기에 배치한다. HIDAF 기법은 데이터 접근빈도를 고려한 트리기반 인덱스를 배치함으로써 데이터를 얻기 위한 클라이언트들의 평균 access time을 줄일 수 있고, 이러한 인덱스에 해싱기반 기법을 추가함으로써 클라이언트의 에너지 효율을 최소화하는 새로운 브로드캐스팅 기법이다. HIDAF 기법은 브로드캐스트 추기에 데이터의 접근빈도를 고려한 인덱스를 교차로 추가하여 핫 데이터에 대한 클라이언트들의 access time을 줄임으로써 전체 사용자에 대한 평균 access time을 최소화하는 동시에 클라이언트들의 제한된 에너지 소비를 최소화하는데 목적이 있다. 제안기법에 대한 평가는 수학적 분석을 통해 HIDAF 기법과 기존의 브로드캐스트 기법의 성능을 비교 분석한다.하였으나 사료효율은 증진시켰으며, 후자(사양, 사료)와의 상호작용은 나타나지 않았다. 이상의 결과는 거세비육돈에서 1) androgen과 estrogen은 공히 자발적인 사료섭취와 등지방 침적을 억제하고 IGF-I 분비를 증가시키며, 2) 성선스테로이드호르몬의 이 같은 성장에 미치는 효과의 일부는 IGF-I을 통해 매개될 수도 있을을 시사한다. 약 $70 {\~} 90\%$의 phenoxyethanol이 유상에 존재하였다. 또한, 미생물에 대한 항균력도 phenoxyethanol이 수상에 많이 존재할수록 증가하는 경향을 나타내었다. 따라서, 제형 내 oil tomposition을 변화시킴으로써 phenoxyethanol의 사용량을 줄일 수 있을 뿐만 아니라, 피부 투과를 감소시켜 보다 피부 자극이 적은 저자극 방부시스템 개발이 가능하리라 보여 진다. 첨가하여 제조한 curd yoghurt는 저장성과 관능적인 면에서 우수한 상품적 가치가 인정되는 새로운 기능성 신제품의 개발에 기여할 수 있을 것으로 사료되었다. 여자의 경우 0.8이상이 되어서 심혈관계 질환의 위험 범위에 속하는 수준이었다. 삼두근의 두겹 두께는 남녀 각각 $20.2\pm8.58cm,\;22.2\pm4.40mm$으로 남녀간에 유의한 차이는 없었다. 조사대상자의 식습관 상태는 전체 대상자의 $84.4\%$가 대부분이 하루 세끼 식사를 규칙적으로 하고 있었으며 식사속도는 허겁지겁 빨리 섭취하는 경우가 남자는 $31.0\%$, 여자는 $21.4\%$로 나타났고 이들을 제외한 나머지 사람들은 보통 속도 혹은 충분한 시간을 가지고 식사를 하였다. 평소 식사량은 조금 적게 혹은 적당하게 섭취하는 사람이 대부분이었으며 남자가 여자보다는 배부르게 먹는 경 향이 유의적으로 높았다(p<0.05). 식사는 혼자 하는 경우가 남자

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.4_1
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• pp.311-318
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• 2014

The data of buildings and structures take over large portions of the mapping database with large numbers. Furthermore, those shapes and attributes of building data continuously change over time. Due to those factors, the efficient methodology of updating database for following the most recent data become necessarily. This study has purposed on extracting needed data, which has been changed, by using overlaying analysis of new and old dataset, during updating processes. Following to procedures, we firstly searched for matching pairs of objects from each dataset, and defined the classification algorithm for building updating cases by comparing; those of shape updating cases are divided into 8 cases, while those of attribute updating cases are divided into 4 cases. Also, two updated dataset are set to be automatically saved. For the study, we selected few guidelines; the layer of digital topographic map 1:5000 for the targeted updating data, the building layer of Korea Address Information System map for the reference data, as well as build-up areas in Gwanak-gu, Seoul for the test area. The result of study updated 82.1% in shape and 34.5% in attribute building objects among all.

• Korean Journal of Optics and Photonics
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• v.11 no.6
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• pp.452-456
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• 2000

A measurement unit and signal processing algorithm have been developed for predicting arterial oxygen saturation noninvasively. The measurement set-up was composed of a probe including light source and photodetector, optical signal processing section, LED driving circuit, PC interface software for data acquisition and data processing software. Light from the LED's was irradiated onto the finger nail bed and transmitted light was measured at different wavelengths. An effective baseline correction method was developed and measured data were analyzed by using various data processing methods and prediction algOlithms. For performance evaluation, a pulse oximeter simulator (Bio- Tek Instrument Inc.) was used as reference. The best performance in terms of the correlation coefficient and the standard deviation was obtained under the following conditions; when the arterial signals were computed in terms of area rather than peak-valley difference, and when the algorithm calculating by $In(I_p/I_v)/I_{avr}$ value for pulsation waveform was used. In in vivo test, prediction was improved when the developed baseline correction method was used. In addition, wavelengths of 660 nm and 940 nm provided better linearity and precision than wavelengths of 660 nm and 805 nm. 05 nm.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.517-524
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• 2004

The fuzzy set theory has been wide used in clustering of machine learning with data mining since fuzzy theory has been introduced in 1960s. In particular, fuzzy C-means algorithm is a popular fuzzy clustering algorithm up to date. An element is assigned to any cluster with each membership value using fuzzy C-means algorithm. This algorithm is affected from the location of initial cluster center and the proper cluster size like a general clustering algorithm as K-means algorithm. This setting up for initial clustering is subjective. So, we get improper results according to circumstances. In this paper, we propose a cluster merging using enhanced density based fuzzy C-means clustering algorithm for solving this problem. Our algorithm determines initial cluster size and center using the properties of training data. Proposed algorithm uses grid for deciding initial cluster center and size. For experiments, objective machine learning data are used for performance comparison between our algorithm and others.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.4
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• pp.41-48
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• 2008

Currently used 3D models, which are mostly focused on visualization of 3D objects and lack topological structure, have limitation in being used for 3D spatial analyses and applications. However, implementing a full topology for the indoor spatial objects is less practical due to the increase of complexity and computation time. This study suggests an alternative method to build a 3D indoor model with less complexity using a spatial DBMS. Storing spatial and nonspatial information of indoor spaces in DB tables enables faster queries, computation and analyses. Also it is possible to display them in 2D or 3D using the queried information. This study suggests a 2D-3D hybrid data model, which combines the 2D topology constructed from CAD floor plans and stored in a spatial DBMS and the 3D visualization functionality. This study showed the process to build the proposed model in a spatial DBMS and use spatial functions and queries to visualize in 2D and 3D. And, then, as an example application, it illustrated the process to build an indoor evacuation simulator.

• Journal of the Korea Computer Industry Society
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• v.2 no.6
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• pp.837-844
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• 2001

XML has already been settled down as a standard for the exchange of commercial data on the web. Though most institutions have a wish to use XML document as an EDI form for all sorts of document exchange, it is unfortune that previous commercial data is still saved in the relational form of data base. Therefore, it is necessary that data saved in the relational form of data base be transformed into XML document form for the better use of document exchange. In order to transform relational form of data base to XML, one solution is to publish XML document by way of mapping each field of the relational form of data base table onto XML. However, in the case of building one XML document out of more i~km two data base tables, a join should be performed since a mere mapping associated with DTD tan not solve the problem. In this paper, we build the view for the XML in which alignments generated from the join are presented. and then through this view the contents with the relational form of data base should be transformed into XML. Briefly speaking, This paper aims to propose algorithm concerned with this transformation and to realize it.

• Journal of Korean Society of Archives and Records Management
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• v.16 no.3
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• pp.99-129
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• 2016

Records and archives on military sexual slavery should be managed systematically due to its historical and educational values. Currently, the National Records Designation related to the military sexual slavery by Japan are managed in various related organizations including the National Archives of Korea. Some private institutions have diverse collections on the military sexual slavery by Japan. They have a collection of various types of records and archives. This study aims to build an integrated metadata schema for managing the records and archives on the military sexual slavery by Japan. To achieve this goal, this study examined the institutions and organizations related to the military sexual slavery by Japan, and analyzed the types and characteristics of their records and archives. Based on the results, a metadata schema was proposed for the records and archives of the "Military Sexual Slavery by Japan."

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.1-6
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• 2019

This study visualized users reaction about movies based on keywords with high frequency. For this work, we collected data of movie reviews on . A total of six movies were selected, and we conducted the work of data gathering and preprocessing. Semantic network analysis was used to understand the relationship among keywords. Also, NetDraw, packaged with UCINET, was used for data visualization. In this study, we identified the differences in characteristics of review contents regarding each movie. The implication of this study is that we visualized movie reviews made by sentence as keywords and explored whether it is possible to construct the interface to check users' reaction at a glance. We suggest that further studies use more diverse movie reviews, and the number of reviews for each movie is used in similar quantities for research.

• The Korean Journal of Applied Statistics
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• v.35 no.5
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• pp.667-684
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• 2022

Gene expression data present the level of mRNA abundance of each gene, and analyses of gene expressions have provided key ideas for understanding the mechanism of diseases and developing new drugs and therapies. Nowadays high-throughput technologies such as DNA microarray and RNA-sequencing enabled the simultaneous measurement of thousands of gene expressions, giving rise to a characteristic of gene expression data known as high dimensionality. Due to the high-dimensionality, learning models to analyze gene expression data are prone to overfitting problems, and to solve this issue, dimension reduction or feature selection techniques are commonly used as a preprocessing step. In particular, we can remove irrelevant and redundant genes and identify important genes using gene selection methods in the preprocessing step. Various gene selection methods have been developed in the context of machine learning so far. In this paper, we intensively review recent works on gene selection methods using machine learning approaches. In addition, the underlying difficulties with current gene selection methods as well as future research directions are discussed.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.133-138
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• 2023

As a side effect of recent rapid climate change and global warming, the frequency and scale of flood disasters are increasing worldwide. In Korea, the water level of the Han River is a major management target for preventing flood disasters in Seoul, the capital of Korea. In this paper, to improve the water level prediction of the Han River based on machine learning, we perform a comprehensive assessment of the quality of related dataset and propose data preprocessing methods to improve it. Specifically, we improve the dataset in terms of completeness, validity, and accuracy through missing value processing and cross-correlation analysis. In addition, we conduct a performance evaluation using random forest and LightGBM to analyze the effect of the proposed data improvement method on the water level prediction performance of the Han River.