• Journal of the Korea Institute of Building Construction
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• v.21 no.3
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• pp.195-202
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• 2021

Concrete quality is mainly managed through the reliable prediction and control of compressive strength. Although related industries have established a relevant datasets based on the mixture proportions and compressive strength gain, whereas they have not been shared due to various reasons including technology leakage. Consequently, the costs and efforts for quality control have been wasted excessively. This study aimed to develop a web-based numerical model, which would present diverse optimal values including concrete strength prediction to the user, and to establish a sustainable database (DB) collection system by inducing the data entered by the user to be collected for the DB. The system handles the overall technology related to the concrete. Particularly, it predicts compressive strength at a mean accuracy of 89.2% by applying the artificial neural network method, modeled based on extensive DBs.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.3
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• pp.23-30
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• 2010

Compression techniques can be applied to large-scale fingerprint systems to store or transmit fingerprint data efficiently. In this paper, we investigate the effects of FBI WSQ fingerprint image compression on the performance of a fingerprint verification system using multiple linear regressions. We propose a maximum compression using fingerprint image quality score. Based on the experiments, we can confirm that the proposed approach can compress the fingerprint images up to 3 times more than the fixed compression ratio without significant degradation of the verification accuracy.

• Journal of the Korea Society of Computer and Information
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• v.5 no.2
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• pp.81-89
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• 2000

In this thesis. we. present a Telemedicine System that uses the communication network as the 2s6kbps exclusive line or 10Mbps Ethernet LAN. This system can make it possible for remote hospital or doctor to search and retrieve medical images and information from the central hospitals the have advanced technologies, and to support Teleconsulting with medical experts. To solve the speed limits. JPEG compression method and Distributed system used.

• Digital Contents
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• no.3 s.94
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• pp.48-49
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• 2001

인터넷이 가상의 세계라는 용어를 붙이기 시작한 것은 이미 오래된 얘기고 또한 보편화되었다. 이제 세계 각국은 그 가상의 공간에 현실의 공간을 압축해서 넣고 있다. 이제 우리는 현실과 가상의 공간을 넘나들며 21세기식의 생활을 영위할 것이다. 이 글은 참고적으로 새로운 인터넷 사업을 구상할 수도 있을 것으로 보여진다.

• Journal of Biomedical Engineering Research
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• v.16 no.1
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• pp.17-24
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• 1995

This paper presents a new compression method (or ECG data using iterated contractive transformations. The method represents any range of ECG signal by piecewise self-afrine fractal Interpolation (PSAFI). The piecewise self-afrine rractal model is used where a discrete data set is viewed as being composed of contractive arfine transformation of pieces of itself. This algorithm was evaluated using MIT/BIH arrhythmia database. PSAFI is found to yield a relatively low reconstruction error for a given compression ratio than conventional direct compression methods. The compression ratio achieved was 883.9 bits per second (bps) - an average percent rms difference (AFRD) of 5.39 percent -with the original 12b ECG samples digitized at 400 Hz.

• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.1023-1043
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• 2010

As main memory get cheaper, it becomes increasingly affordable to load entire index of DBMS and to access the index. Since speed gap between CPU and main memory is growing bigger, many researches to reduce a cost of main memory access are under the progress. As one of those, cache conscious trees can reduce the cost of main memory access. Since cache conscious trees reduce the number of cache miss by compressing data in node, cache conscious trees can reduce the cost of main memory. Existing cache conscious trees use only fixed one compression technique without consideration of properties of data in node. First, this paper proposes the DC-tree that uses various compression techniques and change data layout in a node according to properties of data in order to reduce cache miss. Second, this paper proposes the level of compression locality that describes properties of data in node by formula. Third, this paper proposes Forced Partial Decomposition (FPD) that reduces the nutter of cache miss. DC-trees outperform 1.7X than B+-tree, 1.5X than simple prefix B+-tree, and 1.3X than pkB-tree, in terms of the number of cache misses. Since proposed DC-trees can be adopted in commercial main memory database system, we believe that DC-trees are practical result.

• Annual Conference of KIPS
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• 2004.11a
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• pp.125-128
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• 2004

최근 이동 통신 기술의 급속한 발달로 인해 휴대폰, PDA 등과 같은 휴대용 단말기의 사용이 보편화 되고 있다. 따라서 이동 객체의 시간에 따른 공간적인 위치정보를 활용하여 다양한 서비스를 제공하는 위치 기반 서비스(Location-Based Service)에 관한 많은 연구가 진행되고 있다. 위치 기반 서비스의 효율적 제공을 위하여 시간에 따라 지속적으로 변하는 이동 객체의 대용량 시공간 정보를 신속하게 저장, 관리, 검색할 수 있는 인덱싱 및 질의 처리 기술이 수반되어야 한다. 본 논문에서는 대용량 이동 객체 데이터베이스를 대상으로 한 효율적인 인덱스 구축을 위한 데이터 압축 표현 방식에 대하여 논한다. 이를 위해 본 논문에서는 기존의 주요 연구에서 2 차원 공간 좌표 (X, Y)로 표현되던 이동 객체의 공간 정보를 계층적 구조를 갖는 행정구역에 기반하여 1 차원의 공간 정보로 압축 표현하는 방식을 제안한다. 이를 이용하여 대용량의 공간정보를 저장하고 있는 이동 객체 데이터베이스의 인덱스 크기의 감소 및 질의 처리 시간의 향상 효과를 얻을 수 있다. 또한, 제안된 방식은 2 차원 공간 좌표를 1 차원의 행정구역 기반의 위치정보로 표현하기 때문에 이로 인한 데이터 손실이 발생할 수 있으나, 일정 공간 내의 객체분포를 필요로 하는 교통 상황 파악, 근사적(approximate) 공간 정보를 필요로 하는 사람${\cdot}$차량 위치 추적 서비스와 같은 위치 기반 서비스를 신속하게 처리하는데 유용하게 사용될 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.11
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• pp.779-789
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• 2014

Cognitive radio (CR) technology based on geo-location database access approach and/or wideband spectrum sensing approach is absolutely vital in order to recognize available frequency bands in white spaces (WSs), and efficiently utilize shared spectrums. This paper presents a new structure for the TVWS database access protocol implementation based on Internet Engineering Task Force (IETF) Protocol to Access WS database (PAWS). A wideband compressive spectrum sensing (WCSS) scheme using a modulated wideband converter is also proposed for the TVWS utilization. The developed database access protocol technology which is adopted in both the TV band device (TVBD) and the TVWS database operates well in the TV frequency bands. The proposed WCSS shows a stable performance in false alarm probability irrespective of noise variance estimation error as well as provides signal detection probabilities greater than 95%. This paper also investigates Federal Communications Commision (FCC) regulatory requirements of TVWS database as well as European Telecommunications Standards Institute (ETSI) policy related to TVWS database. A standardized protocol to achieve interoperability among multiple TVBDs and TVWS databases, which is currently prepared in the IETF, is discussed.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.653-659
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• 2011

In general, electrocardiogram(ECG) signals are sampled with a frequency over 200Hz and stored for a long time. It is required to compress data efficiently for storing and transmitting them. In this paper, a method for compression of ECG data is proposed, using by Non Uniform B-spline approximation, which has been widely used to approximation theory of applied mathematics and geometric modeling. ECG signals are compressed and reconstructed using B-spline basis function which curve has local controllability and control a shape and curve in part. The proposed method selected additional knot with each step for minimizing reconstruction error and reduced time complexity. It is established that the proposed method using B-spline approximation has good compression ratio and reconstruct besides preserving all feature point of ECG signals, through the experimental results from MIT-BIH Arrhythmia database.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.77-83
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• 2015

Frequent pattern mining, which is one of the major areas actively studied in data mining, is a method for extracting useful pattern information hidden from large data sets or databases. Moreover, frequent pattern mining approaches have been actively employed in a variety of application fields because the results obtained from them can allow us to analyze various, important characteristics within databases more easily and automatically. However, traditional frequent pattern mining methods, which simply extract all of the possible frequent patterns such that each of their support values is not smaller than a user-given minimum support threshold, have the following problems. First, traditional approaches have to generate a numerous number of patterns according to the features of a given database and the degree of threshold settings, and the number can also increase in geometrical progression. In addition, such works also cause waste of runtime and memory resources. Furthermore, the pattern results excessively generated from the methods also lead to troubles of pattern analysis for the mining results. In order to solve such issues of previous traditional frequent pattern mining approaches, the concept of representative pattern mining and its various related works have been proposed. In contrast to the traditional ones that find all the possible frequent patterns from databases, representative pattern mining approaches selectively extract a smaller number of patterns that represent general frequent patterns. In this paper, we describe details and characteristics of pattern condensing techniques that consider the maximality or closure property of generated frequent patterns, and conduct comparison and analysis for the techniques. Given a frequent pattern, satisfying the maximality for the pattern signifies that all of the possible super sets of the pattern must have smaller support values than a user-specific minimum support threshold; meanwhile, satisfying the closure property for the pattern means that there is no superset of which the support is equal to that of the pattern with respect to all the possible super sets. By mining maximal frequent patterns or closed frequent ones, we can achieve effective pattern compression and also perform mining operations with much smaller time and space resources. In addition, compressed patterns can be converted into the original frequent pattern forms again if necessary; especially, the closed frequent pattern notation has the ability to convert representative patterns into the original ones again without any information loss. That is, we can obtain a complete set of original frequent patterns from closed frequent ones. Although the maximal frequent pattern notation does not guarantee a complete recovery rate in the process of pattern conversion, it has an advantage that can extract a smaller number of representative patterns more quickly compared to the closed frequent pattern notation. In this paper, we show the performance results and characteristics of the aforementioned techniques in terms of pattern generation, runtime, and memory usage by conducting performance evaluation with respect to various real data sets collected from the real world. For more exact comparison, we also employ the algorithms implementing these techniques on the same platform and Implementation level.