• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권12호
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• pp.4835-4855
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• 2015

TV white space (TVWS) is showing promise to become the first widespread practical application of cognitive technology. In fact, regulators worldwide are beginning to allow access to the TV band for secondary users, on the provision that they access the geolocation database. Device-to-device (D2D) can improve the spectrum efficiency, but large-scale D2D communications that underlie TVWS may generate undesirable interference to TV receivers and cause severe mutual interference. In this paper, we use an established geolocation database to investigate the power allocation problem, in order to maximize the total sum throughput of D2D links in TVWS while guaranteeing the quality-of-service (QoS) requirement for both D2D links and TV receivers. Firstly, we formulate an optimization problem based on the system model, which is nonconvex and intractable. Secondly, we use an effective approach to convert the original problem into a series of convex problems and we solve these problems using interior point methods that have polynomial computational complexity. Additionally, we propose an iterative algorithm based on the barrier method to locate the optimal solution. Simulation results show that the proposed algorithm has strong performance with high approximation accuracy for both small and large dimensional problems, and it is superior to both the active set algorithm and genetic algorithm.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.673-673
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• 2015

Earthwork is an operation that provides space for structures, and it takes up a large portion of the construction costs in a construction project. In large-scale earthwork, numerous types of construction equipment are used in the operation. The types of equipment should be selected based on the field conditions and the construction methods. These construction vehicles are constantly changing positions during the earthwork operation. Therefore, the equipment operators require effective communication to ensure the efficiency of the earthwork operation. All equipment operators should exchange information with the other equipment operators. Information should be exchanged continuously to support decision making and increase productivity during the earthwork operation at the construction site. This paper investigates the attributes required for an information interface between construction vehicles during an earthwork operation. This paper 1) discusses the importance of an information interface for construction vehicles in order to increase productivity during an earthwork operation, 2) analyses the types of attributes that need to be communicated between construction vehicles, and 3) provides a database that has been built for attribute control. The database built for the information interface between construction vehicles will enhance communication between vehicle operators. Table I shows the typical attributes that should be shared between the excavator operator and the dump truck operator. This information needs to be shared among the operators, as it helps them to plan the earthwork operation in a more efficient manner. A database has been developed to store this information in an entity relation diagram. A user-interface display environment is also developed to provide this information to the operators in the construction vehicles. The proposed interface can help exchange information effectively and facilitate a common understanding during the earthwork operation. For example, the vehicle operators will be aware of the planned volume, excavated volume, transportation time, and transportation numbers. As a part of this study, mobile devices, such as mobile phones and google glasses, will be used as hands-on communication tools.

• BMB Reports
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• 제45권1호
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• pp.47-50
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• 2012

The International HapMap Project and the Human Genome Diversity Project (HGDP) provide plentiful resources on human genome information to the public. However, this kind of information is limited because of the small sample size in both databases. A Genome-Wide Association Study has been conducted with 8,842 Korean subjects as a part of the Korea Association Resource (KARE) project. In an effort to build a publicly available browsing system for genome data resulted from large scale KARE GWAS, we developed the KARE browser. This browser provides users with a large amount of single nucleotide polymorphisms (SNPs) information comprising 1.5 million SNPs from population-based cohorts of 8,842 samples. KAREBrowser was based on the generic genome browser (GBrowse), a web-based application tool developed for users to navigate and visualize the genomic features and annotations in an interactive manner. All SNP information and related functions are available at the web site http://ksnp.cdc. go.kr/karebrowser/.

• Bioinformatics and Biosystems
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• 제1권2호
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• pp.89-94
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• 2006

Mass spectrometry (MS) is widely applied for high throughput proteomics analysis. When large-scale proteome analysis experiments are performed, it generates massive amount of data. To search these proteomics data against protein databases, fully automated database search algorithms, such as Mascot and SEQUEST are routinely employed. At present, it is critical to reduce false positives and false negatives during such analysis. In this review we have focused on aspects of automated protein identification using tandem mass spectrometry (MS/MS) spectra and validation of the protein identifications of two most common automated protein identification algorithms Mascot and SEQUEST.

• 에너지공학
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• 제12권4호
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• pp.274-280
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• 2003

본 논문은 전력계통에서 데이터베이스를 이용하여 발전기 기동정지계획 문제를 해결하는 발전비용에 의한 순위법을 제안한다. 발전기 기동정지계획의 정식화는 비선형 프로그래밍으로 표현된다. 하지만 대규모시스템에서 연속변수와 불연속변수를 동시에 최적화하는 것은 매우 어려운 문제이다. 발전비용에 의한 순위법은 발전시간의 발전기 운전비용에 기반한다. 본 논문에서는 제안한 알고리즘의 유효성과 경제적 효율성을 보여준다.

• Asia pacific journal of information systems
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• 제2권1호
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• pp.57-76
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• 1992

Material Requirement Planning(MRP) has been the most widely implemented large scale production management system in the manufacturing industry. Computerization of MRP systems involves, in general, Bill Of Material(BOM) explosion algolithms which usually takes heavy computation time. In order to improve the effectiveness of the MRP systems, we propose to build a logical BOM database in advance, which reflects the Join operations for the BOM explosion. It reduces the response time for the BOM indented explosion. It reduces the MRP processing time. It also increased main memory utilization.

• 대한산업공학회지
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• 제26권2호
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• pp.171-182
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• 2000

For the last five years, data mining has drawn much attention by researchers and practitioners because of its many applicable domains. This article presents an adaptive decision tree algorithm for dynamically reasoning machine failure cause out of real-time, large-scale machine status database. Among many data mining methods, intelligent decision tree building algorithm is especially of interest in the sense that it enables the automatic generation of decision rules from the tree, facilitating the construction of expert system. On the basis of experiment using semiconductor etching machine, it has been verified that our model outperforms previously proposed decision tree models.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 추계학술대회 논문집 전력기술부문
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• pp.161-163
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• 2001

This paper presents a Case-Sort method to solve the unit commitment problem using database in electric power systems. The formulation of the unit commitment may be described as nonlinear mixed integer programming. However, it is hard to optimize a problem with discrete and continuous variables in a large-scale system at the same time. The Case-Sort method is based on the unit [MW] generation cost considered drive hour. Then, this paper shows effectiveness and economical efficiency of the proposed algorithm.

• 반도체디스플레이기술학회지
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• 제19권1호
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• pp.6-10
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• 2020

Unlike modern photography technology, in the early days, efforts to physically compose an image with a concept similar to the current photograph have not been popular or commercially successful. The limitation of the use of images as artistic media or recordings has reached the stage of introducing the technology of image analysis to automate the function that humans recognize and judge through vision. In addition, the accuracy of the image has exceeded the human visual ability, enabling the technology that enables the step of recognizing and informing the fact that the human is not aware of it. Based on such a base, the range that can be applied through the image data in the future era can be said to be unpredictable, and the technology that targets large scale image database instead of an image is also expanding the possibilities as a new application technology. In order to identify a particular image from a massive database, different methodologies have been introduced. In this paper, we discuss image identifier production methods based on multi-resolution pyramid.

• 한국정보통신학회논문지
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• 제20권9호
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• pp.1657-1665
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• 2016

CNN(Convolutional Neural Network)을 사용한 심화 학습이 다양한 분야에서 진행되고 있으며 관련 연구들은 이미지 인식의 많은 분야에서 높은 성능을 보이고 있다. 본 논문에서는 한글 인식을 위해 대규모 한글 데이터베이스를 학습할 수 있는 CNN 구조의 간소화된 GoogLeNet을 사용한다. 본 논문에 사용된 데이터베이스는 대규모 한글 데이터베이스인 PHD08로 총 2,350개의 한글 문자에 대해 각 2,187개의 샘플을 가져 총 5,139,450개의 데이터로 구성되어 있다. 간소화된 GoogLeNet은 학습의 결과로 학습 종료 시점에서 PHD08에 대해 99% 이상의 Top-1 테스트 정확도를 보였으며 실험의 객관성을 높이기 위해 PHD08에 존재하지 않는 한글 폰트로 이루어진 한글 데이터를 제작하여 상용 OCR 프로그램들과 분류 성능을 비교하였다. 상용 OCR 프로그램들은 66.95%에서 83.17%의 분류 성공률을 보인 반면, 제안하는 간소화된 GoogLeNet은 평균 89.14%의 분류 성공률을 보여 상용 OCR 프로그램들보다 높은 분류 성공률을 보였다.