• 반도체디스플레이기술학회지
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• 제22권3호
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• pp.142-148
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• 2023

In this paper, we identify performance issues in executing compute kernels from PolyBench, which includes compute kernels that are the core computational units of various data-intensive workloads, such as deep learning and data-intensive applications, on Processing-in-Memory (PIM) devices. Therefore, using our in-house simulator, we measured and compared the various performance metrics of workloads based on traditional out-of-order and in-order processors with Processing-in-Memory-based systems. As a result, the PIM-based system improves performance compared to other computing models due to the short-term data reuse characteristic of computational kernels from PolyBench. However, some kernels perform poorly in PIM-based systems without a multi-layer cache hierarchy due to some kernel's long-term data reuse characteristics. Hence, our evaluation and analysis results suggest that further research should consider dynamic and workload pattern adaptive approaches to overcome performance degradation from computational kernels with long-term data reuse characteristics and hidden data locality.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제11권9호
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• pp.355-362
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• 2022

농업에 정보 통신 기술을 접목한 스마트팜은 단순한 생육 환경 모니터링에서 벗어나 작물 생육을 위한 최적의 환경을 발견하고 자율제어가 가능한 농업의 형태로 나아가고 있다. 이를 위해서는 관련 데이터를 수집하는 것도 중요하지만, 재배 경험과 지식을 가진 농업인 사용자들이 수집된 데이터를 다양한 관점에서 분석하여 작물 생육 환경 제어에 유용한 정보를 도출해야 할 필요가 있다. 본 연구에서는 작물 생육과 관련된 데이터를 가지고 필요한 정보를 얻고자 하는 농업인 사용자가 쉽게 데이터 분석을 할 수 있는 웹 서비스를 개발하였다. 개발한 웹 기반 데이터 분석 서비스는 데이터 분석을 위하여 R 언어를 사용하며 Node.js를 위한 익스프레스 웹 애플리케이션 프레임워크를 기반으로 개발하였다. 데이터 분석 서비스를 운영 중인 생육 환경 모니터링 시스템과 함께 적용해 본 결과 사용자는 웹 상에서 CSV 형식의 파일을 입력하거나 직접 데이터 입력함으로써 서버가 제공하는 데이터 분석을 위한 R 스크립트를 실행하여 데이터 분석을 수행할 수 있었다. 서비스 제공자는 다양한 데이터 분석 서비스를 쉽게 제공할 수 있었고, R 스크립트만 새로 추가하면 애플리케이션에 대한 수정 없이 새로운 데이터 분석 서비스 추가가 용이함을 확인하였다.

• Korean Journal of Mathematics
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• 제29권4호
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• pp.649-664
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• 2021

There have been numerous efforts to provide legal information to the general public easily. Most of the existing legal information services are based on keyword-oriented legal ontology. However, this keyword-oriented ontology construction has a sense of disparity from the relationship between the laws used together in actual cases. To solve this problem, it is necessary to study which laws are actually used together in various judicial precedents. However, this is difficult to implement with the existing methods used in computer science or law. In our study, we analyzed this by using topological data analysis, which has recently attracted attention very promisingly in the field of data analysis. In this paper, we applied the the Mapper algorithm, which is one of the topological data analysis techniques, to visualize the relationships that laws form organically in actual precedents.

• International Journal of Computer Science & Network Security
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• 제22권9호
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• pp.403-413
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• 2022

Classification and analysis are improved factors for the realtime automation system. In the field of agriculture, the cultivation of different paddy crop depends on the atmosphere and the soil nature. We need to analyze the moisture level in the area to predict the type of paddy that can be cultivated. For this process, Ensemble Modulation Pattern system and Block Probability Neural Network based classification models are used to analyze the moisture and temperature of land area. The dataset consists of the collections of moisture and temperature at various data samples for a land. The Ensemble Modulation Pattern based feature analysis method, the extract of the moisture and temperature in various day patterns are analyzed and framed as the pattern for given dataset. Then from that, an improved neural network architecture based on the block probability analysis are used to classify the data pattern to predict the class of paddy crop according to the features of dataset. From that classification result, the measurement of data represents the type of paddy according to the weather condition and other features. This type of classification model assists where to plant the crop and also prevents the damage to crop due to the excess of water or excess of temperature. The result analysis presents the comparison result of proposed work with the other state-of-art methods of data classification.

• 대한가정학회지
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• 제37권4호
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• pp.1-16
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• 1999

The objectives of this study are examine the variables effecting management behavior of home-band worker through empirical study. The data used for statistical analysis is 285 home-based worker. The statistical methods used for data analysis were frequencies, mean, t-test, multiple regression, factor analysis and path analysis. The major findings can be summarized as fellows. Home-based workers' various characteristics were statistically significant variable to management behavior. Home-based work income were higher for older women, no employ experience in out of home, lower age of children, business owner, lower time flexibility. In cause-effect model analysis that affects life satisfaction was related to work management, home management behavior and income. Based on the finds of the study, it was found that home-based work can be good alternative to induce married women to labour market if some problems are covered.

• Journal of Construction Engineering and Project Management
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• 제3권1호
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• pp.14-21
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• 2013

To analyze building energy consumption, the building description for building energy performance analysis (BEPA) is required. The required data input for subject building is a basic step in the BEPA process. Since building information modeling (BIM) is applied in the construction industry, the required data for BEPA can be gathered from a single international standard file format like IFCXML. However, in most BEPA processes, since the required data cannot be fully used from the IFCXML file, a building description for BEPA must be created again. This paper proposes IFCXML-based automatic data input approach for BEA. After the required data for BEPA has been defined, automatic data input for BEPA is developed by a prototype system. To evaluate the proposed system, a common BIM file from the BuildingSMART website is applied as a sample model. This system can increase the efficiency and reliability of the BEPA process, since the data input is automatically and efficiently improved by directly using the IFCXML file..

• 국제학술발표논문집
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• The 5th International Conference on Construction Engineering and Project Management
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• pp.173-180
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• 2013

To analyze building energy consumption, the building description for building energy performance analysis (BEPA) is required. The required data input for subject building is a basic step in the BEPA process. Since building information modeling (BIM) is applied in the construction industry, the required data for BEPA can be gathered from a single international standard file format like IFCXML. However, in most BEPA processes, since the required data cannot be fully used from the IFCXML file, a building description for BEPA must be created again. This paper proposes IFCXML-based automatic data input approach for BEA. After the required data for BEPA has been defined, automatic data input for BEPA is developed by a prototype system. To evaluate the proposed system, a common BIM file from the BuildingSMART website is applied as a sample model. This system can increase the efficiency and reliability of the BEPA process, since the data input is automatically and efficiently improved by directly using the IFCXML file.

• 한국경영과학회지
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• 제39권4호
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• pp.51-69
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• 2014

Times to multiple events (TMEs) are a major data type in large-scale business and medical data. Despite its importance, the analysis of TME data has not been well studied because of the analysis difficulty from censoring of observation. To address this difficulty, we have developed a Bayesian-based multivariate survival analysis method, which can successfully estimate the joint probability density of survival times. In this work, we extended this method for the analysis of precedence, dependency and causality among multiple events. We applied this method to the electronic health records of 2,111 patients in a children's hospital in the US and the proposed analysis successfully shows the relation between times to two types of hospital visits for different medical issues. The overall result implies the usefulness of the multivariate survival analysis method in large-scale big data in a variety of areas including marketing, human resources, and e-commerce. Lastly, we suggest our future research directions based multivariate survival analysis method.

• 한국빅데이터학회지
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• 제5권2호
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• pp.171-186
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• 2020

우리나라의 영세 소상공인과 자영업자의 비중이 주요 선진국에 비해 과도하게 높고 빈번한 창업과 폐업이 반복되어 국가 경제에 막대한 피해를 초래하고 있다. 이러한 문제를 해결하기 위해 소상공인을 위한 다양한 연구가 진행 중이며, 정부는 소상공인을 위해 빅 데이터를 이용한 상권정보 분석 서비스를 제공하고 있다. 상권정보 분석 서비스 중 서울시에서 운영하는 우리마을가게 상권분석서비스는 소상공인 관련 빅 데이터 분석 서비스를 제공하기 위해 지속적인 서비스 개선을 진행하고 있다. 그러나 다양한 기관에서 제공받은 빅 데이터를 통합하여 서비스를 구축하였기 때문에 데이터 신뢰성의 한계, 데이터 분석의 한계, 서비스 구성의 한계가 존재한다. 이러한 한계를 극복하기 위해 본 논문에서는 빅 데이터 기반의 상권 서비스와 연계 분석이 가능한 위치기반 설문조사시스템을 제안한다. 제안된 설문조사시스템은 설문정보와 상권정보를 연계하여 빅 데이터 상권 분석 서비스를 확장할 수 기반을 마련하였다.

• Management Science and Financial Engineering
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• 제12권2호
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• pp.71-85
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• 2006

Collaborative filtering, among other recommender systems, has been known as the most successful recommendation technique. However, it requires the user-item rating data, which may not be easily available. As an alternative, some collaborative filtering algorithms have been developed recently by utilizing the market basket data in the form of the binary user-item matrix. Viewing the recommendation scheme as a two-class classification problem, we proposed a new collaborative filtering scheme using a regularized discriminant analysis applied to the binary user-item data. The proposed discriminant model was built in terms of the major principal components and was used for predicting the probability of purchasing a particular item by an active user. The proposed scheme was illustrated with two modified real data sets and its performance was compared with the existing user-based approach in terms of the recommendation precision.