• Journal of the Korean Institute of Gas
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• v.22 no.2
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• pp.1-20
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• 2018

Despite many measures, still from time to time catastrophic events occur, even after reviewing potential scenarios with HAZID tools. Therefore, it is evident that in order to prevent such events, answering the question: "What can go wrong?" requires more enhanced HAZID tools. Recently, new system based approaches have been proposed, such as STPA (system-theoretic process analysis) and Blended Hazid, but for the time being for several reasons their availability for general use is very limited. However, by making use of available advanced software and technology, traditional HAZID tools can still be improved in degree of completeness of identifying possible hazards and in work time efficiency. The new HAZID methodology proposed here, the Data-based semi-Automatic HAZard IDentification (DAHAZID), seeks to identify possible scenarios with a semi-automated system approach. Based on the two traditional HAZID tools, Hazard Operability (HAZOP) Study and Failure Modes, Effects, and Criticality Analysis (FMECA), the new method will minimize the limitations of each method. This will occur by means of a thorough systematic preparation before the tools are applied. Rather than depending on reading drawings to obtain connectivity information of process system equipment elements, this research is generating and presenting in prepopulated work sheets linked components together with all required information and space to note HAZID results. Next, this method can be integrated with proper guidelines regarding process safer design and hazard analysis. To examine its usefulness, the method will be applied to a case study.

• Journal of KIISE
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• v.43 no.11
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• pp.1210-1215
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• 2016

Readership of online newspapers has grown with the proliferation of smart devices. However, fierce competition between Internet newspaper companies has resulted in a large increase in the number of hoax articles. Hoax articles are those where the title does not convey the content of the main story, and this gives readers the wrong information about the contents. We note that the hoax articles have certain characteristics, such as unnecessary celebrity quotations, mismatch in the title and content, or incomplete sentences. Based on these, we extract and validate features to identify hoax articles. We build a large-scale training dataset by analyzing text keywords in replies to articles and thus extracted five effective features. We evaluate the performance of the support vector machine classifier on the extracted features, and a 92% accuracy is observed in our validation set. In addition, we also present a selective bigram model to measure the consistency between the title and content, which can be effectively used to analyze short texts in general.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.38-39
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• 2010

수도권 대중교통 이용자는 2004년 서울시의 대중교통 체계 개편에 따라 교통 카드를 사용하여 버스와 지하철을 이용하게 되었다. 교통 카드를 사용하는 각 승객의 승차와 하차에 관한 데이터가 하나의 트랜잭션으로 구성되고, 하루 천만 건 이상의 트랜잭션들로 구성된 대용량 교통카드 트랜잭션 데이터베이스가 만들어지고 있다. 대중교통을 이용하는 승객들의 승차와 하차에 관한 여러 정보를 담고 있는 교통카드 트랜잭션 데이터베이스에서 유용한 패턴이나 정보를 탐사해내는 연구가 계속 진행되고 있다. 이런 연구 결과는 수도권 대중교통 정책을 입안하는데 중요한 기초 자료가 되고 수도권 승객들에게 대중교통을 보다 잘 이용할 수 있는 정보로 제공된다. 교통카드 이용률은 2006년 79.5%, 2007년 80.3%, 2008년 81.6%로 점차적으로 증가하고 있다. 대용량의 교통카드 트랜잭션 데이터베이스에 대한 연구를 살펴보면 하루 동안의 교통카드 트랜잭션 데이터베이스에서 순차 패턴을 탐사하는 알고리즘을 연구하였고[1], 승객들의 통행 패턴에 대한 분석연구를 확장하여 일 년에 하루씩 2004년에서 2006년까지 3일간의 교통카드 트랜잭션 데이터베이스로부터 승객 시퀀스의 평균 정류장 개수와 환승 횟수 등을 연도별로 비교하였다[2]. 수도권 지하철 시스템의 특성에 관한 연구로는 네트워크 구조 분석이 있었고[3], 승객의 기종점 통행 행렬(Origin-Destination trip matrix)에 의한 승객 흐름의 분포가 멱함수 법칙(power law)임을 보여주는 연구가 있었고[4], 지하철 교통망에서 모든 링크상의 승객들의 흐름을 찾아내는 연구가 있었다[5]. 본 논문에서는 교통카드 트랜잭션 데이터베이스에서 지하철 승객들의 통근 패턴을 탐사해내는 방법을 연구하였다. 수도권 지하철 네트워크에 대한 정보를 입력하고 하루치의 교통카드 트랜잭션 데이터베이스에 연구된 방법을 적용하여 8가지 통근 패턴들을 탐사해내고 분석하였다. 탐사된 패턴들 중에서 많은 승객들이 지지하는 출퇴근 패턴에 대해서는 시간대별로 승객수를 그래프로 보여주었다.

• International journal of advanced smart convergence
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• v.5 no.2
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• pp.53-58
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• 2016

With the growing use of big data and data mining, it serves to understand how such techniques can be used to understand various relationships in the healthcare field. This study uses hierarchical methods of data analysis to explore similarities in hospitalization across several New York state counties. The study utilized methods of measuring crowding distance of data for age-specific hospitalization period. Crowding distance is defined as the longest distance, or least similarity, between urban cities. It is expected that the city of Clinton have the greatest distance, while Albany the other cities are closer because they are connected by the shortest distance to each step. Similarities were stronger across hospital stays categorized by age. Hierarchical clustering can be applied to predict the similarity of data across the 10 cities of hospitalization with the measurement of crowding distance. In order to enhance the performance of hierarchical clustering, comparison can be made across congestion distance when crowding distance is applied first through the application of converting text to an attribute vector. Measurements of similarity between two objects are dependent on the measurement method used in clustering but is distinguished from the similarity of the distance; where the smaller the distance value the more similar two things are to one other. By applying this specific technique, it is found that the distance between crowding is reduced consistently in relationship to similarity between the data increases to enhance the performance of the experiments through the application of special techniques. Furthermore, through the similarity by city hospitalization period, when the construction of hospital wards in cities, by referring to results of experiments, or predict possible will land to the extent of the size of the hospital facilities hospital stay is expected to be useful in efficiently managing the patient in a similar area.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.5
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• pp.207-214
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• 2020

Nowadays, the use of smart phones and various electronic devices is increasing, the Internet and SNS are activated, and we live in the flood of information. The amount of information has grown exponentially, making it difficult to look at a lot of information, and more and more people want to see only key keywords in a document, and the importance of research to extract topics that are the core of information is increasing. In addition, it is also an important issue to extract the topic and compare it with the past to infer the current trend. Topic modeling techniques can be used to extract topics from a large volume of documents, and these extracted topics can be used in various fields such as trend prediction and data analysis. In this paper, we inquire the topic of the three-year papers of 2016, 2017, and 2018 in the field of computing using the LDA algorithm, one of Probabilistic Topic Model Techniques, in order to analyze the rapidly changing trends and keep pace with the times. Then we analyze trends and flows of research.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.1-18
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• 2017

Recently, identification of the extremely stressed condition of children is an essential skill for real-time recognition of a dangerous situation because incidents of children have been dramatically increased. In this paper, therefore, we present a model based on machine learning techniques for stress status identification of a child by using bio-signals such as voice and heart rate that are major factors for presenting a child's emotion. In addition, a smart band for collecting such bio-signals and a mobile application for monitoring child's stress status are also suggested. Specifically, the proposed method utilizes stress patterns of children that are obtained in advance for the purpose of training stress status identification model. Then, the model is used to predict the current stress status for a child and is designed based on conventional machine learning algorithms. The experiment results conducted by using a real-world dataset showed that the possibility of automated detection of a child's stress status with a satisfactory level of accuracy. Furthermore, the research results are expected to be used for preventing child's dangerous situations.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.60-69
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• 2012

Public Transport Information Service which use smartphone Apps has received attention as the way of solution that reduced transport problem. Smartphone can offer real-time information because of a LBS(Location Based Service) system. This study try to find out which factor affect mode choice ratio of public transport, especially smartphone Apps. The result shows that rising oil price, traffic congestion, public information service with smartphone apps, BIS(Bus Information System) factors get 0.39, 0.27, 0.18, 0.16 scores with paired comparison. Younger and student respondents prefer smart phone public information service. Decision Tree shows that the most important decision factor is smartphone information service factor.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.18-29
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• 2019

In the field of Human-Computer Interaction design, persuasive design has gradually been applied to the system development and design process, especially for mobile application design. However, most mobile applications have hitherto a very short using lifecycle. Especially, design features with long-term persuasive effectiveness remain to be further researched and developed. In this study, we focused on investigating and identifying the durative persuasive design characteristics through a data mining process and evaluating the durative effectiveness through a long-term observation process. Total five hundred healthcare-related mobile applications were selected from Apple iTunes Store and a mixed method was conducted to extract the most common persuasive design characteristics. Based on the results of extraction, a representative healthcare-related mobile application was selected as experimental subject. Total one hundred and twenty participants were observed during a six-months experiment and the monitoring data of app usage of all participants was collected once a week. According to the evaluation model for behavior change identification process, participants with habit formation features were proved to have a significant long-term perception level for ten persuasive design characteristics. Further interview research was performed to investigate the participant's long-term perceptions on those characteristics for the purpose of identifying the durative persuasions. The results indicated that a long-term durative effectiveness can be observed and healthcare-related apps designed with those characteristics could have durative effectiveness. This study may contribute to the improvement of future mobile application designs in user experience and durative persuasion, as well as bringing future benefits for both mobile application developers and users.

• Smart Structures and Systems
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• v.22 no.6
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• pp.675-687
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• 2018

In the previous studies on the porous rock strength the effect of pore number and its diameter is not explicitly defined. In this paper crack initiation, propagation and coalescence in Brazilian model disc containing a single cylindrical hole and or multiple holes have been studied numerically using PFC3D. In model with internal hole, the ratio of hole diameter to model diameter was varied between 0.03, 0.17, 0.25, 0.33, and 0.42. In model with multiple hole number of holes was different in various model, i.e., one hole, two holes, three holes, four holes, five holes, six holes, seven holes, eight holes and nine holes. Diameter of these holes was 5 mm, 10 mm and 12 mm. The pre-holed Brazilian discs are numerically tested under Brazilian test. The breakage load in the ring type disc specimens containing an internal hole with varying diameters is measured. The mechanism of cracks propagation in the wall of the ring type specimens is also studied. In the case of multi-hole Brazilian disc, the cracks propagation and b cracks coalescence are also investigated. The results shows that breaking of the pre-holed disc specimens is due to the propagation of radially induced tensile cracks initiated from the surface of the central hole and propagating toward the direction of diametrical loading. In the case of disc specimens with multiple holes, the cracks propagation and cracks coalescence may occur simultaneously in the breaking process of model under diametrical compressive loading. Finally the results shows that the failure stress and crack initiation stress decreases by increasing the hole diameter. Also, the failure stress decreases by increasing the number of hole which mobilized in failure. The results of these simulations were comprised with other experimental and numerical test results. It has been shown that the numerical and experimental results are in good agreement with each other.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.161-166
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• 2021

The macroeconomic concept represents the movement of a country's economy, and it affects the overall economic activities of business, government, and households. In the macroeconomy, by looking at changes in national income, inflation, unemployment, currency, interest rates, and raw materials, it is possible to understand the effects of economic actors' actions and interactions on the prices of products and services. The US Federal Reserve System (FED) is leading the world economy by offering various stimulus measures to overcome the corona economic recession. Although the stock price continued to decline on March 20, 2020 due to the current economic recession caused by the corona, the US S&P 500 index began rebounding after March 23 and to 3,694.62 as of December 15 due to quantitative easing, a powerful stimulus for the FED. Therefore, the FED's economic stimulus measures based on macroeconomic indicators are more influencing, rather than judging the stock price forecast from the corporate financial statements. Therefore, this study was conducted to reduce losses in stock investment and establish sound investment by analyzing the FED's economic stimulus measures and its effect on stock prices.