• Korean Journal of Construction Engineering and Management
• /
• v.25 no.2
• /
• pp.23-35
• /
• 2024

This study analyzed the correlation between each of the 12 influencing factors in FAR 16.04 and the decision-making process for construction contract types, using data from a total of 2,406 DoD Construction Acquisitions spanning from 2008 to 2022. The study considered 12 independent variables, grouped into 4 Characteristics with 3 factors each. Meanwhile, all other contract types were categorized into two types: Firm-Fixed-Price (FFP) and Cost-Reimbursement Contract (CRC), which served as the dependent variables. The findings revealed that FFP contracts significantly dominated in terms of acquisition volume. In line with prevailing beliefs, logistic data analysis and Analytical Hierarchy Process (AHP) analysis of Relative Weights from Experts' Survey demonstrated that independent variables like Uncertainty of the Scope of Work and Complexity found out to be increasing the likelihood of selecting CRC. The number of contractors in the market does indeed influence the possibilities of contract decision-making between CRC and FFP. Meanwhile, the p-values of the top 3 influencing factors on CRC from the AHP analysis-namely, Appropriateness of CAS, Project Urgency, and Cost Analysis-exceeded 0.05 in the binominal regression results, rendering it inconclusive whether they significantly influenced the construction contract type decision, particularly with respect to payment methods. This outcome partly results from the fact that a majority of respondents possessed specific experiences related to the USFK relocation project. Furthermore, influencing factors in construction projects behave differently than common beliefs suggest. As a result, it is imperative to consider the 12 influencing factors categorized into 4 Characteristics areas before establishing acquisition strategies for targeted construction projects.

• Korean Security Journal
• /
• no.18
• /
• pp.169-190
• /
• 2009

Today, the rapid advance of scientific technologies has brought about fundamental changes to the types and levels of terrorism while the war against the world more than one thousand small and big terrorists and crime organizations has already begun. A method highly likely to be employed by terrorist groups that are using 21st Century state of the art technology is cyber terrorism. In many instances, things that you could only imagine in reality could be made possible in the cyber space. An easy example would be to randomly alter a letter in the blood type of a terrorism subject in the health care data system, which could inflict harm to subjects and impact the overturning of the opponent's system or regime. The CIH Virus Crisis which occurred on April 26, 1999 had significant implications in various aspects. A virus program made of just a few lines by Taiwanese college students without any specific objective ended up spreading widely throughout the Internet, causing damage to 30,000 PCs in Korea and over 2 billion won in monetary damages in repairs and data recovery. Despite of such risks of cyber terrorism, a great number of Korean sites are employing loose security measures. In fact, there are many cases where a company with millions of subscribers has very slackened security systems. A nationwide preparation for cyber terrorism is called for. In this context, this research will analyze the current status of Korea's cyber security systems and its laws from a policy perspective, and move on to propose improvement strategies. This research suggests the following solutions. First, the National Cyber Security Management Act should be passed to have its effectiveness as the national cyber security management regulation. With the Act's establishment, a more efficient and proactive response to cyber security management will be made possible within a nationwide cyber security framework, and define its relationship with other related laws. The newly passed National Cyber Security Management Act will eliminate inefficiencies that are caused by functional redundancies dispersed across individual sectors in current legislation. Second, to ensure efficient nationwide cyber security management, national cyber security standards and models should be proposed; while at the same time a national cyber security management organizational structure should be established to implement national cyber security policies at each government-agencies and social-components. The National Cyber Security Center must serve as the comprehensive collection, analysis and processing point for national cyber crisis related information, oversee each government agency, and build collaborative relations with the private sector. Also, national and comprehensive response system in which both the private and public sectors participate should be set up, for advance detection and prevention of cyber crisis risks and for a consolidated and timely response using national resources in times of crisis.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.221-241
• /
• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.125-148
• /
• 2018

Recently, as the demand for big data analysis increases, cases of analyzing unstructured data and using the results are also increasing. Among the various types of unstructured data, text is used as a means of communicating information in almost all fields. In addition, many analysts are interested in the amount of data is very large and relatively easy to collect compared to other unstructured and structured data. Among the various text analysis applications, document classification which classifies documents into predetermined categories, topic modeling which extracts major topics from a large number of documents, sentimental analysis or opinion mining that identifies emotions or opinions contained in texts, and Text Summarization which summarize the main contents from one document or several documents have been actively studied. Especially, the text summarization technique is actively applied in the business through the news summary service, the privacy policy summary service, ect. In addition, much research has been done in academia in accordance with the extraction approach which provides the main elements of the document selectively and the abstraction approach which extracts the elements of the document and composes new sentences by combining them. However, the technique of evaluating the quality of automatically summarized documents has not made much progress compared to the technique of automatic text summarization. Most of existing studies dealing with the quality evaluation of summarization were carried out manual summarization of document, using them as reference documents, and measuring the similarity between the automatic summary and reference document. Specifically, automatic summarization is performed through various techniques from full text, and comparison with reference document, which is an ideal summary document, is performed for measuring the quality of automatic summarization. Reference documents are provided in two major ways, the most common way is manual summarization, in which a person creates an ideal summary by hand. Since this method requires human intervention in the process of preparing the summary, it takes a lot of time and cost to write the summary, and there is a limitation that the evaluation result may be different depending on the subject of the summarizer. Therefore, in order to overcome these limitations, attempts have been made to measure the quality of summary documents without human intervention. On the other hand, as a representative attempt to overcome these limitations, a method has been recently devised to reduce the size of the full text and to measure the similarity of the reduced full text and the automatic summary. In this method, the more frequent term in the full text appears in the summary, the better the quality of the summary. However, since summarization essentially means minimizing a lot of content while minimizing content omissions, it is unreasonable to say that a "good summary" based on only frequency always means a "good summary" in its essential meaning. In order to overcome the limitations of this previous study of summarization evaluation, this study proposes an automatic quality evaluation for text summarization method based on the essential meaning of summarization. Specifically, the concept of succinctness is defined as an element indicating how few duplicated contents among the sentences of the summary, and completeness is defined as an element that indicating how few of the contents are not included in the summary. In this paper, we propose a method for automatic quality evaluation of text summarization based on the concepts of succinctness and completeness. In order to evaluate the practical applicability of the proposed methodology, 29,671 sentences were extracted from TripAdvisor 's hotel reviews, summarized the reviews by each hotel and presented the results of the experiments conducted on evaluation of the quality of summaries in accordance to the proposed methodology. It also provides a way to integrate the completeness and succinctness in the trade-off relationship into the F-Score, and propose a method to perform the optimal summarization by changing the threshold of the sentence similarity.

• Journal of Radiation Protection and Research
• /
• v.39 no.3
• /
• pp.127-133
• /
• 2014

North Korea's uranium enrichment facility is a matter of international concern. It is of particular alarming to South Korea with regard to the security and safety of the country. This situation requires continuous monitoring of the DPRK and emergency preparedness on the part of the ROK. To assess the detectability of an undeclared uranium enrichment plant in North Korea, uranium concentrations in the air at both a short and a long distance from the enrichment facility were estimated. $UF_6$ source terms were determined by using existing information on North Korean facility and data from the operation experience of enrichment plants from other countries. Using the calculated source terms, two atmospheric dispersion models (Gaussian Plume Model and HYSPLIT models) and meteorological data were used to estimate the uranium particle concentrations from the Yongbyon enrichment facility. A maximum uranium concentration and its location are dependent upon the meteorological conditions and the height of the UF6 release point. This study showed that the maximum uranium concentration around the enrichment facility was about $1.0{\times}10^{-7}g{\cdot}m^{-3}$. The location of the maximum concentration was within about 0.4 km of the facility. It has been assumed that the uranium sample of about a few micrograms (${\mu}g$) could be obtained; and that few micrograms of uranium can be easily measured with current measurement instruments. On the contrary, a uranium concentration at a distance of more than 100 kilometers from the enrichment facility was estimated to be about $1.0{\times}10^{-13}{\sim}1.0{\times}10^{-15}g{\cdot}m^{-3}$, which is less than back-ground level. Therefore, based on the results of our paper, an air sample taken within the vicinity of the Yongbyon enrichment facility could be used to determine as to whether or not North Korea is carrying out an undeclared nuclear program. However, the air samples taken at a longer distance of a few hundred kilometers would prove difficult in detecting a clandestine nuclear activities.

• Journal of The Korean Association For Science Education
• /
• v.34 no.5
• /
• pp.437-447
• /
• 2014

Learning progressions (LP), which describe how students may develop more sophisticated understanding over a defined period of time, can inform the design of instructional materials and assessment by providing a coherent, systematic measure of what can be regarded as "level appropriate." We developed LPs for the nature of matter for grades K-16. In order to empirically test Korean students, we revised one of the constructs and associated assessment items based on Korean National Science Standards. The assessment was administered to 124 Korean secondary students to measure their knowledge and submicroscopic representations, and to assign them to a level of learning progression for the particle nature of matter. We characterized the level of students' understanding and models of the particle nature of matter, and described how students interpret various representations of atoms and molecules to explain scientific phenomena. The results revealed that students have difficulties in understanding the relationship between the macroscopic and molecular levels of phenomena, even in high school science. Their difficulties may be attributed to a limited understanding of scientific modeling, a lack of understanding of the models used to represent the particle nature of matter, or limited understanding of the structure of matter. This work will inform assessment and curriculum materials development related to the fundamental relationship between macroscopic, observed phenomena and the behavior of atoms and molecules, and can be used to create individualized learning environments. In addition, the results contribute to scientific research literature on learning progressions on the nature of matter.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.14 no.2
• /
• pp.138-144
• /
• 2010

Purpose: Despite the rapidly changing healthcare environment, healthcare organizations have recognized the importance of patient safety management. But patient safety management has the problem of the lack of participation of members due to the process of focusing on the follow-up service and punishment. The department of nuclear medicine in Uijeongbu St. Mary's Hospital started this research to reduce the near miss and prevent patient safety accidents by both initiating the participatory near-miss-proof activities as an advance management and constructing a system without disadvantages of reporting. In addition, this research aims to establish a differentiated patient safety management system in the department of nuclear medicine. Materials and Methods: 1. Colleting cases of team members' past and present near miss and accidents(First data collection). 2. Quantifying the cases of near miss and accidents after identifying the degree of importance and urgency through surveys(Second data collection). 3. Quantifying cases and indentifying important points of contact through data analysis. 4. Making and standardizing a manual for important points of contact, and initiating participatory activities to prevent errors. 5. Activating web-based community for establishing the report system of near miss. 6. Estimating the result of before and after activities through surveys and focus group interviews. Results: 1) Quantified safety accidents and near miss in the department of nuclear medicine. About 50 near misses a month and one safety accident a year. 2) Establishing improvement measurements based on quantified data. About 11 participatory activities, the improvement of process, a manual for standardization. 3) Creating a system of safety culture and high participation rate of team members. Constructing a report system, making a check list and a slogan for safety culture, and establishing assessment index. 4) Activating communities for sharing the information of cases of near misses and accidents. 5) As the result of activities, the rate of near miss occurrence declined by 50% and the safety accident did not happen. Conclusion: The best service in the department of nuclear medicine is to provide patients with safety-guaranteed high-quality examination and cure. This research started from the question, 'what is the most faithful-to-the-basics way to provide the best service for patients?' and team members' common answer for this question was building a system with participation of all members. Building a system through the participatory improvement activities for preventing near miss and creating safety culture resulted in the 50% decline of near miss occurrence and no accident. This is a meaningful result from the perspective of advance management for patient safety. Moreover, this research paved the way for creating a culture to report and admit near miss or accidents by establishing a report system with no disadvantage of reporting. The system which sticks to the basics is the best service for patients and will form a patient safety culture system, which will lead to the customer satisfaction. Therefore, all members of the department of nuclear medicine will develop a differentiated patient safety culture with stabilizing the established system.

• Korean Journal of Remote Sensing
• /
• v.29 no.5
• /
• pp.517-525
• /
• 2013

Time-series data of Normal Difference Vegetation Index (NDVI) obtained by the Moderate-resolution Imaging Spectroradiometer(MODIS) satellite imagery gives a waveform that reveals the characteristics of the phenology. The waveform can be decomposed into harmonics of various periods by the Fourier transformation. The resulting $n^{th}$ harmonics represent the amount of NDVI change in a period of a year divided by n. The values of each harmonics or their relative relation have been used to classify the vegetation species and to build a vegetation map. Here, we propose a method to estimate the annual amount of carbon absorbed on the forest from the $1^{st}$ harmonic NDVI value. The $1^{st}$ harmonic value represents the amount of growth of the leaves. By the allometric equation of trees, the growth of leaves can be considered to be proportional to the total amount of carbon absorption. We compared the $1^{st}$ harmonic NDVI values of the 6220 sample points with the reference data of the carbon absorption obtained by the field survey in the forest of South Korea. The $1^{st}$ harmonic values were roughly proportional to the amount of carbon absorption irrespective of the species and ages of the vegetation. The resulting proportionality constant between the carbon absorption and the $1^{st}$ harmonic value was 236 tCO2/5.29ha/year. The total amount of carbon dioxide absorption in the forest of South Korea over the last ten years has been estimated to be about 56 million ton, and this coincides with the previous reports obtained by other methods. Considering that the amount of the carbon absorption becomes a kind of currency like carbon credit, our method is very useful due to its generality.

• Atmosphere
• /
• v.20 no.4
• /
• pp.467-482
• /
• 2010

In this study, characteristics of various stability indexes (SI) and environmental parameters (EP) for the lightning are analysed by using 5 upper air observatories (Osan, Gwangju, Jeju, Pohang, and Baengnyeongdo) for the years 2002-2006 over South Korea. The analysed SI and EP are the lifted index, K-index, Showalter stability index, total precipitable water, mixing ratio, wind shear and temperature of lifting condensation level. The lightning data occurred on the range of -2 hr~+1 hr and within 100 km based on the launch time of rawinsonde and observing location are selected. In general, summer averaged temperature and mixing ratio of lower troposphere for the lightning cases are higher about 1 K and $1{\sim}2gkg^{-1}$ than no lightning cases, respectively. The Box-Whisker plot shows that the range of various SI and EP values for lightning and no lightning cases are well separated but overlapping of SI and EP values between lightning and no lightning are not a little. The optimized threshold values for the detection of lightning are determined objectively based on the highest Heidke skill socre (HSS), which is the most favorable validation parameter for the rare event, such as lightning, by using the simulation of SI and EP threshold values. Although the HSS is not high (0.15~0.30) and the number and values of selected SI and EP are dependent on geographic location, the new threshold values can be used as a supplementary tool for the detection or forecast of lightning over South Korea.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.15 no.4
• /
• pp.109-120
• /
• 2020

This study examines how the government's fairness in entrepreneurship support affects satisfaction and management performance, and examines whether these influences are different for each growth stage of start-up companies. For this study, data were collected for start-up companies that received government support for start-up within the past 5 years. Total 611 copies of the data were used in this study. The collected data were analyzed using SPSS and AMOS. The fairness used in this study was divided into three types, procedural fairness, interactive fairness, and distributed fairness. The effect of the three fairness on the satisfaction of start-up support project was analyzed. In addition, the effect of business support satisfaction on business performance was analyzed, where the business performance was evaluated by the questioner's satisfaction with their business. The start-up phase was divided into the start phase, early growth phase, stagnant phase, and high-level growth phase, and the moderating effect between the fairness and satisfaction of the government-supported projects by start-up phase was analyzed. As a result, it was found that every concept of fairness had a positive (+) effect on the satisfaction of the entrepreneurship support project, and the satisfaction of the entrepreneurship support project had a positive (+) effect on the management performance. The concept of procedural fairness in the start phase, procedural fairness in the early growth phase, interactive fairness, and the concept of all fairness in the stagnant phase influenced the satisfaction of the start-up support project. In this study, the fairness and effect of government-supported projects affecting the management performance of start-ups were identified by growth phase of start-ups. The results of these studies will help build a systematic system for entrepreneurship support and for start-ups, it will also greatly contribute to finding differentiated growth plans by growth stages of start-up companies.