• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.6
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• pp.381-389
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• 2023

One of the crucial components in building information modeling (BIM) is data. To systematically manage these data, various research studies have focused on the creation of object breakdown structures and property sets. Specifically, crucial data for managing programs and payments involves work breakdown structures (WBSs) and cost breakdown structures (CBSs), which are indispensable for mapping BIM objects. Achieving this requires disassembling CBS quantities based on 3D objects and WBS. However, this task is highly tedious owing to the large volume of CBS and divergent coding practices employed by different organizations. Manual processes, such as those based on Excel, become nearly impossible for such extensive tasks. In response to the challenge of computing quantities that are difficult to derive from BIM objects, this study presents methods for disassembling length-based quantities, incorporating significant portions of the bill of quantities (BOQs). The proposed approach recommends suitable CBS by leveraging the accumulated history of WBS-CBS mapping databases. Additionally, it establishes a unified CBS code, facilitating the effective operation of CBS databases.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.2
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• pp.81-97
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• 2022

This paper's purpose is to get hold of the recent research trend by analyzing the variables uesd in startups related papers. The startups related papers in this paper are the papers which include 'startups' in the title of the registered papers from the year 2013 to the year 2020. This study's analysis methods are text-mining of all variables and text-network analysis of affected variables. Visualizing tool for network analysis is Gephi. The result of variables' analysis is as follows. First, independent variables consist mainly of variables about startups' internal factors and outside environment, but due to startups' features like early stage company's features, innovative features, most of variables are about enterprise internal competitiveness, marketing 4P strategy, entrepreneurship, coopreation method, transformational leadership, enterprise features, lean startup strategy, enterprise internal communication, value orientation, task conflict, relationship conflict, knowledge sharing, etc. Second, dependent variables are mainly about outcome, and are classified into financial performance and non-financial performance by overall concept. In other words, startups related papers have higher interest in non-financial performance, like management performance, team performance, SCM performance as well as financial performance like sales quantity owing to startups' immaturity in getting good financial performance. Through this study we can find out as follows. Although there are not many officially registered papers dealing with startups, those papers include various themes about stratups. For example, there are trendy themes like lean startups strategy, crowdfunding, influencer and accelerator, etc.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6D
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• pp.771-778
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• 2011

Preliminary feasibility study on Busan metro line #1 in Yangsan line (Nopo-Bukjeong) depending on active volume of mass transportation between Yangsan city and Busan city was conducted. As the study concluded that it's valid, the necessity to establish the metro railroad network connecting to Busan, Ulsan and Gyeongnam Province is demanded to improve the transportation issues in Ungsang area vulnerable to metro service and to drive the balanced development between metropolitan cities. In addition, the volume of transportation depending on methods in target areas and road traffic assignment are surveyed to put a stress on the necessity to establish the metro railroad network. As the demand of transportation for alternative lines is predicted, the budget and benefits for construction for each alternative line set for the rough economic analysis depending on traffic volume for each method and traffic assignment results. The total project budget necessary for construction of proposal line #1 set as effective one among target three lines in this project is calculated in 794.32 billion won. Construction accounts for the most expensive in expenses for project and contingency allowances, purchases for vehicles and collateral expense are followed in orders. However, compensation for lands is not counted. In particular, according to economic analysis in proposal #1, ratio of benefit/cost (B/C) is 0.584, net present value (NPV) is -217.47 billion won, the internal rate of return (IRR) is analyzed in 0.604 %. At the current stage, it is not economically feasible, but the B/C is 0.737 in long-term upon construction of Yangsan line between Wolpheong and Yongdang which is proposal line #3. Therefore, when Busan metro basic plan is reorganized to aim the benefit of residents in Ungsang area vulnerable to the metro service, we think it must be necessary to establish the metro railroad network connecting to Busan-Yangsan-Ulsan which is proposal line #2 by extending the existing Sinjeong line and including this task line in high-ranked plan related to metro railroad.

• Journal of The Korean Association For Science Education
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• v.38 no.4
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• pp.541-553
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• 2018

The purpose of this study is to explore the relationship between epistemic goals, epistemic considerations and complexity of reasoning of science high school students in an open inquiry and to explore the context on how open inquiry compares with the characteristics of an authentic scientific inquiry. Two teams were selected as focus groups and a case study was conducted. The findings are as follows: First, the contexts, such as 'sharing the value for the phenomenon understanding, reflection on the value of the research, task characteristics that require collaboration and consensus, and sufficient communication opportunities,' promote epistemic goals and considerations. On the other hand, contexts such as 'lack of opportunity for critical review of related literature and environmental constraints' lowered epistemic sides. Second, epistemic goals and considerations influenced the reasoning complexity. The goal of 'scientific sense making' led to reasoning that pose testable hypotheses based on students' own questions. The high justification considerations led to purposely focusing attention to the control designs and developing creative experimental know-how. The high audience considerations led to defending their findings through argumentation and suggesting future research. On the other hand, the goal of 'doing the lesson' and the low justification considerations led to reasoning that did not interpret the meaning of the data and did not control the limit of experiment. The low audience considerations led to reasoning that did not actively defend their findings and not suggest future research. The results of this study suggest that guidance should provide communication and critical review opportunities.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• The Korean Journal of Archival Studies
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• no.12
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• pp.81-135
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• 2005

The release of administrative information has been the challenge of our age following the maturation of democratic ideology in our society. However, differences of opinion and conflict still exist between the government and private sectors regarding the issue, and it seems that the technical and policy-related insufficiencies of information and record management that actually operate the release of information are the main causes. From the perspective of records management, records or information are variable in their nature, value, and influence during their life span. The most controversial issue is the records and information in the current stage of carrying out business activities. This is because the records and information pertaining to finished business are but evidence to ascertain the past, and have only a limited relationship to the ideal of the 'democratic participation' by citizens in activities of the public sector. The current information release policies are helpless against the 'absence of information,' or incomplete records, but such weakness can be supplemented by enforcing record management policies that make obligatory the recording of all details of business activities. In addition, it is understood that the installation of 'document offices("Jaryogwan")' that can manage each organization's information and records will be an important starting point to integrate the release, management, and preservation of information and records. Nevertheless, it seems that the concept of 'release' in information release policies refers not to free use by all citizens but is limited to the 'provision' of records according to public requests, and the concept of 'confidential' refers not to treating documents with total secrecy but varies according to the particulars of each situation, making the actual practice of information release difficult. To solve such problems, it is absolutely necessary to collect the opinions of various constituents associated with the recorded information in question, and to effectively mediate the collective opinions and the information release requests coming from applicants, to carry out the business more practically. Especially crucial is the management of the process by which the nature and influence of recorded information changes, so that information which has to be confidential at first may become available for inquiry and use over time through appropriate procedures. Such processes are also part of the duties that record management, which is in charge of the entire life span of documents, must perform. All created records will be captured within a record management system, and the record creation data thus collected will be used as a guide for inquiry and usage. With 'document offices(Jaryogwan)' and 'archives' controlling the entire life span of records, the release of information will become simpler and more widespread. It is undesirable to try to control only through information release policies those records the nature of which has changed because, unlike the ones still in the early stages of their life span and can directly influence business activities, their work has finished, and they have become historical records or evidences pointing to the truth of past events. Even in the past, when there existed no formal policy regarding the release of administrative information, the access and use of archival records were permitted. A more active and expanded approach must be taken regarding the 'usage' of archival records. If the key factor regarding 'release' lies in the provision of information, the key factor regarding 'usage' lies in the quality and level of the service provided. The full-scale usage of archival records must be preceded by the release of such records, and accordingly, a thorough analysis of the nature, content, and value of the records and their changes must be implemented to guarantee the release of information before their use is requested. That must become a central task of document offices and "Today's information" will soon become "yesterday's records," and the "reality" of today will become "history" of the past. The policies of information release and record management share information records as their common objective. As they have a mutual relationship that is supplementary and leads toward perfection, the two policies must both be differentiated and integrated with each another. It is hoped that the policies and business activities of record management will soon become normalized and reformed for effective and fair release of information.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.1-15
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• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.19-29
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• 2022

The result of a questionnaire survey conducted on fishermen using coastal fish traps shows that fall accidents during trap dropping and pulling constitute the highest proportion of accidents at 42.1 %, whereas slipping accidents on the deck or stricture accidents to the body due to the trap winding device constitute 21.1 % each. In addition, 53.2 % of all surveyed subjects responded that trap pulling is the most dangerous task, followed by fish sorting 33.8 %, and trap dropping 9.1 %. As for the main items requested by fishermen for improving the trap winding device, 36.8 % indicated a method to easily lift the trap from the water to the work deck, and 31.6 % indicated a method to overcome the rope tension and prevent slip when pulling the trap to reduce the accidents. The small trap fishing vessel winding device proposed herein can increase the winding force by strengthening the rope contact area and friction coefficient via an appropriate contact angle between the driving roller of the winding device and the rope. When the contact angles between the driving roller and the rope are 1°, 5°, 9°, 14° and 19°, the rope tension showed a difference according to each contact angle. When the contact angle is 9°, the rope tension is the highest at 392.62 kgf. Based on these experimental results, a prototype winding device is manufactured, and 25 traps are installed on a rope with a total length of 100 m at 4 m intervals in the sea, and then the rope tension is measured during trap pulling. As a result, the rope tension increases rapidly at the initial stage of trap pulling and shows the highest value of 31.89 kgf, which subsequently decreases significantly. Therefore, it is appropriate to design the winding force of a small trap fishing vessel winding device based on the maximum tension value of the rope specified at the beginning of the trap pulling operation.

• Asia pacific journal of information systems
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• v.20 no.4
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• pp.53-79
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• 2010

The study was originated from recognition that project participants' satisfaction should be Improved to raise project performance and to make progress of a successful project since the above dissatisfaction was operated as a danger factor of the project. The study selected one large-scale sample project and attempted measuring characteristics of the project, participants' satisfaction and project performance with the whole project participants. The study analyzed correlations between individual level (team members) and group level (development team), and examined what effect a sub project manager under complicated hierarchical organization of the large-scale project, namely PL (project leader)'s leadership style had on each individual project participant's satisfaction and what effect project uncertainty in organization/technology environment had on project participants' satisfaction and project performance. The study verified that development team (group) had an effect on team member (individual)-level project participants' satisfaction by disclosing that there was a significant dispersion among groups within project participants' satisfaction by each individual. It is analyzed that it is necessary to make improvement through approach by each pertinent team to raise individual-level project participants' satisfaction. The study also verified PL's ideal leadership under strict methodology and hierarchical control of the large-scale project. Based on the verification of the hypotheses, the results of the analysis were produced as follows. First, the development team affects the satisfaction level that an individual has when he/she participates in a project. This suggests that the satisfaction with project participation should be improved at the team level. In addition, the project management style and leadership orientation of the manager of a sub project who is mostly affected by the team proved to have a direct influence on the satisfaction with project participation and project performances. Second, both the performance-oriented leadership and the relationship-oriented leadership of the PL of the development team were verified to have a significant effect on the satisfaction of the team members associated with project participation. In other words, when the team members recognize that the PL of the development team shows both the performance-oriented leadership and the relationship-oriented leadership, their satisfaction with project participation increases accordingly. Third, it was verified that the uncertainty of the organizational environment significantly affects the satisfaction level when the PL of the development team exerts a relationship-oriented and performance-oriented leadership. The higher the uncertainty of the organizational environment is, the more the satisfaction with project participation decreases whereas the relationship-oriented leadership has a more positive effect on the satisfaction than the performance-oriented leadership style. Fourth, when the PL of the development team exerts the relationship-related and performance-related leadership, the uncertainty of the technological environment has a significant influence on the satisfaction level. The higher the uncertainty of the technological environment is, the more the satisfaction with project participation decreases whereas the performance-oriented leadership has a more positive effect on the satisfaction than the relationship-oriented leadership style. The result of the research on the uncertainty of the project environment suggests that when the development team leader exerts a relationship-oriented and performance-oriented leadership style, the uncertainty of the organizational environment has a significant effect on the satisfaction with project participation; the higher the uncertainty of the organizational environment, the more the satisfaction level decreases, and the relationship-oriented leadership style affects the satisfaction level more positively than the performance-oriented leadership style. In addition, when the development team leader displays a relationship-oriented and performance-oriented leadership style, the uncertainty of the technological environment has a significant effect on the satisfaction with project participation; the higher the uncertainty of the technological environment. the more the satisfaction level decreases. The performance-oriented leadership style as well affects the satisfaction level more positively than the relationship-oriented leadership style. Based on the above results, the research provides the following implications when handling multiple concurrent projects. First, the satisfaction with the participation in the multiple concurrent projects needs to be enhanced at the team (group) level. Second. the manager of the project team, particularly the middle managers should have both a performance-oriented and relationship (task and human)-oriented attitude and exert a consolidated leadership in order to improve the satisfaction of team members with project participation and their performances. Third, as the uncertainty factor of the technological and organizational environment among the characteristics factors of the project has room for methodological improvement depending on one's effort even though there are some complications, we need to continuously prevent and control the risks resulting from the uncertainties of the technological and organizational environment of the project in order to enhance the satisfaction of project participation and project performances. Fourth, the performance (task)-oriented leadership is required when there is uncertainty in a technological environment while the relationship (human)-oriented leadership is required when there is uncertainty in an organizational environment. This research has the following limitations. First, this research intended to select one large-sized sample project and measure the project characteristics, the satisfaction of all the participants associated with project participation, and their performances. Therefore, it is inappropriate to generalize and apply the result of this result onto other numerous projects. Second, as this case study entailed a survey to measure the characteristics factors and performance of the project, since the result value was based on the perception of project team members, the data may have insufficient objectivity. Third, though this research targeted on all the project participants, some development teams did not provide sufficient data and questionnaires were collected from some specific development teams among the 23 development teams, causing a significant deviation in the response rate among the development teams. Therefore, we need to continuously conduct the follow-up researches making comparisons among the multiple projects, and centering on the characteristics factors of the project and its satisfaction level.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.19-43
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• 2014

The Pareto principle, also known as the 80-20 rule, states that roughly 80% of the effects come from 20% of the causes for many events including natural phenomena. It has been recognized as a golden rule in business with a wide application of such discovery like 20 percent of customers resulting in 80 percent of total sales. On the other hand, the Long Tail theory, pointing out that "the trivial many" produces more value than "the vital few," has gained popularity in recent times with a tremendous reduction of distribution and inventory costs through the development of ICT(Information and Communication Technology). This study started with a view to illuminating how these two primary business paradigms-Pareto principle and Long Tail theory-relates to the success of virtual knowledge collaboration. The importance of virtual knowledge collaboration is soaring in this era of globalization and virtualization transcending geographical and temporal constraints. Many previous studies on knowledge sharing have focused on the factors to affect knowledge sharing, seeking to boost individual knowledge sharing and resolve the social dilemma caused from the fact that rational individuals are likely to rather consume than contribute knowledge. Knowledge collaboration can be defined as the creation of knowledge by not only sharing knowledge, but also by transforming and integrating such knowledge. In this perspective of knowledge collaboration, the relative distribution of knowledge sharing among participants can count as much as the absolute amounts of individual knowledge sharing. In particular, whether the more contribution of the upper 20 percent of participants in knowledge sharing will enhance the efficiency of overall knowledge collaboration is an issue of interest. This study deals with the effect of this sort of knowledge sharing distribution on the efficiency of knowledge collaboration and is extended to reflect the work characteristics. All analyses were conducted based on actual data instead of self-reported questionnaire surveys. More specifically, we analyzed the collaborative behaviors of editors of 2,978 English Wikipedia featured articles, which are the best quality grade of articles in English Wikipedia. We adopted Pareto ratio, the ratio of the number of knowledge contribution of the upper 20 percent of participants to the total number of knowledge contribution made by the total participants of an article group, to examine the effect of Pareto principle. In addition, Gini coefficient, which represents the inequality of income among a group of people, was applied to reveal the effect of inequality of knowledge contribution. Hypotheses were set up based on the assumption that the higher ratio of knowledge contribution by more highly motivated participants will lead to the higher collaboration efficiency, but if the ratio gets too high, the collaboration efficiency will be exacerbated because overall informational diversity is threatened and knowledge contribution of less motivated participants is intimidated. Cox regression models were formulated for each of the focal variables-Pareto ratio and Gini coefficient-with seven control variables such as the number of editors involved in an article, the average time length between successive edits of an article, the number of sections a featured article has, etc. The dependent variable of the Cox models is the time spent from article initiation to promotion to the featured article level, indicating the efficiency of knowledge collaboration. To examine whether the effects of the focal variables vary depending on the characteristics of a group task, we classified 2,978 featured articles into two categories: Academic and Non-academic. Academic articles refer to at least one paper published at an SCI, SSCI, A&HCI, or SCIE journal. We assumed that academic articles are more complex, entail more information processing and problem solving, and thus require more skill variety and expertise. The analysis results indicate the followings; First, Pareto ratio and inequality of knowledge sharing relates in a curvilinear fashion to the collaboration efficiency in an online community, promoting it to an optimal point and undermining it thereafter. Second, the curvilinear effect of Pareto ratio and inequality of knowledge sharing on the collaboration efficiency is more sensitive with a more academic task in an online community.