• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.25-40
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• 2019

Many companies are executing big data analysis and utilization projects to legitimize the development of new business areas or conversion of management or technical strategies. In Korea and abroad, however, such projects are failing because they are not completed within specified deadlines, which is not unrelated to the current situation in which the knowledge base for big data project risk management from an engineering perspective is grossly lacking. As such, the current study analyzes the risk factors of big data implementation and utilization projects, in addition to finding risk factors that are highly important. To achieve this end, the study extracts project risk factors via literature review, after which they are grouped using affinity methodology and sifted through expert surveys. The deduced risk factors are structuralize using factor analysis to develop a table that categorizes various types of big data project risk factors. The current study is significant that in it provides a basis for developing basic control indicators related to risk identification, risk assessment, and risk analysis. The findings from the study contribute greatly to the success of big data projects, by providing theoretical basis regarding efficient big data project risk management.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.178-185
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• 2018

A self-report evaluation is used to prevent driving accidents by elderly drivers. The majority of normal older adults may have mild cognitive impairment with reduced cognitive function. These depressed cognitive functions may be variables that affect the performance of elderly drivers. This study confirmed the cognitive functions that affect the self-reported evaluation for elderly drivers with mild cognitive impairment. Based on the results of the Korean Version of the Montreal Cognitive Assessment, 103 elderly drivers were classified into mild cognitive impairment and normal groups of elderly drivers. The Korean-Drivers 65 plus scores used in the self-reported evaluation of the two groups were compared, and the cognitive functions affecting the evaluation were analyzed. Results found the mild cognitive impairment group showed a significantly lower evaluation performance compared to the normal group, and the self-reported evaluation results of the elderly driver with mild cognitive impairment showed a significant correlation between visuoconstructional skills and delayed recall. As a result of regression analysis, the visuoconstructional skill was identified as the cognitive function with the strongest influence on the self-reported evaluation performance. Delayed recall was also found to have a partial effect but not at the level of altering the self-reported evaluation results of the elderly driver with mild cognitive impairment.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.745-760
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• 2021

Prediction of a stock price has been a subject of interest for a long time in financial markets, and thus, many studies have been conducted in various directions. As the efficient market hypothesis introduced in the 1970s acquired supports, it came to be the majority opinion that it was impossible to predict stock prices. However, recent advances in predictive models have led to new attempts to predict the future prices. Here, we summarize past studies on the price prediction by evaluation measures, and predict the direction of stock prices of Samsung Electronics, LG Chem, and NAVER by applying various machine learning models. In addition to widely used technical indicator variables, accounting indicators such as Price Earning Ratio and Price Book-value Ratio and outputs of the hidden Markov Model are used as predictors. From the results of our analysis, we conclude that no models show significantly better accuracy and it is not possible to predict the direction of stock prices with models used. Considering that the models with extra predictors show relatively high test accuracy, we may expect the possibility of a meaningful improvement in prediction accuracy if proper variables that reflect the opinions and sentiments of investors would be utilized.

• Science of Emotion and Sensibility
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• v.23 no.4
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• pp.61-72
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• 2020

Social problems, such as economic instability, aging population, heightened competition, and changes in personal values, might become more serious in the near future. Affective computing has received much attention in the scholarly community as a possible solution to potential social problems. Accordingly, we examined domestic and global knowledge structure, major keywords, current research status, international research collaboration, and network for each major keyword, focusing on keywords related to affective computing. We searched for articles on a specialized academic database (Scopus) using major keywords and carried out bibliometric and network analyses. We found that China and the United States (U.S.) have been active in producing knowledge on affective computing, whereas South Korea lags well behind at around 10%. Major keywords surrounding affective computing include computing, processing, affective analysis, research, user modeling categorizing recognitions, and psychological analysis. In terms of international research collaboration structure, China and the U.S. form the largest cluster, whereas other countries like the United Kingdom, Germany, Switzerland, Spain, and Canada have been strong collaborators as well. Contrastingly, South Korea's research has not been diverse and has not been very successful in producing research outcomes. For the advancement of affective computing research in South Korea, the present study suggests strengthening international collaboration with major countries, including the U.S. and China and diversifying its research partners.

• Journal of Korea Foundry Society
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• v.41 no.1
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• pp.26-38
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• 2021

The status of Ppuri industry, including foundry industry was analyzed through statistical surveys over the past 10 years from 2009 to 2018, and summarized for each six Ppuri industries' points of view. Various statistics of Ppuri industry defined by the KSIC (Korean Standard Industry Classification) was obtained, and the status of Ppuri industry was identified through a sample survey of 5,000 companies from more than 30,000 target business companies of Ppuri industry. Throughout the analyzing process, we presented a variety of indicators, such as the number of the Ppuri companies and its ratio, regional distribution through Korean provinces, number of workers, characteristics by age group, sales, profit rates, etc. By devising a comparative method to measure the relative strength of Ppuri industry in Korea, Germany, and Japan, we have presented the competitiveness index change over the 10 years of time. The competitiveness index can be effectively and meaningfully used during various activities of the development of Ppuri industry in the forth coming future. With the current obtained data, we figured out the status of each 6 Ppuri industries, regional distribution, status of workers, sales and profit rates. We also suggested various proposals for strategy and policy making for each sector with urging voluntary response from Ppuri industry.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.9
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• pp.709-719
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• 2021

Recent progress in analysis and flight simulation methods enables wider use of a virtual certification and reduces number of certification flight tests. Aerodynamic database (AeroDB) is one of the most important components for the flight simulation. It is composed of aerodynamic coefficients at a range of flight conditions and control deflections. This paper proposes and efficient method for construction of AeroDB that combines Gaussian Process based Variable Fidelity Modeling with adaptive sampling algorithm. A case study of virtual certification of a F-16 fighter is presented. Four AeroDB were constructed using different number and distribution of high-fidelity data points. The constructed database is then used to simulate gliding, short pitch, and roll response. Compliance with certification regulations is then checked. The case study demonstrates that the proposed method can significantly reduce number of high-fidelity data points while maintaining high accuracy of the simulation.

• Journal of Korean Society of Forest Science
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• v.110 no.2
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• pp.210-216
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• 2021

Musculoskeletal disorders affect workers' safety in most industries, and forest operations are classified as a musculoskeletal burden according to the Occupational Safety and Health Act in South Korea. In particular, felling and delimbing operations are mainly conducted by manpower, and then, it is necessary to evaluate ergonomic risk assessment for safety of felling and delimbing workers. Three ergonomic risk assessment methods, such as Ovako Working posture Analysis System (OWAS), Rapid Upper Limb Assessment (RULA), and Rapid Entire Body Assessment (REBA), are available for assessing exposure to risk factors associated with timber harvesting operations. Here, three ergonomic risk assessment methods were applied to examine ergonomic risk assessments in chainsaw felling and delimbing operations. Additionally, exposure to risk factors in each method was analyzed to propose an optimal working posture in felling and delimbing operations. The risk levels of these operations were evaluated to be highest in the RULA method, followed by the OWAS and REBA methods, and most of the exposed working postures were examined with a low-risk level of two and three without requiring any immediate working posture changes. However, two significant working postures, including the bending posture of the waist and leg in felling operation and standing posture on the fallen trees in delimbing operation, were assessed as the high-risk level and needed immediate working posture changes. Low-risk work levels were examined in the squatting posture for felling operation and the straightened posture of the waist and leg for delimbing operation. Moreover, the slope in felling operation and the tree height in delimbing operation significantly affected risk level assessment of working posture. Therefore, our study supports that felling and delimbing workers must operate with low-risk working postures for safety.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.251-256
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• 2021

This study analyzed the most frequently used navigation cases in a desktop environment. As a result of the research, GNB induces users' search as the top element of the search structure and can place color, text, icon, and image elements. LNB could be classified in the form of a dropdown, flyout, dropline and mega menu. In this study, the navigation structure of Interpark and Interpark among open markets used by users was analyzed. G-Market's GNB has a two-tier structure with color, text, image, and icon elements, and Interpark has a three-tiered horizontal label. Interpark's GNB drew attention by placing a badge on the seasonal label, which is a temporary content section, unlike G-market. It can be seen that the LNBs of both shopping malls have flyout menus that protrude when you mouse over the category menu arranged in a vertical text form under the logo placed on the left. The flyout menu has a complex structure consisting of the layout of the mega menu. This study is meaningful in revealing user experience elements by analyzing the GNB and LNB of shopping malls these days where internet shopping is increasing.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.707-725
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• 2021

Energy management systems (EnMS) contribute to sustainable energy saving and greenhouse gas reduction by emphasizing the role of energy management in production-oriented economies. Although understanding the methods used to measure energy performance is a key factor in constructing successful EnMS, few attempts have been made to examine these methods, their applicability, and their utility in practice. To fill this research gap, this study aimed to deepen the understanding of energy performance measures by focusing on four energy performance indicators (EnPIs) proposed by ISO 50006, namely the measured energy value, ratio between measured values, linear regression model, and nonlinear regression model. This paper presents policy and managerial implications to facilitate the effective use of these measures. An analytic hierarchy process (AHP) analysis was conducted with 41 experts to analyze the preference for EnPIs and their key selection criteria by the industry sector, and organization and user type. The findings suggest that the most preferred EnPI is the ratio between the measured values followed by the measured energy value. The ease of use was considered to be most important while choosing EnPIs.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.489-495
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• 2020

The amount of data is increasing through various IT devices in a hyper-connected society where the 4th revolution is progressing, and new value can be created by analyzing that data. This paper was collected total 1,526 articles from 2017 to 2019 in central magazines, economic magazines, regional associations, and major broadcasting companies with the keyword "(East Coast Tourism or East Coast Travel) and Gangwon-do" through Bigkinds. It was performed the topic modeling using LDA algorithm implemented in the R language to analyze the collected 1,526 articles. It was extracted keywords for each year from 2017 to 2019, and classified and compared keywords with high frequency for each year. It was setted the optimal number of topics to 8 using Log Likelihood and Perplexity, and then inferred 8 topics using the Gibbs Sampling method. The inferred topics were Gangneung and Beach, Goseong and Mt.Geumgang, KTX and Donghae-Bukbu line, weekend sea tour, Sokcho and Unification Observatory, Yangyang and Surfing, experience tour, and transportation network infra. The changes of articles on East coast tourism was was analyzed using the proportion of the inferred eight topics. As the result, the proportion of Unification Observatory and Mt. Geumgang showed no significant change, the proportion of KTX and experience tour increased, and the proportion of other topics decreased in 2018 compared to 2017. In 2019, the proportion of KTX and experience tour decreased, but the proportion of other topics showed no significant change.