• Journal of IKEEE
• /
• v.25 no.2
• /
• pp.243-251
• /
• 2021

In this paper, we propose a measurement technique of indoor location based on markerless applicable to AR. The proposed technique has the following originality. The first is to extract feature points and use them to generate local patches to enable faster computation by learning and using only local patches that are more useful than the surroundings without learning the entire image. Second, learning is performed through deep learning using the convolution neural network structure to improve accuracy by reducing the error rate. Third, unlike the existing feature point matching technique, it enables indoor location measurement including left and right movement. Fourth, since the indoor location is newly measured every frame, errors occurring in the front side during movement are prevented from accumulating. Therefore, it has the advantage that the error between the final arrival point and the predicted indoor location does not increase even if the moving distance increases. As a result of the experiment conducted to evaluate the time required and accuracy of the measurement technique of indoor location based on markerless applicable to AR proposed in this paper, the difference between the actual indoor location and the measured indoor location is an average of 12.8cm and a maximum of 21.2cm. As measured, the indoor location measurement accuracy was better than that of the existing IEEE paper. In addition, it was determined that it was possible to measure the user's indoor location in real time by displaying the measured result at 20 frames per second.

• Journal of the Korean Society of Safety
• /
• v.36 no.2
• /
• pp.49-57
• /
• 2021

In the case of military supplies, any potential failure and causes of failures must be considered. This study is aimed at examining the failure modes of a rotorcraft landing system to identify the priority items. Failure mode and effects analysis (FMEA) is applied to the rotorcraft landing system. In general, the FMEA is used to evaluate the reliability in engineering fields. Three elements, specifically, the severity, occurrence, and detectability are used to evaluate the failure modes. The risk priority number (RPN) can be obtained by multiplying the scores or the risk levels pertaining to severity, occurrence, and detectability. In this study, different weights of the three elements are considered for the RPN assessment to implement the FMEA. Furthermore, the FMEA is implemented using a fuzzy rule base, similarity aggregation model (SAM), and grey theory model (GTM) to perform a comparative analysis. The same input data are used for all models to enable a fair comparison. The FMEA is applied to military supplies by considering methodological issues. In general, the fuzzy theory is based on a hypothesis regarding the likelihood of the conversion of the crisp value to the fuzzy input. Fuzzy FMEA is the basic method to obtain the fuzzy RPN. The three elements of the FMEA are used as five linguistic terms. The membership functions as triangular fuzzy sets are the simplest models defined by the three elements. In addition, a fuzzy set is described using a membership function mapping the elements to the intervals 0 and 1. The fuzzy rule base is designed to identify the failure modes according to the expert knowledge. The IF-THEN criterion of the fuzzy rule base is formulated to convert a fuzzy input into a fuzzy output. The total number of rules is 125 in the fuzzy rule base. The SAM expresses the judgment corresponding to the individual experiences of the experts performing FMEA as weights. Implementing the SAM is of significance when operating fuzzy sets regarding the expert opinion and can confirm the concurrence of expert opinion. The GTM can perform defuzzification to obtain a crisp value from a fuzzy membership function and determine the priorities by considering the degree of relation and the form of a matrix and weights for the severity, occurrence, and detectability. The proposed models prioritize the failure modes of the rotorcraft landing system. The conventional FMEA and fuzzy rule base can set the same priorities. SAM and GTM can set different priorities with objectivity through weight setting.

• The Journal of the Korea Contents Association
• /
• v.21 no.6
• /
• pp.639-652
• /
• 2021

In accordance with the rapidly changing social environment, it is becoming more important to cultivate creative and convergent practical talents with flexible thinking skills and problem-solving skills. Therefore, it is necessary for universities to provide educational experiences that enable students to cooperate and converge multidisciplinaryly to carry out on-the-job projects based on what they have learned at school. Therefore, this study designed, developed, and operated with the aim of cultivating creative talents with integrated problem-solving ability through a multidisciplinary capstone design curriculum based on industry-academia cooperation. To this end, the curriculum was developed together by recruiting participating companies and forming a convergence professor team, and it was operated for 15 weeks for students majoring in cosmetics engineering at D University. After the education was over, learning satisfaction and perceived academic achievement were surveyed, and as a result of the analysis, it was found to be above average with 3.77 points and 3.86 points, respectively. And as a result of the in-depth interview on the participation experience, five themes related to the positive experience and three themes related to the negative experience were derived. This study will be able to provide basic data when operating a multidisciplinary convergence capstone design curriculum based on industry-academia cooperation in the future.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.41 no.3
• /
• pp.305-316
• /
• 2021

Construction accidents occur due to a number of reasons-worker carelessness, non-adoption of safety equipment, and failure to comply with safety rules are some examples. Because much construction work is done outdoors, weather conditions can also be a factor in accidents. Past construction accident data are useful for accident prevention, but since construction accident data are often in a text format consisting of natural language, extracting construction hazards from construction accident data can take a lot of time and that entails extra cost. Therefore, in this study, we extracted construction hazards from 2,026 domestic construction accident reports using text mining and performed a seasonal analysis of construction hazards through frequency analysis and centrality analysis. Of the 254 construction hazards defined by Korea's Ministry of Land, Infrastructure, and Transport, we extracted 51 risk factors from the construction accident data. The results showed that a significant hazard was "Formwork" in spring and autumn, "Scaffold" in summer, and "Crane" in winter. The proposed method would enable construction safety managers to prepare better safety measures against outdoor construction accidents according to weather, season, and climate.

• Journal of Internet Computing and Services
• /
• v.22 no.3
• /
• pp.27-35
• /
• 2021

With the development of the Internet, various IT technologies such as IoT, Cloud, etc. have been developed, and various systems have been built in countries and companies. Because these systems generate and share vast amounts of data, they needed a variety of systems that could detect threats to protect the critical data contained in the system, which has been actively studied to date. Typical techniques include anomaly detection and misuse detection, and these techniques detect threats that are known or exhibit behavior different from normal. However, as IT technology advances, so do technologies that threaten systems, and these methods of detection. Advanced Persistent Threat (APT) attacks national or companies systems to steal important information and perform attacks such as system down. These threats apply previously unknown malware and attack technologies. Therefore, in this paper, we propose a hybrid intrusion detection system that combines anomaly detection and misuse detection to detect unknown threats. Two detection techniques have been applied to enable the detection of known and unknown threats, and by applying machine learning, more accurate threat detection is possible. In misuse detection, we applied Classification based on Association Rule(CBA) to generate rules for known threats, and in anomaly detection, we used One-Class SVM(OCSVM) to detect unknown threats. Experiments show that unknown threat detection accuracy is about 94%, and we confirm that unknown threats can be detected.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.2
• /
• pp.602-609
• /
• 2021

Under accrual basic accounting, financial statements may be less reliable compared to cash basis accounting. The purpose of this study is to conduct an empirical analysis to determine the possibility of profit adjustment through the increase and decrease of deferred tax accounts. For our empirical analysis, a dummy variable of '1' was used as a dependent variable when the deferred tax net assets increased from the previous year and '0' when the deferred tax net assets decreased. Meanwhile, the variables of interest were discretionary accruals and ROA variation compared to the previous year. Logistic regression analysis was performed to establish the relevance between variables. Results found larger discretionary accruals related to lower net deferred tax assets compared to the previous year. In addition, there was a correlation between ROA and net deferred tax assets only if the ROA increased and net profit was greater than '0'. Study results will enable deferred tax information to be used in investment decision-making, and supervisory institutions can establish policies to prevent profit adjustments and enhance reporting standards.

• Journal of Convergence for Information Technology
• /
• v.11 no.1
• /
• pp.143-155
• /
• 2021

The purpose of this study is to adopt qualitative research methods for alpine snowboard athlete to analyze their injury factors in depth from a psychological perspective. Therefore, in-depth interviews were conducted on four outstanding Alpine Snowboard athlete, and the results were as follows. Among the factors of the injury of Alpine snowboard athlete, the psychological point of view was derived from five factors: 'Trait Anxiety', 'Personality Characteristic', 'Expectancies of Significant Others, 'Discrepancy between ability and expectation' and 'Trauma Injuries'. The five psychological injury factors have expressed the raw data of the subject in a case-oriented manner, and empirical and field-oriented interview data will enable in-depth analysis of psychological factors related to injury to future Alpine snowboard athlete and coaches. It is expected to be used as a basis for injury prevention and countermeasures. All data can be used as a basis for positive effects on the quality of life of athletes and athletes in winter sports.

• Smart Media Journal
• /
• v.9 no.4
• /
• pp.66-72
• /
• 2020

As the online education market expands, educational contents with various presentation methods are being developed and released. In addition, it is imperative to develop content that reflects the usability and user environment of users who use this educational content. However, for qualitative growth of contents that will support quantitative expansion of markets, existing model analysis methods are urgently needed at a time when development direction of newly developed contents is secured. In this process of content development, a typical model for setting development goals is needed, as the rules of the prototype affect the entire development process and the final development outcome. It can also provide a positive benefit that screens the issue of performance dualization between processes due to the absence of communication between a single entity or between a number of entities. In the case of AR-based educational content which is effective to secure data necessary for development by securing samples of similar categories because there are not enough ready-made samples released. Therefore, a big data statistical analysis service is needed that can easily collect data and make decisions using big data. In this paper, we would like to design analysis services that enable the selection and detection of intuitive multidimensional factors and attributes, and propose big data-based statistical analysis services that can assist cooperative activities within an organization or among many companies.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.3
• /
• pp.181-189
• /
• 2021

This study uses a structural equation model for the turnover intention of female nurses performing shift work at a tertiary hospital. Data collection was conducted from November 11 to December 20, 2015, and 283 samples were included in the final analysis. As a result, 12 of the 19 hypotheses of the final model were supported. It was confirmed that external employment opportunities, nursing professional value, nursing organizational culture, job stress, job satisfaction, organizational commitment, and burn out accounted for 47.8% of the turnover intention. Burn out(+) and organizational commitment(-)had direct effects on turnover intentions, and nursing professional, relationship-oriented nursing organizational culture, and job stress showed indirect effects. Therefore, in order to reduce the turnover intention of female nurses working in shifts at tertiary hospitals, it is necessary to prevent burnout, increase organizational commitment, and job satisfaction. For this purpose, measures to strengthen relation-oriented nursing organizational culture and nursing professional intuition are required. In terms of hospital manpower management, the institutional arrangements of hospitals that enable flexible working hours adjustment, mutually respectful relationship-centered organizational culture, education, and policy support to reinforce nursing professional intuition, and the institutional system of hospitals to work with pride should be implemented.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.3
• /
• pp.597-602
• /
• 2021

Even in the era of the 4th industrial revolution, the prevention of industrial accidents is still an important issue in industrial sites. In solving the problem of industrial safety, a product can be difficult to market if there is a lack of standard or method for a reliable performance evaluation. The purpose of this study was to develop and evaluate a test method for a wearable airbag product for protecting the body from falls that was newly developed to respond to fall accidents in industrial sites. As a research method, reliable evaluation standards were developed and applied through four stages of the evaluation and development process (Step 1: Product review, Step 2: Data research, Step 3: Expert meeting, Step 4: Drawing evaluation standard). In addition, the impact force was evaluated according to the developed evaluation standard. The fall impact force obtained through the evaluation showed a reduction effect of approximately 96% compared to the existing impact force. Therefore, the fall impact force was reduced significantly when the airbag was applied. This will enable new convergence products to be launched on the market and produce an environment where industrial workers can work safely.