• Journal of Industrial Convergence
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• v.22 no.1
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• pp.105-115
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• 2024

This study aimed to analyze the impact of mental strength on the competitive performance of student Taekwondo sparring athletes. A total of 343 middle school, high school, and university students registered as Taekwondo sparring athletes with the Korea Taekwondo Association were conveniently sampled. The Mental Toughness Test developed by Loehr was utilized after expert consultations. Data analysis involved t-tests and one-way ANOVA to assess the levels of mental strength sub-factors based on general characteristics, followed by post hoc tests using the Schéffe method for intergroup comparisons. Correlation analysis and multiple regression were conducted to examine the relationship between sub-factors of mental strength and competitive ability. The results indicated significant differences in mental strength sub-factors-confidence, level of awakening regulation, visualization and mental imagery regulation, motivation level, positive energy, and attitude control-based on gender and age among Taekwondo sparring student athletes. In terms of perceived competitive ability, significant differences were found based on age and sports experience. Consequently, beyond psychological training, the study revealed that age and diverse experiences positively influence specific aspects of mental strength among Taekwondo sparring student athletes. Therefore, coaching and training for these athletes, particularly during middle and high school years, should incorporate psychological aspects alongside diverse competition experiences and training to help overcome performance evaluation anxieties during matches.

• Clinical Endoscopy
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• v.57 no.2
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• pp.217-225
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• 2024

Background/Aims: This study aims to compare polyp detection performance of "Deep-GI," a newly developed artificial intelligence (AI) model, to a previously validated AI model computer-aided polyp detection (CADe) using various false positive (FP) thresholds and determining the best threshold for each model. Methods: Colonoscopy videos were collected prospectively and reviewed by three expert endoscopists (gold standard), trainees, CADe (CAD EYE; Fujifilm Corp.), and Deep-GI. Polyp detection sensitivity (PDS), polyp miss rates (PMR), and false-positive alarm rates (FPR) were compared among the three groups using different FP thresholds for the duration of bounding boxes appearing on the screen. Results: In total, 170 colonoscopy videos were used in this study. Deep-GI showed the highest PDS (99.4% vs. 85.4% vs. 66.7%, p<0.01) and the lowest PMR (0.6% vs. 14.6% vs. 33.3%, p<0.01) when compared to CADe and trainees, respectively. Compared to CADe, Deep-GI demonstrated lower FPR at FP thresholds of ≥0.5 (12.1 vs. 22.4) and ≥1 second (4.4 vs. 6.8) (both p<0.05). However, when the threshold was raised to ≥1.5 seconds, the FPR became comparable (2 vs. 2.4, p=0.3), while the PMR increased from 2% to 10%. Conclusions: Compared to CADe, Deep-GI demonstrated a higher PDS with significantly lower FPR at ≥0.5- and ≥1-second thresholds. At the ≥1.5-second threshold, both systems showed comparable FPR with increased PMR.

• Korean Chemical Engineering Research
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• v.62 no.3
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• pp.214-224
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• 2024

Valves play an essential role in a chemical plant such as regulating fluid flow and pressure. Therefore, optimal selection of the valve size and type is essential task. Valve size and type have been selected based on theoretical formulas about calculating valve sizing coefficient (Cv). However, this approach has limitations such as requiring expert knowledge and consuming substantial time and costs. Herein, this study developed a model for predicting valve sizes and types using machine learning. We developed models using four algorithms: ANN, Random Forest, XGBoost, and Catboost and model performances were evaluated using NRMSE & R² score for size prediction and F1 score for type prediction. Additionally, a case study was conducted to explore the impact of phases on valve selection, using four datasets: total fluids, liquids, gases, and steam. As a result of the study, for valve size prediction, total fluid, liquid, and gas dataset demonstrated the best performance with Catboost (Based on R², total: 0.99216, liquid: 0.98602, gas: 0.99300. Based on NRMSE, total: 0.04072, liquid: 0.04886, gas: 0.03619) and steam dataset showed the best performance with RandomForest (R²: 0.99028, NRMSE: 0.03493). For valve type prediction, Catboost outperformed all datasets with the highest F1 scores (total: 0.95766, liquids: 0.96264, gases: 0.95770, steam: 1.0000). In Engineering Procurement Construction industry, the proposed fluid-specific machine learning-based model is expected to guide the selection of suitable valves based on given process conditions and facilitate faster decision-making.

• Journal of Service Research and Studies
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• v.9 no.4
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• pp.41-62
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• 2019

In this intangible good-oriented, modern service economy era, we have to first understand the characteristics of the healthcare service in order to enhance the competitiveness of the healthcare industry and achieve continuous growth. In addition, service nature and characteristics should be reinforced so that connections can be made to the organizational job performance. To achieve the aforementioned results, this study analyzes the direct effects service nature and characteristics have on job performance in the healthcare industry and investigates the indirect effects with individual personality as the moderating effect. While conducting this study, a total of 340 healthcare workers were surveyed. Survey data from a total of 315 workers were used for analysis during empirical investigation of the research hypothesis. According to the analysis, it was proven that interactivity and horizontality among service nature and characteristics have a positive (+) effect on job effectiveness. This means that customer needs can be identified at customer touchpoints to quickly and accurately provide customers with the products and services they want, while horizontality among service nature and characteristics have a positive (+) effect on job effectiveness. This means that customer needs can be identified at customer touchpoints to quickly and accurately provide customers with the products and services they want, while horizontal communication enhance from department to department and from colleague to colleague within the organization can be linked to job performance. Also, with regards to the relationship shared between the customer or the patient, the job performance of healthcare workers may also improve if they provide customers with their desired service as an expert at the same level. In a rapidly changing healthcare environment, if the healthcare service nature and characteristics are put into practical use, it will be possible to propel the growth of hospitals and sustain it while investigating the moderating effects of individual personality, a partial moderating effect was observed for self-esteem and growth desire. As the study on service nature and characteristics came about only just recently, there is a needs for futher research. The study focuses on the healthcare service industry and hopefully, it will serve as a base study that can be applied to different service industries as well.

• Journal of the Korean Academy of Esthetic Dentistry
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• v.28 no.2
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• pp.116-126
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• 2019

Objectives: Currently, oral health of the disabled is taken care of by the social workers, not by dental hygienists, who are the oral health professional in this area. Therefore, we aim to enhance the equity of oral health for the disabled by providing the correct oral health care method to social workers residing in the welfare facility for the disabled. Methods: Four dental hygienists and four social workers were given the class I intellectual disabilities living in 'o' welfare facilities for disabled people in Songpa-gu, Seoul from April 13, 2019 to April 20, 2019. Patient Hygiene Performance(PHP) Index were measured and compared. In advance, the social workers were taught brushing (Rolling method), and the method of brushing and measuring tools were integrated. Results: Twice a total of dental hygienists and social workers practiced toothbrushing(Rolling method) for the class I intellectual disabilities who is a person to be brushed. When comparing the Patient Hygiene Performance(PHP) Index after the second round, the result shows that both the first and second dental hygienists' Patient Hygiene Performance(PHP) Index is lower. Conclusions: Comparing oral health knowledge level and Patient Hygiene Performance(PHP) index of dental hygienist and social workers, the result shows that dental hygienist has higher oral health care ability. Therefore, the dental hygienist should be placed in welfare facility for the disabled as an expert in oral health management to create an environment in which the disabled and social workers can be trained. In addition, the curriculum of the college that nurtures the dental hygienists should have a course to understand the characteristics of the disabled person in order to enhance the professionalism of dental hygienists.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.109-131
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• 2014

As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.177-193
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• 2014

Over the past decade, there has been a rapid diffusion of electronic commerce and a rising number of interconnected networks, resulting in an escalation of security threats and privacy concerns. Electronic commerce has a built-in trade-off between the necessity of providing at least some personal information to consummate an online transaction, and the risk of negative consequences from providing such information. More recently, the frequent disclosure of private information has raised concerns about privacy and its impacts. This has motivated researchers in various fields to explore information privacy issues to address these concerns. Accordingly, the necessity for information privacy policies and technologies for collecting and storing data, and information privacy research in various fields such as medicine, computer science, business, and statistics has increased. The occurrence of various information security accidents have made finding experts in the information security field an important issue. Objective measures for finding such experts are required, as it is currently rather subjective. Based on social network analysis, this paper focused on a framework to evaluate the process of finding experts in the information security field. We collected data from the National Discovery for Science Leaders (NDSL) database, initially collecting about 2000 papers covering the period between 2005 and 2013. Outliers and the data of irrelevant papers were dropped, leaving 784 papers to test the suggested hypotheses. The co-authorship network data for co-author relationship, publisher, affiliation, and so on were analyzed using social network measures including centrality and structural hole. The results of our model estimation are as follows. With the exception of Hypothesis 3, which deals with the relationship between eigenvector centrality and performance, all of our hypotheses were supported. In line with our hypothesis, degree centrality (H1) was supported with its positive influence on the researchers' publishing performance (p<0.001). This finding indicates that as the degree of cooperation increased, the more the publishing performance of researchers increased. In addition, closeness centrality (H2) was also positively associated with researchers' publishing performance (p<0.001), suggesting that, as the efficiency of information acquisition increased, the more the researchers' publishing performance increased. This paper identified the difference in publishing performance among researchers. The analysis can be used to identify core experts and evaluate their performance in the information privacy research field. The co-authorship network for information privacy can aid in understanding the deep relationships among researchers. In addition, extracting characteristics of publishers and affiliations, this paper suggested an understanding of the social network measures and their potential for finding experts in the information privacy field. Social concerns about securing the objectivity of experts have increased, because experts in the information privacy field frequently participate in political consultation, and business education support and evaluation. In terms of practical implications, this research suggests an objective framework for experts in the information privacy field, and is useful for people who are in charge of managing research human resources. This study has some limitations, providing opportunities and suggestions for future research. Presenting the difference in information diffusion according to media and proximity presents difficulties for the generalization of the theory due to the small sample size. Therefore, further studies could consider an increased sample size and media diversity, the difference in information diffusion according to the media type, and information proximity could be explored in more detail. Moreover, previous network research has commonly observed a causal relationship between the independent and dependent variable (Kadushin, 2012). In this study, degree centrality as an independent variable might have causal relationship with performance as a dependent variable. However, in the case of network analysis research, network indices could be computed after the network relationship is created. An annual analysis could help mitigate this limitation.

• Journal of Biomedical Engineering Research
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• v.19 no.5
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• pp.455-468
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• 1998

For the objective interpretation of cerebral metabolic patterns in epilepsy patients, we developed computer-aided classifier using artificial neural network. We studied interictal brain FDG PET scans of 257 epilepsy patients who were diagnosed as normal(n=64), L TLE (n=112), or R TLE (n=81) by visual interpretation. Automatically segmented volume of interest (VOI) was used to reliably extract the features representing patterns of cerebral metabolism. All images were spatially normalized to MNI standard PET template and smoothed with 16mm FWHM Gaussian kernel using SPM96. Mean count in cerebral region was normalized. The VOls for 34 cerebral regions were previously defined on the standard template and 17 different counts of mirrored regions to hemispheric midline were extracted from spatially normalized images. A three-layer feed-forward error back-propagation neural network classifier with 7 input nodes and 3 output nodes was used. The network was trained to interpret metabolic patterns and produce identical diagnoses with those of expert viewers. The performance of the neural network was optimized by testing with 5~40 nodes in hidden layer. Randomly selected 40 images from each group were used to train the network and the remainders were used to test the learned network. The optimized neural network gave a maximum agreement rate of 80.3% with expert viewers. It used 20 hidden nodes and was trained for 1508 epochs. Also, neural network gave agreement rates of 75~80% with 10 or 30 nodes in hidden layer. We conclude that artificial neural network performed as well as human experts and could be potentially useful as clinical decision support tool for the localization of epileptogenic zones.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.2
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• pp.29-39
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• 2011

Recent interests in the quality of urban space have raised awareness on the role and importance of landscape planning. Although laws and guidelines are officially ready to be imposed as for landscape planning, we do not have concrete materials that can be utilized in the course of practices. The aim of this paper in this regard is to disclose the possible difference in awareness on 'visual landscape control elements' among experts engaged with urban space planning. The expert groups are distinguished to three which are for a planning, design and engineering and the survey is made by questionnaires. The results are analyzed through basic technology statistics in SPSS and independent-sample t-test provided. The survey is done by tens of 'control elements' and the result is that specially, group 1 and group 2 in mixed landscape has the most discrepancy in awareness on those elements but relatively, they has less discrepancy in awareness on compare with other groups through all landscape area. In case of artificial landscape and mixed landscape in 'landscape controled area', the result for comparing between G1 and G2 is that there are the most discrepancy in awareness which are 7 control elements. In case of mixed landscape in 'landscape promoted area', there are 4 control elements for discrepancy in awareness between G2 and G3 which is quite different. The control elements which show the most discrepancy in awareness is height, floor space and building to land ratio in order. The shape elements has only discrepancy in awareness for comparing between G1 and G2 of artificial landscape in 'landscape controled area'. In terms of the average evaluation score of the appropriateness of these control elements, G1 seems to appreciate the role of these elements in systematic landscape planning more than the other group does. In other words, relatively low scores are given by G2 as for the overall functionality of visual landscape control elements. The texture, floor space and building of land ratio has low evaluation score for all area and types. It means that it should reverify for appropriateness of performance for landscape planning as visual landscape control elements.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.57-75
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• 2019

In this paper, we conducted a study focusing on the innovation direction of the documentary model on the Internet of Things industry, which is the most actively industrialized among the core technologies of the 4th Industrial Revolution. Policy, economic, social, and technical issues were derived using PEST analysis for global trend analysis. It also presented future prospects for the Internet of Things industry of ICT-related global research institutes such as Gartner and International Data Corporation. Global research institutes predicted that competition in network technologies will be an issue for industrial Internet (IIoST) and IoT (Internet of Things) based on infrastructure and platforms. As a result of the PEST analysis, developed countries are pushing policies to respond to the fourth industrial revolution through cooperation of private (business/ research institutes) led by the government. It was also in the process of expanding related R&D budgets and establishing related policies in South Korea. On the economic side, the growth tax of the related industries (based on the aggregate value of the market) and the performance of the entity were reviewed. The growth of industries related to the fourth industrial revolution in advanced countries overseas was found to be faster than other industries, while in Korea, the growth of the "technical hardware and equipment" and "communication service" sectors was relatively low among industries related to the fourth industrial revolution. On the social side, it is expected to cause enormous ripple effects across society, largely due to changes in technology and industrial structure, changes in employment structure, changes in job volume, etc. On the technical side, changes were taking place in each industry, representing the health and medical sectors and manufacturing sectors, which were rapidly changing as they merged with the technology of the Fourth Industrial Revolution. In this paper, various management methodologies for innovation of existing business model were reviewed to cope with rapidly changing industrial environment due to the fourth industrial revolution. In addition, four criteria were established to select a management model to cope with the new business environment: 'Applicability', 'Agility', 'Diversity' and 'Connectivity'. The expert survey results in an AHP analysis showing that Business Model Canvas is best suited for business model innovation methodology. The results showed very high importance, 42.5 percent in terms of "Applicability", 48.1 percent in terms of "Agility", 47.6 percent in terms of "diversity" and 42.9 percent in terms of "connectivity." Thus, it was selected as a model that could be diversely applied according to the industrial ecology and paradigm shift. Business Model Canvas is a relatively recent management strategy that identifies the value of a business model through a nine-block approach as a methodology for business model innovation. It identifies the value of a business model through nine block approaches and covers the four key areas of business: customer, order, infrastructure, and business feasibility analysis. In the paper, the expansion and application direction of the nine blocks were presented from the perspective of the IoT company (ICT). In conclusion, the discussion of which Business Model Canvas models will be applied in the ICT convergence industry is described. Based on the nine blocks, if appropriate applications are carried out to suit the characteristics of the target company, various applications are possible, such as integration and removal of five blocks, seven blocks and so on, and segmentation of blocks that fit the characteristics. Future research needs to develop customized business innovation methodologies for Internet of Things companies, or those that are performing Internet-based services. In addition, in this study, the Business Model Canvas model was derived from expert opinion as a useful tool for innovation. For the expansion and demonstration of the research, a study on the usability of presenting detailed implementation strategies, such as various model application cases and application models for actual companies, is needed.