• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권3호
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• pp.678-700
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• 2023

Diagnosing breast diseases using ultrasound (US) images remains challenging because it is time-consuming and requires expert radiologist knowledge. As a result, the diagnostic performance is significantly biased. To assist radiologists in this process, computer-aided diagnosis (CAD) systems have been developed and used in practice. This type of system is used not only to assist radiologists in examining breast ultrasound images (BUS) but also to ensure the effectiveness of the diagnostic process. In this study, we propose a new approach for breast lesion localization and segmentation using a multi-scale pyramid of the ultrasound image of a breast organ and a convolutional semantic segmentation network. Unlike previous studies that used only a deep detection/segmentation neural network on a single breast ultrasound image, we propose to use multiple images generated from an input image at different scales for the localization and segmentation process. By combining the localization/segmentation results obtained from the input image at different scales, the system performance was enhanced compared with that of the previous studies. The experimental results with two public datasets confirmed the effectiveness of the proposed approach by producing superior localization/segmentation results compared with those obtained in previous studies.

• 대한인간공학회지
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• 제20권1호
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• pp.45-62
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• 2001

This study suggests a genetic algorithm-based partial least squares (GA-based PLS) method to select the design variables for building a usability model. The GA-based PLS uses a genetic algorithm to minimize the root-mean-squared error of a partial least square regression model. A multiple linear regression method is applied to build a usability model that contains the variables seleded by the GA-based PLS. The performance of the usability model turned out to be generally better than that of the previous usability models using other variable selection methods such as expert rating, principal component analysis, cluster analysis, and partial least squares. Furthermore, the model performance was drastically improved by supplementing the category type variables selected by the GA-based PLS in the usability model. It is recommended that the GA-based PLS be applied to the variable selection for developing a usability model.

• Journal of Information Processing Systems
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• 제15권6호
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• pp.1489-1502
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• 2019

This work introduces a novel unweighted combination method (UCSS) for business failure perdition (BFP). With considering features of BFP in the age of big data, UCSS integrates the quantitative and qualitative analysis by utilizing soft set theory (SS). We adopt the conventional expert system (ES) as the basic qualitative classifier, the logistic regression model (LR) and the support vector machine (SVM) as basic quantitative classifiers. Unlike other traditional combination methods, we employ soft set theory to integrate the results of each basic classifier without weighting. In this way, UCSS inherits the advantages of ES, LR, SVM, and SS. To verify the performance of UCSS, it is applied to real datasets. We adopt ES, LR, SVM, combination models utilizing the equal weight approach (CMEW), neural network algorithm (CMNN), rough set and D-S evidence theory (CMRD), and the receiver operating characteristic curve (ROC) and SS (CFBSS) as benchmarks. The superior performance of UCSS has been verified by the empirical experiments.

• 한국건축친환경설비학회 논문집
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• 제12권6호
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• pp.579-590
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• 2018

Anomaly detection on building energy consumption has been regarded as an effective tool to reduce energy saving on building operation and maintenance. However, it requires energy model and FDD expert for quantitative model approach or large amount of training data for qualitative/history data approach. Both method needs additional time and labors. This study propose a machine learning and data science approach to define faulty conditions on hourly building energy consumption with reducing data amount and input requirement. It suggests an application of Support Vector Data Description (SVDD) method on training normal condition of hourly building energy consumption incorporated with hourly outdoor air temperature and time integer in a week, 168 data points and identifying hourly abnormal condition in the next day. The result shows the developed model has a better performance when the ${\nu}$ (probability of error in the training set) is 0.05 and ${\gamma}$ (radius of hyper plane) 0.2. The model accuracy to identify anomaly operation ranges from 70% (10% increase anomaly) to 95% (20% decrease anomaly) for daily total (24 hours) and from 80% (10% decrease anomaly) to 10%(15% increase anomaly) for occupied hours, respectively.

• 국제학술발표논문집
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• The 5th International Conference on Construction Engineering and Project Management
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• pp.308-314
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• 2013

Although global construction spending has experienced slow growth due to consecutive economic crises, global contractors have consistently attempted to expand their overseas market share, leading to more intense competition among contractors in the international construction market. In this market environment, owners, clients and financial institutions require reasonable and systematic criteria to effectively assess the business capabilities of international construction firms. However, the existing evaluation methods for construction firms rarely consider overseas-focused business capabilities. To address this problem, this study proposes a quantitative approach to assessing the overseas business capabilities of international construction firms. The limitations of existing approaches are reviewed, and the capabilities required to perform overseas businesses are analyzed through expert interviews. Finally, 18 evaluation indices are suggested in four categories: technology resources, project management, experience and performance, and sustainability. The relative weight of each index is determined according to the Analytical Hierarchy Process (AHP) method, and a preliminary investigation of 11 Korean construction firms is conducted. The proposed method is expected that it will provide the rational criteria for international owners, clients, and financial institutions for decision-making and for evaluating international contractors.

• 가정간호학회지
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• 제25권1호
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• pp.67-77
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• 2018

Purpose: The purpose of this study was to compare the efficiency of general ward nurses in hospitals using Data Envelopment Analysis (DEA). Methods: Participants were 30 nurses working at a general ward. Input variables were labor cost and time of direct nursing. Output variables were prevention rate of medication error and bedsores, and patient satisfaction. These variables were extracted using literature review and CVI of an expert group. Data were collected from September 18 to October 7, 2017. Data were analyzed using EMS 3.1 program for DEA and descriptive statistics. Results: The average efficiency score of 30 nurses was 0.986, which was very high over all. In the super-efficiency analysis of 11 nurses, their efficiency ranged from 1.0 to 1.047. In addition, when the current output was fixed, the labor cost of nurses did not affect efficiency. Conclusion: This study attempted a new approach concerning performance evaluation of nurses using DEA. This method was useful during appraisal of nurses. We suggest that various input and output variables that were not considered in this study should be added to develop a integrative performance analysis model for nurses.

• 산업경영시스템학회지
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• 제39권4호
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• pp.72-80
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• 2016

The market size of plant projects in overseas is so large that domestic EPC project contractors are actively seeking the overseas projects and then trying to meet completion plans since successful fulfillment of these projects can provide great opportunities for them to expand into new foreign markets. International EPC projects involve all of the uncertainties common to domestic projects as well as uncertainties specific to foreign projects including marine transportation, customs, regulations, nationality, culture and so on. When overseas project gets off-schedule, the resulting uncertainty may trigger unexpected exceptions and then critical effects to the project performance. It usually require much more time and costs to encounter these exceptions in foreign sites compared to domestic project sites. Therefore, an exception handling approach is required to manage exceptions effectively for successful project progress in foreign project sites. In this research, we proposed a methodology for prediction and evaluation of exceptions caused by risks in international EPC projects based on sensitivity analysis and Bayesian Networks. First, we identified project schedule risks and related exceptions, which may meet during the fulfillment of foreign EPC projects that is performed in a sequence of engineering, procurement, preparatory manufacture, foreign shipping, construction, inspection and modification activities, and affect project performance, using literature review and expert interviews. The impact of exceptions to the schedule delay were also identified. Second, we proposed a methodology to predict the occurrence of exceptions caused by project risks and evaluate them. Using sensitivity analysis, we can identify activities that critically affect schedule delay and need to focus by priority. Then, we use Bayesian Networks to predict and evaluate exceptions. Third, we applied the proposed methodology to an international EPC project example to validate the proposed approach. Finally, we concluded the research with the further research topics. We expect that the proposed approach can be extended to apply in exception management in project management.

• 한국문헌정보학회지
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• 제49권1호
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• pp.483-511
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• 2015

The efficiency and quality of the social reference sites are being challenged because a large quantity of the questions have not been answered or satisfied for quite a long time. Main goal of this study is to investigate important factors that affect the performance of question triage to relevant answerers in the context of social reference. To achieve the goal, expert finding techniques were used to construct an automated question triage approach to resolve this problem. Furthermore, important factors affecting triage decisions in digital reference were first examined, and extended them to the social reference setting by investigating important factors affecting the performance of automated question triage in the social reference setting. The study was conducted using question-answer pairs collected from Ask Metafilter. For the evaluation, logistic regression analyses were conducted to examine which factors would significantly affect the performance of predicting relevant answerers to questions. The results of the current study have important implications for research and practice in automated question triage for social reference. Furthermore, the results will offer insights into designing user-participatory digital reference systems.

• 한국경영과학회지
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• 제30권2호
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• pp.185-199
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• 2005

With the growth of internet shopping malls, there is increasing interest in comparison shopping mall. However most comparison sites compare only book prices by collecting simple XML data and do not provide .the exact comparison Including precise shipping costs. Shipping costs vary depending on each customer's address, the delivery method, and the category of selected goods, so rule based system is required in order to calculate exact shipping costs. Therefore, we designed and implemented comparison shopping mall which compares not only book prices but also shipping costs using rule based inference. By adopting the extensible Rule Markup language (XRML) approach, we proposed the methodology of extracting delivery rules from Web pages of each shopping mall. The XRML approach can facilitate nearly automatic rule extraction from Web pages and consistency maintenance between Web pages and rule base. We developed a ConsiderD system which applies our rule acquisition methodology based on XRML. The objective of the ConsiderD system is to compare the exact total cost of books including the delivery cost over Amazon.com, BarnesandNoble.com, and Powells.com. With this prototype, we conducted an experiment to show the potential of automatic rule acquisition from Web pages and illustrate the effect of delivery cost.

• 한국환경과학회지
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• 제31권7호
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• pp.579-592
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• 2022

Much controversy has been generated over whether the ecological restoration project in Korea is faithful to the basic approach of ecological restoration compared to projects aimed at creating parks or green spaces. This study was aimed at understanding the level of awareness of practitioners in the planting design method, which is recognized as relatively important in landscape architecture and ecological restoration. The proficiency of practitioners in planting design techniques for ecological restoration projects was investigated and analyzed in seven areas: overall planting design awareness, plant species selection method, planting tree sizes, planting density, use of native species, vegetation climatic zone, soil environment, and weed control. There was no statistically significant difference between the group who thought they were experts in the field of ecological restoration and the group who thought they were experts in the field of parks and green spaces. Moreover, there was no statistically significant difference between the degree of work performance, that is, the group whose main industry was ecological restoration, the group that performed relatively more ecological restoration work, and the group that rarely performed it. Therefore, to apply desirable ecological restoration techniques in the future and to clearly differentiate between the approach in the field of parks and green spaces, the appropriate tree size or planting density selected in the ecological restoration planting design stage must be chosen. To this end, the awareness of expert groups must be improved and related laws, systems, and guidelines must be revised.