• Journal of Information Technology Services
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• v.14 no.1
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• pp.237-249
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• 2015

The volume of unstructured text data generated by various social media has been increasing rapidly; therefore, use of text mining to support decision making has also been increasing. Especially, issue Clustering-determining a new relation with various issues through clustering-has gained attention from many researchers. However, traditional issue clustering methods can only be performed based on the co-occurrence frequency of issue keywords in many documents. Therefore, an association between issues that have a low co-occurrence frequency cannot be discovered using traditional issue clustering methods, even if those issues are strongly related in other perspectives. Therefore, issue clustering that fits each of criteria needs to be performed by the perspective of analysis and the purpose of use. In this study, a multi-dimensional issue clustering is proposed to overcome the limitation of traditional issue clustering. We assert, specifically in this study, that issue clustering should be performed for a particular purpose. We analyze the results of applying our methodology to two specific perspectives on issue clustering, (i) consumers' interests, and (ii) related R&D terms.

• Smart Structures and Systems
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• v.15 no.6
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• pp.1583-1600
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• 2015

When natural disasters occur, including earthquakes, tsunamis, and debris flows, they are often accompanied by various types of damages such as the collapse of buildings, broken bridges and roads, and the destruction of natural scenery. Natural disaster detection and warning is an important issue which could help to reduce the incidence of serious damage to life and property as well as provide information for search and rescue afterwards. In this study, we propose a novel computer vision technique for debris flow detection which is feature-based that can be used to construct a debris flow event warning system. The landscape is composed of various elements, including trees, rocks, and buildings which are characterized by their features, shapes, positions, and colors. Unlike the traditional methods, our analysis relies on changes in the natural scenery which influence changes to the features. The "background module" and "monitoring module" procedures are designed and used to detect debris flows and construct an event warning system. The multi-criteria decision-making method used to construct an event warring system includes gradient information and the percentage of variation of the features. To prove the feasibility of the proposed method for detecting debris flows, some real cases of debris flows are analyzed. The natural environment is simulated and an event warning system is constructed to warn of debris flows. Debris flows are successfully detected using these two procedures, by analyzing the variation in the detected features and the matched feature. The feasibility of the event warning system is proven using the simulation method. Therefore, the feature based method is found to be useful for detecting debris flows and the event warning system is triggered when debris flows occur.

• Steel and Composite Structures
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• v.37 no.4
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• pp.493-501
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• 2020

The paper describes an optimization method based on the mathematical model of interaction within multibody 'bridge-track-cars" dynamic system. The interaction is connected with considerable dynamic phenomena influenced by high traffic speed (up to 400 km/h) on high-speed railroads. The trend analysis of a structure is necessary to determine the direction and resource of optimizing the system. Thus, scientific methods of decision-making process are necessary. The process requires a great amount of information analysis dealing with behavior and changes of the "bridge-track-cars system" that consists of mechanisms and structures, including transitions. The paper shows the algorithm of multi-criteria optimization that can essentially reduce weight of a bridge superstructure using big data analysis. This reduction is carried out in accordance with the constraints that have to be satisfied in any case. Optimization of real steel-concrete beam is exemplified. It demonstrates possibility of measures that are offered by the algorithm.

• Asian Journal of Innovation and Policy
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• v.8 no.1
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• pp.73-96
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• 2019

This study suggests a new approach for identifying core robot tech-nologies based on technological cross-impact. Specifically, the approach applies data mining techniques and multi-criteria decision-making methods to the co-classification information of registered patents on the robots. First, a cross-impact matrix is constructed with the confidence values by applying association rule mining (ARM) to the co-classification information of patents. Analytic network process (ANP) is applied to the co-classification frequency matrix for deriving weights of each robot technology. Then, a technique for order performance by similarity to ideal solution (TOPSIS) is employed to the derived cross-impact matrix and weights for identifying core robot technologies from the overall cross-impact perspective. It is expected that the proposed approach could help robot technology managers to formulate strategy and policy for technology planning of robot area.

• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.147-163
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• 2004

For the purchase of a cheaper product on the Internet, many customers have been trying to search online shopping mall sites and visit comparison-pricing shops that compare prices and other criteria of the product. Others have been participating into online auction markets or group-buying markets. However, a lot of online shopping malls, auction markets, and group-buying markets provide the same product with different prices. Since these marketplaces have different price settlement mechanism, it is very difficult for the customers to determine marketplace to purchase, considering different kinds of marketplaces at the same time. To overcome such limitations, decision rules and solution procedures for purchase decision making are necessary, which can cover multiple marketplaces simultaneously. For this purpose, purchase decision making in each market must be conducted to maximize customer's utility, and conflicts with other marketplaces must be resolved. Therefore, we have developed the rules and methods that can negotiate cooperatively the purchase decision making in several marketplaces, and designed an architecture of Intelligent Buyer Agent and a message structure to support the idea.

• International Journal of Highway Engineering
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• v.18 no.3
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• pp.47-57
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• 2016

PURPOSES : This study aims to examine the differences between the existing traffic demand forecasting method and the traffic demand forecasting method considering future regional development plans and new road construction and expansion plans using a four-step traffic demand forecast for a more objective and sophisticated national highway maintenance. This study ultimately aims to present future pavement deterioration and budget forecasting planning based on the examination. METHODS : This study used the latest data offered by the Korea Transport Data Base (KTDB) as the basic data for demand forecast. The analysis scope was set using the Daejeon Metropolitan City's O/D and network data. This study used a traffic demand program called TransCad, and performed a traffic assignment by vehicle type through the application of a user equilibrium-based multi-class assignment technique. This study forecasted future traffic demand by verifying whether or not a realistic traffic pattern was expressed similarly by undertaking a calibration process. This study performed a life cycle cost analysis based on traffic using the forecasted future demand or existing past pattern, or by assuming the constant traffic demand. The maintenance criteria were decided according to equivalent single axle loads (ESAL). The maintenance period in the concerned section was calculated in this study. This study also computed the maintenance costs using a construction method by applying the maintenance criteria considering the ESAL. The road user costs were calculated by using the user cost calculation logic applied to the Korean Pavement Management System, which is the existing study outcome. RESULTS : This study ascertained that the increase and decrease of traffic occurred in the concerned section according to the future development plans. Furthermore, there were differences from demand forecasting that did not consider the development plans. Realistic and accurate demand forecasting supported an optimized decision making that efficiently assigns maintenance costs, and can be used as very important basic information for maintenance decision making. CONCLUSIONS : Therefore, decision making for a more efficient and sophisticated road management than the method assuming future traffic can be expected to be the same as the existing pattern or steady traffic demand. The reflection of a reliable forecasting of the future traffic demand to life cycle cost analysis (LCCA) can be a very vital factor because many studies are generally performed without considering the future traffic demand or with an analysis through setting a scenario upon LCCA within a pavement management system.

• Child Health Nursing Research
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• v.22 no.2
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• pp.107-116
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• 2016

Purpose: Involvement of families in rounds is one strategy to implement patient- and family-centered care to help families get clear information about their child, and be actively involved in decision making. The purpose of this paper was to identify the major concepts of family-centered rounds for hospitalized children. Methods: We searched five electronic databases for relevant articles and used Whittemore and Knafl's integrative review methods to synthesize the literature. Articles published between June 2003 and January 2016 were reviewed and through full text screening 24 peer-reviewed articles were found that met the selection criteria for this review. Results: Through in-depth discussion and investigation of the relevant literature, four overarching components emerged: (a) cognition of parents and medical staff, (b) effective communication, (c) collaboration of family and medical staff, (d) coaching of medical staff. Conclusion: For successful family-centered rounds positive cognition is important. Appropriate communication skills and consideration of multi-cultural family can lead to effective communication. Offering consistent and transparent information is important for collaboration between family and medical staff. Prior education on family-centered rounds is also important. Four major components have been identified as basic standards for implementing family-centered rounds for hospitalized children.

• Safety and Health at Work
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• v.15 no.3
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• pp.327-337
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• 2024

Background: As the tremendous impact of extreme workloads, arduous working conditions, and disorganization disrupt humane job definitions in some industries, the need for workplace re-articulation was interfered to ameliorate psycho-social factors and suggest organizational intervention strategies. Especially for colossally wounded health-care (HC) systems, today it is now even more unrealizable to retain workforce resilience considering the immense impact of overwhelming working conditions. Methods: This study introduces employment of concurrent engineering tools to re-design humane workplaces annihilating abatement over devoured resources. The study handles HC-workforce resilience in a pioneering motive to introduce transformation of well-known motivators and proposes solutions for retention and resilience issues grounding on HC workers' own voice. Results: The proposed adjustable approach introduces integral use of focus group studies, SWARA, and QFD methods, and was practiced on a real-world case regarding Turkish HC workforce. The paper also presents widespread effects of findings by tendering generalized psycho-social rehabilitation strategies. Results confirmed the modifications of the most potent incessant motivators. Conclusion: "Burn out issues" and "Challenging work" were found as the most important motivator and satisfier, respectively, to be exigently fulfilled. Corrective interventions, required resolutions, and workplace articulation connotations were arbitrated in terms of entire outcomes on four dimensions in three different planning periods considering the current status, repercussions of pandemic, and contingency of similar catastrophes. Descriptive illustrations were additionally presented to support deducted interpretations.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.388-398
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• 2012

In this study, Entropy method and PROMETHEE(Preference Ranking organization METHod for Enrichment Evaluations) which is one of the multi criteria decision making methods are applied to estimate the relative inundation risk ranking of the urban sewer systems. Then, the evaluation factors were selected considering two main items to estimate the inundation risk using Entropy and PROMETHEE. In the first item considering topographical and environmental factor, average elevation, average slope, width of area, population, density of conduit were selected as the detailed factors of first item which have influence of the overflow occurrence and damage scale in urban sewer system. And, the relative reliability of sewer network was considered as the second item which can quantify the inundation appearance. Then, the reliability is estimated considering the number of overflow nodes and overflow volume simultaneously. Therefore, the suggested inundation risk evaluation method can be used as the evaluation index for sewer networks and contribute to decision making for the sewer rehabilitation policy.

• Journal of the Korean GEO-environmental Society
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• v.21 no.10
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• pp.11-16
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• 2020

Korea's agricultural reservoir is one of the country's major infrastructures and plays an important role in people's lives. However, aging reservoirs are a risk for life and property. Currently, large and small dams and reservoirs have been constructed nationwide for more than 40 years of aging. Dams and reservoirs built nationwide are managed by various institutions. Therefore, it is difficult to manage all dams and reservoirs due to cost and time. Managers in the field with less management personnel and lack of expertise should be able to quickly identify risk factors for multiple reservoirs. In this study, risk factors such as seepage, leakage, settlement slide, crack and erosion were selected. To assess the risk of the items, we used the analytical hierarchical process (AHP), one of the Multi-Criteria Decision Making (MCDM) methods. The analysis showed that seepage has the greatest impact on reservoir collapse. It is judged that the priority of detailed diagnosis can be determined by evaluating the risk of dam reservoir collapse in a convenient way in advance using the calculated weight.