• The Journal of Information Systems
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• v.31 no.1
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• pp.271-287
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• 2022

Purpose This research aims to study the changes in recruitment needed for the growth and survival of companies in the rapidly changing industry. In particular, we built a real company's worklist accounting for the rapidly advancing data-driven digital transformation, and presented the capabilities and conditions required for work. Design/methodology/approach we selected 37 jobs based on NCS to develop the employment search requirements by analyzing the business characteristics and work capabilities of the industry and company. The business specification indicators were converted into a matrix through the TF-IDF process, and the NMF algorithm is used to extract the features of each document. Also, the cosine distance measurement method is utilized to determine the similarity of the job specification conditions. Findings Companies tended to prefer "IT competency," which is a specification related to computer use and certification, and "experience competency," which is a specification for experience and internship. In addition, 'foreign language competency' was additionally preferred depending on the job. This analysis and development of job requirements would not only help companies to find the talents but also be useful for the jobseekers to easily decide the priority of their specification activities.

• The Journal of Korea Robotics Society
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• v.17 no.1
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• pp.76-85
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• 2022

One of the most fundamental challenges when designing controllers for dynamic systems is the adjustment of controller parameters. Usually the system model is used to get the initial controller, but eventually the controller parameters must be manually adjusted in the real system to achieve the best performance. To avoid this manual tuning step, data-driven methods such as machine learning were used. Recently, reinforcement learning became one alternative of this problem to be considered as an agent learns policies in large state space with trial-and-error Markov Decision Process (MDP) which is widely used in the field of robotics. However, on initial training step, as an agent tries to explore to the new state space with random action and acts directly on the controller parameters in real systems, MDP can lead the system safety-critical system failures. Therefore, the issue of 'safe exploration' became important. In this paper we meet 'safe exploration' condition with Control Barrier Function (CBF) which converts direct constraints on the state space to the implicit constraint of the control inputs. Given an initial low-performance controller, it automatically optimizes the parameters of the control law while ensuring safety by the CBF so that the agent can learn how to predict and control unknown and often stochastic environments. Simulation results on a quadrotor UAV indicate that the proposed method can safely optimize controller parameters quickly and automatically.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.937-944
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• 2022

Electric vehicles (EVs) have been growing to reduce energy consumption and greenhouse gas (GHG) emissions in the transportation sector. The increasing number of EVs requires adequate recharging infrastructure, and at the same time, adopts low- or zero-emission electricity production because the GHG emissions are highly dependent on primary sources of electricity production. Although previous research has studied solar photovoltaic (PV) -integrated EV charging stations, it is challenging to optimize spatial areas between where the charging stations are required and where the renewable energy sources (i.e., solar photovoltaic (PV)) are accessible. Therefore, the primary objective of this research is to support decisions of siting EV charging stations using a spatial data clustering method integrated with Geographic Information System (GIS). This research explores spatial relationships of PV power outputs (i.e., supply) and traffic flow (i.e., demand) and tests a community in the state of Indiana, USA for optimal sitting of EV charging stations. Under the assumption that EV charging stations should be placed where the potential electricity production and traffic flow are high to match supply and demand, this research identified three areas for installing EV charging stations powered by rooftop PV in the study area. The proposed strategies will drive the transition of existing energy infrastructure into decentralized power systems. This research will ultimately contribute to enhancing economic efficiency and environmental sustainability by enabling significant reductions in electricity distribution loss and GHG emissions driven by transportation energy.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.6
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• pp.1137-1156
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• 2023

With the advent of artificial intelligence (AI) during the Fourth Industrial Revolution, the fashion industry has simplified the production process and overcome the technical difficulties of design. This study anticipates likely changes in the digital age and develops a model that will allow consumers to design textile patterns using AI technology. Previous studies and industrial examples of AI technology's use in the textile design industry were investigated, and a textile pattern was developed using an AI algorithm. A new textile design model was then proposed based on its application to both virtual and physical clothing. Inspired by traditional Korean masks and props, AI technology was used to input color data from open application programming interface images. By inserting these into various repeating structures, a textile design was developed and simulated as garments for both virtual and real garments. We expect that this study will establish a new textile design development method for Generation Z, who favor customized designs. This study can inform the use of personalization in generative textile design as well as the systemization of technology-driven methods for customized and participatory textile design.

• Journal of the Korean Society of Clothing and Textiles
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• v.48 no.1
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• pp.108-119
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• 2024

In this study, we aimed to propose enhancements to the dimensions and design of walking aids tailored for elderly women. Specifically, we focused on wheeled walking assistance devices and aligned each structural component with the appropriate human body dimensions to suggest appropriate product dimensions organized by size clusters, aiming to maximize the practicality of the results. We extracted essential factors required for product design, including human body size elements. The dimension extraction method was clustered to establish connections between key human body parameters-such as height, weight, and age groups-and product dimensions. We conducted a comparative analysis of walking aid product dimensions according to the design elements and sizes of models currently available in the market. The outcomes of this study offer objective, data-driven insights into areas where existing models on the market could benefit from improvement and we anticipate that the findings of this study will provide a solid, quantitative foundation for individuals when selecting the most suitable model for their needs.

• Journal of Wind Energy
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• v.14 no.3
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• pp.34-42
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• 2023

The reduction of operation and maintenance (O&M) costs is a critical factor in determining the competitiveness of wind energy. Predictive maintenance based on the estimation of remaining useful life (RUL) is a key technology to reduce logistic costs and increase the availability of wind turbines. Although a mechanical component usually has sudden changes during operation, most RUL estimation methods use the trend of a state index over the whole operation period. Therefore, overestimation of RUL causes confusion in O&M plans and reduces the effect of predictive maintenance. In this paper, two RUL estimation methods (load based and data driven) are proposed for the bearings of a wind turbine with the results of trend classification, which differentiates constant and increasing states of the state index. The proposed estimation method is applied to a bearing degradation test, which shows a conservative estimation of RUL.

• Journal of the Society of Disaster Information
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• v.15 no.4
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• pp.548-559
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• 2019

Purpose: Analysis method of V2I data driven motorway service area usage behavior to cope with manpower survey. Method: Segmentation of traveling state group and boundary using the distribution characteristics of traveling speed data of individual vehicles. Result: As a result of the verification, the use rate of resting places in lunchtime surged, and the boundary between the distribution status of the traffic speed data was clearly or unclear. Conclusion: The effect of the cost reduction is big because it can cope with the use of rest area survey by manpower and there is no limit in the time and space range of investigation. The dynamic utilization rate of each time sequence, such as a service area/drowsiness shelter/simple service area, with a V2I system, can be calculated. Identify illegal parking on highway section. Identify the unexpected situation in the road section. Identify the real-time service area utilization rate and congestion information.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.1_2
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• pp.125-134
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• 2004

Recently, an on-chip compressed cache system was presented to alleviate the processor-memory Performance gap by reducing on-chip cache miss rate and expanding memory bandwidth. This research Presents an extended on-chip compressed cache system which also significantly expands main memory capacity. Several techniques are attempted to expand main memory capacity, on-chip cache capacity, and memory bandwidth as well as reduce decompression time and metadata size. To evaluate the performance of our proposed system over existing systems, we use execution-driven simulation method by modifying a superscalar microprocessor simulator. Our experimental methodology has higher accuracy than previous trace-driven simulation method. The simulation results show that our proposed system reduces execution time by 4-23% compared with conventional memory system without considering the benefits obtained from main memory expansion. The expansion rates of data and code areas of main memory are 57-120% and 27-36%, respectively.

• Spatial Information Research
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• v.9 no.1
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• pp.73-89
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• 2001

In the recent rapidly changing technology environment the computerization of administration business using GIS is driven or will be driven to give improved information services for the people by local government or central government with huge budget. Development of GIS for local governments is investigated with huge budge. Development of GIS for local governments is investigated to prevent local government from investing redundant money and to reuse the existing investment at this time. The purpose of this study is finding the development method of Land Management Information System (LMIS) to give service and share data in various computing environment of local governments. To do this, we have to develop LMIS as open system with interoperability and we explain it with a focus to framework of Open LMIS. According to recent trend of technology we developed Open LMIS for convenient maintenance with nationwide LMIS expansion at hand. This system was developed at the $\ulcorner$Land Management Information System Development$\lrcorner$project which was managed by Ministry of Construction and Transportation (MOCT). GIS application was based on OpenGIS CORBA specification for development of standard interface and RUP(Rational Unified Process) for development method and LML(Unified Modeling Language) for system design. Developed systems were land administration system for local government, spatial planning support system for regional government, and land policy support system for MOCT.

• Journal of Korea Water Resources Association
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• v.50 no.8
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• pp.521-535
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• 2017

Acoustic Doppler Current Profilers (ADCPs) have been widely utilized for assessing streamflow discharge, yet few comprehensive studies were conducted to evaluate discharge uncertainty in consideration of individual uncertainty components. It could be mostly because it was not easy to determine which uncertainty framework can be appropriate to rigorously analyze streamflow discharge driven by ADCPs. In this regard, considerable efforts have been made by scientific and engineering societies to develop a standardized theoretical framework for uncertainty analysis in hydrometry. One of the well-established UA methodology based on sound statistical and engineering concepts is Guide to the Expression of Uncertainty Measurement (GUM) adopted widely by various scientific and research communities. This research fundamentally adapted the GUM framework to assess individual uncertainty components of ADCP discharge measurements, and subsequently provided results of a customized experiment in a controllable real-scale artificial river channel. We focused particularly upon sensitivities of uncertainty components in the GUM framework driven by ADCPs direct measurements such as depths, edge distance, submerged depth, velocity gap, sampling time, repeatability, bed roughness and so on. Section-by-Section method for ADCP discharge measurement was applied for uncertainty analysis for this study. All of measurements were carefully compared with data using other instrumentations such as ADV to evaluate individual uncertainty components.