• Journal of The Korea Institute of Healthcare Architecture
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• v.23 no.1
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• pp.7-14
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• 2017

Purpose: Since the large hospitals are one of the most intensive energy users among building types in Korea, it is important to investigate and apply appropriate energy conservation measures. There are many researches on energy conservation measures for HVAC system in hospitals, but only few useful guidelines for envelope design variables were existed. The building envelope is one of the important factors to building energy consumption and patients' comfort. The purpose of this study is to suggest the most influential envelope design variables for each end-use energy demand. Methods: 100 samples were generated by LHS(Latin Hypercube Sampling) method. After energy performance simulation, global sensitivity analysis was performed by the regression method. DesignBuilder, Simlab 2.2 and JEPlus were used in this process. Results: The most influencing variables are SHGC, SHGC and VT for heating, cooling, and lighting, respectively. However, the most influencing variable for total energy demand is WWR(Window to Wall Ratio). The analysis was conducted based on the coefficient of variance results. Implications: The six envelop design variables were ranked according to the end-use energy demand.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.8
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• pp.86-92
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• 2021

As interest and demand for high value-added industries, including the global automobile and aerospace industries, have increased recently, demand for line centers with excellent performance that can respond to the production system for producing high value-added products is also rapidly increasing. A line center improves productivity based on the installed area using a multi-spindle compared to a conventional machining center. However, as the number of spindles increases, the weight increases and results in structural problems owing to the heat and vibration generated by each spindle. Therefore, it is necessary to improve machining precision through the structural improvement of the line center. This study presents research on the stabilization design of the line center through structural stability analysis through structural analysis to develop a compact multi-axis line center. An optimization model of the line center has been proposed to improve the processing precision and increase the rigidity by performing weight reduction based on the structural analysis results.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.160-172
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• 2023

In contemporary global warfare, the significance and imperative of air transportation have been steadily growing. The Republic of Korea Air Force currently operates only light and medium-sized military cargo planes, but does not have a heavy one. The current air transportation capability is limited to meet various present and future air transport needs due to lack of performance such as payload, range, cruise speed and altitude. The problem of population cliffs and lack of airplane parking space must also be addressed. These problems can be solved through the introduction of heavy cargo planes. Until now, most studies on the need of heavy cargo plane and increasing air transport capability have focused on the necessity. Some of them suggested specific quantity and model but have not provided scientific evidence. In this study, the appropriate ratio of heavy cargo plane suitable for the Korea's national power was calculated using principal component analysis and cluster analysis. In addition, an optimization model was established to maximize air transport capability considering realistic constraints. Finally we analyze the results of optimization model and compare two alternatives for force structure.

• Information Systems Review
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• v.26 no.1
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• pp.251-268
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• 2024

In the Fourth Industrial Revolution era, global powers are enhancing R&D support to leverage innovations like AI, IoT, and big data for productivity gains and structural economic and social reforms. Yet, the declining R&D budget growth rate and the forecasted sharp cut in South Korea's R&D budget in 2024 highlight the critical need for national R&D performance management system discussions. Diverging from previous studies focused on quantitative analysis of performance determinants, this research utilizes fuzzy set qualitative comparative analysis(fsQCA) to explore the interplay of factors affecting research institutions' outcomes comprehensively. Analyzing data from 2018 to 2022, it examines three outcome types of research institutions, identifying factor combinations crucial for success. By pinpointing these factors' configurations, the study offers institution-specific performance enhancement guidelines and insights for national R&D policy management and performance evaluation efficiency.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.2
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• pp.135-142
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• 2015

This paper analyzed the effects of changes in temporary workers on firm performances, and the effects of different workforce portions of business functions on corporate performances, respectively, using Korean venture business survey conduected in 2013. Results show that the performance of venture businesses decreases significantly, as the portion of temporary workers increases, which is more pronounced in small companies than in medium companies. In addition, the portions of workforce for administration, R&D, production, and sales don't have uniform effect on firm performance, where medium companies are affected significantly by the portions of production and sales, while small companies do not show significant relationship. This analysis implies that innovative firms, based on knowledge workers, need to use caution when they plan to increase temporary workers, which may lead to lower performance. However, we need further research for the basic causes of the possible lower performance.

• Journal of Digital Convergence
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• v.10 no.1
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• pp.241-251
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• 2012

Despite the increasing importance that companies currently place on employee wellness, few studies have explored the impact of wellness on individual and team performance in the workplace. Drawing on the broaden-and-build theory, we hypothesize that wellness intention, wellness leadership, and wellness climate influence the performance of both individuals and teams. We tested our hypotheses using data collected from 495 employees of 81 teams in 11 Korean companies. Our analysis indicates that wellness leadership and wellness climate are meaningful interventions between perceived wellness and performance. Wellness intention did not impact perceived wellness. However, the interaction between wellness intention and wellness leadership impacted perceived wellness. Wellness climate negatively moderated the relationship between perceived wellness and performance.

• Atmosphere
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• v.29 no.1
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• pp.21-39
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• 2019

The conventional observations of the Korea Meteorological Administration (KMA) and National Centers for Environmental Prediction (NCEP) are compared in the numerical weather forecast system at the Korea Institute of Atmospheric Prediction Systems (KIAPS). The weather forecasting system used in this study is consists of Korea Integrated Model (KIM) as a global numerical weather prediction model, three-dimensional variational method as a data assimilation system, and KIAPS Package for Observation Processing (KPOP) as an observation pre-processing system. As a result, the forecast performance of NCEP observation was better while the number of observation is similar to the KMA observation. In addition, the sensitivity of forecast performance was investigated for each SONDE, SURFACE and AIRCRAFT observations. The differences in AIRCRAFT observation were not sensitive to forecast, but the use of NCEP SONDE and SURFACE observations have shown better forecast performance. It is found that the NCEP observations have more wind observations of the SONDE in the upper atmosphere and more surface pressure observations of the SURFACE in the ocean. The results suggest that evenly distributed observations can lead to improved forecast performance.

• Atmosphere
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• v.31 no.5
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• pp.511-523
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• 2021

This study explores the optimal ensemble size to improve the prediction performance of the Korea Meteorological Administration's operational climate prediction system, global seasonal forecast system version 5 (GloSea5). The GloSea5 produces an ensemble of hindcast data using the stochastic kinetic energy backscattering version2 (SKEB2) and timelagged ensemble. An experiment to increase the hindcast ensemble from 3 to 14 members for four initial dates was performed and the improvement and effect of the prediction performance considering Root Mean Square Error (RMSE), Anomaly Correlation Coefficient (ACC), ensemble spread, and Ratio of Predictable Components (RPC) were evaluated. As the ensemble size increased, the RMSE and ACC prediction performance improved and more significantly in the high variability area. In spread and RPC analysis, the prediction accuracy of the system improved as the ensemble size increased. The closer the initial date, the better the predictive performance. Results show that increasing the ensemble to an appropriate number considering the combination of initial times is efficient.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.212-217
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• 2009

Strategic alliance is a proactive management process that integrates and optimizes value-added services of each party to best achieve business objectives of all parties within the relationship. Under the current competitive global environment, strategic alliance can produce a "Win-Win" situation and thus change paradigm that has resided in the construction industry. While many studies revealed the significance of alliance relationship in the industry, its impact on project performance has rarely been analyzed. Using the data obtained from 661 construction projects in the Construction Industry Institute database (359 projects from 38 owners and 302 projects from 29 contractors), this study first diagnoses the implementation status of strategic alliance at both project and company levels. Then, its impact on project performance is quantified and discussed. The descriptive analysis performed in this study revealed that an average of 79% of owner companies and 69% of contractor companies have ever implemented strategic alliance into at least one of their projects. However, both owner and contractor companies did not always use the strategy for all or their projects. Only 33% and 30% of projects reported by owners and contractors have been completed under alliance relationship, respectively. Analyzing the alliance impact on project performance, this study also establishes that strategic alliance positively affects project performance of both owners and contractors while owners should consider and control the level of its use for their projects. Recognizing and understanding the benefits from strategic alliance will be a starting point to produce mutual success among project participants, ultimately allowing the construction industry to go forward to a sustainable industry that transfers success from one project to the other.

• Journal of KIISE:Software and Applications
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• v.29 no.8
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• pp.521-528
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• 2002

We propose a new approach to the feature selection for the classification of handwritten characters using two-dimensional(2D) wavelet packet bases. To extract key features of an image data, for the dimension reduction Principal Component Analysis(PCA) has been most frequently used. However PCA relies on the eigenvalue system, it is not only sensitive to outliers and perturbations, but has a tendency to select only global features. Since the important features for the image data are often characterized by local information such as edges and spikes, PCA does not provide good solutions to such problems. Also solving an eigenvalue system usually requires high cost in its computation. In this paper, the original data is transformed with 2D wavelet packet bases and the best discriminant basis is searched, from which relevant features are selected. In contrast to PCA solutions, the fast selection of detailed features as well as global features is possible by virtue of the good properties of wavelets. Experiment results on the recognition rates of PCA and our approach are compared to show the performance of the proposed method.