• Structural Engineering and Mechanics
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• v.89 no.5
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• pp.479-489
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• 2024

The cracking mechanism in ceramsite aerated concrete block (CACB) infill walls were studied in low seismic fortification intensity coastal areas with frequent occurrence of typhoons. The inter-story drifts of an eight-story residential building under wind loads and a seismic fortification intensity of six degrees were analyzed by using the PKPM software. The maximum inter-story drift ratio of the structure in wind load was found to be comparable to that under the seismic fortification intensity of six degrees. However, when accounting for the large gust wind speed of typhoon, the maximum inter-story drift ratio was much larger than that obtained under reference wind load. In addition, the finite element models of RC frames were employed by displacement loading to simulate two scenarios with and without window hole in the CACB infill walls, respectively. The simulation results show no signs of cracking in both the infill walls with window hole and those without window for the inter-story drift caused by seismic loads and the reference wind load. However, both types of infill walls experienced structural creaking when assessing the gust wind pressure recorded from previous typhoon monitoring. It is concluded that an underestimate of wind loads may contribute substantially to the cracking of frame CACB infill walls in low seismic fortification intensity coastal areas. Consequently, it is imperative to adopt wind pressure values derived from gust wind speeds in the design of CACB infill walls within frame structures. Finally, the future research directions of avoiding cracks in CACB filled walls were proposed. They were the material performance improving and building structure optimizing.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.67-84
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• 2010

In terms of business, forecasting is a work of what is expected to happen in the future to make managerial decisions and plans. Therefore, the accurate forecasting is very important for major managerial decision making and is the basis for making various strategies of business. But it is very difficult to make an unbiased and consistent estimate because of uncertainty and complexity in the future business environment. That is why we should use scientific forecasting model to support business decision making, and make an effort to minimize the model's forecasting error which is difference between observation and estimator. Nevertheless, minimizing the error is not an easy task. Case-based reasoning is a problem solving method that utilizes the past similar case to solve the current problem. To build the successful case-based reasoning models, retrieving the case not only the most similar case but also the most relevant case is very important. To retrieve the similar and relevant case from past cases, the measurement of similarities between cases is an important key factor. Especially, if the cases contain symbolic data, it is more difficult to measure the distances. The purpose of this study is to improve the forecasting accuracy of case-based reasoning approach using fuzzy relation and composition. Especially, two methods are adopted to measure the similarity between cases containing symbolic data. One is to deduct the similarity matrix following binary logic(the judgment of sameness between two symbolic data), the other is to deduct the similarity matrix following fuzzy relation and composition. This study is conducted in the following order; data gathering and preprocessing, model building and analysis, validation analysis, conclusion. First, in the progress of data gathering and preprocessing we collect data set including categorical dependent variables. Also, the data set gathered is cross-section data and independent variables of the data set include several qualitative variables expressed symbolic data. The research data consists of many financial ratios and the corresponding bond ratings of Korean companies. The ratings we employ in this study cover all bonds rated by one of the bond rating agencies in Korea. Our total sample includes 1,816 companies whose commercial papers have been rated in the period 1997~2000. Credit grades are defined as outputs and classified into 5 rating categories(A1, A2, A3, B, C) according to credit levels. Second, in the progress of model building and analysis we deduct the similarity matrix following binary logic and fuzzy composition to measure the similarity between cases containing symbolic data. In this process, the used types of fuzzy composition are max-min, max-product, max-average. And then, the analysis is carried out by case-based reasoning approach with the deducted similarity matrix. Third, in the progress of validation analysis we verify the validation of model through McNemar test based on hit ratio. Finally, we draw a conclusion from the study. As a result, the similarity measuring method using fuzzy relation and composition shows good forecasting performance compared to the similarity measuring method using binary logic for similarity measurement between two symbolic data. But the results of the analysis are not statistically significant in forecasting performance among the types of fuzzy composition. The contributions of this study are as follows. We propose another methodology that fuzzy relation and fuzzy composition could be applied for the similarity measurement between two symbolic data. That is the most important factor to build case-based reasoning model.

• Journal of Distribution Science
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• v.11 no.6
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• pp.59-65
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• 2013

Purpose - Studies of mechanism as a competitive strategy, a relatively new field in the study of strategic management research, has recently drawn the attention of the business management scholars. The literature has so far proposed the subjective-based view, environment-based view, and the resource-based view in its analyses of firm management. Hence, it is highly likely for the firm management to be reasonably thought of as a combination of and interaction among the three key elements of subject, environment, and resources this is the mechanism-based view (MBV). It is reasonable to consider firm management to be the combination of and interaction among the three key elements of subject, environment, and resources. The overall dynamic process that integrates these three elements and creates functional harmony is identified as the mechanism, the principle of firm management. Much of the extant literatures on MBV has mainly focused on case studies, a qualitative approach prone to subjectivity of the researcher, although the intuition from the study may lead to meaningful insights into a firm-specific mechanism. This study's focus is also on case analysis, but it still attempts a quantitative approach in order to reach a scientific and systematic understanding of the MBV. Research design, data, and methodology - I used both a qualitative and quantitative approach to a single model, given the complexity of the innovation processes. I conducted in-depth interviews with POSCO employees-20 from general management, two from human resources, eight from information technology, five from finance and accounting, and five from production and logistics management. Once the innovative events were selected, the interview results were double-checked by the interviewees themselves to ensure the accuracy of the answers recorded. Based on the interview, I then conducted statistical validation using the survey results as well. Results - This study analyzes the building process of innovation and the effect of the mechanism pattern on innovation by examining the case of POSCO, which has survived over the past 21 years. I apply a new analytical tool to study mechanism innovation types, perform a new classification, and describe the interrelationships among the mechanism factors. This process allows me to see how the "Subject"factor interacts with the other factors. I found that, in the innovation process of the adoption stage, Subject had a mediating effect but that the mediating effect of resource and performance was smaller than the effect of Subject on performance alone. During the implementation stage, the mediating effect of Subject increased. Conclusion - Therefore, I have confirmed that the subject utilizes resources reasonably and efficiently. I have also advanced mechanism studies: whereas the field's research methods have been largely confined to single case studies, I have used both qualitative and quantitative methods to examine the relationships among mechanisms.

• Journal of Korea Technology Innovation Society
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• v.14 no.4
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• pp.833-859
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• 2011

This study aims to draw the characteristics of the regional operation system of the shared research instrument service, which contributes to the R&D investment efficiency by the avoidance of duplicated research instrument investment and the enhancement of the network collaboration. So from the perspective of technology infrastructure policy and regional innovation system, Gyeonggi region of Korean metropolitan area has been analyzed for the case study. The case study has been conducted by 2 step process of within-case analysis and cross-case analysis. Firstly, the characteristics of operation system of the shared research instrument have been examined through various research methods. Secondly, in the cross-case analysis, the examined issues and problems have been organized by the matrix of 3 organizational governance characteristics and 4 issues to facilitate the regional policy approach. The issues deducted by the cross-case analysis have been deducted as (1) 'usage fee charge system', 'relevant method for the performance index and measurement of the instrument service management' for the regional policy led case, (2) 'performance management issue', 'financial and managerial accounting system for the instrument operating division', and 'change of budget support scheme' for the joint operation case and lastly (3) 'usage facilitation after the expiration of research lab support project' for the university led case.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.9
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• pp.39-45
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• 2009

When Mobile IPv6 is deployed in commercial network, a mobile node needs AAA services for an authentication, authorization and accounting. AAA and Mobile IPv6 are protocols which are operated independently. Then schemes which merge these protocols have been emerged. These schemes can enable a mobile node to establish a security association between the mobile node and a home agent and to perform a binding update for the home agent using AAA authentication request. But these schemes introduce many signal messages and long handover latency during the handover, since Route Optimization mode for Mobile Ipv6 is performed using Return Routability procedure. To solve this problem, we propose a scheme for Route Optimization mode that the home agent performs the binding update for a correspondent node via the AAA infrastructure between the home agent and the correspondent node instead of Return Routability procedure. For performance evaluation, we analyze signal message transmission costs and handover latencies during handover. We show performance improvement of the proposed scheme which reduces handover latency as 61% compared with the existing scheme.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.6
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• pp.139-150
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• 2017

In Korea, small and medium-sized enterprises (SMEs) play an pivotal role in the national economy, accounting for 99.9% of all enterprises, 87.9% of total employment, and 48.3% of production. In spite of their crucial role in the national development, most of SMEs suffer from a lack of R&D related resources. Public R&D organizations such as government-funded research institutes can provide SMEs with valuable supplementary technological knowledge and help them build technological capacity. In this regard, this study estimated the effect of internal R&D investment and private-public R&D cooperation on technological innovation of ICT SMEs based on 2016 ETRI Survey. Building on previous literatures, the study established and tested a research model using binary logistic regression analysis. First, internal R&D investment and preferences for open innovation demonstrated the strengthening of R&D collaboration. Second, internal R&D investment and R&D cooperation showed a positive effect on both product and process innovation. Therefore, internal R&D capability and taking advantage of R&D collaboration are needed to achieve technological innovation for SMEs in ICT sector. This study also discuss implications for encouraging private-public R&D cooperation.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.67-74
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• 2024

In this paper, we present a study aimed at analyzing how different rainfall measurement methods affect the performance of reservoir water level predictions. This work is particularly timely given the increasing emphasis on climate change and the sustainable management of water resources. To this end, we have employed rainfall data from ASOS, AWS, and Thiessen Network-based measures provided by the KMA Weather Data Service to train our neural network models for reservoir yield predictions. Our analysis, which encompasses 34 reservoirs in Jeollabuk-do Province, examines how each method contributes to enhancing prediction accuracy. The results reveal that models using rainfall data based on the Thiessen Network's area rainfall ratio yield the highest accuracy. This can be attributed to the method's accounting for precise distances between observation stations, offering a more accurate reflection of the actual rainfall across different regions. These findings underscore the importance of precise regional rainfall data in predicting reservoir yields. Additionally, the paper underscores the significance of meticulous rainfall measurement and data analysis, and discusses the prediction model's potential applications in agriculture, urban planning, and flood management.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.3062-3071
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• 2011

This study proposed to compare the performance differences between a manufacturing company and a construction company in accordance with the mutual relations and ownership structures with the management performance based on the increase or decrease of the large shareholders' share-holding ratio (insider ownership, foreign share-holding, institutional investors' share-holding) of a KOSPI listed company in Korea during 10 years(1998-2007). To sum up the research work, first, the increase of foreign share-holding supported the results of previous studies which foreign share-holding has a positive effect on the long term performance by having a positive(+) effect on MTB, and the increase of an insider ownership supported the management entrenchment hypothesis of previous studies by having a negative(-) effect on MTB. However, relations between institutional investors's share-holding and MTB could not find out linkages in spite of the results of previous studies where dealt with the active monitoring hypothesis. Also, to examine the linkages of ROA and the ownership structure, though the increases of foreign share-holding and insider ownership had a positive(+) effect on ROA, the increases of institutional investors' share-holding had a negative(-) effect on it. It showed different analysis results from the active monitoring hypothesis of institutional investors. As a result of verifying whether there is "any difference in the management performances between the construction industry and the manufacturing industry according to the equity structure" which is the second hypothesis, nothing of the insider ownership and whether or not there is the construction industry, foreign share-holding and whether or not there is the construction, and the institutional ownership and whether or not there is the construction industry gave a statistical difference to MTB and ROA. Accordingly, it was possible to find out there is no difference in the management performance between the construction industry and the manufacturing industry based on the ownership structure in spite of different characteristics from the manufacturing industry such as the revenue recognition in ordering, production and accounting.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.2
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• pp.221-233
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• 2019

In Korea, small and medium sized domestic enterprises(SMEs) play an pivotal role in the national economy, accounting for 99.9% of all enterprises, 87.9% of total employment, and 48.3% of production. and SMEs was driving a real force of the development of national economy in many respects such as innovation, job creation, industrial diversity, balanced regional development. Despite their crucial role in the national development, most of SMEs suffer from a lack of R&D capabilities and equipments as well as funding capacity. Public R&D institutes can provide SMEs with valuable supplementary technological knowledge and help them build technological capacity. so, In order to effectively support SMEs, government and public R&D institutes must be a priority to know about the factors influencing the performance related to technology transfer and technological collaborations. In particular, SMEs are not only taking up a large portion of the national economy, but also their influence in politics and economy so strong that raising the competitiveness of small and medium-sized companies is a national policy goal that must be achieved in order to achieve sustained economic growth. For this reason, it is necessary to look specifically at the relationship between concepts such as the environment, strategy, and organizational culture surrounding the enterprise to enhance the competitiveness of SMEs. The paper analyzes 665 companies to find out which organizational culture affects their performance by classification and type of business of SMEs. This study demonstrated that when SMEs seek consistency in their external environment, strategies, and organizational structure to maintain their continued competitiveness. According to three-way analysis of variance (3-way ANOVA) indicates that classification of industries in SMEs has statistically significant main effects, but the type of business and organizational culture do not have significant effects. However, the company's organizational performance (operating profit) of SMES were found to differ significantly in comparison between groups according to classification standards of industries, and therefore adopted some parts. In addition, an analysis of the effect of interaction between the three independent variables of small and medium-sized enterprises has shown that there are statistically significant interaction effects among classification, types of business, and organizational cultures. The results shows that there is an organizational culture suitable for each industry classification and type of business of an entity, and is expected to be used as a basis for establishing promotion policies related to the incubation and commerciality of small and medium-sized venture companies in the future.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.