• Smart Media Journal
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• v.9 no.3
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• pp.31-40
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• 2020

Currently, black-box-based machine learning algorithms are used to analyze big data in manufacturing. This algorithm has the advantage of having high analytical consistency, but has the disadvantage that it is difficult to interpret the analysis results. However, in the manufacturing industry, it is important to verify the basis of the results and the validity of deriving the analysis algorithms through analysis based on the manufacturing process principle. To overcome the limitation of explanatory power as a result of this machine learning algorithm, we propose a manufacturing big data analysis method using genetic programming. This algorithm is one of well-known evolutionary algorithms, which repeats evolutionary operators such as selection, crossover, mutation that mimic biological evolution to find the optimal solution. Then, the solution is expressed as a relationship between variables using mathematical symbols, and the solution with the highest explanatory power is finally selected. Through this, input and output variable relations are derived to formulate the results, so it is possible to interpret the intuitive manufacturing mechanism, and it is also possible to derive manufacturing principles that cannot be interpreted based on the relationship between variables represented by formulas. The proposed technique showed equal or superior performance as a result of comparing and analyzing performance with a typical machine learning algorithm. In the future, the possibility of using various manufacturing fields was verified through the technique.

• Journal of Energy Engineering
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• v.26 no.3
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• pp.51-63
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• 2017

Paris Agreement on Climate Change(2015) requires to reduce the greenhouse gas emission. One of the responses to the requirement is to change the proportion of power generation, which is summarized to the decrease in thermal power and the increase in new and renewable power. This article conducts a comparative analysis on the economic effects between thermal- and new and renewable- power generations, using the Input-Output Table from The Bank of Korea. The results of this analysis show that the new and renewable power generation has got the larger effects in production-inducing, value-added-inducing, employment-inducing, and supply-shortage scopes, while the smaller effect in price-pervasive scope than the thermal power generation. According to these results, the complex consideration should be taken into when the changes in power generation mix are tried. Especially, the political efforts to reduce the supply-shortage effect of new and renewable power and the price-pervasive effect of thermal power will be important.

• Journal of the Korea Society of Computer and Information
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• v.20 no.6
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• pp.141-150
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• 2015

The aim of this study is to analysis the efficiency of the Long-term Care facilities as well as make counterproposals to conduct of efficient management for the Long-term Care facilities. The data of professionals states of Long-term Care facilities and wages state of Long-term Care facilities from regions in 2014. To analyse the data, the number of professionals and facilities are an input variable whereas the size of number and wages are the output variables. The results showed as below. First, according to the CCR test, Kangwon, Gyeonggi, GyeongNam, Deajeon, Seoul, Ulsan, Incheon, Jeju, and Chong Buk showed significance, but Daegu and Busan showed no significance. Second, the BCC result showed that Kangwon, Gyeonggi, GyeongNam, Deajeon, Seoul, Ulsan, Incheon, Jeju, and Chong Buk has efficiency whereas Daegu and Busan has no efficiency. The result of excess efficieincy analysis confirmed 133.5% in Jeju as the highest area, 37.54% of the highest efficiency of the care provider, and 28.61% of imporvable possibility with doctor's number. The realization of increasing numbers, the ensure of the doctor's number, and consolidating of the care provider's the espertise are required for the future.

• Journal of Korea Port Economic Association
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• v.30 no.2
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• pp.113-132
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• 2014

With the global warming phenomenon, the deep sea water area that fishing vessels can enter and operate is ever widening. For example, the Arctic Ocean recently has overall competitive advantages due to having many deep-sea fish stocks. The North Pacific region is a strategic coastal district, the closest access point of Arctic Ocean. For Korean fishing vessels which now operate in North Pacific region, and want to entry the Arctic Ocean, the analysis of technical efficiency is needed for preparing the better industry's future. This paper aims to analyze the relative efficiency, and select the low effective deep-sea fishing vessels in the North Pacific, and to suggest their desirables strategies. As a research methodology, Data Envelopment Analysis (DEA) and Malmquist Index are applied to 16 fishing vessels for the periods(2009 to 2013). To draw out the efficiency of targeted deep-sea fishing vessels, gross tons, horsepowers, and operating days are used as input variables while total catch stands for an output variable. As a result, CCR efficiency, BCC efficiency and scalability efficiency are measured to be 0.8405, 0.9484 and 0.8858 respectively for 5 years (2009 to 2013). In conclusion, 38% of total tons, 36% of horsepowers and 29% of operating days each fishing vessel should be reduced to keep their competitive powers.

• Korea Journal of Hospital Management
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• v.16 no.4
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• pp.35-66
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• 2011

This study analyzed efficiency by utilizing DEA analytical technique centering on materials for 2009 of 20 major university hospitals in capital area. Input variables were utilized professor & full-time doctor, resident, nurse & number of bed hospitals. Output variables were analyzed by dividing number of annual outpatients & number of annual inpatients, and annually total outpatient profit & inpatient profit into a model of the standard for number of patients and the standard for medical profit. DEA analysis was elicited efficiency score by applying CCR, BCC, BFG, scale profit, and SE model. Through t-test after eliciting efficiency score, the implications were suggested by comparing efficiency between DMU in Seoul and DMU in capital area, by comparing between high-class general hospitals and general hospitals, and by comparing between high-class general hospitals in Seoul and 5 big hospitals. As a result of analysis, the major university hospitals in capital area showed high efficiency as a whole close to "1," but indicated low efficiency relatively in CCR field. Thus, the expansion in scale within capital area was indicated to reach the limit. Second, in a model of analyzing the standard for number of patients, the medical institutions, which are being operated efficiently, were indicated to be 10 DMUs. In the standard for medical profit, 12 DMUs were analyzed to be operated efficiently. Third, the efficiency in general hospital was higher than high-class general hospital. Thus, the efficiency of operation was indicated to be more important than scale. Also, large high-class hospitals(big 5) where are located in downtown Seoul showed the higher efficiency than other general high-class general hospitals, but were indicating very low efficiency in some DMUs. Fourth, as a result of generalizing and evaluating the number of patients and the medical profit, the efficient DMU was indicated to be more when analyzing on the basis of medical profit than the standard for number of patients. Thus, major university hospitals in capital area were indicated to make more effort for section in medical profit. Based on the analytical results of efficiency, a strategy for reinforcing efficiency in inefficient DMU was indicated to be needed a strategy of creating customers for promoting number of patients and a strategy for making operation efficient for increasing profitability.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.127-133
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• 2014

In order to protect information asset from various malicious code, Honeypot system is implemented. Honeypot system is designed to elicit attacks so that internal system is not attacked or it is designed to collect malicious code information. However, existing honeypot system is designed for the purpose of collecting information, so it is designed to induce inflows of attackers positively by establishing disguised server or disguised client server and by providing disguised contents. In case of establishing disguised server, it should reinstall hardware in a cycle of one year because of frequent disk input and output. In case of establishing disguised client server, it has operating problem such as procuring professional labor force because it has a limit to automize the analysis of acquired information. To solve and supplement operating problem and previous problem of honeypot's hardware, this thesis suggested hybrid honeypot. Suggested hybrid honeypot has honeywall, analyzed server and combined console and it processes by categorizing attacking types into two types. It is designed that disguise (inducement) and false response (emulation) are connected to common switch area to operate high level interaction server, which is type 1 and low level interaction server, which is type 2. This hybrid honeypot operates low level honeypot and high level honeypot. Analysis server converts hacking types into hash value and separates it into correlation analysis algorithm and sends it to honeywall. Integrated monitoring console implements continuous monitoring, so it is expected that not only analyzing information about recent hacking method and attacking tool but also it provides effects of anticipative security response.

• Journal of Navigation and Port Research
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• v.39 no.6
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• pp.507-514
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• 2015

The purpose of this study is to analyze the efficiency of resident companies in port hinterland logistics that are currently operating. The subjects of the efficiency analysis include 13 logistics hinterland resident companies in Incheon Port and Busan Port. Investment amounts, area, and number of employees were selected as input variables, and volume and sales amounts were selected as output variables. As for the efficiency analysis methods, traditional CCR and BCC models were applied. To overcome the limits of these models, a super-efficiency model and a Super-SBM model were also applied. According to the super-efficiency model analysis, the mean was 0.777 and the standard deviation was 0.54, indicating an approximate 33% difference of efficiency among the companies. According to the Super-SBM model analysis, the mean was 0.649 and the standard deviation was 0.489. When considering residuals in the super-efficiency model, the average efficiency score among the companies decreased by approximately 13%. This means that the efficiency score decrease of DMU, where non-radial residuals exist at about 18% on average. Examining the inefficiency of the inputs, the inefficiency of the number of employees turned out to be largest at -45%, compared to 'area' at -33% and 'investment amount' at -33%.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.161-172
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• 2005

This study is to develop Bus Transit Route Analysis and Evaluation Model that can product the quantitative performance measures for Bus Transit Route Network Design. So far, in Korea, there are no so many models that evaluate a variety of other performance measures or service quality that are of concern to both the transit users and operator because of lower-level bus database system and transit route network analysis algorithm's limit. The BTRAEM in this research differ from the previous approach in that the BTRAEM employs a multiple path transit trip assignment model that explicitly considers the transfer and different travel time after boarding. And we develop input-output data structure and quantitative performance measure for the BTRAEM. In the numerical experimental applying BTRAEM to Mandl transit network, We got the meaningful results on performance measure of bus transit route network. In the future, we expect BTRAEM to give a good solution in real transit network.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.360-375
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• 2019

This paper tries to study the ecosystem after constructing the network of the continuing transactions associated with distribution industry with the data of more than 50 thousands firms provided by the Korean enterprise data (KED) for 2015. After applying the clustering method, one of social network analysis tools, we find the firms in the network grouped into 732 clusters occupying about 80% of whole distribution industry sales in KED data. The firms in a cluster have most of their transactions with other firms in the cluster. But the clusters have smaller firm numbers in the cluster and sales portion of the biggest firms in the industry than the case of the manufacturing industry. The Input-output analysis for the biggest distribution firms show that the small and medium size enterprise(SME)s have very high sale dependency on a main firm in some clusters. This fact implies more efficient fair transaction policies within the clusters. And small number of big distribution firms have very high rear production linkage effects on SMEs or on the 10th or 31th group with high portion of SME employment. They should be considered important in the SME growth and employment policies.

• Journal of the Microelectronics and Packaging Society
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• v.26 no.1
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• pp.29-33
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• 2019

With shrinking form factor and improving performance of electronic packages, high input/output (I/O) density is considered as an important factor. Fan out wafer-level packaging (FO-WLP) has been paid great attention as an alternative. However, FO-WLP is vulnerable to warpage during its manufacturing process. Minimizing warpage is essential for controlling production yield, and in turn, package reliability. While many studies investigated the effect of process and design parameters on warpage using finite element analysis, they did not take uncertainty into consideration. As parameters, including material properties, chip positions, have uncertainty from the point of manufacturing view, the uncertainty should be considered to reduce the gap between the results from the field and the finite element analysis. This paper focuses on the effect of uncertainty of Young's modulus of chip on fan-out wafer level packaging warpage using finite element analysis. It is assumed that Young's modulus of each chip follows the normal distribution. Simulation results show that the uncertainty of Young's modulus affects the maximum von Mises stress. As a result, it is necessary to control the uncertainty of Young's modulus of silicon chip since the maximum von Mises stress is a parameter related to the package reliability.