• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.867-879
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• 2020

As the era of space technology utilization is approaching, the launch of CAS (Compact Advanced Satellite) 500-1/2 satellites is scheduled during 2021 for acquisition of high-resolution images. Accordingly, the increase of image usability and processing efficiency has been emphasized as key design concepts of the CAS 500-1/2 ground station. In this regard, "CAS 500-1/2 Image Acquisition and Utilization Technology Development" project has been carried out to develop core technologies and processing systems for CAS 500-1/2 data collecting, processing, managing and distributing. In this paper, we introduce the results of the above project. We developed an operation system to generate precision images automatically with GCP (Ground Control Point) chip DB (Database) and DEM (Digital Elevation Model) DB over the entire Korean peninsula. We also developed the system to produce ortho-rectified images indexed to 1:5,000 map grids, and hence set a foundation for ARD (Analysis Ready Data)system. In addition, we linked various application software to the operation system and systematically produce mosaic images, DSM (Digital Surface Model)/DTM (Digital Terrain Model), spatial feature thematic map, and change detection thematic map. The major contribution of the developed system and technologies includes that precision images are to be automatically generated using GCP chip DB for the first time in Korea and the various utilization product technologies incorporated into the operation system of a satellite ground station. The developed operation system has been installed on Korea Land Observation Satellite Information Center of the NGII (National Geographic Information Institute). We expect the system to contribute greatly to the center's work and provide a standard for future ground station systems of earth observation satellites.

• The Journal of Korean Society for Radiation Therapy
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• v.26 no.1
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• pp.137-147
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• 2014

Purpose : The purpose of this study is to verify the accuracy of dose delivery according to the patient's breathing cycle in Gated Volumetric Modulated Arc Therapy Materials and Methods : TrueBeam STxTM(Varian Medical System, Palo Alto, CA) was used in this experiment. The Computed tomography(CT) images that were acquired with RANDO Phantom(Alderson Research Laboratories Inc. Stamford. CT, USA), using Computerized treatment planning system(Eclipse 10.0, Varian, USA), were used to create VMAT plans using 10MV FFF with 1500 cGy/fx (case 1, 2, 3) and 220 cGy/fx(case 4, 5, 6) of doserate of 1200 MU/min. The regular respiratory period of 1.5, 2.5, 3.5 and 4.5 sec and the patients respiratory period of 2.2 and 3.5 sec were reproduced with the $QUASAR^{TM}$ Respiratory Motion Phantom(Modus Medical Devices Inc), and it was set up to deliver radiation at the phase mode between the ranges of 30 to 70%. The results were measured at respective respiratory conditions by a 2-Dimensional ion chamber array detector(I'mRT Matrixx, IBA Dosimetry, Germany) and a MultiCube Phantom(IBA Dosimetry, Germany), and the Gamma pass rate(3 mm, 3%) were compared by the IMRT analysis program(OmniPro I'mRT system software Version 1.7b, IBA Dosimetry, Germany) Results : The gamma pass rates of Case 1, 2, 3, 4, 5 and 6 were the results of 100.0, 97.6, 98.1, 96.3, 93.0, 94.8% at a regular respiratory period of 1.5 sec and 98.8, 99.5, 97.5, 99.5, 98.3, 99.6% at 2.5 sec, 99.6, 96.6, 97.5, 99.2, 97.8, 99.1% at 3.5 sec and 99.4, 96.3, 97.2, 99.0, 98.0, 99.3% at 4.5 sec, respectively. When a patient's respiration was reproduced, 97.7, 95.4, 96.2, 98.9, 96.2, 98.4% at average respiratory period of 2.2 sec, and 97.3, 97.5, 96.8, 100.0, 99.3, 99.8% at 3.5 sec, respectively. Conclusion : The experiment showed clinically reliable results of a Gamma pass rate of 95% or more when 2.5 sec or more of a regular breathing period and the patient's breathing were reproduced. While it showed the results of 93.0% and 94.8% at a regular breathing period of 1.5 sec of Case 5 and 6, it could be confirmed that the accurate dose delivery could be possible on the most respiratory conditions because based on the results of 100 patients's respiratory period analysis as no one sustained a respiration of 1.5 sec. But, pretreatment dose verification should be precede because we can't exclude the possibility of error occurrence due to extremely short respiratory period, also a training at the simulation and careful monitoring are necessary for a patient to maintain stable breathing. Consequently, more reliable and accurate treatments can be administered.

• Journal of Global Scholars of Marketing Science
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• v.18 no.4
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• pp.119-155
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• 2008

Customer Relationship Management(CRM) has been a sustainable competitive edge of many companies. CRM analyzes customer data for designing and executing targeted marketing analysing customer behavior in order to make decisions relating to products and services including management information system. It is critical for companies to get and maintain profitable customers. How to manage relationships with customers effectively has become an important issue for both academicians and practitioners in recent years. However, the existing academic literature and the practical applications of customer relationship management(CRM) strategies have been focused on the technical process and organizational structure about the implementation of CRM. These limited focus on CRM lead to the result of numerous reports of failed implementations of various types of CRM projects. Many of these failures are also related to the absence of marketing approach. Identifying successful factors and outcomes focused on marketing concept before introducing a CRM project are a pre-implementation requirements. Many researchers have attempted to find the factors that contribute to the success of CRM. However, these research have some limitations in terms of marketing approach without explaining how the marketing based factors contribute to the CRM success. An understanding of how to manage relationship with crucial customers effectively based marketing approach has become an important topic for both academicians and practitioners. However, the existing papers did not provide a clear antecedent and outcomes factors focused on marketing approach. This paper attempt to validate whether or not such various marketing factors would impact on relational quality and CRM performance in terms of marketing oriented perceptivity. More specifically, marketing oriented factors involving market orientation, customer orientation, customer information orientation, and core customer orientation can influence relationship quality(satisfaction and trust) and CRM outcome(customer retention and customer share). Another major goals of this research are to identify the effect of relationship quality on CRM outcomes consisted of customer retention and share to show the relationship strength between two factors. Based on meta analysis for conventional studies, I can construct the following research model. An empirical study was undertaken to test the hypotheses with data from various companies. Multiple regression analysis and t-test were employed to test the hypotheses. The reliability and validity of our measurements were tested by using Cronbach's alpha coefficient and principal factor analysis respectively, and seven hypotheses were tested through performing correlation test and multiple regression analysis. The first key outcome is a theoretically and empirically sound CRM factors(marketing orientation, customer orientation, customer information orientation, and core customer orientation.) in the perceptive of marketing. The intensification of ${\beta}$coefficient among antecedents factors in terms of marketing was not same. In particular, The effects on customer trust of marketing based CRM antecedents were significantly confirmed excluding core customer orientation. It was notable that the direct effects of core customer orientation on customer trust were not exist. This means that customer trust which is firmly formed by long term tasks will not be directly linked to the core customer orientation. the enduring management concerned with this interactions is probably more important for the successful implementation of CRM. The second key result is that the implementation and operation of successful CRM process in terms of marketing approach have a strong positive association with both relationship quality(customer trust/customer satisfaction) and CRM performance(customer retention and customer possession). The final key fact that relationship quality has a strong positive effect on customer retention and customer share confirms that improvements in customer satisfaction and trust improve accessibility to customers, provide more consistent service and ensure value-for-money within the front office which result in growth of customer retention and customer share. Particularly, customer satisfaction and trust which is main components of relationship quality are found to be positively related to the customer retention and customer share. Interactive managements of these main variables play key roles in connecting the successful antecedent of CRM with final outcome involving customer retention and share. Based on research results, This paper suggest managerial implications concerned with constructions and executions of CRM focusing on the marketing perceptivity. I can conclude in general the CRM can be achieved by the recognition of antecedents and outcomes based on marketing concept. The implementation of marketing concept oriented CRM will be connected with finding out about customers' purchasing habits, opinions and preferences profiling individuals and groups to market more effectively and increase sales changing the way you operate to improve customer service and marketing. Benefiting from CRM is not just a question of investing the right software, but adapt CRM users to the concept of marketing including marketing orientation, customer orientation, and customer information orientation. No one deny that CRM is a process or methodology used to develop stronger relationships being composed of many technological components, but thinking about CRM in primarily technological terms is a big mistake. We can infer from this paper that the more useful way to think and implement about CRM is as a process that will help bring together lots of pieces of marketing concept about customers, marketing effectiveness, and market trends. Finally, a real situation we conducted our research may enable academics and practitioners to understand the antecedents and outcomes in the perceptive of marketing more clearly.

• The Korean Journal of Nuclear Medicine Technology
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• v.20 no.2
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• pp.3-8
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• 2016

Purpose SUV is one of the parameters that assist diagnosis in origin, metastasis and staging of cancer. Specially, it is important to compare SUV before and after chemo or radiation therapy to find out effectiveness of treatment. Storing PET data which has no quantitative change is needed for SUV comparison. However, there is a possibility to loss the data in external hard drive or MINIpacs that are managed by department of nuclear medicine. The aim of this study is to evaluate SUV and metabolic tumor volume (MTV) among reconstructed data (R-D) in workstation, R-D and re-sliced data (S-D) in PACS. Materials and Methods Data of 20 patients (aged $60.5{\pm}8.3y$) underwent $^{18}F-FDG$ PET (Biograph truepoint 40, mCT 40, mCT 64, mMR, Siemens) study were analysed. $SUV_{max}$, $SUV_{peak}$ and MTV were measured in liver, aorta and tumor after sending R-D in workstation, R-D and S-D in PACS to syngo.via software. Results R-D of workstation and PACS showed the same value as mean $SUV_{max}$ in liver, aorta and tumor were $2.95{\pm}0.59$, $2.35{\pm}0.61$, $10.36{\pm}6.15$ and $SUV_{peak}$ were $2.70{\pm}0.51$, $2.07{\pm}0.43$, $7.67{\pm}3.73$(p>0.05) respectively. Mean $SUV_{max}$ of S-D in PACS were decreased by 5.18%, 7.22%, 12.11% and $SUV_{peak}$ 2.61%, 3.63%, 10.07%(p<0.05). Correlation between R-D and S-D were $SUV_{max}$ 0.99, 0.96, 0.99 and $SUV_{peak}$ 0.99, 0.99, 0.99. And 2SD in balnd-altman analysis were $SUV_{max}$ 0.125, 0.290, 1.864 and $SUV_{peak}$ 0.053, 0.103, 0.826. MTV of R-D in workstation and PACS show the same value as $14.21{\pm}12.72cm^3$(p>0.05). MTV in PACS was decreased by 0.12% compared to R-D(p>0.05). Correlation and 2SD between R-D and S-D were 0.99 and 2.243. Conclusion $SUV_{max}$, $SUV_{peak}$, MTV showed the same value in both of R-D in workstation and PACS. However, there was statistically difference in $SUV_{max}$, $SUV_{peak}$ of S-D compare to R-D despite of high correlation. It is possible to analyse reliable pre and post SUV if storing R-D in main hospital PACS system.

• The Journal of Korean Society for Radiation Therapy
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• v.24 no.1
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• pp.1-10
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• 2012

Purpose: To evaluate dose distribution differences when the dose rates are randomly changed in intensity-modulated radiation therapy using a dynamic multileafcollimator. Materials and Methods: Two IMRT treatment plans including small-field and large-field plans were made using a commercial treatment planning system (Eclipse, Varian, Palo Alto, CA). Each plan had three sub-plans according to various dose rates of 100, 400, and 600 MU/min. A chamber array (2D-Array Seven729, PTW-Freiburg) was positioned between solid water phantom slabs to give measurement depth of 5 cm and backscattering depth of 5 cm. Beam deliveries were performed on the array detector using a 6 MV beam of a linear accelerator (Clinac 21EX, Varian, Palo Alto, CA) equipped with 120-leaf MLC (Millenium 120, Varian). At first, the beam was delivered with same dose rates as planned to obtain reference values. After the standard measurements, dose rates were then changed as follows: 1) for plans with 100 MU/min, dose rate was varied to 200, 300, 400, 500 and 600 MU/min, 2) for plans with 400 MU/min, dose rate was varied to 100, 200, 300, 500 and 600 MU/min, 3) for plans with 600 MU/min, dose rate was varied to 100, 200, 300, 400 and 500 MU/min. Finally, using an analysis software (Verisoft 3.1, PTW-Freiburg), the dose difference and distribution between the reference and dose-rate-varied measurements was evaluated. Results: For the small field plan, the local dose differences were -0.8, -1.1, -1.3, -1.5, and -1.6% for the dose rate of 200, 300, 400, 500, 600 MU/min, respectively (for 100 MU/min reference), +0.9, +0.3, +0.1, -0.2, and -0.2% for the dose rate of 100, 200, 300, 500, 600 MU/min, respectively (for 400 MU/min reference) and +1.4, +0.8, +0.5, +0.3, and +0.2% for the dose rate of 100, 200, 300, 400, 500 MU/min, respectively (for 600 MU/min reference). On the other hand, for the large field plan, the pass-rate differences were -1.3, -1.6, -1.8, -2.0, and -2.4% for the dose rate of 200, 300, 400, 500, 600 MU/min, respectively (for 100 MU/min reference), +2.0, +1.8, +0.5, -1.2, and -1.6% for the dose rate of 100, 200, 300, 500, 600 MU/min, respectively (for 400 MU/min reference) and +1.5, +1.9, +1.7, +1.9, and +1.2% for the dose rate of 100, 200, 300, 400, 500 MU/min, respectively (for 600 MU/min reference). In short, the dose difference of dose-rate variation was measured to the -2.4~+2.0%. Conclusion: Using the Varian linear accelerator with 120 MLC, the IMRT dose distribution is differed a little <(${\pm}3%$) even though the dose-rate is changed.

• Progress in Medical Physics
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• v.27 no.2
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• pp.64-71
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• 2016

We develop a manufacture procedure for the production of a patient specific customized bolus (PSCB) using a 3D printer (3DP). The dosimetric accuracy of the 3D-PSCB is evaluated for electron beam therapy. In order to cover the required planning target volume (PTV), we select the proper electron beam energy and the field size through initial dose calculation using a treatment planning system. The PSCB is delineated based on the initial dose distribution. The dose calculation is repeated after applying the PSCB. We iteratively fine-tune the PSCB shape until the plan quality is sufficient to meet the required clinical criteria. Then the contour data of the PSCB is transferred to an in-house conversion software through the DICOMRT protocol. This contour data is converted into the 3DP data format, STereoLithography data format and then printed using a 3DP. Two virtual patients, having concave and convex shapes, were generated with a virtual PTV and an organ at risk (OAR). Then, two corresponding electron treatment plans with and without a PSCB were generated to evaluate the dosimetric effect of the PSCB. The dosimetric characteristics and dose volume histograms for the PTV and OAR are compared in both plans. Film dosimetry is performed to verify the dosimetric accuracy of the 3D-PSCB. The calculated planar dose distribution is compared to that measured using film dosimetry taken from the beam central axis. We compare the percent depth dose curve and gamma analysis (the dose difference is 3%, and the distance to agreement is 3 mm) results. No significant difference in the PTV dose is observed in the plan with the PSCB compared to that without the PSCB. The maximum, minimum, and mean doses of the OAR in the plan with the PSCB were significantly reduced by 9.7%, 36.6%, and 28.3%, respectively, compared to those in the plan without the PSCB. By applying the PSCB, the OAR volumes receiving 90% and 80% of the prescribed dose were reduced from $14.40cm^3$ to $0.1cm^3$ and from $42.6cm^3$ to $3.7cm^3$, respectively, in comparison to that without using the PSCB. The gamma pass rates of the concave and convex plans were 95% and 98%, respectively. A new procedure of the fabrication of a PSCB is developed using a 3DP. We confirm the usefulness and dosimetric accuracy of the 3D-PSCB for the clinical use. Thus, rapidly advancing 3DP technology is able to ease and expand clinical implementation of the PSCB.

• Investigative Magnetic Resonance Imaging
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• v.12 no.1
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• pp.8-19
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• 2008

Purpose : To investigate the 3-bond and spatial connectivity of human brain metabolites by scalar coupling and dipolar nuclear Overhauser effect/enhancement (NOE) interaction through 2D- correlation spectroscopy (COSY) and 2D- NOE spectroscopy (NOESY) techniques. Materials and Methods : All 2D experiments were performed on Bruker Avance 500 (11.8 T) with the zshield gradient triple resonance cryoprobe at 298 K. Human brain metabolites were prepared with 10% $D_2O$. Two-dimensional spectra with 2048 data points contains 320 free induction decay (FID) averaging. Repetition delay was 2 sec. The Top Spin 2.0 software was used for post-processing. Total 7 metabolites such as N-acetyl aspartate (NAA), creatine (Cr), choline (Cho), lutamine (Gln), glutamate (Glu), myo-inositol (Ins), and lactate (Lac) were included for major target metabolites. Results : Symmetrical 2D-COSY and 2D-NOESY pectra were successfully acquired: COSY cross peaks were observed in the only 1.0-4.5 ppm, however, NOESY cross peaks were observed in the 1.0-4.5 ppm and 7.9 ppm. From the result of the 2-D COSY data, cross peaks between the methyl protons ($CH_3$(3)) at 1.33 ppm and methine proton (CH(2)) at 4.11 ppm were observed in Lac. Cross peaks between the methylene protons (CH2(3,$H{\alpha}$)) at 2.50ppm and methylene protons ($CH_2$,(3,$H_B$)) at 2.70 ppm were observed in NAA. Cross peaks between the methine proton (CH(5)) at 3.27 ppm and the methine proton (CH(4,6)) at 3.59 ppm, between the methine proton (CH(1,3)) at 3.53 ppm and methine proton (CH(4,6)) at 3.59 ppm, and between the methine proton (CH(1,3)) at 3.53 ppm and methine proton (CH(2)) at 4.05 ppm were observed in Ins. From the result of 2-D NOESY data, cross peaks between the NH proton at 8.00 ppm and methyl protons ($CH_3$) were observed in NAA. Cross peaks between the methyl protons ($CH_3$(3)) at 1.33 ppm and methine proton (CH(2)) at 4.11 ppm were observed in Lac. Cross peaks between the methyl protons (CH3) at 3.03 ppm and methylene protons (CH2) at 3.93 ppm were observed in Cr. Cross peaks between the methylene protons ($CH_2$(3)) at 2.11 ppm and methylene protons ($CH_2$(4)) at 2.35 ppm, and between the methylene protons($CH_2$ (3)) at 2.11 ppm and methine proton (CH(2)) at 3.76 ppm were observed in Glu. Cross peaks between the methylene protons (CH2 (3)) at 2.14 ppm and methine proton (CH(2)) at 3.79 ppm were observed in Gln. Cross peaks between the methine proton (CH(5)) at 3.27 ppm and the methine proton (CH(4,6)) at 3.59 ppm, and between the methine proton (CH(1,3)) at 3.53 ppm and methine proton (CH(2)) at 4.05 ppm were observed in Ins. Conclusion : The present study demonstrated that in vitro 2D-COSY and NOESY represented the 3-bond and spatial connectivity of human brain metabolites by scalar coupling and dipolar NOE interaction. This study could aid in better understanding the interactions between human brain metabolites in vivo 2DCOSY study.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.25-44
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• 2013

Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.51-69
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• 2020

Now, it is a stylized fact that a small number of technology firms such as Apple, Alphabet, Microsoft, Amazon, Facebook and a few others have become larger and dominant players in an industry. Coupled with the rise of these leading firms, we have also observed that a large number of young firms have become an acquisition target in their early IPO stages. This indeed results in a sharp decline in the number of new entries in public exchanges although a series of policy reforms have been promulgated to foster competition through an increase in new entries. Given the observed industry trend in recent decades, a number of studies have reported increased concentration in most developed countries. However, it is less understood as to what caused an increase in industry concentration. In this paper, we uncover the mechanisms by which industries have become concentrated over the last decades by tracing the changes in industry concentration associated with a firm's status change in its early IPO stages. To this end, we put emphasis on the case in which firms are acquired shortly after they went public. Especially, with the transition to digital-based economies, it is imperative for incumbent firms to adapt and keep pace with new ICT and related intelligent systems. For instance, after the acquisition of a young firm equipped with AI-based solutions, an incumbent firm may better respond to a change in customer taste and preference by integrating acquired AI solutions and analytics skills into multiple business processes. Accordingly, it is not unusual for young ICT firms become an attractive acquisition target. To examine the role of M&As involved with young firms in reshaping the level of industry concentration, we identify a firm's status in early post-IPO stages over the sample periods spanning from 1990 to 2016 as follows: i) being delisted, ii) being standalone firms and iii) being acquired. According to our analysis, firms that have conducted IPO since 2000s have been acquired by incumbent firms at a relatively quicker time than those that did IPO in previous generations. We also show a greater acquisition rate for IPO firms in the ICT sector compared with their counterparts in other sectors. Our results based on multinomial logit models suggest that a large number of IPO firms have been acquired in their early post-IPO lives despite their financial soundness. Specifically, we show that IPO firms are likely to be acquired rather than be delisted due to financial distress in early IPO stages when they are more profitable, more mature or less leveraged. For those IPO firms with venture capital backup have also become an acquisition target more frequently. As a larger number of firms are acquired shortly after their IPO, our results show increased concentration. While providing limited evidence on the impact of large incumbent firms in explaining the change in industry concentration, our results show that the large firms' effect on industry concentration are pronounced in the ICT sector. This result possibly captures the current trend that a few tech giants such as Alphabet, Apple and Facebook continue to increase their market share. In addition, compared with the acquisitions of non-ICT firms, the concentration impact of IPO firms in early stages becomes larger when ICT firms are acquired as a target. Our study makes new contributions. To our best knowledge, this is one of a few studies that link a firm's post-IPO status to associated changes in industry concentration. Although some studies have addressed concentration issues, their primary focus was on market power or proprietary software. Contrast to earlier studies, we are able to uncover the mechanism by which industries have become concentrated by placing emphasis on M&As involving young IPO firms. Interestingly, the concentration impact of IPO firm acquisitions are magnified when a large incumbent firms are involved as an acquirer. This leads us to infer the underlying reasons as to why industries have become more concentrated with a favor of large firms in recent decades. Overall, our study sheds new light on the literature by providing a plausible explanation as to why industries have become concentrated.

• Korean Journal of Poultry Science
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• v.46 no.2
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• pp.65-75
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• 2019

A number of Korean native chicken(KNC) populations were registered in FAO (Food and Agriculture Organization) DAD-IS (Domestic Animal Diversity Information Systems, http://www.fao.org/dad-is). But there is a lack of scientific basis to prove that they are unique population of Korea. For this reason, this study was conducted to prove KNC's uniqueness using 25 Microsatellite markers. A total of 548 chickens from 11 KNC populations (KNG, KNB, KNR, KNW, KNY, KNO, HIC, HYD, HBC, JJC, LTC) and 7 introduced populations (ARA: Araucana, RRC and RRD: Rhode Island Red C and D, LGF and LGK: White Leghorn F and K, COS and COH: Cornish brown and Cornish black) were used. Allele size per locus was decided using GeneMapper Software (v 5.0). A total of 195 alleles were observed and the range was 3 to 14 per locus. The MNA, $H_{\exp}$, $H_{obs}$, PIC value within population were the highest in KNY (4.60, 0.627, 0.648, 0.563 respectively) and the lowest in HYD (1.84, 0.297, 0.286, 0.236 respectively). The results of genetic uniformity analysis suggested 15 cluster (${\Delta}K=66.22$). Excluding JJC, the others were grouped in certain cluster with high genetic uniformity. JJC was not grouped in certain cluster but grouped in cluster 2 (44.3%), cluster 3 (17.7%) and cluster8 (19.1%). As a results of this study, we can secure a scientific basis about KNC's uniqueness and these results can be use to basic data for the genetic evaluation and management of KNC breeds.