• Journal of Venture Innovation
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• v.4 no.1
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• pp.51-65
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• 2021

The HR policy in the public sector was closed and operated mainly on written tests, but in 2006, a new evaluation, promotion and education system based on competence was introduced in the promotion and selection system of civil servants. In particular, the seniority-oriented promotion system was evaluated based on competence by operating an Assessment Center related to promotion. Competency evaluation is known to be the most reliable and valid evaluation method among the evaluation methods used to date and is also known to have high predictive feasibility for performance. In 2001, 19 government standard competency models were designed. In 2006, the competency assessment was implemented with the implementation of the high-ranking civil service team system. In the public sector, the purpose of the competency evaluation is mainly to select third-grade civil servants, assign fourth-grade civil servants, and promotion fifth-grade civil servants. However, competency assessments in the public sector differ in terms of competency assessment objectives, assessment processes and competency assessment programmes compared to those in the private sector. For the purposes of competency assessment, the public sector is for the promotion of candidates, and the private sector focuses on career development and fostering. Therefore, it is not continuously developing capabilities than the private sector and is not used to enhance performance in performing its duties. In relation to evaluation items, the public sector generally operates a system that passes capacity assessment at 2.5 out of 5 for 6 competencies, lacks feedback on what competencies are lacking, and the private sector uses each individual's competency score. Regarding the selection and operation of evaluators, the public sector focuses on fairness in evaluation, and the private sector focuses on usability, which is inconsistent with the aspect of developing capabilities and utilizing human resources in the right place. Therefore, the public sector should also improve measures to identify outstanding people and motivate them through capacity evaluation and change the operation of the capacity evaluation system so that they can grow into better managers through accurate reports and individual feedback

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.7-7
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• 2023

Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.129-141
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• 2023

Crop models have been used to predict yield under diverse environmental and cultivation conditions, which can be used to support decisions on the management of forage crop. Cultivar parameters are one of required inputs to crop models in order to represent genetic properties for a given forage cultivar. The objectives of this study were to compare calibration and ensemble approaches in order to minimize the uncertainty of crop yield estimates using the SIMPLE crop model. Cultivar parameters were calibrated using Log-likelihood (LL) and Generic Composite Similarity Measure (GCSM) as an objective function for Metropolis-Hastings (MH) algorithm. In total, 20 sets of cultivar parameters were generated for each method. Two types of ensemble approach. First type of ensemble approach was the average of model outputs (E_em), using individual parameters. The second ensemble approach was model output (E_pm) of cultivar parameter obtained by averaging given 20 sets of parameters. Comparison was done for each cultivar and for each error calculation methods. 'Jowoo' and 'Yeongwoo', which are forage rice cultivars used in Korea, were subject to the parameter calibration. Yield data were obtained from experiment fields at Suwon, Jeonju, Naju and I ksan. Data for 2013, 2014 and 2016 were used for parameter calibration. For validation, yield data reported from 2016 to 2018 at Suwon was used. Initial calibration indicated that genetic coefficients obtained by LL were distributed in a narrower range than coefficients obtained by GCSM. A two-sample t-test was performed to compare between different methods of ensemble approaches and no significant difference was found between them. Uncertainty of GCSM can be neutralized by adjusting the acceptance probability. The other ensemble method (E_pm) indicates that the uncertainty can be reduced with less computation using ensemble approach.

• Clean Technology
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• v.30 no.1
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• pp.37-46
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• 2024

Environmental problems caused by plastic waste have been continuously growing around the world, and plastic waste is increasing even faster after COVID-19. In particular, PP and PE account for more than half of all plastic production, and the amount of waste from these two materials is at a serious level. As a result, researchers are searching for an alternative method to plastic recycling, and plastic pyrolysis is one such alternative. In this paper, a numerical study was conducted on the pyrolysis behavior of non-condensable gas to predict the chemical reaction behavior of the pyrolysis gas. Based on gas products estimated from preceding literature, the behavior of non-condensable gas was analyzed according to temperature and residence time. Numerical analysis showed that as the temperature and residence time increased, the production of H₂ and heavy hydrocarbons increased through the conversion of the non-condensable gas, and at the same time, the CH₄ and C₆H₆ species decreased by participating in the reaction. In addition, analysis of the production rate showed that the decomposition reaction of C₂H₄ was the dominant reaction for H₂ generation. Also, it was found that more H₂ was produced by PE with higher C₂H₄ contents. As a future work, an experiment is needed to confirm how to increase the conversion rate of H₂ and carbon in plastics through the various operating conditions derived from this study's numerical analysis results.

• Journal of Venture Innovation
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• v.7 no.1
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• pp.1-15
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• 2024

This study aims to elucidate the characteristics of big tech platform companies' sports content business in an environment of rapid digital transformation. Specifically, this study examines the market structure of big tech platform companies with a focus on Amazon, revealing the role of sports content within this structure through an analysis of Amazon's sports marketing business and provides an outlook on the sports content business of big tech platform companies. Based on two-sided market platform business models, big tech platform companies incorporate sports content as a strategy to enhance the value of their platforms. Therefore, sports content is used as a tool to enhance the value of their platforms and to consolidate their monopoly position by maximizing profits by increasing the synergy of platform ecosystems such as infrastructure. Amazon acquires popular live sports broadcasting rights on a continental or national basis and supplies them to its platforms, which not only increases the number of new customers and purchasing effects, but also provides IT solution services to sports organizations and teams while planning and supplying various promotional contents, thus creates synergy across Amazon's platforms including its advertising business. Amazon also expands its business opportunities and increases its overall value by supplying live sports contents to Amazon Prime Video and Amazon Prime, providing technical services to various stakeholders through Amazon Web Services, and offering Amazon Marketing Cloud services for analyzing and predicting advertisers' advertising and marketing performance. This gives rise to a new paradigm in the sports marketing business in the digital era, stemming from the difference in market structure between big tech companies based on two-sided market platforms and legacy global companies based on one-sided markets. The core of this new model is a business through the development of various contents based on live sports streaming rights, and sports content marketing will become a major field of sports marketing along with traditional broadcasting rights and sponsorship. Big tech platform global companies such as Amazon, Apple, and Google have the potential to become new global sports marketing companies, and the current sports marketing and advertising companies, as well as teams and leagues, are facing both crises and opportunities.

• Journal of Distribution Research
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• v.17 no.4
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• pp.55-80
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• 2012

I. Introduction Developing the relationships between companies is very important issue to ensure a competitive advantage in today's business environment (Bleeke & Ernst 1991; Mohr & Spekman 1994; Powell 1990). Partnerships between companies are based on having same goals, pursuing mutual understanding, and having a professional level of interdependence. By having such a partnerships and cooperative efforts between companies, they will achieve efficiency and effectiveness of their business (Mohr and Spekman, 1994). However, it is difficult to expect these ideal results only in the B2B corporate transaction. According to agency theory which is the well-accepted theory in various fields of business strategy, organization, and marketing, the two independent companies have fundamentally different corporate purposes. Also there is a higher chance of developing opportunism and conflict due to natures of human(organization), such as self-interest, bounded rationality, risk aversion, and environment factor as imbalance of information (Eisenhardt 1989). That is, especially partnerships between principal(or buyer) and agent(or supplier) of companies within supply chain, the business contract itself will not provide competitive advantage. But managing partnership between companies is the key to success. Therefore, managing partnership between manufacturer and supplier, and finding causes of conflict are essential to improve B2B performance. In conclusion, based on prior researches and Agency theory, this study will clarify how business hazards cause conflicts on supply chain and then identify how developed conflicts have been managed by two control mechanisms. II. Research model III. Method In order to validate our research model, this study gathered questionnaires from small and medium sized enterprises(SMEs). In Korea, SMEs mean the firms whose employee is under 300 and capital is under 8 billion won(about 7.2 million dollar). We asked the manufacturer's perception about the relationship with the biggest supplier, and our key informants are denied to a person responsible for buying(ex)CEO, executives, managers of purchasing department, and so on). In detail, we contact by telephone to our initial sample(about 1,200 firms) and introduce our research motivation and send our questionnaires by e-mail, mail, and direct survey. Finally we received 361 data and eliminate 32 inappropriate questionnaires. We use 329 manufactures' data on analysis. The purpose of this study is to identify the anticipant role of business hazard (environmental dynamism, asset specificity) and investigate the moderating effect of control mechanism(formal control, social control) on conflict-performance relationship. To find out moderating effect of control methods, we need to compare the regression weight between low versus. high group(about level of exercised control methods). Therefore we choose the structural equation modeling method that is proper to do multi-group analysis. The data analysis is performed by AMOS 17.0 software, and model fits are good statically (CMIN/DF=1.982, p<.000, CFI=.936, IFI=.937, RMSEA=.056). IV. Result V. Discussion Results show that the higher environmental dynamism and asset specificity(on particular supplier) buyer(manufacturer) has, the more B2B conflict exists. And this conflict affect relationship quality and financial outcomes negatively. In addition, social control and formal control could weaken the negative effect of conflict on relationship quality significantly. However, unlikely to assure conflict resolution effect of control mechanisms on relationship quality, financial outcomes are changed by neither social control nor formal control. We could explain this results with the characteristics of our sample, SMEs(Small and Medium sized Enterprises). Financial outcomes of these SMEs(manufacturer or principal) are affected by their customer(usually major company) more easily than their supplier(or agent). And, in recent few years, most of companies have suffered from financial problems because of global economic recession. It means that it is hard to evaluate the contribution of supplier(agent). Therefore we also support the suggestion of Gladstein(1984), Poppo & Zenger(2002) that relational performance variable can capture the focal outcomes of relationship(exchange) better than financial performance variable. This study has some implications that it tests the sources of conflict and investigates the effect of resolution methods of B2B conflict empirically. And, especially, it finds out the significant moderating effect of formal control which past B2B management studies have ignored in Korea.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.1-19
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• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.

• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.10
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• pp.1346-1355
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• 2012

This study was carried out to investigate the characteristics of black jujube and Zizyphus jujube extracts during lactic acid fermentation. Both extracts were fermented using Lactobacillus fermentum YL-3. As a result, viable cell number rapidly increased until 24 hours, after which it gradually decreased. Before lactic acid fermentation, the $IC_{50}$ of black jujube, which was 0.014 mg/mL, was lower than that of Zizyphus jujube. Further, black jujube showed stronger antioxidant activity (374.21 mg AA eq/g) than Zizyphus jujube. Contents of total polyphenolics in both extracts were 15.46 mg/g and 13.61 mg/g, respectively, whereas contents of total flavonoids were 374.21 ${\mu}g/g$ and 64.25 ${\mu}g/g$. After lactic acid fermentation, there was no significant increase in DPPH or ABTS free radical scavenging activity. Total polyphenolic content of Zizyphus jujube decreased to 12.39 mg/g upon fermentation, whereas flavonoid content significantly increased to 291.58 ${\mu}g/g$. Further, polyphenolic and flavonoid contents of black jujube increased from 15.46 mg/g to 17.46 mg/g and from 374.21 ${\mu}g/g$ to 1,135.29 ${\mu}g/g$, respectively. These results demonstrate that 9-Times Steamed and Dried increased functional components. Especially, lactic acid fermented black jujube showed remarkably high antioxidant activity. These results confirm the potential use of lactic acid fermented black jujube as a valuable resource for the development of functional foods.

• Korean Journal of Soil Science and Fertilizer
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• v.40 no.5
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• pp.383-391
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• 2007

This study was conducted for an assessment through the estimation of soil loss by each catchment classified by soil catena. Ten catchments, which are Geumgang21, Namgang03, Dongjincheon, Gapyongcheon01, Gyongancheon02, Geumgang16, Byongsungcheon01, Daesincheon, Bukcheon02, Youngsangang08, were selected from the hydrologic unit map and the detailed soil digital map (1:25,000) for this study. The catchments like Geumgang21, Namgang03, Dongjincheon, Gapyongcheon01 and Gyongancheon02 were mainly composed with soils originated from gneiss. The catchments like Geumgang16, Byongsungcheon01, Daesincheon, Bukcheon02 and Youngsangang08 were mainly composed with soils originated from granites. The grades, which are divided into seven grades with A(very tolerable), B(tolerable), C(moderate), D(low), E(high), F(severe), G(very severe), of soil erosion estimated by USLE in catchments were distributed in most A and B because of paddy land and forestry. In detailed, the soil erosion grade of catchments mainly distributing soils originated from gneiss showed more the distribution of B and C than it of catchments mainly distributing soils originated from granites. The reason of results would be derived from topographic characteristics of soils originated from gneiss located at mountainous. The soil loss according to soil catena linked with Songsan and Jigok series, which are soils originated from gneiss was calculated with $7.66ton\;ha^{-1}\;yr^{-1}$. The soil loss of Geumgang16, Byongsungcheon01, Daesincheon, Bukcheon02 which have the soil catena linked with Samgak and Sangju soil series originated from granite, was calculated with $5.55ton\;ha^{-1}\;yr^{-1}$. The soil loss of Youngsangang08 which have the soil catena linked with Songjung and Baeksan soil series originated from granite was calculated with $9.6ton\;ha^{-1}\;yr^{-1}$, but the conclusion on soil loss in this kind of soil catena would be drawn from the analysis of more catchments. In conclusion, the results of this study inform that the classification of soil catena by catchments and estimation of soil loss according to soil catena would be effective for analysis on the grade of non-point pollution by soil erosion in a catchment.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.175-196
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• 2022

Information and communication and home appliance industries, which were one of South Korea's main industries, are gradually losing their export share as their export competitiveness is weakening. This study objectively analyzed export competitiveness and suggested export-promising countries in order to help South Korea's information communication and home appliance industries improve exports. In this study, network properties, centrality, and structural hole analysis were performed during network analysis to evaluate export competitiveness. In order to select promising export countries, we proposed a new variable that can take into account the characteristics of an already established International Trade Network (ITN), that is, the Global Value Chain (GVC), in addition to the existing economic factors. The conditional log-odds for individual links derived from the Exponential Random Graph Model (ERGM) in the analysis of the cross-border trade network were assumed as a proxy variable that can indicate the export potential. In consideration of the possibility of ERGM linkage, a parametric approach and a non-parametric approach were used to recommend export-promising countries, respectively. In the parametric method, a regression analysis model was developed to predict the export value of the information and communication and home appliance industries in South Korea by additionally considering the link-specific characteristics of the network derived from the ERGM to the existing economic factors. Also, in the non-parametric approach, an abnormality detection algorithm based on the clustering method was used, and a promising export country was proposed as a method of finding outliers that deviate from two peers. According to the research results, the structural characteristic of the export network of the industry was a network with high transferability. Also, according to the centrality analysis result, South Korea's influence on exports was weak compared to its size, and the structural hole analysis result showed that export efficiency was weak. According to the model for recommending promising exporting countries proposed by this study, in parametric analysis, Iran, Ireland, North Macedonia, Angola, and Pakistan were promising exporting countries, and in nonparametric analysis, Qatar, Luxembourg, Ireland, North Macedonia and Pakistan were analyzed as promising exporting countries. There were differences in some countries in the two models. The results of this study revealed that the export competitiveness of South Korea's information and communication and home appliance industries in GVC was not high compared to the size of exports, and thus showed that exports could be further reduced. In addition, this study is meaningful in that it proposed a method to find promising export countries by considering GVC networks with other countries as a way to increase export competitiveness. This study showed that, from a policy point of view, the international trade network of the information communication and home appliance industries has an important mutual relationship, and although transferability is high, it may not be easily expanded to a three-party relationship. In addition, it was confirmed that South Korea's export competitiveness or status was lower than the export size ranking. This paper suggested that in order to improve the low out-degree centrality, it is necessary to increase exports to Italy or Poland, which had significantly higher in-degrees. In addition, we argued that in order to improve the centrality of out-closeness, it is necessary to increase exports to countries with particularly high in-closeness. In particular, it was analyzed that Morocco, UAE, Argentina, Russia, and Canada should pay attention as export countries. This study also provided practical implications for companies expecting to expand exports. The results of this study argue that companies expecting export expansion need to pay attention to countries with a relatively high potential for export expansion compared to the existing export volume by country. In particular, for companies that export daily necessities, countries that should pay attention to the population are presented, and for companies that export high-end or durable products, countries with high GDP, or purchasing power, relatively low exports are presented. Since the process and results of this study can be easily extended and applied to other industries, it is also expected to develop services that utilize the results of this study in the public sector.