• Journal of Information Technology Services
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• v.14 no.3
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• pp.85-97
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• 2015

The information and communications construction business has the characteristics of an infrastructure industry and responsibility for the construction and maintenance of all ICT infrastructures. With the recent proliferation of the smart convergence of various industries based on ICT infrastructure, the role of the information and communications construction business has been highlighted to accommodate the convergence and implementation environment in construction and medical industries. Therefore, this paper seeks policy measures to establish the new role of the information and communications business under the rapidly developing smart convergence environment and the priorities of policy measures to strengthen the capability of the information and communications business using a quantitative model. The analysis result suggests that the difference in importance of each policy measure should be considered in order to execute effectively the policy of promoting the information and communications construction business. Given the constraint of limited budget, policy priorities include the development of new markets, and establishment of incentive for new technology. This study is significant for its theoretical contribution, being the first quantitative approach to policy priorities for the promotion of information and communications construction business under the smart convertgence environment.

• ETRI Journal
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• v.45 no.2
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• pp.267-276
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• 2023

R&D strategies of companies with low and high technological levels are discussed based on the concept of technology convergence and divergence. However, empirically detecting enterprise technology convergence in the distribution of enterprise technology (total productivity increase) over time and identifying key change factors are challenging. This study used a novel statistical indicator that captures the internal technology distribution change with a single number to clearly measure the technology distribution peak as a change in critical bandwidth for enterprise technology convergence and presented it as evidence of each technology convergence or divergence. Furthermore, this study applied the quantitative technology convergence identification method. Technology convergence appeared from the separation of total corporate productivity distribution of 69 IT companies in Korea in 2019-2020 rather than in 2015-2016. Results indicated that when the total technological level was separated from the technology leading and technology catch-up, IT companies were found to be pursuing R&D strategies for technology catch-up.

• Journal of Digital Convergence
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• v.13 no.6
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• pp.125-132
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• 2015

It is current situation that a number of issues are being raised how the weight is calculated from customer satisfaction survey. This study investigated how the weight of satisfaction for each quantile is different by comparing ordinary least square regression model to quantile regression model and carried out bootstrap verification to find the influence difference of regression coefficient for each quantile. As the analysis result of using R(Quantreg package) that is open software, it appeared that there was the influence size of satisfaction factor along study result and quantile and there was the significant difference statistically regarding regression coefficient for each quantile. So, to use quantile regression model that offers the influence of satisfaction factor for each customer group along satisfaction level would contribute to plan the quantitative convergence policy for customer satisfaction.

• Asian Journal of Innovation and Policy
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• v.5 no.3
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• pp.251-274
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• 2016

Practical methodology for categorizing collaborative disciplines or research in a quantitative manner is presented by developing a Correlation Matrix of Major Disciplines (CMMD) using bibliometric data collected between 2009 and 2014. First, 21 major disciplines in science and engineering are defined based on journal publication frequency. Second, major disciplines using a comparing discipline correlation matrix is created and correlation score using CMMD is calculated based on an analyzer function that is given to the matrix elements. Third, a correlation between the major disciplines and 14 research fields using CMMD is calculated for validation. Collaborative researches are classified into three groups by partially accepting the definition of pluri-discipline from peer review manual, European Science Foundation, inner-discipline, inter-discipline and cross-discipline. Applying simple categorization criteria identifies three groups of collaborative research and also those results can be visualized. Overall, the proposed methodology supports the categorization for each research field.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.4_2
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• pp.645-653
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• 2022

Recently, deep reinforcement learning has been applied to a variety of industries, such as games, robotics, autonomous vehicles, and data cooling systems. An algorithm called reinforcement learning allows for automated asset allocation without the requirement for ongoing monitoring. It is free to choose its own policies. The purpose of this paper is to carry out an empirical analysis of the performance of asset allocation strategies. Among the strategies considered were the conventional Mean- Variance Optimization (MVO) and the Proximal Policy Optimization (PPO). According to the findings, the PPO outperformed both its benchmark index and the MVO. This paper demonstrates how dynamic asset allocation can benefit from the development of a reinforcement learning algorithm.

• Journal of Internet Computing and Services
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• v.15 no.4
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• pp.67-79
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• 2014

One of the core policies recently implemented by the Korean government is the introduction of a creative economy, a concept that integrates ICT with the existing economic structure in order to create new growth factors and jobs. In June of 2013, the National Assembly passed a bill for the institutional practice of a creative economy. The concept of a creative economy is to integrate industries centered on ICT in order to form a new-concept industry paradigm that creates new values and services that exceed past industrial categories. In other words, smart convergence, which integrates ICT with various industries, is evaluated as a core factor for boosting the creative economy. Thus, based on the definition of 'smart convergence', this study predicted the economic effects and sociocultural changes that will ensue due to the future era of smart convergence. Also, this study proposes policies for enhancing the creative economy in various ways. More specifically, in-depth interviews with convergence industry experts were carried out and quantitative analyses were performed employing a Solow Model. Furthermore, as a means to revitalize the creative economy, this study underscores the significance of the preemptive institutionalization of legislations and suggests several policy proposals regarding smart convergence rooted in market supply and the demand chain, smart convergence through selective focus, and smart work. This study is differentiated from previous studies that have only focused in establishing theories in that it offers quantitative research with a consideration of the feasibility of proposed policies. The leading experience of Korea regarding smart convergence can provide important lessons to other countries that hope to promote a creative economy as a means to create new growth factors and jobs.

• Journal of the Korean Operations Research and Management Science Society
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• v.42 no.1
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• pp.53-63
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• 2017

Managing the quantitative measurement of the data control activities in enterprise wide is important to secure management of data governance. However, research on data governance is limited to concept definitions and components, and data governance research on evaluation models is lacking. In this study, we developed a model of quantitative assessment for data governance including the assessment area, evaluation index and evaluation matrix. We also, proposed a method of developing the model of quantitative assessment for data governance. For this purpose, we used previous studies and expert opinion analysis such as the Delphi technique, KJ method in this paper. This study contributes to literature by developing a quantitative evaluation model for data governance at the early stage of the study. This paper can be used for the base line data in objective evidence of performance in the companies and agencies of operating data governance.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.467-476
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• 2022

The Bank of Korea raised the benchmark interest rate by a quarter percentage point to 1.75 percent per year, and analysts predict that South Korea's policy rate will reach 2.00 percent by the end of calendar year 2022. Furthermore, because market volatility has been significantly increased by a variety of factors, including rising rates, inflation, and market volatility, many investors have struggled to meet their financial objectives or deliver returns. Banks and financial institutions are attempting to provide Robo-Advisors to manage client portfolios without human intervention in this situation. In this regard, determining the best hyper-parameter combination is becoming increasingly important. This study compares some activation functions of the Deep Deterministic Policy Gradient(DDPG) and Twin-delayed Deep Deterministic Policy Gradient (TD3) Algorithms to choose a sequence of actions that maximizes long-term reward. The DDPG and TD3 outperformed its benchmark index, according to the results. One reason for this is that we need to understand the action probabilities in order to choose an action and receive a reward, which we then compare to the state value to determine an advantage. As interest in machine learning has grown and research into deep reinforcement learning has become more active, finding an optimal hyper-parameter combination for DDPG and TD3 has become increasingly important.

• Asian Journal of Innovation and Policy
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• v.3 no.2
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• pp.154-171
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• 2014

This article aims to examine the achievement and limitation of adaptation of supply chain management (SCM) to IT human resource development (HRD) in Korea and to derive the implication of the Korean experience to other countries. In late 1990s, the IT New Deal Policy and the quantitative expansion of IT HR were introduced. Since mid-2000s, there has been much innovation in IT products as well as increased demand of highly qualified IT experts. The SCM in IT HRD was introduced in 2004 and continuously developed more. Since the late 2000s, IT convergence expanded to traditional industries and the new IT-based-industries were created in Korea. In this regard, Korea established the Seoul Accord as an international IT engineering education accreditation system in 2008. In response to the paradigm change, in 2011, the Korean government developed TOPCIT, which is a kind of competency test for evaluating IT competency.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.1-7
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• 2015

Many people are interesting software quality. Because of, we depend on software in our life. In terms of, I think, good software is a good quality software. So, when we develop the software, we need trying to improve software quality. In this paper, we analyze software test data. We emphasize that software quality is very important in our life. We use software experimental data, in order to analyze of software quality. On the basis of ISO/IEC 9126-2, we classify the test data and we analyze the difference of error frequency according to functionality, reliability, usability, efficiency, maintainability, portability. We analyze the number of test and used time according software type. We want to search effect variable, going through testing result and measurement convergence, we know the effect variable of functionality and efficiency.