• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.167-179
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• 2024

This study addresses the challenge of objectively evaluating the performance of early-stage startups amidst limited information and uncertainty. Focusing on companies selected by TIPS, a leading private sector-driven startup support policy in Korea, the research develops a new indicator to assess technological efficiency. By analyzing various input and output variables collected from Crunchbase and KIND (Korea Investor's Network for Disclosure System) databases, including technology use metrics, patents, and Crunchbase rankings, the study derives technological efficiency for TIPS-selected startups. A prediction model is then developed utilizing machine learning techniques such as Random Forest and boosting (XGBoost) to classify startups into efficiency percentiles (10th, 30th, and 50th). The results indicate that prediction accuracy improves with higher percentiles based on the technical efficiency index, providing valuable insights for evaluating and predicting startup performance in early markets characterized by information scarcity and uncertainty. Future research directions should focus on assessing growth potential and sustainability using the developed classification and prediction models, aiding investors in making data-driven investment decisions and contributing to the development of the early startup ecosystem.

• The Journal of the Korea Contents Association
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• v.20 no.4
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• pp.14-24
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• 2020

This paper aims to establish an efficient national R&D Application Programming Interface (API) management system for national R&D data-driven management and explore the possibility of using operational data according to the recent global data openness and sharing policy. In accordance with the trend of opening and sharing of national R&D data, we plan to improve management efficiency by analyzing operational data of the national R&D API service. For this purpose, we standardized the parameters for the national R&D APIs that were distributed separately by integrating the individual APIs to build a national R&D API management system. The results of this study revealed that the service call traffic of the national R&D API has shown 554.5% growth in the year as compared to the year 2015 when the measurement started. In addition, this paper also evaluations the possibility of using operational data through data preparation, analysis, and prediction based on service operations management data in the actual operation of national R&D integrated API management system.

• Journal of the Korean Society for information Management
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• v.35 no.4
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• pp.263-284
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• 2018

Academic libraries need to select and purchase essential collections to support students and faculty in education and research. Therefore, libraries reflect patrons' information needs on collection development through patron purchase requests. This study analyzed the pattern and efficiency of patron purchase requests in a longer-term perspective; for over a decade. Patron purchase requests show different tendencies depending on academic characteristics, which enabled libraries to identify the users' information needs in various subjects. Typically users contributed to collection development by expressing information needs in their fields of study through purchase requests. In the meantime, users in certain fields showed interest in other subject areas besides their own to select general books on various topics. Through this study, it became evident that a major portion of library collections were affected by active purchase requests from a small number of users. However those books were proven to be in demand in terms of effectiveness. Patron-driven acquisition is being implemented as an effective collection development policy.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.181-189
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• 2022

The purpose of this study is to investigate the innovation of business model and the effectiveness of the data-driven model. the main concepts and policies related to the data economy are reviewed, and implications are drawn through the analysis of data-based convergence service creation cases. This study identified the existing data-driven business model of the creation of MyData service industry in the financial industry and concept of the data economy. According to the empirical analysis result, this study confirmed that t considering the mobile environment and consumer acceptance of data portability, the ripple effect of the implementation of My Data on the financial industry is expected to be significant.

• The Journal of Korea Robotics Society
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• v.19 no.3
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• pp.293-310
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• 2024

In this paper, we propose an agent model for Language-Driven Zero-Shot Object Navigation (L-ZSON) tasks, which takes in a freeform language description of an unseen target object and navigates to find out the target object in an inexperienced environment. In general, an L-ZSON agent should able to visually ground the target object by understanding the freeform language description of it and recognizing the corresponding visual object in camera images. Moreover, the L-ZSON agent should be also able to build a rich spatial context map over the unknown environment and decide efficient exploration actions based on the map until the target object is present in the field of view. To address these challenging issues, we proposes AML (Agent Model for L-ZSON), a novel L-ZSON agent model to make effective use of AI foundation models such as Large Language Model (LLM) and Vision-Language model (VLM). In order to tackle the visual grounding issue of the target object description, our agent model employs GLEE, a VLM pretrained for locating and identifying arbitrary objects in images and videos in the open world scenario. To meet the exploration policy issue, the proposed agent model leverages the commonsense knowledge of LLM to make sequential navigational decisions. By conducting various quantitative and qualitative experiments with RoboTHOR, the 3D simulation platform and PASTURE, the L-ZSON benchmark dataset, we show the superior performance of the proposed agent model.

• The KIPS Transactions:PartA
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• v.11A no.3
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• pp.199-206
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• 2004

Under the multiprogrammed situation, the performance of multiprocessor system is affected by the process allocation policy of the operating systems. The lowest communication cost can be achieved when the related processes positioned to the adjacent processors. While the effective allocation is quite difficult to the real situation, and the processing of the allocation policy consumes some computation time. The dual-ring CC-NUMA systems exhibit a quite performance difference according to the process a1location policy due to a lot of unbalanced memory transactions on the interconnection networks. In this paper, I propose a load balanced dual-link CC-NUMA system that does not requires the processes allocation policy. By the program-driven simulation results. the proposed system shows no remarkable difference according to the allocation policy while the dual-ring systems shows 10％ performance improvement by the process allocation. In addition, the proposed system outperforms the dual~ring systems about 1.5 times.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4467-4488
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• 2014

The bibliometric analysis is widely used for understanding research domains, trends, and knowledge structures in a particular field. The analysis has majorly been used in the field of information science, and it is currently applied to other academic fields. This paper describes the analysis of academic literatures for classifying research domains and for suggesting empty research areas in the telecommunications policy. The application software is developed for retrieving Thomson Reuters' Web of Knowledge (WoK) data via web services. It also used for conducting text mining analysis from contents and citations of publications. We used three text mining techniques: the Keyword Extraction Algorithm (KEA) analysis, the co-occurrence analysis, and the citation analysis. Also, R software is used for visualizing the term frequencies and the co-occurrence network among publications. We found that policies related to social communication services, the distribution of telecommunications infrastructures, and more practical and data-driven analysis researches are conducted in a recent decade. The citation analysis results presented that the publications are generally received citations, but most of them did not receive high citations in the telecommunications policy. However, although recent publications did not receive high citations, the productivity of papers in terms of citations was increased in recent ten years compared to the researches before 2004. Also, the distribution methods of infrastructures, and the inequity and gap appeared as topics in important references. We proposed the necessity of new research domains since the analysis results implies that the decrease of political approaches for technical problems is an issue in past researches. Also, insufficient researches on policies for new technologies exist in the field of telecommunications. This research is significant in regard to the first bibliometric analysis with abstracts and citation data in telecommunications as well as the development of software which has functions of web services and text mining techniques. Further research will be conducted with Big Data techniques and more text mining techniques.

• Health Policy and Management
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• v.30 no.2
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• pp.253-262
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• 2020

Background: The public health care system of a country is shaped and driven by its historical background as well as social, economic, and cultural structures. This study sheds light on the unique features, strengths, and weaknesses of the health insurance systems of South Korea (Korea) and Peru. Methods: The capacity mapping tool was used to explore the Korean and Peruvian population and geographical structures; health insurance laws, regulations, and policies; payment systems; eligibility and contribution collection; and long-term care insurance. Results: The study found that the Korean government took the lead in integrating multiple insurers into a single-payer system in an effort to reinforce and stabilize its health insurance system in 2000. Peru has been developed mixed model such based on taxes and contributions, to address a gap between different social classes. Peruvian government developed a two-axis system, one for low-income earners, financed by taxes, and another financed by contributions paid by workers and government officials in the formal sector. Peru has introduced many variations to its fee payment and insurer systems, target population, and coverage scope, and maintains its health insurance system accordingly to this day. Conclusion: The current study provides observation of the Health Insurance System in two different countries and helps to understand possible ways to improve the health insurance system in both countries. Based on this study, Peru will be able to see how its system differs from Korea's and benefit from the related policy implications.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.875-886
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• 2016

In this study, we investigate an influence of the China government's software support policy on the revenue of software export. In the analysis in the areas of technology development, manpower development, quality control and marketing reinforcement from 2008 to 2014, it has been found that the amounts of the policy influence and annual revenue of software export increase simultaneously, proving that the China government's support policy has a close relationship with the software export revenue. However, the annual ratio of the software export revenue to the gross software production revenue has decreased over the period, which indicates that the growth of software industry in China has been mainly driven by domestic market.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.5
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• pp.1205-1219
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• 2019

As the ability to use data becomes competitive power in the data-driven economy, the effort to create economic value by using personal data is emphasized as much as to protect personal data. EU's PSD2(the second Payment Service directive) became the initiative of the Open Banking trends all over the world, as it is the Mydata policy which protects the data subject's right by empowering the subject to control over the personal data with the right to data portability and promotes personal data usages and transfer. Korean government is now fast adopting EU's PSD2 in financial sector, but there is growing concerns in personal data abuse and misuse, and data breach. This study analyzes domestic financial Mydata policy in comparison with EU's PSD2 and focus on Personal information life-cycle risks of financial Mydata policy. Some suggestions on how to promote personal information and privacy in domestic financial Mydata Policy will be given.