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The Effectiveness of Fiscal Policies for R&D Investment (R&D 투자 촉진을 위한 재정지원정책의 효과분석)

  • Song, Jong-Guk;Kim, Hyuk-Joon
    • Journal of Technology Innovation
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    • v.17 no.1
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    • pp.1-48
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    • 2009
  • Recently we have found some symptoms that R&D fiscal incentives might not work well what it has intended through the analysis of current statistics of firm's R&D data. Firstly, we found that the growth rate of R&D investment in private sector during the recent decade has been slowdown. The average of growth rate (real value) of R&D investment is 7.1% from 1998 to 2005, while it was 13.9% from 1980 to 1997. Secondly, the relative share of R&D investment of SME has been decreased to 21%('05) from 29%('01), even though the tax credit for SME has been more beneficial than large size firm, Thirdly, The R&D expenditure of large size firms (besides 3 leading firms) has not been increased since late of 1990s. We need to find some evidence whether fiscal incentives are effective in increasing firm's R&D investment. To analyse econometric model we use firm level unbalanced panel data for 4 years (from 2002 to 2005) derived from MOST database compiled from the annual survey, "Report on the Survey of Research and Development in Science and Technology". Also we use fixed effect model (Hausman test results accept fixed effect model with 1% of significant level) and estimate the model for all firms, large firms and SME respectively. We have following results from the analysis of econometric model. For large firm: i ) R&D investment responds elastically (1.20) to sales volume. ii) government R&D subsidy induces R&D investment (0.03) not so effectively. iii) Tax price elasticity is almost unity (-0.99). iv) For large firm tax incentive is more effective than R&D subsidy For SME: i ) Sales volume increase R&D investment of SME (0.043) not so effectively. ii ) government R&D subsidy is crowding out R&D investment of SME not seriously (-0.0079) iii) Tax price elasticity is very inelastic (-0.054) To compare with other studies, Koga(2003) has a similar result of tax price elasticity for Japanese firm (-1.0036), Hall((l992) has a unit tax price elasticity, Bloom et al. (2002) has 0.3540.124 in the short run. From the results of our analysis we recommend that government R&D subsidy has to focus on such an areas like basic research and public sector (defense, energy, health etc.) not overlapped private R&D sector. For SME government has to focus on establishing R&D infrastructure. To promote tax incentive policy, we need to strengthen the tax incentive scheme for large size firm's R&D investment. We recommend tax credit for large size film be extended to total volume of R&D investment.

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Research on ITB Contract Terms Classification Model for Risk Management in EPC Projects: Deep Learning-Based PLM Ensemble Techniques (EPC 프로젝트의 위험 관리를 위한 ITB 문서 조항 분류 모델 연구: 딥러닝 기반 PLM 앙상블 기법 활용)

  • Hyunsang Lee;Wonseok Lee;Bogeun Jo;Heejun Lee;Sangjin Oh;Sangwoo You;Maru Nam;Hyunsik Lee
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.11
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    • pp.471-480
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    • 2023
  • The Korean construction order volume in South Korea grew significantly from 91.3 trillion won in public orders in 2013 to a total of 212 trillion won in 2021, particularly in the private sector. As the size of the domestic and overseas markets grew, the scale and complexity of EPC (Engineering, Procurement, Construction) projects increased, and risk management of project management and ITB (Invitation to Bid) documents became a critical issue. The time granted to actual construction companies in the bidding process following the EPC project award is not only limited, but also extremely challenging to review all the risk terms in the ITB document due to manpower and cost issues. Previous research attempted to categorize the risk terms in EPC contract documents and detect them based on AI, but there were limitations to practical use due to problems related to data, such as the limit of labeled data utilization and class imbalance. Therefore, this study aims to develop an AI model that can categorize the contract terms based on the FIDIC Yellow 2017(Federation Internationale Des Ingenieurs-Conseils Contract terms) standard in detail, rather than defining and classifying risk terms like previous research. A multi-text classification function is necessary because the contract terms that need to be reviewed in detail may vary depending on the scale and type of the project. To enhance the performance of the multi-text classification model, we developed the ELECTRA PLM (Pre-trained Language Model) capable of efficiently learning the context of text data from the pre-training stage, and conducted a four-step experiment to validate the performance of the model. As a result, the ensemble version of the self-developed ITB-ELECTRA model and Legal-BERT achieved the best performance with a weighted average F1-Score of 76% in the classification of 57 contract terms.

Influencing Factors Analysis for the Number of Participants in Public Contracts Using Big Data (빅데이터를 활용한 공공계약의 입찰참가자수 영향요인 분석)

  • Choi, Tae-Hong;Lee, Kyung-Hee;Cho, Wan-Sup
    • The Journal of Bigdata
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    • v.3 no.2
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    • pp.87-99
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    • 2018
  • This study analyze the factors affecting the number of bidders in public contracts by collecting contract data such as purchase of goods, service and facility construction through KONEPS among various forms of public contracts. The reason why the number of bidders is important in public contracts is that it can be a minimum criterion for judging whether to enter into a rational contract through fair competition and is closely related to the budget reduction of the ordering organization or the profitability of the bidders. The purpose of this study is to analyze the factors that determine the participation of bidders in public contracts and to present the problems and policy implications of bidders' participation in public contracts. This research distinguishes the existing sampling based research by analyzing and analyzing many contracts such as purchasing, service and facility construction of 4.35 million items in which 50,000 public institutions have been placed as national markets and 300,000 individual companies and corporations participated. As a research model, the number of announcement days, budget amount, contract method and winning bid is used as independent variables and the number of bidders is used as a dependent variable. Big data and multidimensional analysis techniques are used for survey analysis. The conclusions are as follows: First, the larger the budget amount of public works projects, the smaller the number of participants. Second, in the contract method, restricted competition has more participants than general competition. Third, the duration of bidding notice did not significantly affect the number of bidders. Fourth, in the winning bid method, the qualification examination bidding system has more bidders than the lowest bidding system.

Sorghum Field Segmentation with U-Net from UAV RGB (무인기 기반 RGB 영상 활용 U-Net을 이용한 수수 재배지 분할)

  • Kisu Park;Chanseok Ryu ;Yeseong Kang;Eunri Kim;Jongchan Jeong;Jinki Park
    • Korean Journal of Remote Sensing
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    • v.39 no.5_1
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    • pp.521-535
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    • 2023
  • When converting rice fields into fields,sorghum (sorghum bicolor L. Moench) has excellent moisture resistance, enabling stable production along with soybeans. Therefore, it is a crop that is expected to improve the self-sufficiency rate of domestic food crops and solve the rice supply-demand imbalance problem. However, there is a lack of fundamental statistics,such as cultivation fields required for estimating yields, due to the traditional survey method, which takes a long time even with a large manpower. In this study, U-Net was applied to RGB images based on unmanned aerial vehicle to confirm the possibility of non-destructive segmentation of sorghum cultivation fields. RGB images were acquired on July 28, August 13, and August 25, 2022. On each image acquisition date, datasets were divided into 6,000 training datasets and 1,000 validation datasets with a size of 512 × 512 images. Classification models were developed based on three classes consisting of Sorghum fields(sorghum), rice and soybean fields(others), and non-agricultural fields(background), and two classes consisting of sorghum and non-sorghum (others+background). The classification accuracy of sorghum cultivation fields was higher than 0.91 in the three class-based models at all acquisition dates, but learning confusion occurred in the other classes in the August dataset. In contrast, the two-class-based model showed an accuracy of 0.95 or better in all classes, with stable learning on the August dataset. As a result, two class-based models in August will be advantageous for calculating the cultivation fields of sorghum.

A Survey on the Critical Success Factors of Knowledge Management Using AHP (AHP 분석을 이용한 지식경영 실천 요소의 중요도에 관한 실증적 연구)

  • 이영수;박준아;정광식;김진우
    • Proceedings of the Korea Database Society Conference
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    • 1999.06a
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    • pp.85-94
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    • 1999
  • 지식경영을 효과적으로 수행하기 위해서 기업은 지식경영을 구성하고 있는 요소를 정확히 이해할 필요가 있고, 이러한 중요 요소에 따라 투자가 이루어져야 한다. 본 연구는 지식경영의 중요 요소들을 제시함으로써, 앞으로 지식경영을 계획하고 있는 기업이 효과적으로 지식경영을 추진할 수 있는 활동 지침 및 투자 방향을 제시하고자 한다. 이를 위해, 본 연구에서는 각종 국내외 지식경영 관련 문헌에서 논의된 사항을 중심으로, 지식경영을 구성하는 30개의 중요요소를 추출하고, 분석계층도(AHP)를 이용하여 지식경영을 달성하기 위한 요소들을 위계적 구조로 정리하고, 최종단계에서 238개의 지식경영 구현의 평가기준을 마련하였다. 또한 실제로 지식경영 구현 요소들의 상대적 중요성을 파악하기 위해, 먼저 국내에서 지식경영을 추진하고 있거나 관심을 보이고 있는 48개 기업의 담당자 및 관련 부서원을 대상으로 설문조사를 실시하였고, 동시에 지식경영을 실제로 수행하고 있는 13개 기업의 담당자를 대상으로 각 기업에서 추진하고 있는 지식경영의 현황 파악을 위해 지식경영 실천의 평가기준에 대한 설문을 실시하였다. 이 두 가지 설문 조사 결과를 종합해 볼 때, 기업에서는 지식경영 구현 요소 중에서 인프라 내의 프로세스와 프로세스를 구성하는 지식의 활용과 전파 등이 중요하다고 인식하고 있는 반면, 실제로는 인프라 내의 정보기술과 프로세스를 구성하는 다른 한 축인 지식의 창출과 축적 면에 투자가 이루어진 것으로 나타났다. 이 외에도 지식화, 성과와 가치의 연계 그리고 지식의 가시화 등의 요소들은 상대적 중요도 인식과는 반대로 지식경영 추진에 있어 외면당하고 있는 것으로 나타났다. 따라서 본 연구는 지식 경영의 이러한 불균형을 시정할 수 있는 방향으로 앞으로의 투자가 수행되어야 할 것을 제안하고 있다. 산업의 밀도를 비재무적 지표변수로 산정하여 로지스틱회귀 분석과 인공신경망 기법으로 검증하였다. 로지스틱회귀분석 결과에서는 재무적 지표변수 모형의 전체적 예측적중률이 87.50%인 반면에 재무/비재무적 지표모형은 90.18%로서 비재무적 지표변수 사용에 대한 개선의 효과가 나타났다. 표본기업들을 훈련과 시험용으로 구분하여 분석한 결과는 전체적으로 재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적 중률을 나타내었다.(ⅱ) managemental and strategical learning to give information necessary to improve the making. program and policy decision making, The objectives of the study are to develop the methodology of modeling the socioeconomic evaluation, and build up the practical socioeconomic evaluation model of the HAN projects including scientific and technological effects. Since the HAN projects consists of 18 subprograms, it is difficult In evaluate all the subprograms

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Energy-Efficient Routing Protocol based on Interference Awareness for Transmission of Delay-Sensitive Data in Multi-Hop RF Energy Harvesting Networks (다중 홉 RF 에너지 하베스팅 네트워크에서 지연에 민감한 데이터 전송을 위한 간섭 인지 기반 에너지 효율적인 라우팅 프로토콜)

  • Kim, Hyun-Tae;Ra, In-Ho
    • The Journal of the Korea Contents Association
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    • v.18 no.3
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    • pp.611-625
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    • 2018
  • With innovative advances in wireless communication technology, many researches for extending network lifetime in maximum by using energy harvesting have been actively performed on the area of network resource optimization, QoS-guaranteed transmission, energy-intelligent routing and etc. As known well, it is very hard to guarantee end-to-end network delay due to uncertainty of the amount of harvested energy in multi-hop RF(radio frequency) energy harvesting wireless networks. To minimize end-to-end delay in multi-hop RF energy harvesting networks, this paper proposes an energy efficient routing metric based on interference aware and protocol which takes account of various delays caused by co-channel interference, energy harvesting time and queuing in a relay node. The proposed method maximizes end-to-end throughput by performing avoidance of packet congestion causing load unbalance, reduction of waiting time due to exhaustion of energy and restraint of delay time from co-channel interference. Finally simulation results using ns-3 simulator show that the proposed method outperforms existing methods in respect of throughput, end-to-end delay and energy consumption.

A Customized Healthy Menu Recommendation Method Using Content-Based and Food Substitution Table (내용 기반 및 식품 교환 표를 이용한 맞춤형 건강식단 추천 기법)

  • Oh, Yoori;Kim, Yoonhee
    • KIPS Transactions on Software and Data Engineering
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    • v.6 no.3
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    • pp.161-166
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    • 2017
  • In recent times, many people have problems of nutritional imbalance; lack or surplus intake of a specific nutrient despite the variety of available foods. Accordingly, the interest in health and diet issues has increased leading to the emergence of various mobile applications. However, most mobile applications only record the user's diet history and show simple statistics and usually provide only general information for healthy diet. It is necessary for users interested in healthy eating to be provided recommendation services reflecting their food interest and providing customized information. Hence, we propose a menu recommendation method which includes calculating the recommended calorie amount based on the user's physical and activity profile to assign to each food group a substitution unit. In addition, our method also analyzes the user's food preferences using food intake history. Thus it satisfies recommended intake unit for each food group by exchanging the user's preferred foods. Also, the excellence of our proposed algorithm is demonstrated through the calculation of precision, recall, health index and the harmonic average of the 3 aforementioned measures. We compare it to another method which considers user's interest and recommended substitution unit. The proposed method provides menu recommendation reflecting interest and personalized health status by which user can improve and maintain a healthy dietary habit.

Negative Transition of Smart Device Utility: Empirical Study on IT-enabled Work Flexibility, After Hours Work Connectivity, and Work-Life Conflict (스마트기기 효용의 부정적 전이: IT기반 업무 유연성, 근무시간 외 업무 연결성, 일-삶 갈등에 관한 실증 연구)

  • Kim, Hyung-Jin;Lee, Yoon-ji;Lee, Ho-Geun
    • Informatization Policy
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    • v.26 no.4
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    • pp.36-61
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    • 2019
  • While smart devices can have a positive impact on work efficiency and productivity by reducing time-space constraints and enabling rapid processing of tasks, side effects can arise from the imbalances between work and personal life. In recent years, as smart devices are increasingly used in work environments, it is more necessary than ever to understand the related phenomenon, find the cause of negative effects, and search for appropriate solutions. This study has developed and verified a theoretical model that shows how the technical characteristics known as the utility of smart devices are converted into negative results such as work-life conflict. As a result of analyzing the collected data from the employees, our study provides significant implications for the researchers, as well as the practitioners and policy makers, regarding various relationships among IT-enabled work flexibility, after-hours work connectivity and work-life conflict, and the new knowledge about the important role of segmentation supplies from the organization.

Improvement Issues of Personal Information Protection Laws through Meta-Analysis (메타분석을 통한 개인정보보호법의 개선과제)

  • Cho, Myunggeun;Lee, Hwansoo
    • Journal of Digital Convergence
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    • v.15 no.9
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    • pp.1-14
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    • 2017
  • As we enter the era of big data, the value of personal information is becoming ever more important. However, personal information protection laws in Korea have several issues. Furthermore, existing research are limited in their ability to facilitate a comprehensive understanding of measures to improve personal information protection laws. Accordingly, this study analyzes improvements to be made in the current personal information protection laws based on existing research. A total of 39 research articles discussing the problems of the personal information protection law were selected and analyzed by applying the meta - analysis technique. According to the results, the various issues such as the meaning and scope of personal information, the role and obligations of relevant parties, provision of personal information to third parties, and redundant and imbalanced regulations in special acts in each field. that exist in the current personal information protection laws were confirmed. This study contributes to the improvement of inconsistency between information protection laws and related special laws in each field in practice. Academically, it will contribute to understanding the problems of th law from the macro perspective and suggesting the integrated improvement ways of the law.

Analysis of the 2015 reform plan of government employees pension system (GEPS) through monte carlo simulations (모의실험을 통한 2015년 공무원 연금제도 개정안의 효과분석)

  • Lee, Jieun;Song, Seongjoo
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.1
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    • pp.19-32
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    • 2016
  • Due to the increasing fiscal burden and structural unbalanced premium/benefit costs, the new reform on the government employees pension system (GEPS) was considered even after the recent reform in 2009. This article examines the various effects of recent amendment in 2015 on GEPS using a simple probabilistic model. We consider effects on both sides, the pensioners and the government. First of all, the expected net value of pension payment for an individual employee was calculated based on the supposed survival distribution. The fairness of individual pension holders was compared using the benefit-cost ratio. Secondly, from pension system users' point of view, the default probability and the government subsidy were examined by Monte-carlo simulation. From the simulation experiment, we could see that the 2015 reform plan indeed reduces the default probability and the size of the fiscal burden of government by increasing the premium and decreasing the benefit. However, the size of the effect is not very standout at this moment because the number of new employees who are fully subject to the reform will be much smaller than the number of previous employees for a while. Thus, the effect of the reform is expected to appear in a slow manner.