• 한국도로학회논문집
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• 제20권2호
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• pp.57-65
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• 2018

PURPOSES : The study aims to predict the service life of national highway asphalt pavements through deep learning methods by using maintenance history data of the National Highway Pavement Management System. METHODS : For the configuration of a deep learning network, this study used Tensorflow 1.5, an open source program which has excellent usability among deep learning frameworks. For the analysis, nine variables of cumulative annual average daily traffic, cumulative equivalent single axle loads, maintenance layer, surface, base, subbase, anti-frost layer, structural number of pavement, and region were selected as input data, while service life was chosen to construct the input layer and output layers as output data. Additionally, for scenario analysis, in this study, a model was formed with four different numbers of 1, 2, 4, and 8 hidden layers and a simulation analysis was performed according to the applicability of the over fitting resolution algorithm. RESULTS : The results of the analysis have shown that regardless of the number of hidden layers, when an over fitting resolution algorithm, such as dropout, is applied, the prediction capability is improved as the coefficient of determination ($R^2$) of the test data increases. Furthermore, the result of the sensitivity analysis of the applicability of region variables demonstrates that estimating service life requires sufficient consideration of regional characteristics as $R^2$ had a maximum of between 0.73 and 0.84, when regional variables where taken into consideration. CONCLUSIONS : As a result, this study proposes that it is possible to precisely predict the service life of national highway pavement sections with the consideration of traffic, pavement thickness, and regional factors and concludes that the use of the prediction of service life is fundamental data in decision making within pavement management systems.

• 기술혁신연구
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• 제22권4호
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• pp.199-233
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• 2014

본 연구의 주요한 목적은 기업이 연구개발활동을 위하여 정부지원을 받은 경우에 그렇지 않은 경우와 비교하여 부가성 효과가 나타나는지와 부가성 효과가 나타난다면 왜, 어떻게 나타나는지를 탐색적으로 규명하는 것이다. 이를 위하여 대전지역의 12개 중소 중견기업을 대상으로 다중사례연구를 진행하였다. 분석을 위하여 기업의 연구개발활동 과정에 따라 기업의 R&D 노력에 영향을 주는 다양한 요소와 이들에 따른 R&D 투자와 의사결정 단계, 기업의 R&D 노력을 통한 행동변화단계, 기업의 R&D 노력에 의한 성과와 피드백단계로 구분하여 전반적인 R&D 활동 및 부가성에 대한 사례를 조사하였다. 아울러, 기업의 유형과 기업의 성장단계에 따른 효과성의 차이를 확인하였다. 실증연구 결과 기업의 연구개발활동에 따른 투입, 행동, 산출부가성이 다양하게 존재하는 것으로 확인되었다. 기업은 창업기의 기업일수록 R&D 활동에서 정부지원사업에 대한 의존성이 매우 높았으며 기업의 주요한 제품개발과 신규사업으로의 전환을 위한 연구개발을 위하여 정부지원사업을 전략적으로 활용하는 것으로 나타났다. 또한 기업의 유형과 기업의 성장단계 별로 각 기업이 정부지원사업으로 추진하는 사업의 성격과 정부지원사업을 활용하는 태도가 다르게 나타났다.

• 한국ITS학회 논문지
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• 제12권3호
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• pp.78-86
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• 2013

모노폴과 IFA(Inverted F Antenna)가 함께 동작하는 하이브리드 안테나를 이용한 MIMO(Multi Input Multi Output) 안테나를 설계한다. 안테나 공간을 줄이기 위하여 Vlade(Vertical lade)기법을 적용하며, 데이터통신을 위해 베어보드 상하단에 대각선으로 급전하는 MIMO 안테나를 설계한다. 설계를 위한 각 부분 길이를 변수로 하여 반사손실 특성의 변화를 나타낸다. LTE700, CDMA, GSM, DCS, PCS 및 WCDMA의 6중 주파수대역에서 동작하는 안테나를 설계하고 이를 구현한다. 구현된 안테나에 대한 반사손실 측정결과, VSWR 3:1 기준으로 설계대역 전체를 만족하였다. 또한 안테나에 대한 방사특성은 LTE700/CDMA/GSM 주파수대역에서 평균이득 -3.76 ~ -2.53dBi 및 42.06 ~ 55.84%의 효율, DCS/PCS/ WCDMA 주파수대역에서는 평균이득 -3.27 ~ -1.21dBi 및 47.08 ~ 75.6%의 효율을 보였다. MIMO특성 중 중요한 요소인 2안테나 간의 분리도는 전 밴드에서 -8.14 ~ -25.77dB로써 양호한 특성을 보였다.

• 전자공학회논문지S
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• 제36S권11호
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• pp.15-21
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• 1999

전송성능 열화요소들을 고려하여 광상호분배기 노드의 극장성을 분석하였다. 고려된 전송성능 열화요소들은 광증폭기에서 발생하는 ASE 잡음 누적과 이득포화 특성, 그리고 파장 다중/역다중화기와 광스위치에서 발생하는 누화 등이 있다. 파장 다중/역다중화기 누화비가 25dB이하이면 10단의 노드를 통과한 후에도 1dB이하의 power penalty를 갖는다. 10Gbps 신호의 다단 전송에서 입출력 포트수가 4와 16일 때 스위치 누화비가 각각 30dB와 45dB이상이면 ASE 잡음누적보다 누화에 의한 성능열화가 보다 지배적이다. 10Gbps 신호를 21dB 손실을 갖는 광섬유 링크 전송시 $10^{-12}$의 BER을 얻기 위해 광상호분배기 노드에서의 최대 손실은 34dB이하이어야 한다.

• 한국통신학회논문지
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• 제25권1B호
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• pp.89-98
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• 2000

본 논문에서는 적응필터를 기반으로 한 웨이브릿 변환 및 서브밴드 필터뱅크를 사용한 능동잡음제거의 모델을 제안한다. 분해 필터뱅크는 입력 및 오차신호를 저주파 및 고주파영역의 QMF 필터뱅크로 분해하며, 각 필터뱅크 에는 dyadic tree 구조를 갖는 웨이브릿 필터를 사용한다. 분해된 입력 및 오차신호는 filtered-X LMS 알고리듬를 사용하여 각 서브밴드의 적응 필터계수를 새롭게 갱신시킨다. 합성 필터뱅크는 그리고 각 서브밴드의 적응필터 출력신호를 합성한 후 완전복원이 되는 광대역의 출력신호를 만든다. 분해 및 합성 필터뱅크는 완전복원을 위하여 공액직교필터를 사용한다. 또한 오차경로의 전달특성을 온라인 추정하기 위한 지연 LMS 알고리듬 모델은 이득과 시간지연인자만을 사용한다. 따라서 제안한 적응 능동잡음제거 모델은 웨이브릿 서브밴드 필터뱅크를 사용하여 계산량과 수렴속도에 유리한 시스템이 되도록 제시한다.

• 지역사회간호학회지
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• 제15권4호
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• pp.539-550
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• 2004

Purpose: The purpose of this study was to evaluate the achievements of the project, and also to find out its strengths and weaknesses. Method: This evaluative study employed system theory and analytic techniques by using criteria which were relevance, appropriateness, adequacy, progress, effectiveness and satisfaction for input, process, output, and outcome of program. Study subjects were participants in the home health care program implemented in G public health center in Inchon metropolitan city in 2003. Results: Input factors including recruitment personnel, and support organization development were not adequately met for the program. However. the goal and objectives of the project were really appropriate for the community needs as well as government's policy. For the Process evaluation, home health care record form and computer data base had not progressed as scheduled, but overall program activities were finished on time. However, cooperation between organizations in the health center during service activity were not supportive. Managerial ability of program charged personnel about coordination and integration of team members was not affirmative. Output and outcome evaluation showed that people improved self care ability were 221 (17.5%). and 71 (5.62%) of subjects were moved into category of possible self-care. Client's satisfaction for this project showed a high degree. Conclusions: Based on the above results support organization and staff personnel for this program should be developed. Also, a community network of resources should be established and case management services should be focused continuously in community based home health care.

• 문화기술의 융합
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• 제6권4호
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• pp.527-533
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• 2020

이 연구의 목적은 진로 성공 대학 졸업생의 교육 참여 경험을 탐색하는 것이다. 교육 참여 경험은 투입과, 환경, 그리고 산출의 세 가지 관점에서 탐색되었다. 학생의 투입 요인으로 입학 전형, 지원 동기, 등록금 충당 방법을 탐색하였다. 환경 요인으로는 교내외 활동, 수업 중 활동, 대학 구성원과의 상호관계를 탐색하였다. 마지막으로 산출요인으로 대학 교육의 성과와 사회 진출에의 인식을 살펴보았다. 연구대상은 스스로 의도한 바대로 사회 진출에 성공한 21명의 학생을 대상으로 인터뷰와 설문이 진행되었고, 이들의 진로 성공에 영향을 미치는 요인들을 세 가지 상위 범주와 각각의 하위 범주로 구분하여 분석함으로써 향후 대학생의 진로 지도를 위한 대학 교육의 방향에 주는 시사점을 도출하고자 하였다.

• International Journal of Computer Science & Network Security
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• 제22권7호
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• pp.91-102
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• 2022

With the evolution of wireless sensor network (WSN) technology, the routing policy has foremost importance in the Internet of Things (IoT). A systematic routing policy is one of the primary mechanics to make certain the precise and robust transmission of wireless sensor networks in an energy-efficient manner. In an IoT environment, WSN is utilized for controlling services concerning data like, data gathering, sensing and transmission. With the advantages of IoT potentialities, the traditional routing in a WSN are augmented with decision-making in an energy efficient manner to concur finer optimization. In this paper, we study how to combine IoT-based deep learning classifier with routing called, Kriging Regressive Deep Belief Neural Learning (KR-DBNL) to propose an efficient data packet routing to cope with scalability issues and therefore ensure robust data packet transmission. The KR-DBNL method includes four layers, namely input layer, two hidden layers and one output layer for performing data transmission between source and destination sensor node. Initially, the KR-DBNL method acquires the patient data from different location. Followed by which, the input layer transmits sensor nodes to first hidden layer where analysis of energy consumption, bandwidth consumption and light intensity are made using kriging regression function to perform classification. According to classified results, sensor nodes are classified into higher performance and lower performance sensor nodes. The higher performance sensor nodes are then transmitted to second hidden layer. Here high performance sensor nodes neighbouring sensor with higher signal strength and frequency are selected and sent to the output layer where the actual data packet transmission is performed. Experimental evaluation is carried out on factors such as energy consumption, packet delivery ratio, packet loss rate and end-to-end delay with respect to number of patient data packets and sensor nodes.

• Journal of Korea Trade
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• 제25권3호
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• pp.48-64
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• 2021

Purpose - This study examined the effect of tariff cuts on productivity in Korea's manufacturing industries and the effect of initial productivity level before tariff cuts on productivity improvement after tariff cuts. We also attempted to identify whether import-driven or export-driven factors are more important for productivity improvement, especially in low productivity industries. Design/methodology - Since tariff reduction is a policy decision that can affect cross-industry, its impact is spread across all industries beyond the scope of a single firm through the input and output network of industry structure. Accordingly, we proposed a new method to measure the change in productivity to reflect the impact of tariff cuts across industries. Through an Armington CGE analysis, changes in endogenous variables can be directly measured after the exogenous shock of tariff reduction, and the amount of movements in productivity triggered by tariff cuts can also be calculated. We can thus assess the effectiveness of exogenous policy, such as tariff cuts, through the difference between the benchmark and counterfactual values of endogenous variables. Findings - This study confirmed that tariff reduction positively affected productivity improvement in Korea's manufacturing industries. It also confirmed that productivity gains occur in Korea's leading export industries. Finally, greater productivity gains were recorded in the group with additional high-export-share or high-import-share conditions for low productivity industries. These results are, in a limited sense, consistent with the existing studies that emphasize the importance of exports and imports on productivity improvement, especially for low productivity industries. Originality/value - The results of our experiments are different from those of non-CGE studies, which measure the industry-level change in productivity with dummy coefficients, in terms of directly calculating the amount of change in productivity. In addition, we propose that the Armington CGE model is more appropriate than the Melitz CGE model to directly measure the productivity after tariff cuts. This is because the Melitz CGE model assumes the given specific productivity density, which does not change after an overall drop of tariffs. To the best of our knowledge, this approach to directly calculating productivity by reflecting the impact of tariff reduction across industries through CGE analysis, is unprecedented in this literature.

• Journal of Korea Trade
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• 제25권2호
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• pp.58-74
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• 2021

Purpose - This paper research on the embodied carbon emission in Sino-Korea trade. It calculates and analyzes the carbon emission coefficient and specific carbon emissions in Sino-Korea trade from 2005 to 2014. Design/methodology - This paper conducted an empirical analysis for embodied carbon emission in Sino-Korea trade during the years 2005-2014, using a multi-region input-output model. First, direct and complete CO2 emission coefficient of the two countries were calculated and compared. On this basis, combined with the world input-output table, the annual import and export volume and sector volume of embodied carbon emission are determined. Then through the comparative analysis of the empirical results, the reasons for the carbon imbalance in Sino-Korea trade are clarified, and the corresponding suggestions are put forward according to the environmental protection policies being implemented by the two countries. Findings - The results show that South Korea is in the state of net trade export and net embodied carbon import. The carbon emission coefficient of most sectors in South Korea is lower than that of China. However, the reduction of carbon emission coefficient in China is significantly faster than that in South Korea in this decade. The change of Korea's complete CO2 emission coefficient shows that policy factors have a great impact on environmental protection. The proportion of intra industry trade between China and South Korea is relatively large and concentrated in mechanical and electrical products, chemical products, etc. These sectors generally have large carbon emissions, which need to be noticed by both countries. Originality/value - To the best knowledge of the authors, this study is the first attempt to research the embodied carbon emission of ten consecutive years in Sino-Korea Trade. In addition, In this paper, some mathematical methods are used to overcome the error problem caused by different statistical caliber in different databases. Finally, the accurate measurement of carbon level in bilateral trade will provide some reference for trade development and environmental protection.