• 한국컴퓨터정보학회논문지
• /
• 제17권2호
• /
• pp.197-206
• /
• 2012

기존의 연관규칙을 이용한 추천시스템은 매번 계속적으로 대량의 데이터를 스캔해야 하므로 속도가 느릴 뿐 아니라 확장성 문제와 정확도 문제가 있다. 본 논문에서는 사용자의 평가 자료에 의존하지 않고 묵시적인(Implicit)방법을 이용하여 RFM(Recency, Frequency, Monetary)기반 FP-tree 마이닝을 이용한 개인화 추천시스템을 제안한다. 구매 가능성이 높은 아이템을 찾기 위해서 고객정보와 구매이력정보를 기반으로 고객과 아이템의 속성 반영이 가능한 RFM기법과 FP-tree 마이닝을 이용한다. 제안 방법으로 RFM기반의 FP-tree 마이닝을 이용하여 후보집합의 발생없이 빈발항목을 구성하고 연관규칙을 생성한다. 생성된 연관규칙의 지지도, 신뢰도, 향상도를 사용하여 추천 효율성이 높은 아이템 추천이 가능하다. 성능평가를 위해 현업에서 사용하는 인터넷 화장품 아이템 쇼핑몰의 데이터를 기반으로 데이터 셋을 구성하여 기존의 시스템과 비교 실험을 통해 성능을 평가하여 효용성과 타당성을 입증하였다.

• Nuclear Engineering and Technology
• /
• 제34권1호
• /
• pp.42-59
• /
• 2002

In order to transmute long-lived radioactive nuclides such as transuranics(TRU), Tc-99, and I- l29 in LWR spent fuel, a preliminary conceptual design study has been performed for the accelerator driven subcritical reactor system, called HYPER(Hybrid Power Extraction Reactor) The core has a hybrid neutron energy spectrum: fast and thermal neutrons for the transmutation of TRU and fission products, respectively. TRU is loaded into the HYPER core as a TRU-Zr metal form because a metal type fuel has very good compatibility with the pyre- chemical process which retains the self-protection of transuranics at all times. On the other hand, Tc-99 and I-129 are loaded as pure technetium metal and sodium iodide, respectively. Pb-Bi is chosen as a primary coolant because Pb-Bi can be a good spallation target and produce a very hard neutron energy spectrum. As a result, the HYPER system does not have any independent spallation target system. 9Cr-2WVTa is used as a window material because an advanced ferritic/martensitic steel is known to have a good performance under a highly corrosive and radiation environment. The support ratios of the HYPER system are about 4∼5 for TRU, Tc-99, and I-129. Therefore, a radiologically clean nuclear power, i.e. zero net production of TRU, Tc-99 and I-129 can be achieved by combining 4 ∼5 LWRs with one HYPER system. In addition, the HYPER system, having good proliferation resistance and high nuclear waste transmutation capability, is believed to provide a breakthrough to the spent fuel problems the nuclear industry is faced with.

• 한국운동역학회지
• /
• 제31권3호
• /
• pp.155-161
• /
• 2021

Objective: There is a lack of studies using the 3D-2D image registration techniques on the mechanism of a shoulder injury for ice hockey players. This study aimed to analyze in vivo 3D glenohumeral joint arthrokinematics in collegiate ice hockey athletes and compare shoulder scaption with or without a hockey stick using the 3D-2D image registration technique. Method: We recruited 12 male elite ice hockey players (age, 19.88 ± 0.65 years). For arthrokinematic analysis of the common shoulder abduction movements of the injury pathogenesis of ice hockey players, participants abducted their dominant arm along the scapular plane and then grabbed a stick using the same motion under C-arm fluoroscopy with 16 frames per second. Computed tomography (CT) scans of the shoulder complex were obtained with a 0.6-mm slice pitch. Data from the humerus translation distances, scapula upward rotation, anterior-posterior tilt, internal to external rotation angles, and scapulohumeral rhythm (SHR) ratio on glenohumeral (GH) joint kinematics were outputted using a MATLAB customized code. Results: The humeral translation in the stick hand compared to the bare hand moved more anterior and more superior until the abduction angle reached 40°. When the GH joint in the stick hand was at the maximal abduction of the scapula, the scapula was externally rotated 2~5° relative to 0°. The SHR ratio relative to the abduction along the scapular plane at 40° indicated a statistically significant difference between the two groups (p < 0.05). Conclusion: With arm loading with the stick, the humeral and scapular kinematics showed a significant correlation in the initial section of the SHR. Although these correlations might be difficult in clinical settings, ice hockey athletes can lead to the movement difference of the scapulohumeral joints with inherent instability.

• 디지털융복합연구
• /
• 제17권7호
• /
• pp.157-165
• /
• 2019

"Aging in place" 실현을 조력하는 제론테크놀로지는 노인의 삶의 질을 높이고 사회적 돌봄 비용을 감소시킬 수 있다. 본 연구는 지역사회 노인의 제론테크놀로지의 사용 전 수용성 및 장애요인을 파악하고 사용 전 수용성의 영향요인을 탐색하는 조사연구로 2019년 3월 16일부터 23일까지 노인복지관을 이용하는 남녀 노인 129명을 대상으로 설문 조사했다. 다중회귀분석을 한 결과 28%의 설명력으로 농촌지역의 대상자와 신체적인 기능이 높을수록, 고비용이나 기술사용에 대한 가족의 지원 부족과 같은 장애요인이 낮을수록 제론테크놀로지의 사용 전 수용성이 높은 것으로 나타났다. 따라서 노인에 대한 보건복지 전략을 개발 할 때 이러한 요인에 대한 고려는 많은 수의 노인이 제론테크놀로지 사용을 촉진하여 향후 노인의 aging in place를 가능하게 할 것이다.

• 국제지역연구
• /
• 제20권2호
• /
• pp.235-256
• /
• 2016

한국 지방정부들은 일찍부터 중국, 미국, 일본을 중심으로 하는 시장성이 크거나 잠재력이 높은 지역에 대하여 경쟁적으로 해외사무소를 설치하였다. 이것은 교류협력을 보다 적극적이고 선제적인 대응전략을 수립 하고자는 목적에서 시작되었다. 그러나 해외사무소가 본래 취지와는 다르게 예산투입 대비 만족스런 성과가 나오지 않는 것이 문제점이며 최근에 들어서는 운영 자체에 대한 비판의 목소리도 커지고 있다. 우리나라 지방정부별 중국사무소의 운영 현황에 대한 심층 분석과 교류협력 확대방안 모색을 위해 직접 10개의 지방자치단체를 방문하여 담당자 인터뷰를 하였다. 분석결과 지방정부들은 민간과 협력 네트워크 구성, 해외사무소의 전문성 강화, 투자유치를 위한 역할 증대, 해외사무소 개설시 메가시티 선호, 해외사무소의 운영비 절감을 중점적으로 추진하고 있다.

• 한국재료학회지
• /
• 제28권11호
• /
• pp.633-639
• /
• 2018

In anion exchange membrane fuel cells, Pd nanoparticles are extensively studied as promising non-Pt catalysts due to their electronic structure similar to Pt. In this study, to fabricate Pd nanoparticles well dispersed on carbon support materials, we propose a synthetic strategy using mixed organic ligands with different chemical structures and functions. Simultaneously to control the Pd particle size and dispersion, a ligand mixture composed of oleylamine(OA) and trioctylphosphine(TOP) is utilized during thermal decomposition of Pd precursors. In the ligand mixture, OA serves mainly as a reducing agent rather than a stabilizer since TOP, which has a bulky structure, more strongly interacts with the Pd metal surface as a stabilizer compared to OA. The specific roles of OA and TOP in the Pd nanoparticle synthesis are studied according to the mixture composition, and the oxygen reduction reaction(ORR) activity and durability of highly-dispersed Pd nanocatalysts with different particles sizes are investigated. The results of this study confirm that the Pd nanocatalyst with large particles has high durability compared to the nanocatalyst with small Pd nanoparticles during the accelerated degradation tests although they initially indicated similar ORR performance.

• 한국해양공학회지
• /
• 제33권3호
• /
• pp.289-299
• /
• 2019

Various sizes of ROVs are being utilized in offshore industrial, scientific, and military applications all around the world. Because of innovative developments in science and technology, image acquisition devices such as sonar devices and cameras have been reduced in size and their performance has been improved. Thus, we can expect better accuracy and higher resolution even in the case of exploration using a small ROV. The purpose of this paper is to prepare a standard procedure for the identification of unidentified hazardous materials found during the National Oceanographic Survey. In this paper, we propose an IDEF (Integrated DEFinition) method modeling technique to identify unidentified targets using a small ROV. In accordance with the proposed procedure, an ROV survey was carried out on target No.16 with a four-ton-class fishing boat as a support vessel on September 18th of 2018 in the sea near Daebu Island. Unidentified targets, which were not known by the multi-beam data obtained from the ship, could be identified as concrete pipes by analyzing the HD camera and high-resolution sonar images acquired by the ROV. The whole proposed procedure could be verified, and the survey with the small ROV required about 10 days to identify the target in one place.

• 농업과학연구
• /
• 제46권2호
• /
• pp.381-393
• /
• 2019

A smart farm is a system that combines information and communication technology (ICT), internet of things (IoT), and agricultural technology that enable a farm to operate with minimal labor and to automatically control of a greenhouse environment. Machine learning based on recently data-driven techniques has emerged with big data technologies and high-performance computing to create opportunities to quantify data intensive processes in agricultural operational environments. This paper presents research on the application of machine learning technology to diagnose the growth status of crops and predicting the harvest time of strawberries in a greenhouse according to image processing techniques. To classify the growth stages of the strawberries, we used object inference and detection with machine learning model based on deep learning neural networks and TensorFlow. The classification accuracy was compared based on the training data volume and training epoch. As a result, it was able to classify with an accuracy of over 90% with 200 training images and 8,000 training steps. The detection and classification of the strawberry maturities could be identified with an accuracy of over 90% at the mature and over mature stages of the strawberries. Concurrently, the experimental results are promising, and they show that this approach can be applied to develop a machine learning model for predicting the strawberry harvesting time and can be used to provide key decision support information to both farmers and policy makers about optimal harvest times and harvest planning.

• 정보보호학회논문지
• /
• 제22권3호
• /
• pp.575-584
• /
• 2012

군의 정보화, 과학화 추진에 따른 환경 변화에 따라 기존 수작업, 오프라인 중심의 제반 군사보안 업무도 효율적이고 체계적인 업무 수행을 지원할 수 있도록 변화와 발전이 필요하다. 이에 본 연구에서는 주요 군사보안 업무 분야에 대한 실태 및 문제점 분석과 미국, 영국 등의 사례 분석을 기반으로, 주요 군사보안 업무를 자동화, 정보화하기 위한 국방통합보안시스템 구축 표준 Model을 제시하였다. 표준 Model은 통합보안체계, 비밀관리시스템, 인원출입 시스템, 차량출입시스템, 첨단경계시스템, 테러 예방시스템 및 보안사고분석시스템 등의 단위 시스템으로 구성되며, 현재 가용한 기술 및 시스템을 기반으로 제안하였는데, 이를 각급부대에 적용할 경우 군사보안 발전에 기여할 것으로 기대된다.

• 한국안전학회지
• /
• 제36권3호
• /
• pp.31-39
• /
• 2021

In Korea, more than half of work-related fatalities have occurred on construction sites. To reduce such occupational accidents, safety inspection by government agencies is essential in construction sites that present a high risk of serious accidents. To address this issue, this study developed risk prediction models of serious accidents in construction sites using five machine learning methods: support vector machine, random forest, XGBoost, LightGBM, and AutoML. To this end, 15 proactive information (e.g., number of stories and period of construction) that are usually available prior to construction were considered and two over-sampling techniques (SMOTE and ADASYN) were used to address the problem of class-imbalanced data. The results showed that all machine learning methods achieved 0.876~0.941 in the F1-score with the adoption of over-sampling techniques. LightGBM with ADASYN yielded the best prediction performance in both the F1-score (0.941) and the area under the ROC curve (0.941). The prediction models revealed four major features: number of stories, period of construction, excavation depth, and height. The prediction models developed in this study can be useful both for government agencies in prioritizing construction sites for safety inspection and for construction companies in establishing pre-construction preventive measures.