Currently, agriculture in Korea is facing a manpower shortage due to a decrease in the population and an aging workforce. Involving disabled people in agriculture as a solution to the problem of manpower shortage in agriculture can help both farmers and people with disabilities. For this, it is necessary to develop agricultural tools that disabled people can use in agricultural activities. This study tried to design agricultural work equipment for the disabled by applying a design technique using a digital human body model. To this end, in this study, a human body model for the disabled was created using anthropometric data for the disabled. After that, the agricultural work simulation using human body models was used to identify the problems in agricultural work of the disabled, and design supplementation was performed to solve the problems. As a result, design dimensions such as the height of the farm work bench for the disabled, the length of the fruit harvester, the length of the sprayer, and the height of the starter switch were determined. This study has significance in that the digital human body model-based design method was applied to the design of agricultural work equipment for the disabled.

전 세계적으로 해상을 마주하고 있는 여러 국가들은 기존의 전력 생산방식의 단점을 극복하고 해상풍력 개발을 통한 친환경에 너지자원을 활용하고 있다. 해상은 넓은 해역에 대규모 풍력단지를 개발할 수 있는 장점이 있으나 해양구조물의 설치로 인해 선박의 안 전운항이 위협받고 있다. 이에 따라, 선박 통항로와 해상풍력단지 간 상호 미치는 영향에 대해 분석하여 선박이 안전하게 운항할 수 있도 록 PIANC에서는 표준 Guideline을 제시하였다. 그럼에도 불구하고, 표준 Guideline은 모든상황에서 동일한 이격거리를 산정하였다. 따라서 본 연구에서는 선회성능, 조우상태, 환경외력, 해상밀집도, 해상풍력발전기, 항로형태 등을 요소로 반영한 선박 통항로와 해상풍력단지 간 최적의 이격거리 산정 모델을 개발하였다. 개발된 모델 검증을 위한 시뮬레이션 결과, 운항 준비상태에 따른 입지 특성별 선회성능 크기 는 산정 모델에서 제시한 크기와 유사하였다.

The Moving Particle Semi-implicit (MPS) method is one of most famous method in the particle-based computational fluid dynamics field. The MPS, the state-of-art method, is simple but intuitive methodology including multi-phase and complex structure interactions problems. However, the concept of particle method may contain the physical weakness. In order to avoid physical violence, the particle number density and kernel function were employed. Despite all the efforts, the microscopic problems were not easily resolved yet. In this study, the surface tension model was developed and added into the MPS method to strengthen physical phenomena and physics laws. The simulation result with new MPS method including surface tension model was compared with corresponding theoretical results and they show good-agreement.

본 연구의 목적은 과거 12년(2010~2021년)간 발생한 상선의 충돌사고 668건을 조사하여 충돌의 원인요인을 조사하고 이를 통계 적으로 분석하여 항해사의 인적과실 예방 충돌회피(HEPCA) 모델을 제안하는 것이다. 중앙해양안전심판원의 통계연보 및 충돌사건 재결서 를 조사하여 상선의 충돌 원인요인 데이터를 수집하고 통계분석 도구인 SPSS를 이용하여 빈도분석을 수행하였다. 1단계 분석으로 상선 충 돌사고 668건을 대상으로 충돌원인을 분석하였고, 2단계 분석에서는 식별된 최대빈도 원인요인을 세부적으로 분석하였다. 분석결과, 충돌 원인은 항해사의 인적과실이 98 %인 것으로 식별되었으며, 빈도 높은 요인 순서는 경계소홀 〉항행법규위반 〉조선 부적절 순이었다. 경계 소홀의 원인 요인은 주로 상대선 초인 후 지속감시 소홀이었으며 상대선박의 존재를 인식하지 못한 원인은 주로 당직시간에 다른 작업을 한 요인이었다. 분석결과를 적용하여 인적과실 예방을 위한 HEPCA 모델을 제안하였고, 이를 재결서의 충돌사건에 적용해보았다. 본 연구결과는 해기사 교육기관 및 실무에서 항해사의 인적과실로 발생하는 충돌사고를 방지하기 위한 교육 자료로 활용이 가능할 것으로 기대된다.

Ball stud parts are manufactured by a cold forging process, and fastening with other parts is secured through a head part cutting process. In order to improve process quality, stabilization of the forging quality of the head is given priority. To this end, in this study, a predictive model was developed for the purpose of improving forging quality. The prediction accuracy of the model based on 450 data sets acquired from the manufacturing site was low. As a result of gradually multiplying the data set based on FE simulation, it was expected that it would be possible to develop a predictive model with an accuracy of about 95%. It is essential to build automated labeling of forging load and dimensional data at manufacturing sites, and to apply a refinement algorithm for filtering data sets. Finally, in order to optimize the ball stud manufacturing process, it is necessary to develop a quality prediction model linked to the forging and cutting processes.

This study compares and analyzes the drogue shape applied to aerial refueling with the U.S. Navy drog shape through basic analysis of the model based on the flying fish shape, a marine creature. Flying fish is a creature that is advantageous for non-powered downhill, and this shape is applied to the probe feeding method to minimize the burden on the pilot and the need for refueling technology, which are disadvantages of the probe method. To this end, the results through analysis of basic studies were confirmed, and the superiority and insufficiency of the flying fish shape model and the US Navy drogue model were compared. Therefore, as confirmed through analysis, the flying fish model had a 14.1% lower maximum air pressure and a 9.1% faster maximum speed. Based on this, it is hoped that the advantages and disadvantages of flying fish shape models will be confirmed through actual flight tests in the future.

The lane departure warning device can not detect the lane to be driven in the future by sensing the departure of the lane passing by during driving and warning the driver. Considering the safe operation of the truck, it is also expected that the departure of the future lanes according to the dynamic weight and speed of the current truck should be predicted. This study attempted to predict whether or not to deviate from the lanes of curved roads to be driven in the future according to the current dynamic driving weight and speed in consideration of the safe driving of trucks.

국내외로 첨단 ICT 융합기술이 농업 분야에 적용되기 시작 하면서, 시설원예 설비들이 고도화되고, 스마트팜 구축 기술 및 인력이 축적되기 시작하였다. 그러나 우리나라 농촌의 경 우, 농업생산 연령의 고령화, 국내 농촌 인구의 지속적인 유출, 저출산 등으로 인하여 스마트팜 확대 및 적용에 어려움이 많 은 실정이다. 따라서 공간 및 시간에 구속을 받지 않는 간편한 농업인 교육 프로그램이 필요하며, 최근 부상하고 있는 시뮬 레이션 기술을 활용한다면 농업 교육용 시뮬레이션 툴 개발도 가능할 것으로 판단된다. 온실 환경 제어 모델을 이용한 시뮬 레이션은 다양한 지역과 기상 조건 하에서 대상 온실의 열과 물질에너지의 상호작용을 합리적으로 예측할 수 있게 해준다. 본 연구에서는 온실 환경 제어 모델을 활용하여 외부 기상 데 이터를 통해 온실의 환경 변화를 예측하고 가상의 환경 제어시스템을 통해 환경 제어 시 필요한 에너지값들을 시뮬레이션 할 수 있었다. 이러한 결과를 통해 이용자가 직접 맞춤형 환경 제어를 할 수 있도록 편의성을 고려한 사용자 인터페이스를 구축할 것이며, 실제 파프리카 재배 온실의 제어 요소들을 반 영할 수 있도록 설계될 것이다. 농업용 교육 시뮬레이션 툴을 최근 활발하게 연구가 이루어지고 있는 작물 생육 모델링 기 술 및 전산유체역학 기술과 융합하면 더욱 타당한 결과를 보 일 것이다.

PURPOSES : Roller-compacted concrete pavement (RCCP) is a superstiff-consistency concrete pavement that exhibits excellent strength development owing to a hydration reaction and interlocking aggregates owing to the roller compaction. A zero-slump concrete mixture is generally used. Hence, it is important to control the consistency of the RCCP mixture to prevent the deterioration of the construction quality (such as material separation during paving). The workability of the RCCP is characterized by its consistency and controlled by the Vebe time, whereas a conventional concrete pavement is controlled based on the slump test. The consistency of the RCCP changes over time after concrete mixing owing to delivery, construction time delays, etc. Thus, it is necessary to use the optimum Vebe time to achieve the best construction quality. Therefore, this study aims to develop a Vebe time prediction model for efficiently controlling the consistency of RCCPs according to random time variations. METHODS : A Vebe time prediction model was developed using a multiple linear regression analysis. A dataset of 131 samples was used to develop the model. The collected data consisted of variables with large potential effects on the consistency of the RCCP, such as the water-cement ratio (W/C), sand/aggregate ratio (S/a), water content (ω), water content per unit volume (W), cement (C), fine aggregate (S), coarse aggregate (G), water reducing admixtrue (PNS), air-entraining admixture (AE), delay time (T), air temperature (TEM), and humidity (HUM). In the multiple linear regression analysis, the mentioned parameters were used as the independent variables, and the Vebe time was the dependent variable. The Vebe time prediction models were evaluated by considering the adjusted R2 and p-values. The selection of the model was based on the largest R2 value and an acceptable p-value (p<0.05). RESULTS : The Vebe time prediction model achieved an adjusted R2 value of 64.14% with a significance level (p-value) of less than 0.05. This shows that the predictive model is adequately described for the dependent variable, and that the model is suitable for Vebe time predictions. Moreover, the significance level of the independent variables is less than 0.05, indicating significant effects on the Vebe time (i.e., the dependent variable). CONCLUSIONS : The Vebe time prediction model developed in this study can be used to estimate Vebe times with an R2 of 63.33% between the measured and predicted values. The proposed Vebe time prediction model is expected to be effectively utilized for the quality control of RCCP mixtures. Moreover, it is expected to contribute to achieving good RCCP construction quality.

현행 발명진흥법 제15조는 직무발명의 보상기 준으로 정당한 보상, 사용자 이익, 발명 완성에 사용자와 종업원이 공헌한 정도 등 추상적 기준 만을 제시하고 있어 현재 민간 기업이 보상기준 작성 시 실질적으로 채택 가능한 법적 가이드라 인(Guideline)이 부재한 상황이다. 따라서 보상 규정이 부재하거나 미비하여 보상에 관한 다툼이 발생하면 소송 또는 산업재산권 분쟁조정위원회의 조정 절차 등을 통해 분쟁을 해결할 수밖에 없다. 이러한 상황에서 특허청과 발명진흥회는 발명 진흥법제11조에 따른 정부 지원시책으로서 구체 적인 보상유형과 보상액 산정 기준을 제시한 ‘직 무발명 보상규정 표준모델’을 작성하여 배포하고 있으며, 이는현행법상구체적인직무발명 보상기 준이 제시되고 있지 않아 보상유형과 보상액 산정기준에 대한 판단을 법원에 의존하고 있는 상 황에서, 민간기업이직무발명보상규정 작성⋅시 행 시 유용한 참고자료가 될 수 있다. 이는 또한 보상의 예측 가능성을 높이며, 법적 분쟁의 발생 을 사전 방지하는 역할을 할 수 있다. 다만, 표준모델은 오늘날 실시나 처분을 넘어 다양한 방식으로 활용되는 특허 활용 경향을 적 절히 반영하고 있지 못한 문제가 있다. 구체적으 로, 시험⋅인허가 절차로 인해 실시나 처분이 상 당 기간 유보되나 장래에 이익이 기대되는 제약 ⋅바이오 분야의 직무발명 또는 직접적인 실시나 처분을 수반하지 않는 방어 특허나 침해 소송으 로 사용자의 이익이 발생한 경우 등에 대해서는 현행 표준모델에 의할 때 정당한 보상이 이루어 지기 어렵다. 따라서 기업이 현행 표준모델에 따 라 보상규정을 작성 시행하는 경우 종업원의 연 구 의욕이 저하되고, 나아가 기업의 혁신 활동이 저해될 우려가 있다. 이에 본 연구에서는 실시 내지 처분이 상당 기 간 유보되는 특수한 성격의 제약⋅바이오 직무발 명, 직접 실시나 처분 없이 사용자 이익이 발생할 수 있는 방어 특허와 침해 소송 유형에 대한 직무 발명 보상규정이 표준모델에서 제시되어야 함을 주장하였다. 나아가독일의사적고용관계에서의 종업원 발명의 보상에 관한 지침 등에 비추어 ① 실적보상, ②실시내지처분유보보상및③침해 보상 등 보상의 유형과 유형별 보상액 산정 기준이 표준모델에 추가로 제시된 표준모델 개선안을 제안한다.

시각적 데이터는 도처에 존재하며 자연어는 인간이 이해할 수 있는 의사소통 수단이다. VQA(Visual Question Answering)는 이미지를 이미지에 대한 입력과 질문으로 취하고 복잡한 추론을 사용하여 자연어 답변을 생성 하는 시스템이다. 따라서, VQA는 답을 예측하기 위해 이미지에 대한 자세한 이해와 복잡한 이유가 필요하 다. 멀티모달 구조와 가능한 실제 구현을 고려할 때, VQA는 인공지능에게 매우 중요한 과제이다. VQA를 위한 심층 신경망에 사용되는 아키텍처와 하이퍼 파라미터는 결과에 큰 영향을 미친다. 이 프로젝트는 이미 지 특징을 추출하기 위해 사전 훈련된 모델(VGGNet)과 단어를 내장하기 위해 Word2Vec를 도입하고 질문에 서 단어 특징을 얻기 위해 LSTM을 도입하고 결과를 결합한 후 가장 높은 확률을 가진 답을 예측한다.

DEA(data envelopment analysis) is a technique for evaluation of relative efficiency of decision making units (DMUs) that have multiple input and output. A DEA model measures the efficiency of a DMU by the relative position of the DMU’s input and output in the production possibility set defined by the input and output of the DMUs being compared. In this paper, we proposed several DEA models measuring the multi-period efficiency of a DMU. First, we defined the input and output data that make a production possibility set as the spanning set. We proposed several spanning sets containing input and output of entire periods for measuring the multi-period efficiency of a DMU. We defined the production possibility sets with the proposed spanning sets and gave DEA models under the production possibility sets. Some models measure the efficiency score of each period of a DMU and others measure the integrated efficiency score of the DMU over the entire period. For the test, we applied the models to the sample data set from a long term university student training project. The results show that the suggested models may have the better discrimination power than CCR based results while the ranking of DMUs is not different.

In this paper, the instability of the domed spatial truss structure using wood and the characteristics of the buckling critical load were studied. Hexagonal space truss was adopted as the model to be analyzed, and two boundary conditions were considered. In the first case, the deformation of the inclined member is only considered, and in the second case, the deformation of the horizontal member is also considered. The materials of the model adopted in this paper are steel and timbers, and the considered timbers are spruce, pine, and larch. Here, the inelastic properties of the material are not considered. The instability of the target structure was observed through non-linear incremental analysis, and the buckling critical load was calculated through the singularities and eigenvalues of the tangential stiffness matrix at each incremental step. From the analysis results, in the example of the boundary condition considering only the inclined member, the critical buckling load was lower when using timber than when using steel, and the critical buckling load was determined according to the modulus of elasticity of timber. In the case of boundary conditions considering the effect of the horizontal member, using a mixture of steel and timber case had a lower buckling critical load than the steel case. But, the result showed that it was more effective in structural stability than only timber was used.

Due to environmental pollution, regulations on fossil fuels are required. There is a movement for the regulations by using LNG fueled propulsion ships. LNG is an eco-friendly fuel that does not emit NOx or SOx during combustion, but its boiling point is -163°C. Under that condition, the use of metal is restricted, and IMO defined applicable materials through IGC code. Among the metals, 9% nickel steel is one of excellent mechanical properties such as yield strength and tensile strength in cryogenic condition. Thus 9% nickel steel is widely used in cryogenic storage containers for ships. In addition, laser welding, which minimizes thermoelastic distortion by applying a concentrated heat source to a narrow area for a short period of time, is in the spotlight. So, this study is a basic research to predict and respond to thermal distortion during laser welding. Secondary version of the representative heat source model was derived through the author's previous research with STS304L, and the heat source model was derived by applying the heat source model to 9% nickel steel in this study. 9% nickel steel is a material that is in high demand and is widely used in the manufacture of cryogenic containers, so this study is expected to be able to respond immediately to the field.

In order to reduce environmental pollution, it is necessary to increase the recycling rate of waste. For this, the separation of recyclables is of utmost importance. The paper conducted a study to automatically discriminate containers by material for beverage containers among recyclables. We developed an algorithm that automatically recognizes containers by four materials: metal, glass, plastic, and paper by measuring the vibration signal generated when the beverage container collides with the bottom plate of the collection box. The amplitude distribution, time series information, and frequency information of the vibration signal were used to extract the characteristics indicating the characteristic difference of the vibration signal for each material, and a classifier was developed through machine learning using these characteristics.

9% nickel steel has remarkable mechanical properties in a cryogenic condition and is widely used in storage containers for LNG fueled ships. Demand for laser welding rather than conventional arc welding has grown to increase manufacturing efficiency. However there are various types of heat sources which are suggested by other researchers. With that, it is difficult to select a proper heat source shape for welding conditions. The author proposed a representative heat source model that can cover most of suggested heat source models through previous studies. Welding power was fixed at 4kW and the speed was changed to 1.0m/min, 1.5m/min, and 2.0m/min respectively. The shapes of the welding heat sources were derived, and the tendency of the main parameters was also deducted. It was observed that the width and depth of the weld bead decreased as the welding speed increased through welding experiment, parameters of welding heat source are changed linearly. Based on this study, it is expected that it will be possible to estimate the shape of the heat source under untested welding conditions.