As technique that can contribute in quality improvement in design process to overcome shortcoming of traditional quality control, call design or development department quality control activity that is achieved to reduce gun damage shuddering at circle minimizing change or side effect of product performance as off-line quality control. This paper discuss optimal process design of investment projects expansion and replacement investment on each line or individual in the production. Generally optimal plant design has add to a few method by Subsidiary means with use a especial method. And then in this paper, a Robust design is presented, which may be effective to the processes appraisal or improvement. We propose that should make a optimal plant design model for reducing field failure rate to assign by real data on different factors in plant system. Using this model, robust design of taguchi method used in this comprehensive method for reducing field failure rate in plant system.

Each method for economic evaluation has its own characteristics. Therefore adoption of each of them in evaluation production investment project results in many problems. Hence combination & modification of them are required to perform more accurate evaluation about investment project. This paper discuss evaluation method of investment projects expansion and replacement investment on each line or individual in the production. Generally investment evaluation method has add to a few method by Subsidiary means with use a especial method. And then in this paper, a Taguchi Techniques is presented, which may be effective to the facilities appraisal or improvement. We propose a decision model to incorporates the values assigned by a group of experts on different factors in production. Using this model, SN ratio of taguchi method for each of subjective factors as well as values of weights are used in this comprehensive method for reducing production rate in production management.

The critical problem in dealing with multiple characteristics is how to compromise the conflict among the selected levels of the design parameters for each individual characteristic. In this study, First, Methodology using SN ratio optimized by univariate technique is proposed and a parameter design procedure to achieve the optimal compromise among several different response variables is developed. Second, to solve the issue on the optimal design for multiple quality characteristics, this study modelled the expected loss function with cross-product terms among the characteristics and derived range of the coefficients of the terms. The model will be used to determine the global optimal design parameters where there exists the conflict among the characteristics, which shows difference in optimal design parameters for the individual characteristics. Third, this paper propose a decision model to incorporates the values assigned by a group of experts on different factors in weighting decision of characteristic. Using this model, SN ratio of taguchi method for each of subjective factors as well as values of weights are used in this comprehensive method for weighting decision of characteristic.

In this paper, under JIT kanban system designed by Moeeni, each performance measures (service level, inventory level) identify the robust optimal level at a uncertain environment, and when there are multiple performance characteristics, it propose the optimal design-method and the optimal level decision-method, which consider multiple performance characteristics.

In this paper, we present auto-annotation tool and synthetic dataset using 3D CAD model for deep learning based object detection. To be used as training data for deep learning methods, class, segmentation, bounding-box, contour, and pose annotations of the object are needed. We propose an automated annotation tool and synthetic image generation. Our resulting synthetic dataset reflects occlusion between objects and applicable for both underwater and in-air environments. To verify our synthetic dataset, we use MASK R-CNN as a state-of-the-art method among object detection model using deep learning. For experiment, we make the experimental environment reflecting the actual underwater environment. We show that object detection model trained via our dataset show significantly accurate results and robustness for the underwater environment. Lastly, we verify that our synthetic dataset is suitable for deep learning model for the underwater environments.

Recently, the safety in vehicle also has become a hot topic as self-driving car is developed. In passive safety systems such as airbags and seat belts, the system is being changed into an active system that actively grasps the status and behavior of the passengers including the driver to mitigate the risk. Furthermore, it is expected that it will be possible to provide customized services such as seat deformation, air conditioning operation and D.W.D (Distraction While Driving) warning suitable for the passenger by using occupant information. In this paper, we propose robust vehicle occupant detection algorithm based on RGB-Depth-Thermal camera for obtaining the passengers information. The RGB-Depth-Thermal camera sensor system was configured to be robust against various environment. Also, one of the deep learning algorithms, OpenPose, was used for occupant detection. This algorithm is advantageous not only for RGB image but also for thermal image even using existing learned model. The algorithm will be supplemented to acquire high level information such as passenger attitude detection and face recognition mentioned in the introduction and provide customized active convenience service.

국립원예특작과학원에서는 2011년 거베라 신품종 ‘Purple Queen’을 품종 육성하였다. ‘Purple Queen’은 2007년 절화장이 긴 ‘Selma’와 자주색 반겹꽃 ‘Marathon’을 교배하여 얻은 실생계통으로부터 2007년부터 2011년까지 5년 동안의 생육특성검정을 거쳐 선발된 절화용 품종이다. 꽃은 암갈심의 자주색(RHS RP66B)으로 평균 직경이 11.4 cm인 반겹꽃 대륜계통이며, 내화경과 화심장은 각각 6.1 cm와 2.3 cm이다. 화경장은 50.3 cm 정도로 매우 길며, 꽃목 직경은 5.0 mm 정도로 굵다. 절화수명은 12.2일로 대조품종에 비해 3일 이상 , 연간 채화량도 51.4본/주로 대조품종보다 4.4본/주 더 많은 다수성 품종이다.

거베라 ‘핑크멜로디(Pink Melody)’는 파스텔 톤의 밝은 분홍색(RHS R55D) 반겹꽃 품종으로, 2011년에 수원 국립원예특작과학원에서 품종 육성되었다. 2007년 분홍색 반겹꽃 ‘에타(Eta)’와 ‘파스칼(Pascal)’을 각각 모본과 부본으로 사용하여 인공교배를 실시하고 당해에 실생 계통을 양성하였으며, 그 중 화색이 선명하고 화형이 안정된 ‘07B3-71’ 계통을 개체 선발하였다. 선발된 계통에 대하여 2008년부터 2010년까지 개체증식 및 개화특성 검정, 1·2차 생육특성검정을 수행하였고, 2011년에는 ‘원교B3-46호’로 계통명을 부여한 후, 화색과 화형이 유사하며 교배모본으로도 사용된 ‘에타’를 대조품종으로 하여 3차 특성검정, 안정성·균일성에 대한 연차별 재현성 및 소비자 기호도 평가를 수행한 결과, 화색과 화형이 우수한 다수성 품종으로 그 우수성이 인정되어 ‘핑크멜로디’로 명명되어 품종등록 되었다. ‘핑크멜로디’는 화경과 내화경이 각각 11.4cm, 7.3cm로 대조품종에 비해 0.6cm, 1.5cm 정도 더 큰 대륜계통의 절화용 품종이다. 꽃대길이가 45.2cm로 대조품종에 비해 약간 짧은 편이었으나, 꽃대가 상부 4.2mm, 중부 5.4mm로 굵어 꽃목굽음이나 경절현상 등의 생리장해 발생이 적었고, 절화수명도 10.8일로 대조품종에 비해 1.5일 정도 더 길었다. 특히, 하계고온 및 동계저온기에도 꽃눈분화가 지속적으로 이루어져 연간 고루 채화할 수 있었으며, 연간 채화량도 주당 52.9본으로 대조품종보다 5본정도 더 많았다.

농촌진흥청 국립원예특작과학원에서는 2007년 백색 반겹꽃 'Wonder King'과 연녹빛의 백색 반겹꽃 'Ever Green'을 교배하여 얻은 실생계통으로부터 2007년부터 2010년까지 4년 동안의 생육특성검정을 거쳐 초세가 강건한 흑심의 순백색(RHS W155D) 반겹꽃 절화용 거베라 신품종 'Whiteny'를 품종육성하였다. 꽃의 직경이 11.5 cm인 대륜계통이며, 내화경과 화심장이 각각 7.8 cm와 2.2 cm이었다. 절화장은 52.2cm로

본 논문은 얼굴의 표정과 몸 동작을 광학식 동작 포착장비를 활용하여 동시에 포착하는 경우에 있어 얼굴 부위 마커들에 대한 노이즈에 강건한 데이터 처리 방법에 대해 다룬다. 일반적인 얼굴 표정만 포착하는 경우와 달리, 몸의 움직임과 동시에 포착할 경우 포착용 카메라가 멀리 있어 얼굴에 붙인 마커들의 궤적 데이터는 특별한 처리를 요한다. 특히 궤적의 표식화, 빈 곳 메우기, 노이즈 제거의 과정이 필수적이며, 이러한 과정을 위해 본 논문에서는 지역좌표에 기반을 둔 궤적 데이터 처리 방법을 제안한다. 지역 좌표는 강체변형에 불변한 특징이 있으며, 얼굴모양의 국지적인 변화를 의미하여, 궤적 데이터처리에 효과적으로 활용 될 수 있음을 보였다. 또한 제안한 방법을 활용하여 애니메이션을 제작해 실제 제작 환경에 적용 가능함을 보였다.