• International Journal of Internet, Broadcasting and Communication
• /
• 제9권1호
• /
• pp.9-17
• /
• 2017

This paper describes a process of developing commercial real time image recognition system with company. In this paper we will make a system that is combining an empirical kernel map method and conjugate least squares support vector machine in order to represent images in a low-dimensional subspace for real time image recognition. In the traditional approach calculating these eigenspace models, known as traditional PCA method, model must capture all the images needed to build the internal representation. Updating of the existing eigenspace is only possible when all the images must be kept in order to update the eigenspace, requiring a lot of storage capability. Proposed method allows discarding the acquired images immediately after the update. By experimental results we can show that empirical kernel map has similar accuracy compare to traditional batch way eigenspace method and more efficient in memory requirement than traditional one. This experimental result shows that proposed model is suitable for commercial real time image recognition system.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2006년도 춘계학술대회 논문집
• /
• pp.635-636
• /
• 2006

A knowledge-based system with CAD is widely used to implement a designer's know-how and a routine calculation within a system. An engineer needs to change several design parameters in an early design stage. However it is not easy to change the design parameters when it needs to update an existing model and data. In this paper, a module has been proposed to make it easy to change the design parameter so that the engineer can easily update and change the design model. Also a flexible interface of the module can easily add or extract the design knowledge.

• 한국측량학회지
• /
• 제20권3호
• /
• pp.313-321
• /
• 2002

고해상도 위성영상의 공급이 현실화됨에 따라 위성영상을 기반으로 한 수치지형도나 주제도의 신규제작 및 갱신에 많은 관심이 모이고 있다. 본 연구는 아이코노스 위성영상을 이용하여 기존의 축척 l/5,000 및 l/25,000수치지도의 수정 및 갱신 가능성을 제시하고자 하였다. 아이코노스 단영상에서 기존 수치지도상의 기준점을 활용하여 기하보정을 수행하였으며, 기존 수치지도의 3차원 등고선자료와 표고성과에 의해 수치표고모형을 추출하여 정사영상을 생성하였다. 정사보정된 위성영상과 기존 수치지도를 중첩하여 변화된 지형지물들을 스크린 디지타이징 방법으로 수정하였고, 위치정확도 분석을 위해 변하지 않은 지역의 지형지물들을 위성영상위에 직접 작도하여 비교하였다. 그 결과, 평면위치오차를 $\pm$3.35m의 평균제곱근오차로 산출할 수 있었으므로 축척 1/10,000 이하의 수치지도 갱신에는 충분히 그 활용이 가능한 것으로 판단되며, 입체영상을 사용하고 지상기준점 측량을 병행한 갱신방법을 사용한다면 축척 l/5,000이상의 대축척 수치지도 갱신도 가능할 것이다.

• 한국방사성폐기물학회:학술대회논문집
• /
• 한국방사성폐기물학회 2018년도 추계학술논문요약집
• /
• pp.217-218
• /
• 2018

• 경영과학
• /
• 제26권3호
• /
• pp.23-35
• /
• 2009

This study deals with the location management in WCDMA (Wideband Code Division Multiple Access) networks. The new location management method is the one of the many techniques used to provide the packet switched (PS) services effectively in WCDMA networks. WCDMA introduces RA (routing area) for the PS services in addition to LA (location area) for the circuit switched (CS) services. WCDMA system also adopts the cooperative paging and the combined area update which are to decrease signaling traffic using the PS network resources for the CS services. Considering the characteristics of the WCDMA networks, this study formulate into the mathematical programming problem for the location management. Rather than the existing researches which consider the single MSC/SGSN networks, we deal with the multi MSC/SGSN networks, where both MSC area and SGSN area should be determined as well. Fairness between traffic loads of MSC/SGSN and the system cost incurred to MSC/SGSN are also incorporated into our model, which make the model more realistic. We propose greedy algorithms for the problems, which consists of the merger of two neighboring areas and the movement of an area. Extensive experiment has been done based on the realistic problem examples. Followed by the analysis of parameter effect on the final solutions and the quality of final solutions obtained by our greedy algorithms. Our proposed model and analysis result can be used to determine WCDMA system areas and to predict the system performance measures by the determination.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제7권3호
• /
• pp.182-187
• /
• 2007

A fuzzy modeling method is proposed to build the dynamic model of a walking-beam reheating furnace from the recorded data. In the proposed method, the number of membership function on each variable is increased individually and the modeling accuracy is evaluated iteratively. When the modeling accuracy is satisfied, the membership functions on each variable are fixed and the structure of fuzzy model is determined. Because the training data is limited, in this process, as the number of membership function increase, it is highly possible that some rules are missing, i.e., no data in the training set corresponds to the consequent part of a missing rule. To complete the rulebase, the output of the model constructed at the previous step is used to generate the consequent part of the missing rules. Finally, in the real time application, a rolling update scheme to rulebase is introduced to compensate the change of system dynamics and fine tune the rulebase. The proposed method is verified by the application to the modeling of a reheating furnace.

• 융합신호처리학회논문지
• /
• 제8권4호
• /
• pp.297-306
• /
• 2007

모델 기준 제어(MRC)는 플랜트가 주어진 기준 모델의 거동을 추종하도록 플랜트를 제어하는 제어 기법이다. 기준 모델은 플랜트가 추종할 이상적인 궤적을 제공한다. 지금까지 많은 종류의 MRC가 제안되었지만, 본 논문에서는 모델 기준 슬라이딩 모드 제어(MRSMC)에 대해 제어 대상 플랜트가 불확실성을 갖는 단일 입출력 2차 시변 선형 시스템인 경우에 대해 연구를 수행하였다. 본 논문에서 MRSMC를 위한 기준 모델의 설계 방법이 제안하였다. 제안된 방법은 제한된 제어 입력, 기준 입력, 시스템 파라미터에 대한 정보를 사용하여 기준 모델을 선정한다. 이러한 선정 결과는 고정된 기준 모델의 선정, 계단 입력 인가시의 가변 기준 모델 갱신, 매 샘플링 시간마다 순간 기준 모델의 갱신 등으로 이용할 수 있다. 모터의 위치 제어 시스템에 대한 시뮬레이션 결과는 제안된 방법의 효용성을 보여준다.

• 한국지리정보학회지
• /
• 제23권4호
• /
• pp.1-15
• /
• 2020

도시가 확장되고 지하시설물 관련 공사가 늘어남에 따라 지하시설물 관로 네트워크를 3차원으로 분석할 수 있는 기술이 절실히 요구되고 있다. 국내에서는 2015년부터 15종의 지하정보(지하시설물, 지하구조물, 지반)를 3차원 기반 지하공간통합지도로 구축하는 사업을 진행하고 있다. 하지만 현재 3차원 지하시설물 구축은 수작업 기반으로서 구축 방법이 매우 복잡하고 지자체별 수백만 건이 넘는 대용량 데이터를 처리하기에는 시간과 비용이 많이 발생한다. 본 논문은 3차원 지하시설물 모델의 가공 및 갱신 자동화 구축 프레임워크를 제시함으로써 3차원 지하시설물 모델을 최소비용으로 신속하게 구축하는 방안을 수립하였다. 본 연구에서 개발된 지하시설물 가공 및 부분갱신 자동화 기술들은 지하공간통합지도 구축사업에 즉시 현장적용이 가능할 것으로 기대한다.

• Journal of Information Processing Systems
• /
• 제8권1호
• /
• pp.55-66
• /
• 2012

This paper presents a dual modeling method that simulates the graphic and haptic behavior of a volumetric deformable object and conveys the behavior to a human operator. Although conventional modeling methods (a mass-spring model and a finite element method) are suitable for the real-time computation of an object's deformation, it is not easy to compute the haptic behavior of a volumetric deformable object with the conventional modeling method in real-time (within a 1kHz) due to a computational burden. Previously, we proposed a fast volume haptic rendering method based on the S-chain model that can compute the deformation of a volumetric non-rigid object and its haptic feedback in real-time. When the S-chain model represents the object, the haptic feeling is realistic, whereas the graphical results of the deformed shape look linear. In order to improve the graphic and haptic behavior at the same time, we propose a dual modeling framework in which a volumetric haptic model and a surface graphical model coexist. In order to inspect the graphic and haptic behavior of objects represented by the proposed dual model, experiments are conducted with volumetric objects consisting of about 20,000 nodes at a haptic update rate of 1000Hz and a graphic update rate of 30Hz. We also conduct human factor studies to show that the haptic and graphic behavior from our model is realistic. Our experiments verify that our model provides a realistic haptic and graphic feeling to users in real-time.

• International journal of advanced smart convergence
• /
• 제8권4호
• /
• pp.68-74
• /
• 2019

Along with the deeper architecture in the deep learning approaches, the need for the data becomes very big. In the real problem, to get huge data in some disciplines is very costly. Therefore, learning on limited data in the recent years turns to be a very appealing area. Meta-learning offers a new perspective to learn a model with this limitation. A state-of-the-art model that is made using a meta-learning framework, Meta-SGD, is proposed with a key idea of learning a hyperparameter or a learning rate of the fast adaptation stage in the outer update. However, this learning rate usually is set to be very small. In consequence, the objective function of SGD will give a little improvement to our weight parameters. In other words, the prior is being a key value of getting a good adaptation. As a goal of meta-learning approaches, learning using a single gradient step in the inner update may lead to a bad performance. Especially if the prior that we use is far from the expected one, or it works in the opposite way that it is very effective to adapt the model. By this reason, we propose to add a weight term to decrease, or increase in some conditions, the effect of this prior. The experiment on few-shot learning shows that emphasizing or weakening the prior can give better performance than using its original value.