The results of the survey on water utilization status, the wasted water factor, the awareness, and the education and promotional activities of water saving in Daejeon City are as follows: The percentage of using tap valve with a closure was 66% when showering. 74% of water was used with closing the tap valve when washing faces with no water needed, it was still considered that there existed a wasting water. The most wasting reasons of water were found to be shower, bath, and laundry in order. In the awareness of practicing tap water saving, 9.1% of respondents acted actively, 53.4% of them were trying to practice it, and more than 63% had a positive awareness. In the contents of practicing saving water, locking water when soaping while showering, non-laundry of small quantity, and using cups when brushing teeth were top priorities. About 50% of the reasons for saving water was to practice purely saving water, when saving for economic help was excluded. The level of water saving awareness was not high when considering that the ratio of usage without water saving equipment and installation, and using method was relatively high when moving in. In order to make usage of water saving equipment more common, it was deemed necessary to provide information on the purchase of water saving equipment and to promote and educate the efficiency of saving of related products. More than about 90% of the respondents responded that water saving education or promotional activities had an effect of improving water saving awareness. The most effective method of education and promotional activities was found to be 40.4% by mass media activities, and 21.7% by promotions through mobile devices.

우리나라의 해운산업에 있어서 부족한 선원들의 중장기적 확보 전략을 세우고, 향후에도 계속해서 안정적으로 선원을 확보할 수 있는 방법을 모색하고자 본 연구를 진행하였다. 연구의 주요내용은 한국 송입 인도네시아 선원의 선상직무환경의 여러 가지 요소들, 즉 이문화, 이가정성, 이사회성, 구속적 근무특성이 조직유효성, 즉 직무만족과 조직몰입, 이직의도에 미치는 영향요인을 실증적으로 검증하였다.

Visual place recognition is widely researched area in robotics, as it is one of the elemental requirements for autonomous navigation, simultaneous localization and mapping for mobile robots. However, place recognition in changing environment is a challenging problem since a same place look different according to the time, weather, and seasons. This paper presents a feature extraction method using a deep convolutional auto-encoder to recognize places under severe appearance changes. Given database and query image sequences from different environments, the convolutional auto-encoder is trained to predict the images of the desired environment. The training process is performed by minimizing the loss function between the predicted image and the desired image. After finishing the training process, the encoding part of the structure transforms an input image to a low dimensional latent representation, and it can be used as a condition-invariant feature for recognizing places in changing environment. Experiments were conducted to prove the effective of the proposed method, and the results showed that our method outperformed than existing methods.

실시간 홍수예측모형의 구성에서 장래 강우 양상(지속기간, 강우강도 등)에 대한 가정으로 인하여 홍수예측의 신뢰성을 높이기 어려웠다는 점을 해결하기 위하여 현재까지의 강우, 수위 및 상류지역의 수위를 기반으로 장래 수위를 예측할 수 있는 회귀모형을 구성하였다. 대상유역인 대전광역시의 도심하천 구간에서 각 수위 및 강우관측소들 간의 자료들을 활용하여 최대 2시간 후의 수위변화를 예측할 수 있는 모형을 구성하였다. 각각의 선행시간에 대하여 예측한 결과 실체

FastSLAM is a factored solution to SLAM problem using a Rao-Blackwellized particle filter. In this paper, we propose a practical FastSLAM implementation method using an infrared camera for indoor environments. The infrared camera is equipped on a Pioneer3 robot and looks upward direction to the ceiling which has infrared tags with the same height. The infrared tags are detected with the infrared camera as measurements, and the Nearest Neighbor method is used to solve the unknown data association problem. The global map is successfully built and the robot pose is predicted in real time by the FastSLAM2.0 algorithm. The experiment result shows the accuracy and robustness of the proposed method in practical indoor environment.

Recently, simultaneous localization and mapping (SLAM) approaches employing Rao-Blackwellized particle filter (RBPF) have shown good results. However, no research is conducted to analyze the result representation of SLAM using RBPF (RBPF-SLAM) when particle diversity is preserved. After finishing the particle filtering, the results such as a map and a path are stored in the separate particles. Thus, we propose several result representations and provide the analysis of the representations. For the analysis, estimation errors and their variances, and consistency of RBPF-SLAM are dealt in this study. According to the simulation results, combining data of each particle provides the better result with high probability than using just data of a particle such as the highest weighted particle representation.

Effective tools which can alleviate the complexity and computational load problem in collision-free motion planning for multi-agent system have steadily been demanded in robotics field. To reduce the complexity, the extended collision map (ECM) which adopts decoupled approach and prioritization is already proposed. In ECM, the collision regions which represent the potential collision of robots are calculated using the computational power; the complexity problem is not resolved completely. In this paper, we propose a mathematical analysis of the extended collision map; as a result, we formulate the collision region as an equation with 5–8 variables. For mathematical analysis, we introduce realistic assumptions as follows; the paths of robots can be approximated to a straight line or an arc and the robots move with uniform velocity or constant acceleration near the intersection between paths. Our result reduces the computational complexity in comparison with the previous result without losing optimality, because we use simple but exact equations of the collision regions. This result can be widely applicable to coordinated multi-agent motion planning.

It is well known that mathematical solutions for multi-agent planning problems are very difficult to obtain due to the complexity of mutual interactions among multi-agent. Most of the past research results thus are based on the probabilistic completeness. However, the practicality and effectiveness of the solution from the probabilistic completeness is significantly reduced by heavy computational burden. In this paper, we propose a practically applicable solution technique for multi-agent planning problems, which assures a reasonable computation time and a real world application for more than 3 multi-agents for the case of general shaped paths in agent movement. First, to reduce the computation time, a collision map is utilized for detecting potential collisions and obtaining collision-free solutions for multi-agents. Second, to minimize the maximum of multi-agent task execution time, a method is developed for selecting an optimal priority order. Simulations are finally provided for more than 20 agents to emphasize the effectiveness of the proposed interactive approach to multi-agent planning problems.

The Mobile robots are increasingly being used to perform tasks in unknown environments. The potential of robots to undertake such tasks lies in their ability to intelligently and efficiently search in an environment. An algorithm has been developed for robots which explore the environment to measure the physical properties (dust in this paper). While the robot is moving, it measures the amount of dust and registers the value in the corresponding grid cell. The robot moves from local maximum to local minimum, then to another local maximum, and repeats. To reach the local maximum or minimum, simple gradient following is used. Robust estimation of the gradient using perturbation/correlation, which is very effective when analytical solution is not available, is described. By introducing the probability of each grid cell, and considering the probability distribution, the robot doesn’t have to visit all the grid cells in the environment still providing fast and efficient sensing. The extended algorithm to coordinate multiple robots is presented with simulation results.

시가지의 확장과 개발 등으로 인한 도시에서의 강우-유출현상은 자연하천유역에 비하여 더욱 복잡한 양상을 가지며, 실제 유역의 변화로 인하여 모형의 적용이 매우 어려운 편이다. 본 연구에서는 SW 모형과 전문가 시스템을 적용하여 도시화 유역에서의 유출 특성을 파악하였다. 연구 유역으로는 대전광역시에서 노은지역을 선정하였으며, 실제 유역 및 시설자료, 강우, 유출자료와 다양한 강우강도식을 사용하였다. 매개변수의 추정 과정을 위하여 전문가시스템을 사용하였으며,

도시유역의 수자원 개발 및 재해예방을 위해서는 정확한 입력정보의 생성방안을 개발하였고, 급속한 도시화의 영향에 따른 수자원 및 환경문제를 보다 효율적으로 해결하기 위하여 전문가시스템의 개발 및 적용방안을 제안하였다. ARC/INFO를 사용한 지리정보체계의 적용과 인공위성 관측자료를 사용함으로써 넓은 공간에서 시간적 변화가 큰 안양천 유역의 자료들을 합리적으로 획득하였으며, CLIPS 6.0을 적용하여 전문가시스템 ESPE를 개발하였다. 재현결과가 측정자

급속한 도시화의 영향에 따른 수자원 및 환경문제를 보다 효율적으로 해결하기 위하여 전문가 시스템의 개발 및 적용방안을 제안하였다. 이에 따라 도시유역의 유출 및 수질에 영향을 미치는 주요 매개변수들을 선별하고 민감도 분석 등을 통해 그 거동특성을 제시하였으며, 이러한 특성들을 바탕으로 효과적 매개변수 결정법칙 등을 제안하였다. CLIPS 6.0을 적용하여 ‘사실’과‘규칙’을 기본으로 한 전문가 시스템 ESPE를 개발하였으며, 이를 안양천 유역에 적용하였