• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1150-1158
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• 2010

In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problem. First, in preprocessing part, we use a CCD camera to obtain a picture frame in real-time. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. We use an AdaBoost algorithm proposed by Viola and Jones, which is exploited for the detection of facial image area between face and non-facial image area. As the feature extraction algorithm, PCA method is used. In this study, the PCA method, which is a feature extraction algorithm, is used to carry out the dimension reduction of facial image area formed by high-dimensional information. Secondly, we use pRBFNNs to identify the ID by recognizing unique pattern of each person. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. Coefficients of connection weight identified with back-propagation using gradient descent method. The output of pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of the Particle Swarm Optimization. The proposed pRBFNNs are applied to real-time face recognition system and then demonstrated from the viewpoint of output performance and recognition rate.

• Korean Journal of Construction Engineering and Management
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• v.12 no.1
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• pp.43-52
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• 2011

Unnecessary transportation of resources are one of the major causes that adversely affect construction site work productivity. Therefore, layout related studies have been conducted with efforts to develop management technologies and techniques to minimize the resource transportation made at site-level. However, although the necessity for floor-level layout planning studies has been increasing as buildings have become larger and floors have become more complicated, studies to optimize the transportation of materials inside buildings are currently not being actively conducted. Therefore, in this study, a model was developed using genetic algorithms(GA) that will enable the optimization of the locations of finishing materials on the work-floor. With the established model, the arrangement of diverse materials on complicated floors can be planned and the optimized material layout planning derived from the model can minimize the total material transportation time spent by laborers during their working day. In addition, to calculate travel distances between work sites and materials realistically, the concept of actual travel distances was applied. To identify the applicability of the developed model and compare it with existing methodologies and analyze it, the model was applied to actual high-rise residential complexes.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.7
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• pp.897-903
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• 2010

Used gas to the vehicle fuel are the problems of the 'survival' beyond the 'quality of life' improvements and revive a new paradigm of 'sustainable development' which pursues economic development in harmony with environmental conservation. However, the fatalities caused by explosions and fires increases every year with the increase in the use of LPG; gas accidents in large-scale storage facilities also cause severe damage to property. In this study, a suitable storage tank is designed in which the surface area of the fuel exposed to flames is minimized in order to prevent explosions; thus, the occurrences of explosions in underground storage tanks can be minimized. According to the optimum design of storage tank obtained in this study, underground containment space was minimized; the minimized diameter and length of a 20-ton storage tank was 3 m and 4.83 m, respectively. Thus, safety was ensured since surface area exposed to flames decreased by 89.4%, which is less than the exposed surface area in the currently used storage tanks.

• Analytical Science and Technology
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• v.25 no.5
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• pp.292-299
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• 2012

GC/MS has been utilized for many applications due to great resolution and reproducibility, which made it possible to build up the database of mass spectrum, while HS-SPME has the advantage of solventfree extraction of volatile compounds. The combination of these two methods, HS-SPME GC/MS, enabled many scientific applications with various possibilities. In this study, the analysis of trail pheromone excreted from live Camponotus japonicus with the feature of solvent-free extraction was carried out and the optimization for this analysis was performed. The major compounds detected were n-decane, n-undecane, and n-tridecane. Optimization for the best detection of these hydrocarbons was processed in the point of SPME parameter (selection of fiber, extraction temperature, extraction time, etc.). The advantage of the analysis of live sample is to analyze phenomenon right after it is excreted by ants. But the experimental process has restriction of extraction temperature and time because of the analysis of live ants. Establishing the process of HS-SPME GC/MS applied to live samples shown in this study can be a breakthrough for the ecofriendly and ethical research of live things.

• Journal of KIISE:Software and Applications
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• v.32 no.7
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• pp.581-591
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• 2005

Collaborative filtering systems have problems involving sparsity and the provision of recommendations by making correlations between only two users' preferences. These systems recommend items based only on the preferences without taking in to account the contents of the items. As a result, the accuracy of recommendations depends on the data from user-rated items. When users rate items, it can be expected that not all users ran do so earnestly. This brings down the accuracy of recommendations. This paper proposes a collaborative recommendation method for extracting typical group preferences using user-item matrix optimization and user profiles in collaborative tittering systems. The method excludes unproven users by using entropy based on data from user-rated items and groups users into clusters after generating user profiles, and then extracts typical group preferences. The proposed method generates collaborative user profiles by using association word mining to reflect contents as well as preferences of items and groups users into clusters based on the profiles by using the vector space model and the K-means algorithm. To compensate for the shortcoming of providing recommendations using correlations between only two user preferences, the proposed method extracts typical preferences of groups using the entropy theory The typical preferences are extracted by combining user entropies with item preferences. The recommender system using typical group preferences solves the problem caused by recommendations based on preferences rated incorrectly by users and reduces time for retrieving the most similar users in groups.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.722-728
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• 2012

Urban sewer systems has a limitation of capacity of rainwater storage and problem of occurrence of untreated sewage, so adopting a storage facility for sewer flooding prevention and urban non-point pollution reduction has a big attention. The Korea Ministry of Environment has recently introduced a new concept of "multi-functional storage facility", which is crucial not only in preventive stormwater management but also in dealing with combined sewer overflow and sanitary sewer discharge, and also has been promoting its adoption. However, reserving a space for a single large-scale storage facility might be difficult especially in urban areas. Thus, decentralized construction of small- and midium-sized storage facilities and its operation have been introduced as an alternative way. In this paper, we propose a model predictive control scheme for an optimized operation of distributed storage facilities and sewer networks. To this aim, we first describe the mathematical model of each component of networks system which enables us to analyze its detailed dynamic behavior. Second, overflow locations and volumes will be predicted based on the developed network model with data on the external inflow occurred at specific locations of the network. MPC scheme based on the introduced particle swarm optimization technique then produces the optimized the gate setting for sewer network flow control, which minimizes sewer flooding and maximizes the potential storage capacity. Finally, the operational efficacy of the proposed control scheme is demonstrated by simulation study with virtual rainstorm event.

• Applied Chemistry for Engineering
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• v.30 no.4
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• pp.421-428
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• 2019

This paper describes a methode to extract yellow pigment from curcuma and turmeric containing natural color curcumin whose target color indexes of L, a, and b were 87.0 7.43, and 88.2, respectively. The pH range and extraction temperature used for the reaction surface analysis method were from pH 3 to pH 7 and between 40 and $70^{\circ}C$, respectively for both natural products. A central synthesis planning model combined with the method was used to obtain optimal extraction conditions to produce the color close to target. Results and regression equations show that the color space and difference of curcuma and turmeric have the greatest influence on the value. In the case of curcuma, the optimum conditions to satisfy all of the response theoretical values of color coordinates of L (74.67), a (5.69), and b (70.08) were at the pH and temperature of 3.43 and $54.8^{\circ}C$, respectively. The experimentally obtained L, a, and b, values under optimal conditions were 72.92, 5.32, and 72.17, respectively. For the case of turmeric, theoretical numerical color coordinates of L, a, and b, under the pH of 5.22 and temperature of $50.4^{\circ}C$ were 82.02, 7.43, and 72.86 respectively. Whereas, the experiment results were L (81.85), a (5.39), and b (71.58). Both cases showed an error range within 1%. Therefore, it is possible to obtain a low error rate when applying the central synthesis planning model to the reaction surface analysis method as an optimization process of the dye extraction of natural raw materials.

• Journal of the Korea Computer Graphics Society
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• v.27 no.5
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• pp.63-71
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• 2021

Among drone autonomous flight technologies, obstacle avoidance is a very important technology that can prevent damage to drones or surrounding environments and prevent danger. Although the LiDAR sensor-based obstacle avoidance method shows relatively high accuracy and is widely used in recent studies, it has disadvantages of high unit price and limited processing capacity for visual information. Therefore, this paper proposes an obstacle avoidance algorithm for drones using camera-based PPO(Proximal Policy Optimization) reinforcement learning, which is relatively inexpensive and highly scalable using visual information. Drone, obstacles, target points, etc. are randomly located in a learning environment in the three-dimensional space, stereo images are obtained using a Unity camera, and then YOLov4Tiny object detection is performed. Next, the distance between the drone and the detected object is measured through triangulation of the stereo camera. Based on this distance, the presence or absence of obstacles is determined. Penalties are set if they are obstacles and rewards are given if they are target points. The experimennt of this method shows that a camera-based obstacle avoidance algorithm can be a sufficiently similar level of accuracy and average target point arrival time compared to a LiDAR-based obstacle avoidance algorithm, so it is highly likely to be used.

• Journal of Astronomy and Space Sciences
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• v.25 no.2
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• pp.181-198
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• 2008

Designing satellite constellations providing partial coverage of certain regions becomes more important as small low-altitude satellites receives an increasing attention due to its cost-effectiveness analysis. Generally, Walker's method is a standard constellation method for global coverage but not effective for partial coverage. The purpose of this study is to design optimal constellation of satellites for effective observation in Korean peninsula regions. In this study, a new constellation design method is presented for partial coverage, using direct control of satellites' orbital elements. And also, a ground repeating circular orbit is considered for each satellite's orbit with the Earth oblateness effect. As the results, at least four satellites are required to observe the Korean peninsula regions effectively when minimum elevation angle is assumed as 12 degrees. The results from new method are better than those from the best Walker method. The proposed algorithm will be useful to design satellite constellation missions of Korea in future.

• Journal of the Korean GEO-environmental Society
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• v.17 no.10
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• pp.5-11
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• 2016

In this study, the factors affecting commercialization of $Pt/TiO_2$ catalyst, which can oxidize HCHO at room temperature, was investigated. In order to determine the optimum noble metal loading, the catalytic activity was evaluated by varying the Pt loadings; the best catalytic activity was achieved for 1 wt% of Pt. In addition, the catalyst prepared under the reduction condition showed an excellent HCHO oxidation conversion at room temperature. Based on these results, it was confirmed that the activity could be changed by oxidation state of active metal, and in case of Pt, metallic Pt ($Pt^0$) species was more active on HCHO oxidation at room temperature. As a result of evaluating an effect of space velocity to determine the optimum operating condition, it was found that in the lower space velocity, conversion rate of HCHO was increased due to increase of catalyst bed. Catalytic activity was greater in the presence of moisture than in its absence. Through above results, the key factors for commercialization of oxidation catalyst, which was operated at room temperature even without any additional energy source was confirmed.