• Tunnel and Underground Space
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• v.27 no.1
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• pp.12-25
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• 2017

In local underground mines heavily depending on the natural ventilation, ducted fan auxiliary ventilation system is strongly recommended instead of the total mine ventilation system requiring large capital and operating costs. Optimizing the installation of ducted fans in series in long large-opening mines is required to assure the economy and efficiency of the ventilation system. The two most critical design parameters for optimization are the wall separation distance and gap length between adjoining ducts. This study aims at deriving the optimal values for those two parameters concerning the economic and environmental aspects through the extensive CFD analysis, which minimizes pressure loss, leakage and entrainment of the contaminated air in the gap space. The ranges of the wall separation distance and gap length for study are selected by taking into consideration the existing recommendations and guidelines. The ultimate goal is to optimize the auxiliary ventilation system using ducted fans in series to provide a reliable and efficient solution to maintain clean and safe workplace environment in local long underground mines.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.155-161
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• 2020

In general, optimization problems are difficult to solve simply. The reason is that the given problem is solved as soon as it is simple, but the more complex it is, the very large number of cases. This study is about the optimization of AI neural network. What we are dealing with here is the relief method for constructing AI network. The main topics deal with non-deterministic issues such as the stability and unstability of the overall network state, cost down and energy down. For this one, we discuss associative memory models, that is, a method in which local minimum memory information does not select fake information. The simulated annealing, this is a method of estimating the direction with the lowest possible value and combining it with the previous one to modify it to a lower value. And nonlinear planning problems, it is a method of checking and correcting the input / output by applying the appropriate gradient descent method to minimize the very large number of objective functions. This research suggests a useful approach to relief method as a theoretical approach to solving optimization problems. Therefore, this research will be a good proposal to apply efficiently when constructing a new AI neural network.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.55-79
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• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.39-47
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• 2010

A research of image-based articulated pose estimation has some problems such as detection of human feature, precise pose estimation, and real-time performance. In particular, various methods are currently presented for recovering many joints of human body. We propose the novel numerical inverse kinematics improved with the UKF(unscented Kalman filter) in order to estimate the human pose in real-time. An existing numerical inverse kinematics is required many iterations for solving the optimal estimation and has some problems such as the singularity of jacobian matrix and a local minima. To solve these problems, we combine the UKF as a tool for optimal state estimation with the numerical inverse kinematics. Combining the solution of the numerical inverse kinematics with the sampling based UKF provides the stability and rapid convergence to optimal estimate. In order to estimate the human pose, we extract the interesting human body using both background subtraction and skin color detection algorithm. We localize its 3D position with the camera geometry. Next, through we use the UKF based numerical inverse kinematics, we generate the intermediate joints that are not detect from the images. Proposed method complements the defect of numerical inverse kinematics such as a computational complexity and an accuracy of estimation.

• Journal of Community Nutrition
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• v.3 no.2
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• pp.103-109
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• 2001

With a continuous and steep increase in life expectancies, Korean society is expected to enter the aged society by year 2020. And as the number of elderly increases, the burden of medical and health care expenses for them becomes greater in every developed society. Hence, the preventive approach for chronic degenerative diseases remains to be the best solution for the above-mentioned problem and warranting optimal nutrition would be one of the most important approaches. We performed a nutrition survey on 585 older adults of 50 years of age and older, residing in 3 metropolitan areas including Daejun, Daeku and Kwangju. Anthropometry, including body composition analysis based on the bioelectrical impedance analysis using InBody 3.0 and dietary intake survey by semi-quantitative flood frequency questionnaires, were used in collecting data. As one of the most important factors affecting the health and nutritional status of the elderly, we focused on living arrangements. Analyses were performed on the data from 550 subjects only, after excluding statistical outliers. Three hundred and sixty-eight of them(66.9%) were female and the number of elderly(65 years of age and older) was 485. According to the statistical analyses, the female elderly were more vulnerable to malnutrition than the male elderly. And the older they befame, the less adequate they were in nutrient intake. In addition to this, the elderly living alone showed the poorest patterns of nutrient intake and anthropometry. Although the exact effect of living alone could differ among different sex-age groups, the fact that the elderly living alone is vulnerable to malnutrition would remain concrete. This raises the utmost necessity of nutrition intervention to be devised and directed to the targeted population, namely the living-alone elderly from the government level. The intervention may include nutrition education, nutrition counseling and support In forms of meal service by networking the efforts of central as well as local governments to ensure the good health of the Korean elderly.

• Advances in aircraft and spacecraft science
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• v.2 no.1
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• pp.95-108
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• 2015

Automatic Dependent Surveillance Broadcast (ADS-B) is quickly being adopted by aviation safety authorities around the world as the standard for aircraft tracking. The technology provides the opportunity for live tracking of aircraft positions within range of an ADS-B receiver stations. Currently these receiver stations are bound by land and local infrastructural constraints. As such there is little to no coverage over oceans and poles, over which many commercial flights routinely travel. A low cost space based ADS-B receiving system is proposed as a constellation of small satellites. The possibility for a link between aircraft and satellite is dependent primarily on proximity. Calculating the likelihood of a link between two moving targets when considering with the non-periodic and non-uniform nature of actual aircraft flight-paths is non-trivial. This analysis of the link likelihood and the performance of the tracking ability of the satellite constellation has been carried out by a direct simulation of satellites and aircraft. Parameters defining the constellation (satellite numbers, orbit size and shape, orbit configuration) were varied between reasonable limits. The recent MH370 disappearance was simulated and potential tracking and coverage was analysed using an example constellation. The trend of more satellites at a higher altitude inclined at 60 degrees was found to be the optimal solution.

• The Korean Journal of Pain
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• v.23 no.3
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• pp.190-197
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• 2010

Background: Conventional spinal saddle block is performed with the patient in a sitting position, keeping the patient sitting for between 3 to 10 min after injection of a drug. This amount of time, however, is long enough to cause prolonged postoperative urinary retention. The trend in this block is to lower the dose of local anesthetics, providing a selective segmental block; however, an optimal dose and method are needed for adequate anesthesia in variable situations. Therefore, in this study, we evaluated the question of whether only 1 min of sitting after drug injection would be sufficient and safe for minor anorectal surgery. Methods: Two hundred and sixteen patients undergoing minor anorectal surgery under spinal anesthesia remained sitting for 1 min after completion of subarachnoid administration of 1 ml of a 0.5% hyperbaric bupivacaine solution (5 mg). They were then placed in the jack-knife position. After surgery, analgesia levels were assessed using loss of cold sensation in the supine position. The next day, urination and 11-point numeric rating scale (NRS) for postoperative pain were assessed. Results: None of the patients required additional analgesics during surgical manipulation. Postoperative sensory levels were T10 [T8-T12] in patients, and no significant differences were observed between sex (P = 0.857), height (P = 0.065), obesity (P = 0.873), or age (P = 0.138). Urinary retention developed in only 7 patients (3.2%). In this group, NRS was $5.0{\pm}2.4$ (P = 0.014). Conclusions: The one-minute sitting position for spinal saddle block before the jack-knife position is a safe method for use with minor anorectal surgery and can reduce development of postoperative urinary retention.

• International Journal of Fluid Machinery and Systems
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• v.10 no.3
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• pp.240-253
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• 2017

Latin hypercube sampling is widely used design-of-experiment technique to select design points for simulation which are then used to construct a surrogate model. The exploration/exploitation properties of surrogate models depend on the size and distribution of design points in the chosen design space. The present study aimed at evaluating the performance characteristics of various surrogate models depending on the Latin hypercube sampling (LHS) procedure (sample size and spatial distribution) for a diverse set of optimization problems. The analysis was carried out for two types of problems: (1) thermal-fluid design problems (optimizations of convergent-divergent micromixer coupled with pulsatile flow and boot-shaped ribs), and (2) analytical test functions (six-hump camel back, Branin-Hoo, Hartman 3, and Hartman 6 functions). The three surrogate models, namely, response surface approximation, Kriging, and radial basis neural networks were tested. The important findings are illustrated using Box-plots. The surrogate models were analyzed in terms of global exploration (accuracy over the domain space) and local exploitation (ease of finding the global optimum point). Radial basis neural networks showed the best overall performance in global exploration characteristics as well as tendency to find the approximate optimal solution for the majority of tested problems. To build a surrogate model, it is recommended to use an initial sample size equal to 15 times the number of design variables. The study will provide useful guidelines on the effect of initial sample size and distribution on surrogate construction and subsequent optimization using LHS sampling plan.

• The KIPS Transactions:PartB
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• v.18B no.4
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• pp.193-200
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• 2011

This paper proposes a low-cost visual analyzer algorithm of human body motion for real-time applications such as human-computer interfacing, virtual reality applications in medicine and telemonitoring of patients. To reduce cost of its use, we design the algorithm to use a single camera. To make the proposed system to be used more conveniently, we avoid from using optical markers. To make the proposed algorithm be convenient for real-time applications, we design it to have a closed-form with high accuracy. To design a closed-form algorithm, we propose an idea that formulates motion of a human body joint as a 2D universal joint model instead of a common 3D spherical joint model, without any kins of approximation. To make the closed-form algorithm has high accuracy, we formulates the estimation process to be an optimization problem. Thus-desined algorithm is applied to each joint of the human body one after another. Through experiments we show that human body motion capturing can be performed in an efficient and robust manner by using our algorithm.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.6
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• pp.57-65
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• 2015

Manufacturing optimization problem is to find the optimal solution under satisfying various and complicated constraints with the design variables of nonlinear types. To achieve the objective, this paper proposes a hybrid approach. The proposed hybrid approach is consist of genetic algorithm(GA), cuckoo search(CS) and hill climbing method(HCM). First, the GA is used for global search. Secondly, the CS is adapted to overcome the weakness of GA search. Lastly, the HCM is applied to search precisely the convergence space after the GA and CS search. In experimental comparison, various types of manufacturing optimization problems are used for comparing the efficiency between the proposed hybrid approach and other conventional competing approaches using various measures of performance. The experimental result shows that the proposed hybrid approach outperforms the other conventional competing approaches.