• Journal of the Korea Organic Resources Recycling Association
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• v.9 no.2
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• pp.87-92
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• 2001

As well as arising the concern about pesticides known as a Carcinogenic or endocrine disorder substrates, magnitude was increased of reducing pesticides in soil or water. In this work, removals of residual pesticides on surface of solid phase were attempted by the photooxidation process with hydrogen peroxide. The optimum conditions for the removals of benomyl (carbamatic pesticide) chlorothalonil (Organochoric pesticide) were 350nm UV wavelegth and 20% (v/v) hydrogen peroxide solution as oxidant. Removals are negligible when UV radiation or the supply of hydrogen peroxide are solely applied on the target compoounds. Removal rates of the pesticides are accelerated by UV radiation with hydrogen addition. After 20 min of the treatment, about $2{\mu}g/cm^2$ of benomyl and $1,88{\mu}g/cm^2$ of chlorothalonil were disappeared on the surface of the solid phase.

• Fibers and Polymers
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• v.7 no.4
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• pp.404-413
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• 2006

This study examines multiple quality optimization of the injection molding for Polyether Ether Ketone (PEEK). It also looks into the dimensional deviation and strength of screws that are reduced and improved for the molding quality, respectively. This study applies the Taguchi method to cut down on the number of experiments and combines grey relational analysis to determine the optimal processing parameters for multiple quality characteristics. The quality characteristics of this experiment are the screws' outer diameter, tensile strength and twisting strength. First, one should determine the processing parameters that may affect the injection molding with the $L_{18}(2^1{\times}3^7)$ orthogonal, including mold temperature, pre-plasticity amount, injection pressure, injection speed, screw speed, packing pressure, packing time and cooling time. Then, the grey relational analysis, whose response table and response graph indicate the optimum processing parameters for multiple quality characteristics, is applied to resolve this drawback. The Taguchi method only takes a single quality characteristic into consideration. Finally, a processing parameter prediction system is established by using the back-propagation neural network. The percentage errors all fall within 2%, between the predicted values and the target values. This reveals that the prediction system established in this study produces excellent results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.387-392
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• 2005

Double-deck train have studied in the next generation train in KRRI. Double-deck train have more seat capacities compared with single deck vehicles and is a efficient, reliable and comfortable alternative train. Because of heavy weight, weight minimization of double-deck train carbody is imperative to reduce cost and extend life-time of train. Weight minimization problem of the double-deck train car-body is required to decide 66 design variables of thicknesses for large aluminum extruded panel while satisfying stress constraints. Design variables are too many and one execution of structural analysis of double-deck train carbody is time-consuming. Therefore, we adopt approximation technique to save computational cost of optimization process. Metamodels such as response surface model (RSM) and kriging model are used to approximate model-based optimization is described. RSM is easy to obtain and expressed explicit function, but this is not suitable for highly nonlinear and large scaled problems. Kriging model employs an interpolation scheme and is developed in the fields of spatial statistics and geostatistics. Target of this design is to find optimum thickness of AEP to minimize weight of doulbe-deck train carbody. In this study, meta model techniques are introduced to carry out weight minimization of a double-deck train car-body.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.5
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• pp.63-69
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• 2000

The main target of this research is investigating the relations between mechanical properties and injection conditions, like injection pressure, packing pressure and packing time for various contents ratio of glass fiber and resin. In general idea, high injection pressure produces high strength of molded parts as a monotonic function. but it was revealed that high pressure does not make high strength directly through various experiments of injection molding. In this experiments, PA66 was selected as resin and Glass Fiber was selected as reinforcing fiber Fiber reinforcement was controlled, as 14%, 25%, 33%, 44% of total volume and packing pressure was divided 55%, 65%, 75%, 85% of reference pressure, i.e. 100% equal to 1400kgf/$\textrm{cm}^2$. Finally, tensile testing was executed for injected test specimen. Optimum results based on authors' experiments have been obtained under conditions of 25% and 33% of glass fiber contents. Tensile strength rather depends on the packing pressure and packing time than injection pressure. Especially almost equal value of tensile strength was obtained for various percentage of packing and injection pressure as 65%, 75% and 85% of reference pressure.

• Journal of the Society of Naval Architects of Korea
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• v.44 no.4
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• pp.349-359
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• 2007

In this study the hull form design with minimum resistance of domestic coastal fishing boat using a computer design procedure is carried out. The target boat is G/T 4.99 ton class fishing boat. which is one of the most popular boat in the coastal sea. For the task, the design parameters needed in preliminary stage are selected or determined from the existing boat. which has excellent resistances characteristics. In the EHP estimation during the design procedure, the main objective function is the hull resistance, and the initial hull forms before the optimization are selected from the boats that are in operation now. The EHP values from the hull after optimization process are also compared with those of the original hull to confirm its effect. Also, optimizing is investigated for the hull form to reestimate such factors as stability, laboring environment for the best design. it is expected that the results of this study here can be effectively used to improve the present design status of domestic small fishing boats.

• Journal of Information Technology Applications and Management
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• v.12 no.2
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• pp.1-13
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• 2005

This paper proposes a software-reliability growth model incoporating the amount of testing effort expended during the software testing phase after developing it. The time-dependent behavior of testing effort expenditures is described by a Logistic curve. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, a software-reliability growth model is formulated by a nonhomogeneous Poisson process. Using this model the method of data analysis for software reliability measurement is developed. After defining a software reliability, This paper discusses the relations between testing time and reliability and between duration following failure fixing and reliability are studied. SRGM in several literatures has used the exponential curve, Railleigh curve or Weibull curve as an amount of testing effort during software testing phase. However, it might not be appropriate to represent the consumption curve for testing effort by one of already proposed curves in some software development environments. Therefore, this paper shows that a logistic testing-effort function can be adequately expressed as a software development/testing effort curve and that it gives a good predictive capability based on real failure data.

• Korean Journal of Artificial Intelligence
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• v.12 no.2
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• pp.17-23
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• 2024

Various methods have been developed to predict the flight path of an air-launched weapon to intercept a fast-moving target in the air. However, it is also getting more challenging to predict the optimal firing zone and provide it to a pilot in real-time during engagements for advanced weapons having new complicated guidance and thrust control. In this study, a method is proposed to develop an optimized weapon engagement zone by the SCG (Scaled Conjugate Gradient) algorithm to achieve both accurate and fast estimates and provide an optimized launch display to a pilot during combat engagement. SCG algorithm is fully automated, includes no critical user-dependent parameters, and avoids an exhaustive search used repeatedly to determine the appropriate stage and size of machine learning. Compared with real data, this study showed that the development of a machine learning-based weapon aiming algorithm can provide proper output for optimum weapon launch zones that can be used for operational fighters. This study also established a process to develop one of the critical aircraft-weapon integration software, which can be commonly used for aircraft integration of air-launched weapons.

• Journal of Korean Society of Environmental Engineers
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• v.27 no.6
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• pp.567-572
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• 2005

In this study, a lab-scale test was performed to apply the ozone process in drinking water treatment plant using dissolved ai, flotation(DAF). The kinetic study on the ozone decay and hydroxyl(OH) radical formation was investigated by several parameters, such as I.D(Instantaneous ozone demand), $k_c$(ozone decomposition rate), ozone-Ct and OH radical-Ct. Ozonation of several target waters, such as raw water, DAF treated water and filtrate, was conducted to select the optimum position and dosage of ozone process. The highest value of Ozone-Ct and OH radical-Ct was observed at DAF treated water at initial run time($0{\sim}30\;min$). From the results of ozonation, the intermediate ozonation was proposed as the optimum position and the effective dose of ozone was determined to be $1{\sim}2\;mg/L$.

• Korean Journal of Materials Research
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• v.11 no.1
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• pp.27-33
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• 2001

The growth characteristics of 4-fold grain which was appeared in KLN deposition on $Pt/Ti/SiO_2/Si(100)$ substrate was studied by varying process variables. Substrate temperature, sputtering pressure, rf power were selected as process variables, and experiment was carried out near optimum fabrication condition. When using K and Li enriched target, the optimum fabrication conditions were substrate temperature of $600^{\circ}C$, sputtering pressure of 150mTorr, rf power of 100 W and its surface morphology is sensitively varied by small deposition condition changes. KLN is composed of elements which have large difference of boiling point. And it is difficult to fabricate thin film at high temperature and high vacuum deposition condition. Furthermore the phenomenon during deposition process can not be explained by using Thorton's model which explains the relation between thin film structure and melting point of thin film materials. These phenomenon can be explained using boiling point of elements which consist of thin film material.

• Journal of Applied Biological Chemistry
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• v.62 no.3
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• pp.251-255
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• 2019

The effect of soaking temperature on the moisture uptake and the protein loss of soybeans during soaking process investigated. As the soaking temperature increased, the soaking rate significantly increased and Peleg model was suitable for describing the soaking characteristics of the soybean with high $R^2$ values (>0.991). The soaking time to achieve the target moisture content of soybean (130%) was estimated to be 12.6, 3.11 and 2.31 h at 25, 35 and $45^{\circ}C$, respectively. Peleg model well described the protein loss kinetics of soybean during soaking with high $R^2$ values (>0.941). The results showed that the protein loss of soybean at the target moisture content were 35.2, 93.1 and 103.0 mg/g at 25, 35 and $45^{\circ}C$, respectively. In this study, the optimum soaking condition for quality of soybean was 12.6 h of soaking time at $25^{\circ}C$.