• Polymer(Korea)
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• v.25 no.5
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• pp.744-753
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• 2001

One of the most important factors which affect the impact strength of high impact polystyrene (HIPS) is the rubber-phase particle size and size distribution. In this study, HIPS was prepared from a batch reactor to observe the influence of reaction conditions such as rubber content, agitation speed and prepolymerization time on the particle size and size distribution. Measurements concerning the particle size distribution were conducted using a particle size analyzer. Due to swelling, the particle suspended in toluene increases in size with lower heat-treatment temperature and shorter heat-treatment time, while the particle in methyl ethyl ketone shows quite reasonable size without any effort of heat-treatment. As rubber content increases, the average particle size increases substantially, but the increase in agitation speed at lower rubber contents does not have much influence on the size. However, the polystyrene-phase particles occluded in rubber-phase become more uniform as agitation speed increases. Longer prepolymerization time produces rubber-phase particles with narrower particle size distribution.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1990.04a
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• pp.222-244
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• 1990

A multi-echelon structure of manufacturing and distribution system in considered, where the raw materials are transformed into a finished good through a number to manufacturing echelons and it is distributed to the lower echelons(retailers, or customers). The raw material, work-in-process, finished good inventory and the distribution costs are unified into one model. The objective is to determine the ordering policy of raw materials, manufacturing lot size, the number of sub-batch and the distribution policy of the finished good which minimize the annual total system cost. A computer program for a heuristic search technique is developed, by which a numerical example is examined.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1859-1864
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• 2004

An effective methodology is reported for the optimal design of multisite batch production/transportation and storage networks under uncertain demand forecasting. We assume that any given storage unit can store one material type which can be purchased from suppliers, internally produced, internally consumed, transported to or from other plant sites and/or sold to customers. We further assume that a storage unit is connected to all processing and transportation stages that consume/produce or move the material to which that storage unit is dedicated. Each processing stage transforms a set of feedstock materials or intermediates into a set of products with constant conversion factors. A batch transportation process can transfer one material or multiple materials at once between plant sites. The objective for optimization is to minimize the probability averaged total cost composed of raw material procurement, processing setup, transportation setup and inventory holding costs as well as the capital costs of processing stages and storage units. A novel production and inventory analysis formulation, the PSW(Periodic Square Wave) model, provides useful expressions for the upper/lower bounds and average level of the storage inventory. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two sub-problems. The first yields analytical solutions for determining lot sizes while the second is a separable concave minimization network flow subproblem whose solution yields the average material flow rates through the networks for the given demand forecast scenario. The result of this study will contribute to the optimal design and operation of large-scale supply chain system.

• Journal of Korean Society of Water and Wastewater
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• v.28 no.4
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• pp.453-459
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• 2014

The excessive concentration of phosphorus in the river and reservoir is a deteriorating factor for the eutrophication. The converter slag was used to remove the phosphate from the synthetic wastewater. Influencing factors were studied to remove soluble orthophosphate with the different particle sizes through the batch and the column experiments by continuous flow. Freundlich and Langmuir adsorption isotherm constants were obtained from batch experiments with $PS_A$ and $PS_B$. Freundlich isotherm was fitted better than Langmuir isotherm. Regression coefficient of Freundlich isotherm was 0.95 for $PS_A$ and 0.92 for $PS_B$, respectively. The adsorption kinetics from the batch experiment were revealed that bigger size of convert slag, $PS_A$ can be applied for the higher than 3.5 mg/L of phosphate concentration. The pilot plant of continuous flow was applied in order to evaluate the pH variation, breakthrough points and breakthrough adsorption capacity of phosphate. The variation of pH was decreased through the experimental hours. The breakthrough time was 1,432 and 312 hours to 10 mg/L and 50 mg/L for the influent concentration, respectively. The breakthrough adsorption capacity was 3.54 g/kg for 10 mg/L, and 1.72 g/kg for 50 mg/L as influent phosphate concentration.

• Journal of Korean Society of Water and Wastewater
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• v.20 no.3
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• pp.367-375
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• 2006

Sequencing Batch Reactor (SBR) is well adopted for community wastewater treatment for its simplicity, performance and various advantageous treatment options. SBR is now drawing attention for its process modification such as coupled with membrane bioreactor, reverse osmosis or applying different media to achieve high removal efficiency. This study focused on the improved efficiency of carbon, nitrogen and phosphorous removal by applying zeolite materials called bioceramics to the SBR. Two laboratory-scale SBR units were operated in the same operating conditions - one with bioceramics called Bioceramic SBR (BCSBR) and the other without bioceramics used as control. Routine monitoring of COD, TP, $NH_3-N$, $NO_3-N$ was performed throughout this study. COD removal was about 80% to 100% and phosphorous removal was about 60% in the process whereas $NH_3-N$ removal efficiency was found to be 99.9% in the BCSBR unit. Addition of bioceramics also improved sludge characteristics such as sludge dewaterability, specific gravity and particle size. BCSBR can withstand high ammonia shock loading leading to the better treatment capacity of high ammonia containing wastewater. The cause of improved removal efficiencies within the biological reactor could be attributed to the biochemosorption mechanisms of bioceramics. Absorption/adsorption or desorption capacity of bioceramics was tested through laboratory experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.11
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• pp.956-962
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• 2005

This paper presents an integrated analysis of production and financing decisions. We assume that a cash storage unit is installed to manage the cash flows related with production activities such as raw material procurement, process operating setup, Inventory holding cost and finished product sales. Temporarily financial investments are allowed for more profit. The production plant is modeled by the Batch-Storage Network with Recycle Streams in Yi and Reklaitis (2003). The objective function of the optimization is minimizing the opportunity costs of annualized capital investment and cash/material inventory while maximizing stockholder's benefit. No depletion of all the material and cash storage units is major constraints of the optimization. A novel production and inventory analysis formulation, the PSW(Periodic Square Wave) model, provides useful expressions for the upper/lower bounds and average level of the cash and material inventory holdups. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two subproblems and analytical lot sizing equations under a mild assumption about the cash flow pattern of stockholder's dividend. The first subproblem is a separable concave minimization network flow problem whose solution yields the average material flow rates through the networks. The second subproblem determines the decisions about financial Investment. Finally, production and financial transaction lot sizes and startup times can be determined by analytical expressions as far as the average flow rates are calculated. The optimal production lot and storage sizes considering financial factors are smaller than those without such consideration. An illustrative example is presented to demonstrate the results obtainable using this approach.

• Journal of Navigation and Port Research
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• v.28 no.3
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• pp.253-258
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• 2004

There have been several problems in treating shipbard sewage due to special environmental conditions of ship, such as limited space, rolling and pitching, change of temperature and so on It was suggested that Sequence Batch Reactor (SBR) might be suitable process for overcome these problems in terms of small size, high capacity of treating wastewater and full automation. In this study a SBR process was employed for biological treatment of organic wastes in the shipboard sewage. This process was able to remove nitrogen and phosphorus as well as organic matter efficiently. Afore than 95％ of chemical oxygen demand(COD) were removed. In addition, about 97％ of total nitrogen (T-N) was reduced. The total phosphorus(T-P) reduction averaged 93％. A disturbance operation caused by the treatment of Methylene Blue Active Substances(MBAS) was not observed.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.6
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• pp.537-544
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• 2004

An effective methodology is reported for determining the optimal lot size of batch processing and storage networks which include uncertain demand forecasting. We assume that any given storage unit can store one material type which can be purchased from suppliers, internally produced, infernally consumed, transported to or from other sites and/or sold to customers. We further assume that a storage unit is connected to all processing and transportation stages that consume/produce or move the material to which that storage unit is dedicated. Each processing stage transforms a set of feedstock materials or intermediates into a set of products with constant conversion factors. A batch transportation process can transfer one material or multiple materials at once between sites. The objective for optimization is to minimize the probability averaged total cost composed of raw material procurement, processing setup, transportation setup and inventory holding costs as well as the capital costs of processing stages and storage units. A novel production and inventory analysis formulation, the PSW(Periodic Square Wave) model, provides useful expressions for the upper/lower bounds and average level of the storage inventory. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two sub-problems. The first yields analytical solutions for determining lot sires while the second is a separable concave minimization network flow subproblem whose solution yields the average material flow rates through the networks for the given demand forecast scenario. The result of this study will contribute to the optimal design and operation of the global supply chain.

• Applied Chemistry for Engineering
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• v.10 no.4
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• pp.586-591
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• 1999

Mixed-firing of a bituminous and an anthracite coal carried out in a batch fluidized bed combustor(0.109 m-I.D., 0.9 m-height). Effect of particle size an mixing fraction of anthracite and bituminous coal combustion characteristics were studied. The temperature profiles and pressure fluctuation properties were measured to interpret the combustion characteristics in a batch fluidized bed combustor. The used domestic anthracite coal has heating value of 2010 kcal/kg and the imported high-calorific bituminous coal has heating value of 6520 kcal/kg. The combustion characteristics in a batch fluidized bed combustor could be interpreted by using pressure fluctuation properties and temperature increasing rates. It was found that the optimum anthracite mixing percentage could be predicted analyzing the combustion rate and fluidization characteristics, The optimum mixing fraction was about 30 %. The different burning region of fluidized bed combustor was measured by temperature increasing rates.

• Journal of Korea Multimedia Society
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• v.23 no.4
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• pp.525-538
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• 2020

A practical animal face classification system that classifies animals in image and video data is considered as a pivotal topic in machine learning. In this research, we are proposing a novel method of fully connected dual Deep Convolutional Neural Network (DCNN), which extracts and analyzes image features on a large scale. With the inclusion of the state of the art Batch Normalization layer and Exponential Linear Unit (ELU) layer, our proposed DCNN has gained the capability of analyzing a large amount of dataset as well as extracting more features than before. For this research, we have built our dataset containing ten thousand animal faces of ten animal classes and a dual DCNN. The significance of our network is that it has four sets of convolutional functions that work laterally with each other. We used a relatively small amount of batch size and a large number of iteration to mitigate overfitting during the training session. We have also used image augmentation to vary the shapes of the training images for the better learning process. The results demonstrate that, with an accuracy rate of 92.0%, the proposed DCNN outruns its counterparts while causing less computing costs.