• Clean Technology
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• v.19 no.4
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• pp.423-429
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• 2013

This study aimed to develop flowable backfill material using oyster shell, coal ash, and surplus soil. The high temperature (> $800^{\circ}C$) reaction was required to convert $CaCO_3$ to CaO. The solid specimens formed by pozzlanic reaction between CaO and coal ash showed low unconfined compressive strength. The effect of kaolin and blast furnace slag was also examined. It was found that CaO and coal ash could not be utilized due to high cost and low performance. The use of oyster shell without calcination ($CaCO_3$) was evaluated. The specimens composing of oyster shell and cement showed the higher unconfined compressive strength than that composing of coal ash and cement. However, use of oyster shell is limited in mortar due to the presence of salt. Addition of soil into oyster shell-coal ash-cement mixture satisfied the specification of flowable backfill material by optimizing their ratio.

• Journal of Korean Society of Environmental Engineers
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• v.27 no.2
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• pp.177-183
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• 2005

The effluent quality is directly affected by the separation of biological solids in a final clarifier because the majority of discharged $BOD_5$ and SS are virtually dependent on the results of biological solids in the sedimentation tank effluent. If a final clarifier is effectively designed and operated, the desired goal of clarification for wastewater can be achieved together with the cost reduction in the treatment of wastewater. To this end flow characteristics and the removal efficiency of SS are numerically investigated especially by the change of the inlet position and the installation of baffle to improve the performance of a rectangular final clarifier. The 2-D computer program developed in a rectangular coordinates has been successfully validated against experimental residence time distribution(RTD) curves obtained by tracing radio-isotope. The lowering of the inlet position weakens the density current and induces the settling of SS in the front zone of a clarifier. Thus the decreased traveling distance of the sludge increases the removal efficiency of SS in the effluent. The inlet baffle installed in the front region of clarifier prevents the short circuiting flow and induces to flow into the dense underflow, which eventually improves the effluent quality. In the case of lower inlet position, however, installation of baffle results in degradation of effluent quality. Consequently it is strongly recommended that in-depth numerical study be performed in advance for optimizing a clarifier design and retrofitting to improve effluent quality in a final clarifier.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.149-156
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• 2012

Support vector machines (SVMs) are well known for their pattern recognition capability, but proper care should be taken to alleviate their inherent implementation cost resulting from high computational intensity and memory requirement, especially in embedded systems where only limited resources are available. Since the memory requirement determined by the dimensionality and the number of support vectors is generally too high for a cache in embedded systems to accomodate, frequent accesses to the main memory occur inevitably whenever the cache is not able to provide requested data to the processor. These frequent accesses to the main memory result in overall performance degradation and increased energy consumption because a memory access typically takes longer and consumes more energy than a cache access or a register access. In this paper, we propose a technique that reduces the number of main memory accesses by optimizing the data access pattern of the SVM-based classifier in such a way that the temporal locality of the accesses increases, fully utilizing data loaded into the processor chip. With experiments, we confirm the enhancement made by the proposed technique in terms of the number of memory accesses, overall execution time, and energy consumption.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1353-1366
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• 2015

These days Shewhart control chart for evaluating stability of the process is widely used in various field. But it must follow strict assumption of distribution. In real-life problems, this assumption is often violated when many quality characteristics follow non-normal distribution. Moreover, it is more serious in multivariate quality characteristics. To overcome this problem, many researchers have studied the non-parametric control charts. Recently, SVDD (Support Vector Data Description) control chart based on RBF (Radial Basis Function) Kernel, which is called K-chart, determines description of data region on in-control process and is used in various field. But it is important to select kernel parameter or etc. in order to apply the K-chart and they must be predetermined. For this, many researchers use grid search for optimizing parameters. But it has some problems such as selecting search range, calculating cost and time, etc. In this paper, we research the efficiency of selecting parameter regions as data structure vary via simulation study and propose a new method for determining parameters so that it can be easily used and discuss a robust choice of parameters for various data structures. In addition, we apply it on the real example and evaluate its performance.

• The KIPS Transactions:PartD
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• v.10D no.2
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• pp.233-246
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• 2003

The mediator-based system integrates heterogeneous information systems with the flexible manner. But it does not give much attention on the query optimization issues, especially for the query reusing. The other thing is that it does not use standardized metadata for schema matching. To improve this two issues, we propose mediator-based Distributed Information Integration System (DIIS) which uses query caching regarding performance and uses ISO/IEC 11179 metadata registry in terms of standardization. The DIIS is designed to provide decision-making support, which logically integrates the distributed heterogeneous business information systems based on the Web environment. We designed the system in the aspect of three-layer expression formula architecture using the layered pattern to improve the system reusability and to facilitate the system maintenance. The functionality and flow of core components of three-layer architecture are expressed in terms of process line diagrams and assembly line diagrams of Eriksson Penker Extension Model (EPEM), a methodology of an extension of UML. For the implementation, Supply Chain Management (SCM) domain is used. And we used the Web-based environment for user interface. The DIIS supports functions of query caching and query reusability through Query Function Manager (QFM) and Query Function Repository (QFR) such that it enhances the query processing speed and query reusability by caching the frequently used queries and optimizing the query cost. The DIIS solves the diverse heterogeneity problems by mapping MetaData Registry (MDR) based on ISO/IEC 11179 and Schema Repository (SCR).

• Journal of the Korean Society for Railway
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• v.16 no.3
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• pp.196-201
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• 2013

As there is no failure data for the entire lifecycle of a product, when analyzing reliability measures based on early failure data only, there may be a significant error between the estimated mean life and the real one, because it can be underestimated, or on the other hand, it can be overestimated when analyzing reliability measures based on a large amount of censored data with the failure data. To resolve the issue, this study proposes an optimal sampling estimation procedure that selects the proportion of censored data to estimate the optimal distribution with the idea that the estimated distribution could be approximated as closely as the real life distribution. This would work if we sampled the optimal proportion on the censored data, because failure data has real intrinsic distribution in any situation. We validate the proposed procedure using an actual example. If the proposed method is applied to the maintenance policy of TWC (Train to Wayside Communication) system, then we can establish the optimal maintenance policy. Thus, we expect that it will be effective for improvement of reliability and cost savings.

• Korean Chemical Engineering Research
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• v.57 no.4
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• pp.525-530
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• 2019

The performance and stability of solid oxide fuel cells (SOFCs) depend on the microstructure of the electrode and electrolyte. In anode, porosity and pore distribution affect the active site and fuel gas transfer. In an electrolyte, density and thickness determine the ohmic resistance. To optimizing these conditions, using costly method cannot be a suitable research plan for aiming at commercialization. To solve these drawbacks, we made high performance unit cells with low cost and highly efficient ceramic processes. We selected the NiO-YSZ cermet that is a commercial anode material and used facile methods like die pressing and dip coating process. The porosity of anode was controlled by the amount of carbon black (CB) pore former from 10 wt% to 20 wt% and final sintering temperature from $1350^{\circ}C$ to $1450^{\circ}C$. To achieve a dense thin film electrolyte, the thickness and microstructure of electrolyte were controlled by changing the YSZ loading (vol%) of the slurry from 1 vol% to 5 vol. From results, we achieved the 40% porosity that is well known as an optimum value in Ni-YSZ anode, by adding 15wt% of CB and sintering at $1350^{\circ}C$. YSZ electrolyte thickness was controllable from $2{\mu}m$ to $28{\mu}m$ and dense microstructure is formed at 3vol% of YSZ loading via dip coating process. Finally, a unit cell composed of Ni-YSZ anode with 40% porosity, YSZ electrolyte with a $22{\mu}m$ thickness and LSM-YSZ cathode had a maximum power density of $1.426Wcm^{-2}$ at $800^{\circ}C$.

• Journal of Platform Technology
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• v.6 no.4
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• pp.59-68
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• 2018

The objective of this study is to develop an embedded antenna structure with NFC and WPC composite functions. By selecting stable materials, the optimal component ratio of the polymer sheet was determined. The low cost embedded winding method compared to the existing FPCB was devised. During the winding process, characterization and process technology were developed. We also fabricated a ferrite mold to process the WPC grooves and developed the process technology for optimizing the WPC antenna. The following conclusions were obtained. (1) Optimum composition ratio was derived as Fe 87.5%, Si 7%, Al 5.5% and selected as the final material. (2) Optimal sheet conditions were derived from the experimental evaluation method and the experimental design method through the combination test of the optimized sheet and the conventional mass production FPCB. (3) According to coil diameter and inner diameter, Q value fluctuation, resistance value and efficiency fluctuation are obtained. Therefore, the most suitable coil condition is selected and Rx matching is performed. (4) The EMV load modulation test and the cognitive distance test of the polymer sheet and the ferrite sheet showed that the recognition distance of the polymer sheet at 1k and 4K was 32-33 mm and the recognition distance of the ferrite sheet at the same condition was 30-31 mm.

• Smart Media Journal
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• v.8 no.1
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• pp.74-81
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• 2019

Recently, machine learning technology has had a significant impact on society, particularly in the medical, manufacturing, marketing, finance, broadcasting, and agricultural aspects of human lives. In this paper, we study how to apply machine learning techniques to foods, which have the greatest influence on the human survival. In the field of Smart Farm, which integrates the Internet of Things (IoT) technology into agriculture, we focus on optimizing the crop growth environment by monitoring the growth environment in real time. KT Smart Farm Solution 2.0 has adopted machine learning to optimize temperature and humidity in the greenhouse. Most existing smart farm businesses mainly focus on controlling the growth environment and improving productivity. On the other hand, in this study, we are studying how to apply machine learning with respect to harvest time so that we will be able to harvest fruits of the highest quality and ship them at an excellent cost. In order to apply machine learning techniques to the field of smart farms, it is important to acquire abundant voluminous data. Therefore, to apply accurate machine learning technology, it is necessary to continuously collect large data. Therefore, the color, value, internal temperature, and moisture of greenhouse-grown fruits are collected and secured in real time using color, weight, and temperature/humidity sensors. The proposed FPSML provides an architecture that can be used repeatedly for a similar fruit crop. It allows for a more accurate harvest time as massive data is accumulated continuously.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.55-62
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• 2022

The perovskite solar cell is an active part of research in renewable energy fields such as solar energy, wind, hydroelectric power, marine energy, bioenergy, and hydrogen energy to replace fossil fuels such as oil, coal, and natural gas, which will gradually disappear as power demand increases due to the increase in use of the Internet of Things and Virtual environments due to the 4th industrial revolution. The perovskite solar cell is a solar cell device using an organic-inorganic hybrid material having a perovskite structure, and has advantages of replacing existing silicon solar cells with high efficiency, low cost solutions, and low temperature processes. In order to optimize the light absorption layer thin film predicted by the existing empirical method, reliability must be verified through device characteristics evaluation. However, since it costs a lot to evaluate the characteristics of the light-absorbing layer thin film device, the number of tests is limited. In order to solve this problem, the development and applicability of a clear and valid model using machine learning or artificial intelligence model as an auxiliary means for optimizing the light absorption layer thin film are considered infinite. In this study, to estimate the light absorption layer thin-film optimization of perovskite solar cells, the regression models of the support vector machine's linear kernel, R.B.F kernel, polynomial kernel, and sigmoid kernel were compared to verify the accuracy difference for each kernel function.