• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.25 no.12
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• pp.974-978
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• 2012

The effect of Cu coating on the sensing properties of nano $SnO_2:Cu$ based sensors for the $CH_4$, $CH_3CH_2CH_3$ gas was studied. This work was focussed on investigating the change of sensitivity of nano $SnO_2:Cu$ based sensors for $CH_4$, $CH_3CH_2CH_3$ gas by Cu coating. Nano sized $SnO_2$ powders were prepared by solution reduction method using stannous chloride($SnCl_2{\cdot}2H_2O$), hydrazine($N_2H_2$) and NaOH and subsequent heat treatment. XRD patterns showed that nano $SnO_2$ powders with rutile structure were grown with (110), (101), (211) dominant peak. The particle size of nano $SnO_2:Cu$ powders at 8 wt% Cu was about 50 nm. $SnO_2$ particles were found to contain many pores, according to SEM analysis. The sensitivity of nano $SnO_2:Cu$ based sensors was measured for 5 ppm $CH_4$ gas and $CH_3CH_2CH_3$ gas at room temperature by comparing the resistance in air with that in target gases. The sensitivity for both $CH_4$ and $CH_3CH_2CH_3$ gases was improved by Cu coating on the nano $SnO_2$ surface. The response time and recovery time of the $SnO_2:Cu$ gas sensors for the $CH_4$ and $CH_3CH_2CH_3$ gases were 18~20 seconds, and 13~15 seconds, respectively.

• 한국신재생에너지학회:학술대회논문집
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• 2010.06a
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• pp.249.2-249.2
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• 2010

최근의 고유가와 환경오염에 대한 대응 수단으로 수송용 바이오연료의 보급에 대한 관심이 세계적으로 높아지고 있다. 이 중 바이오디젤은 동식물성 기름으로부터 메탄올과의 전이에스테르화 반응에 의해 생산되는 경유대체 연료로서 환경 친화성과 지속가능성이 인정됨에 따라 그 생산량이 급격히 증가하고 있다. 바이오디젤의 생산량이 증가함에 따라 대두유, 유채유, 팜유 등의 원료유 가격 상승 및 수급 불안정 문제가 대두되고 있으며 식량자원과의 충돌 문제도 발생되고 있다. 이를 해결하기 위한 방안으로 유리지방산 함량이 높은 저가유지 자원(폐식용유, 폐돈지, 폐우지, soapstock, trapped grease)을 이용한 공정 개발 연구가 활발히 진행되고 있다. 본 연구에서는 비활용되고 있는 해외 열대작물 열매씨앗에서 착유한 식물성 오일의 바이오디젤 원료유로서의 사용 가능성을 검토하였다. 열대작물 오일의 물성 분석 결과 고형물, 수분, 인, 유리지방산 함량이 대두원유보다 매우 높게 나타났다. 오일 중의 인지질은 바이오디젤 제조 반응후 에스테르와 글리세린의 층분리를 방해하여 공정 효율을 감소시키고 유리지방산은 염기촉매와 결합하여 지방산염을 생성해 생산수율을 감소시키는 문제를 일으킨다. 고형물과 수분은 여과와 감압증발에 의해 쉽게 제거가 가능하였다. 15~20%의 유리지방산 함유 열대작물 오일의 전처리를 위해 균질계 산촉매와 비균질 고체 산촉매를 이용해 에스테르화 반응 효율을 조사한 결과 황산이 가장 높은 효율을 보였다. 반응표면분석법(Response Surface Method, RSM)을 적용해 메탄올과 촉매량의 2변수 에스테르화반응 최적화를 수행한 결과 메탄올 26%, 촉매 0.98%로 최적 조건이 도출되었으며 초기 산가 33mgKOH/g에서 0.98mgKOH/g으로 감소됨을 확인하였다. 전처리 정제한 오일의 물성분석 결과 고형물 0.1%, 수분 0.10%, 산가 1.0mgKOH/g, 인함량 20ppm 이하로 바람직한 원료유가 생산됨을 알 수 있었다. 제조된 원료유를 이용해 전이에스테르화 반응 최적화 실험을 RSM에 근거하여 진행한 결과 KOH 0.8%, 메탄올:오일 몰비 6.2:1, 반응온도 $60^{\circ}C$, 교반속도 200rpm, 반응시간 30분으로 나타났으며 증류 정제전 97.3%, 증류후 100.0%의 바이오디젤을 생산 할 수 있었다. 열대작물 오일의 전처리 공정은 메탄올을 과잉양으로 사용함으로 효과적인 알콜 회수 공정이 중요하다. 전처리 후 층분리를 통해 회수되는 메탄올 중의 수분함량은 2%~7%로서 이를 전처리 반응에 재사용하기 위해서는 0.3%이하의 수분함량으로 정제가 필요하다. 본 연구에서는 고가의 증류탑 형태가 아닌 단증류방식으로 2단계 내지 3단계로 0.3% 수분의 메탄올 회수 조건을 도출하였으며 파일롯 공정 설계를 진행하고 있다. 이로서 본 연구의 열대작물 오일은 저가로 충분한 물량의 확보가 가능하다면 바이오디젤 원료 자원으로서 큰 활용가치가 있는 것으로 판단된다.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.2
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• pp.69-78
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• 1999

In this paper, a neural network approach to forecast Korean regional precipitation is presented. We first analyze the characteristics of the conventional models for time series prediction, and then propose a new model and its learning method for the precipitation forecast. The proposed model is a layered network in which the outputs of a layer are buffered within a given period time and then fed fully connected to the upper layer. This study adopted the dual connections between two layers for the model. The network behavior and learning algorithm for the model are also described. The dual connection structure plays the role of the bias of the ordinary Multi-Layer Perceptron(MLP), and reflects the relationships among the features effectively. From these advantageous features, the model provides the learning efficiency in comparison with the FIR network, which is the most popular model for time series prediction. We have applied the model to the monthly and seasonal forecast of precipitation. The precipitation data and SST(Sea Surface Temperature) data for several decades are used as the learning pattern for the neural network predictor. The experimental results have shown the validity of the proposed model.

• Korean Journal of Food Science and Technology
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• v.47 no.6
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• pp.772-778
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• 2015

Hydrolysis of isolate soybean protein (ISP) using subcritical water (SCW) was conducted to study the feasibility for producing protein hydrolyzate. SCW hydrolysis of SPI suspension (5-15%) was conducted in an electrically heated batch reactor (2 L). The effects of temperature (230 to $270^{\circ}C$) and holding time (10 to 50 min) on the degree of hydrolysis (DH) and the production of amino acids were studied by surface response method. The DH was determined by derivatizing the hydrolyzates with ortho-phthalaldehyde (OPA) solution. It was confirmed that reaction temperature and holding time affected the hydrothermolysis of soybean protein. However, the holding time was less effective on amino acid yield when the temperature was higher than $230^{\circ}C$. In order to achieve optimal yields of amino acids exceeding 43%, the temperature should be within the range between 256 and $268^{\circ}C$ with holding time from 29 to 41 min, respectively. A maximum estimated amino acid yield of 43.5% was obtained at $268^{\circ}C$ for 35 min.

• Archives of design research
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• v.17 no.2
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• pp.5-14
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• 2004

Introducing human capacities of control and sensation which have been overlooked into Human-Computer Interaction(HCI), Ubiquitous computing, Augmented Reality and others have been researched recently. New vision of HCI has embodied in Tangible User Interface(TUI). TUI allows users to grasp and manipulate bits with everyday physical object and architectural surface and also TUI enables user to be aware of background object at the periphery of human perception using ambient display media such of light, sound, airflow and water movement. Tangibles, physical object which constitutes TUI system, is the physical object embodied digital bit. Tangibles is not only input device but also the configuration of computing. To get feedback of computing result, user controls the system with Tangibles as action and the system represents reaction in response to User's action. User appreciates digital representation (sound, graphic information) and physical representation (form, size, location, direction etc.) for reaction. TUI's characters require the consideration about both user's action and system's reaction. Therefore we have to need the method to be concerned about physical object and interaction which can be combined with action, reaction and feedback.

• Korean Journal of Food Science and Technology
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• v.26 no.1
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• pp.37-43
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• 1994

Optimization study was conducted for preparation of uncompressed soy protein isolate(SPI) tofu in the aspects of water addition ratio, second heating temperature and amounts of oil and dextrin added. The SPI tofu was prepared without compression step with SPI-oil-dextrin mixture and $CaSO_4-GDL$ mixed coagulants. The data were statistically analyzed by multiple regresstion and response surface methodology(RSM). Addition of dextrin increased the hardness of tofu, particularly for the second heating at $85^{\circ}C$ and 8 times of water to SPI. RSM figure showed that the effect of dextrin on hardness became to be less as the heating temperature increased. The hardness increase effect was no significant except addition of 25% oil and 8 times of water and second heating at $85^{\circ}C$. The addition of 25% oil and $10{\sim}15%$ dextrin and second heating at $90^{\circ}C$ for $45{\sim}60$ minutes resulted hardness and cohesive tofu. The optimal method proposed for uncompressed SPI tofu on the basis of textural and sensory properties was first heating of homogenized SPI-oil-dextrin(100:25:15) with addition of 8 times of water(on the basis of SPI) at $100^{\circ}C$ for 6 minutes, cooling to $40^{\circ}C$, additon of mixed coagulants of $CaSO_{4}-GDL$(0.07 g, 0.0075 g/SPI) and second heating at $90^{\circ}C$ for 45 minutes.

• Journal of the Korean Society of Food Science and Nutrition
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• v.40 no.10
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• pp.1430-1437
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• 2011

Synthesis conditions of cocoa butter equivalents were optimized using the response surface method (RSM) by interesterification of canola oil (Ca), palmitic ethyl ester (PEE), and stearic ethyl ester (StEE). The reaction was catalyzed by immobilized lipase (Lipozyme TLIM) from Thermomyces lanuginosa to produce structured lipids containing a composition of triacylglycerols similar to cocoa butter. Reaction conditions were optimized using D-optimal design with the three reaction factors of the substrate molar ratio of canola oil to palmitic ethyl ester and stearic ethyl ester (Ca : PEE : StEE=1:1:3, 1:1.66:5, 1:2:6, 1:2.33:7, 1:3:9, $X_1$), enzyme ratio (2~6%, $X_2$), and reaction time (30~270 min, $X_3$). The optimal conditions that minimized acyl-migration while maximizing 1-palmitoyl-2-oleoyl-3-stearoyl glycerol (POS), 1,3-distearoyl-2-oleoyl glycerol (SOS), and 1,3-dipalmitoyl-2-oleoyl glycerol (POP) were predicted, resulting in Ca : PEE : StEE=1:3:9, 6% of enzyme ratio, and 40 min of reaction time. The reaction product of structured lipids was synthesized again under the same conditions, showing 10.43 area% of acyl-migration, 25.31 area% of POS/PSO, 19.79 area% of SOS, and 11.22 area% of POP.

• Journal of Microbiology and Biotechnology
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• v.19 no.7
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• pp.718-726
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• 2009

The objective of this study was to develop and validate secondary models that can predict growth parameters of L. monocytogenes Scott A as a function of concentrations (0-3%) of a commercial potassium lactate (PL) and sodium diacetate (SDA) mixture, pH (5.5-7.0), and temperature (4-37DC). A total of 120 growth curves were fitted to the Baranyi primary model that directly estimates lag time (LT) and specific growth rate (SGR). The effects of the variables on L. monocytogenes Scott A growth kinetics were modeled by response surface analysis using quadratic and cubic polynomial models of the natural logarithm transformation of both LT and SGR. Model performance was evaluated with dependent data and independent data using the prediction bias ($B_f$) and accuracy factors ($A_f$) as well as the acceptable prediction zone method [percentage of relative errors (%RE)]. Comparison of predicted versus observed values of SGR indicated that the cubic model fits better than the quadratic model, particularly at 4 and $10^{\circ}C$. The $B_f$and $A_f$for independent SGR were 1.00 and 1.08 for the cubic model and 1.08 and 1.16 for the quadratic model, respectively. For cubic and quadratic models, the %REs for the independent SGR data were 92.6 and 85.7, respectively. Both quadratic and cubic polynomial models for SGR and LT provided acceptable predictions of L. monocytogenes Scott A growth in the matrix of conditions described in the present study. Model performance can be more accurately evaluated with $B_f$and $A_f$and % RE together.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.603-610
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• 2016

Over 12 years have passed since the first commercial operation of a Korean high-speed train. Since then, the transport capacity of the high-speed lines has become almost saturated. Therefore, studies have been carried out to increase the operating speed of the trains in order to increase their transportation capacity. This study was carried out to improve the critical speed of the KTX-Sancheon, Korean high-speed train, in order to increase its operating speed. A dynamic analysis of the KTX-Sancheon train was performed using the contact data obtained from the wheel wear profiles that were measured from a KTX-Sancheon train in commercial operation. The analysis results were verified by comparing them with the measurement acceleration data obtained from KTX-Sancheon. The suspension parameters were optimized to improve the operation speed. The critical speed of KTX-Sancheon was increased by 9.4% after the optimization by the response surface method. The optimized suspension parameters are expected to be used for the new bogie design to increase the operating speed of KTX-Sancheon from 300km/h to 350km/h.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.7
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• pp.729-736
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• 2011

The technique for order preference by similarity to ideal solution (TOPSIS) is regarded as a classical method of multiple attribute decision making (MADM), often used to solve various decision-making or selection problems. It is based on the concept that the chosen alternative should have the shortest distance from the positive ideal solution and the farthest distance from the negative ideal solution. The TOPSIS can be applied to a design process for carrying out multi-objective shape optimization wherein the best and worst alternatives are to be decided. In this paper, multi-objective shape optimization using the TOPSIS and Rational Bezier curve was applied to the funnel of a cathode-ray tube (CRT). In order to minimize the weight and first principal stress, a new multi-objective shape optimization methodology is proposed, wherein the relative-closeness coefficients of the TOPSIS are defined as the performance indices of a multi-objective function and evaluated by response surface models. This methodology enables the designer to decide on the best solution from a number of design specification groups by examining the various conflicts between the weight and the first principal stress.