• Journal of the Korean Crystal Growth and Crystal Technology
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• v.22 no.1
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• pp.5-10
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• 2012

In general, the fabrications of the LEDs with mesa structure are performed grown by MOCVD method. In order to etch and separate each chips, the LEDs are passed the RIE and scribing processes. The RIE process using plasma dry etching occur some problems such as defects, dislocations and the formation of dangling bond in surface result in decline of device characteristic. The SAG method has attracted considerable interest for the growth of high quality GaN epi layer on the sapphire substrate. In this paper, the SAG method was introduced for simplification and fabrication of the high quality epi layer. And we report that the size of selective area do not affect the characteristics of original LED. The diameter of SAG circle patterns were choose as 2500, 1000, 350, and 200 ${\mu}m$. The SAG-LEDs were measured to obtain the device characteristics using by SEM, EL and I-V. The main emission peaks of 2500, 1000, 350, and 200 ${\mu}m$ were 485, 480, 450, and 445 nm respectively. The chips of 350, 200 ${\mu}m$ diameter were observed non-uniform surface and resistance was higher than original LED, however, the chips of 2500, 1000 ${\mu}m$ diameter had uniform surface and current-voltage characteristics were better than small sizes. Therefore, we suggest that the suitable diameter which do not affect the characteristic of original LED is more than 1000 ${\mu}m$.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.5
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• pp.587-609
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• 2019

Short-and long-term stabilities of bentonite, favored material as buffer in geological repositories for high-level waste were reviewed in this paper in addition to alternative design concepts of buffer to mitigate the thermal load from decay heat of SF (Spent Fuel) and further increase the disposal efficiency. It is generally reported that the irreversible changes in structure, hydraulic behavior, and swelling capacity are produced due to temperature increase and vapor flow between $150{\sim}250^{\circ}C$. Provided that the maximum temperature of bentonite is less than $150^{\circ}C$, however, the effects of temperature on the material, structural, and mineralogical stability seems to be minor. The maximum temperature in disposal system will constrain and determine the amount of waste to be disposed per unit area and be regarded as an important design parameter influencing the availability of disposal site. Thus, it is necessary to identify the effects of high temperature on the performance of buffer and allow for the thermal constraint greater than $100^{\circ}C$. In addition, the development of high-performance EBS (Engineered Barrier System) such as composite bentonite buffer mixed with graphite or silica and multi-layered buffer (i.e., highly thermal-conductive layer or insulating layer) should be taken into account to enhance the disposal efficiency in parallel with the development of multilayer repository. This will contribute to increase of reliability and securing the acceptance of the people with regard to a high-level waste disposal.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.221-241
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• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.04a
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• pp.1-2
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• 2011

Hybrid rockets have lately attracted attention as a strong candidate of small, low cost, safe and reliable launch vehicles. A significant topic is that the first commercially sponsored space ship, SpaceShipOne vehicle chose a hybrid rocket. The main factors for the choice were safety of operation, system cost, quick turnaround, and thrust termination. In Japan, five universities including Hokkaido University and three private companies organized "Hybrid Rocket Research Group" from 1998 to 2002. Their main purpose was to downsize the cost and scale of rocket experiments. In 2002, UNISEC (University Space Engineering Consortium) and HASTIC (Hokkaido Aerospace Science and Technology Incubation Center) took over the educational and R&D rocket activities respectively and the research group dissolved. In 2008, JAXA/ISAS and eleven universities formed "Hybrid Rocket Research Working Group" as a subcommittee of the Steering Committee for Space Engineering in ISAS. Their goal is to demonstrate technical feasibility of lowcost and high frequency launches of nano/micro satellites into sun-synchronous orbits. Hybrid rockets use a combination of solid and liquid propellants. Usually the fuel is in a solid phase. A serious problem of hybrid rockets is the low regression rate of the solid fuel. In single port hybrids the low regression rate below 1 mm/s causes large L/D exceeding a hundred and small fuel loading ratio falling below 0.3. Multi-port hybrids are a typical solution to solve this problem. However, this solution is not the mainstream in Japan. Another approach is to use high regression rate fuels. For example, a fuel regression rate of 4 mm/s decreases L/D to around 10 and increases the loading ratio to around 0.75. Liquefying fuels such as paraffins are strong candidates for high regression fuels and subject of active research in Japan too. Nakagawa et al. in Tokai University employed EVA (Ethylene Vinyl Acetate) to modify viscosity of paraffin based fuels and investigated the effect of viscosity on regression rates. Wada et al. in Akita University employed LTP (Low melting ThermoPlastic) as another candidate of liquefying fuels and demonstrated high regression rates comparable to paraffin fuels. Hori et al. in JAXA/ISAS employed glycidylazide-poly(ethylene glycol) (GAP-PEG) copolymers as high regression rate fuels and modified the combustion characteristics by changing the PEG mixing ratio. Regression rate improvement by changing internal ballistics is another stream of research. The author proposed a new fuel configuration named "CAMUI" in 1998. CAMUI comes from an abbreviation of "cascaded multistage impinging-jet" meaning the distinctive flow field. A CAMUI type fuel grain consists of several cylindrical fuel blocks with two ports in axial direction. The port alignment shifts 90 degrees with each other to make jets out of ports impinge on the upstream end face of the downstream fuel block, resulting in intense heat transfer to the fuel. Yuasa et al. in Tokyo Metropolitan University employed swirling injection method and improved regression rates more than three times higher. However, regression rate distribution along the axis is not uniform due to the decay of the swirl strength. Aso et al. in Kyushu University employed multi-swirl injection to solve this problem. Combinations of swirling injection and paraffin based fuel have been tried and some results show very high regression rates exceeding ten times of conventional one. High fuel regression rates by new fuel, new internal ballistics, or combination of them require faster fuel-oxidizer mixing to maintain combustion efficiency. Nakagawa et al. succeeded to improve combustion efficiency of a paraffin-based fuel from 77% to 96% by a baffle plate. Another effective approach some researchers are trying is to use an aft-chamber to increase residence time. Better understanding of the new flow fields is necessary to reveal basic mechanisms of regression enhancement. Yuasa et al. visualized the combustion field in a swirling injection type motor. Nakagawa et al. observed boundary layer combustion of wax-based fuels. To understand detailed flow structures in swirling flow type hybrids, Sawada et al. (Tohoku Univ.), Teramoto et al. (Univ. of Tokyo), Shimada et al. (ISAS), and Tsuboi et al. (Kyushu Inst. Tech.) are trying to simulate the flow field numerically. Main challenges are turbulent reaction, stiffness due to low Mach number flow, fuel regression model, and other non-steady phenomena. Oshima et al. in Hokkaido University simulated CAMUI type flow fields and discussed correspondence relation between regression distribution of a burning surface and the vortex structure over the surface.

• Journal of Bio-Environment Control
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• v.24 no.4
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• pp.308-316
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• 2015

This study was conducted to investigate the situation of ICT apply to plastic greenhouse, and the results be apply to design of new one. A CFD analysis were conducted to monitering the ventilation and energy saving of the single span greenhouse newly designed. The causes of delay to apply ICT to plastic greenhouse are the high cost for installation(24%), insufficiency of after services(19%), often disorder(16%), unskillful management of soft ware(15%), insufficient ICT efficiency(13%) and unsatisfying of income increase(12%). The parts of problem occurred in ICT plastic greenhouse are the structure, actuator, environmental control system and sensor(approximate 14%, respectively), remote control technique(13%), plant management technique(12%), energy saving technique(10%) and utilization of software(8%). In the condition of lateral window closed, the average wind speed changed to slow, but it was faster in the condition of leeward side window opened than in the condition of lee and winward side window opened. The air movement in the condition of lateral window closed occur by air moving fan not by out air. It is not affect the room temperature but effective the uniformity of room temperature. The average temperature of low height greenhouse was uniform than high height one. The average temperature in condition of 3rd curtain opened become same with outside temperature after 2 hours, but take more 5 hours in condition of 3rd curtain closed.

• Journal of Bio-Environment Control
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• v.13 no.4
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• pp.217-225
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• 2004

This study was performed to provide the basic knowledge about the mushroom cultivation facilities. Classified current status of cultivation facilities in Gyeongnam province was investigated by questionnaire. The structure of Pleurotus eryngii cultivation facilities can be classified into the simple and permanent frame type. The simple frame structures were mostly single-span type, on the other hand, the permanent frame structures were more multi-span than simple structures. And the scale of cultivation facilities was very different regardless of structural type. But as a whole, the length, width and ridge height were prevailing approximately 20.0 m, $6.6\~7.0m$ and $4.6\~5.0m$ range, respectively. The floor area was about $132\~160\;m^2$, and floor was built with concrete to protect mushrooms from various harmful infection. The roof slope of the simple and permanent type showed about $41.5^{\circ}\;and\;18.6\~28.6^{\circ}$, respectively. The width and layer number of growing bed for mushroom cultivation were around $1.2\~1.6m$, 4 layers in common, respectively. Most of year round cultivation facilities were equipped with cooler, heater, humidifier, and ventilating fan. Hot water boiler was the most commonly used heating system, the next was electric heater and then steam boiler. The industrial air conditioner has been widely used for cooling. And humidity was controlled mostly by ultra-wave or centrifuging humidifier. But some farmers has been using nozzle system for auxiliary purpose. More then $90\%$ of the mushroom house had the independent environment control system. The inside temperature was usually controlled by sensor, but humidity and $CO_2$ concentration was controlled by timer for each growing stage. The capacity of medium bottle was generally 850 cc and 1100cc, some farms used 800 cc, 950 co and 1,250 cc. Most of mushroom producted has been usually shipped to both circulating company and joint market.

• The Korean Journal of Petroleum Geology
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• v.14 no.1
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• pp.1-11
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• 2008

As conventional oil and gas reservoirs become depleted, interests for oil sands has rapidly increased in the last decade. Oil sands are mixture of bitumen, water, and host sediments of sand and clay. Most oil sand is unconsolidated sand that is held together by bitumen. Bitumen has hydrocarbon in situ viscosity of >10,000 centipoises (cP) at reservoir condition and has API gravity between $8-14^{\circ}$. The largest oil sand deposits are in Alberta and Saskatchewan, Canada. The reverves are approximated at 1.7 trillion barrels of initial oil-in-place and 173 billion barrels of remaining established reserves. Alberta has a number of oil sands deposits which are grouped into three oil sand development areas - the Athabasca, Cold Lake, and Peace River, with the largest current bitumen production from Athabasca. Principal oil sands deposits consist of the McMurray Fm and Wabiskaw Mbr in Athabasca area, the Gething and Bluesky formations in Peace River area, and relatively thin multi-reservoir deposits of McMurray, Clearwater, and Grand Rapid formations in Cold Lake area. The reservoir sediments were deposited in the foreland basin (Western Canada Sedimentary Basin) formed by collision between the Pacific and North America plates and the subsequent thrusting movements in the Mesozoic. The deposits are underlain by basement rocks of Paleozoic carbonates with highly variable topography. The oil sands deposits were formed during the Early Cretaceous transgression which occurred along the Cretaceous Interior Seaway in North America. The oil-sands-hosting McMurray and Wabiskaw deposits in the Athabasca area consist of the lower fluvial and the upper estuarine-offshore sediments, reflecting the broad and overall transgression. The deposits are characterized by facies heterogeneity of channelized reservoir sands and non-reservoir muds. Main reservoir bodies of the McMurray Formation are fluvial and estuarine channel-point bar complexes which are interbedded with fine-grained deposits formed in floodplain, tidal flat, and estuarine bay. The Wabiskaw deposits (basal member of the Clearwater Formation) commonly comprise sheet-shaped offshore muds and sands, but occasionally show deep-incision into the McMurray deposits, forming channelized reservoir sand bodies of oil sands. In Canada, bitumen of oil sands deposits is produced by surface mining or in-situ thermal recovery processes. Bitumen sands recovered by surface mining are changed into synthetic crude oil through extraction and upgrading processes. On the other hand, bitumen produced by in-situ thermal recovery is transported to refinery only through bitumen blending process. The in-situ thermal recovery technology is represented by Steam-Assisted Gravity Drainage and Cyclic Steam Stimulation. These technologies are based on steam injection into bitumen sand reservoirs for increase in reservoir in-situ temperature and in bitumen mobility. In oil sands reservoirs, efficiency for steam propagation is controlled mainly by reservoir geology. Accordingly, understanding of geological factors and characteristics of oil sands reservoir deposits is prerequisite for well-designed development planning and effective bitumen production. As significant geological factors and characteristics in oil sands reservoir deposits, this study suggests (1) pay of bitumen sands and connectivity, (2) bitumen content and saturation, (3) geologic structure, (4) distribution of mud baffles and plugs, (5) thickness and lateral continuity of mud interbeds, (6) distribution of water-saturated sands, (7) distribution of gas-saturated sands, (8) direction of lateral accretion of point bar, (9) distribution of diagenetic layers and nodules, and (10) texture and fabric change within reservoir sand body.