• Clean Technology
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• v.13 no.1 s.36
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• pp.1-15
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• 2007

Biological treatment is a relatively recent air pollution control technology in which off-gases containing biodegradable odors and volatile organic compounds(VOCs) are vented through microbes. It is a promising alternative to conventional air pollution control methods. Bioreactors for air pollution control have found most of their success in the treatment of dilute and high flow waste air streams containing VOCs and odor compounds. They offer several advantages over traditional technologies such as incineration or adsorption. These include lower treatment costs, absence of formation of secondary pollutants, no spent chemicals, low energy demand and low temperature treatment. The three most widely used technologies are described, namely biofiltration, biotrickling filtration, bioscrubbing. The most widely used bioreactor for air pollution control is biofilter, but it has several limitations. In the past years major progress has been accomplished in the development of vapor phase bioreaction systems, for solving problems of biofilter. Biotrickling filters are more complex than biofilters, but are usually more effective, especially for the treatment of compounds which are difficult to degrade or compounds that generate acidic by-products. This, paper reviews fundamental and theoretical/practical aspect of air pollution control in biofilter, biotrickling filter and bioscrubber, focusing more extensively on biotrickling filtration. Special emphasis is given to the operating parameters and the factors influencing performance for air pollution control, and cost estimation in biotreatment technologies.

• Korean Journal of Agricultural Science
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• v.4 no.1
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• pp.34-42
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• 1977

Three kinds of selection indexes were calculated and compared for effectiveness in selecting best performing hybrids from yield trial of corn. The following four characters were used in calculating indexes; yield, moisture content, and root and stalk lodging. 1. Among three indexes calculated, William's base index was more simple in calculation and more efficient in selection of a hybrid than other indexes. 2. Pesek and Baker's estimated index was considered less effective in this test, because of low estimation of genetic variance and covariances of characters from the limited materials and years of experiment. 3. Index calculated according to the Purdue University method (1976) was least effective, even though calculation was simple and easy. The less effectiveness of the index was due to the fact that equal importance of characters were given to each character without considering the differences in economic weight of each character. 4. Equations for expressing moisture content and root and stalk lodging in terms of market price were formulated and they were as follow : 1) Moisture content : $(Y-15.5){\times}$0.0065{\times}bushels/acre$, where Y was the average moisture content of a hybrid at the time harvest. The $0.0065 was the expenses required for removing one per cent of moisture from a bushel of shelled corn in 1976. 2) Root and stalk lodging:$Percent\;lodging{\times}price/Bu.{\div}50{\div}average$ yield of all entries in the test.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.539-553
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• 2017

We propose a multi-state model to analyze semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the three states of the illness-death model: healthy, disease, and dead. The 'diseased' state can be considered as the intermediate event. Two more states are added into the illness-death model to incorporate the missing events, which are caused by a loss of follow-up before the end of a study. One of them is a state of the lost-to-follow-up (LTF), and the other is an unobservable state that represents an intermediate event experienced after the occurrence of LTF. Given covariates, we employ the Lin and Ying additive hazards model with log-normal frailty and construct a conditional likelihood to estimate transition intensities between states in the multi-state model. A marginalization of the full likelihood is completed using adaptive importance sampling, and the optimal solution of the regression parameters is achieved through an iterative quasi-Newton algorithm. Simulation studies are performed to investigate the finite-sample performance of the proposed estimation method in terms of empirical coverage probability of true regression parameters. Our proposed method is also illustrated with a dataset adapted from Helmer et al. (2001).

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.6
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• pp.173-183
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• 2015

The aim of this study was to develop a soil moisture simulation model equipped with meteorological data enhanced by WRF (Weather Research and Forecast) model, and this soil moisture model was applied for quantifying soil moisture content and irrigation requirement. The WRF model can provide grid based meteorological data at various resolutions. For applicability assessment, comparative analyses were conducted using WRF data and weather data obtained from weather station located close to test bed. Water balance of each upland grid was assessed for soils represented with four layers. The soil moisture contents simulated using the soil moisture model were compared with observed data to evaluate the capacity of the model qualitatively and quantitatively with performance statistics such as correlation coefficient (R), coefficient of determination (R2) and root mean squared error (RMSE). As a result, R is 0.76, $R^2$ is 0.58 and RMSE 5.45 mm in soil layer 1 and R 0.61, $R^2$ 0.37 and RMSE 6.73 mm in soil layer 2 and R 0.52, $R^2$ 0.27 and RMSE 8.64 mm in soil layer 3 and R 0.68, $R^2$ 0.45 and RMSE 5.29 mm in soil layer 4. The estimated soil moisture contents and irrigation requirements of each soil layer showed spatiotemporally varied distributions depending on weather and soil texture data incorporated. The estimated soil moisture contents using weather station data showed uniform distribution about all grids. However the estimated soil moisture contents from WRF data showed spatially varied distribution. Also, the estimated irrigation requirements applied WRF data showed spatial variabilities reflecting regional differences of weather conditions.

• Journal of Biomedical Engineering Research
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• v.25 no.1
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• pp.21-26
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• 2004

Recently, many people want to know their state of health, such as a body fat rate, anywhere and anytime. The Personal Digital Assistance(PDA) is the portable wireless apparatus that has become widely popular. There are many application areas of the IDA to be in mobile care devices. In this study, we developed the PDA based body fat measurement system, composed of a cradle type measurement module and a WindowCE operated software module, a regression equation for predicting lean body mass (LBM). Sixty-three weight-stable subjects (53 men, 10 women) aged 20∼32yr participated in this study. A regression model, LBM ＝ (0.0005＊Height2 - 0.0160＊Impedance ＋ 0.3920＊Weight - 0.0684＊Age - 5.8141＊Sex ＋ 25.984, was found. The correlation coefficient( r) of body fat rate between developed system and HTM1000plus(BionetTM) was 0.928. HTM1000plus is a commercially available and approved by KFDA. These results indicated that developed system is reliable for estimation of body fat rate. Although developed system is the PDA based miniaturized, it shows good performance comparing with other commercial product.

• JSTS:Journal of Semiconductor Technology and Science
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• v.5 no.3
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• pp.149-158
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• 2005

This paper describes design, fabrication, and application of the silicon based temperature controllable micro reactor. In order to achieve fast temperature variation and low energy consumption, reaction chamber of the micro reactor was thermally isolated by etching the highly conductive silicon around the reaction chamber. Compared with the model not having thermally isolated structure, the thermally isolated micro reactor showed enhanced thermal performances such as fast temperature variation and low energy consumption. The performance enhancements of the micro reactor due to etched holes were verified by thermal experiment and numerical analysis. Regarding to 42 percents reduction of the thermal mass achieved by the etched holes, approximately 4 times faster thermal variation and 5 times smaller energy consumption were acquired. The total size of the fabricated micro reactor was $37{\times}30{\times}1mm^{3}$. Microchannel and reaction chamber were formed on the silicon substrate. The openings of channel and chamber were covered by the glass substrate. The Pt electrodes for heater and sensor are fabricated on the backside of silicon substrate below the reaction chamber. The dimension of channel cross section was $200{\times}100{\mu}m^{2}$. The volume of reaction chamber was $4{\mu}l$. The temperature of the micro reactor was controlled and measured simultaneously with NI DAQ PCI-MIO-16E-l board and LabVIEW program. Finally, the fabricated micro reactor and the temperature control system were applied to the thermal denaturation and the trypsin digestion of protein. BSA(bovine serum albumin) was chosen for the test sample. It was successfully shown that BSA was successfully denatured at $75^{\circ}C$ for 1 min and digested by trypsin at $37^{\circ}C$ for 10 min.

• Journal of the Korean Geotechnical Society
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• v.21 no.8
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• pp.73-84
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• 2005

A three layered neural network model was developed using back propagation algorithm to estimate the UU undrained shear strength of Korean soft soil based on the database of actual undrained shear strengths and piezocone measurements compiled from 8 sites over the Korea. The developed model was validated by comparing model predictions with measured values about new piezocone data, which were not previously employed during development of model. Performance of the neural network model was also compared with conventional empirical methods. It was found that the number of neuron in hidden layer is different for the different combination of transfer functions of neural network models. However, all piezocone neural network models are successful in inferring a complex relationship between piezocone measurements and the undrained shear strength of Korean soft soils, which give relatively high coefficients of determination ranging from 0.69 to 0.72. Since neural network model has been generalized by self-learning from database of piezocone measurements and undrained shear strength over the various sites, the developed neural network models give more precise and generally reliable undrained shear strengths than empirical approaches which still need site specific calibration.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8B
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• pp.637-646
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• 2012

Recently, Wireless Sensor Networks (WSNs) are used in many applications. When sensor nodes are deployed on special areas, where humans have any difficulties to get in, the nodes form network topology themselves. By using the sensor nodes, users are able to obtain environmental information. Due to the lack of the battery capability, sensor nodes should be efficiently managed with energy consumption in WSNs. In specific applications (e.g. in intrusion detections), intruders tend to occur unexpectedly. For the energy efficiency in the applications, an appropriate algorithm is strongly required. In this paper, we propose tree-based routing algorithm for the specific applications, which based on the intrusion detection. In addition, In order to decrease traffic density, the proposed algorithm provides enhanced method considering link cost and load balance, and it establishes efficient links amongst the sensor nodes. Simultaneously, by using the proposed scheme, parent and child nodes are (re-)defined. Furthermore, efficient routing table management facilitates to improve energy efficiency especially in the limited power source. In order to apply a realistic military environment, in this paper, we design three scenarios according to an intruder's moving direction; (1) the intruder is passing along a path where sensor nodes have been already deployed. (2) the intruders are crossing the path. (3) the intruders, who are moving as (1)'s scenario, are certainly deviating from the middle of the path. In conclusion, through the simulation results, we obtain the performance results in terms of latency and energy consumption, and analyze them. Finally, we validate our algorithm is highly able to adapt on such the application environments.

• The KIPS Transactions:PartA
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• v.14A no.1 s.105
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• pp.63-72
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• 2007

This paper introduces a load-balancing algorithm focusing on distributing web requests evenly into the web cluster servers. The load-balancing algorithms based on conventional periodic load-information update mechanism are not suitable for dynamic page applications, which are common in Cyber Foraging services, due to the problems caused by periodic synchronized load-information updating and the difficulties of work load estimation caused by embedded executing scripts of dynamic pages. Update-on-Finish algorithm solves this problem by using non-periodic load-update mechanism, and the web switch knows the servers' real load information only after their reporting and then distributes new loads according to the new load-information table, however it results in much communication overhead. Our proposed mechanism improve update-on-finish algorithm by using K-Percents-Finish mechanism and thus largely reduce the communication overhead. Furthermore, we consider the different capabilities of servers with a threshold Ti value and propose a load-balancing algorithm for servers with various capabilities. Simulation results show that the proposed K-Percents-Finish Reporting mechanism can at least reduce 50% communication overhead than update-on-finish approach while sustaining better load balancing performance than periodic mechanisms in related work.

• Korean Journal of Construction Engineering and Management
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• v.13 no.5
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• pp.3-11
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• 2012

The most of domestic bridge has an used life under 30 years, Future maintenance budgets can be expected to increase. However, because of bridge maintenance budgets are limited, demand for asset management being performed to achieve required performance within available budget is increasing. To perform effective asset management of bridges should be made the best use of information to occur in all phase of construction project. Therefore, the development of system and DB is required to support asset management by effective information management. The objective of this study is the development of the BIM-based bridge asset management model. Through previous research survey, BIM capabilities and asset management components were established and mutual linkages were examined. Bridge asset management model was composed of alternate assessment model. In addition, BIM-based asset management model was performed case studies to verify feasibility and applicability. The proposed model can be applied to a current bridge maintenance procedures and supported to perform effective bridge maintenance tasks within a limited budget.