• Journal of the Korean Institute of Gas
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• v.12 no.2
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• pp.38-41
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• 2008

In this research, we propose a new method for tracking the release rate using the concentration data obtained from the sensor. We used a sensor network that has already been set surrounding the area where hazardous gas releases can occur. From the real-time sensor data, we detected and analyzed releases of harmful materials and their concentrations. Based on the results, the release rate is estimated using the neural network. This model consists of 14 input variables (sensor data, material properties, process information, meteorological conditions) and one output (release rate). The dispersion model then performs the simulation of the expected dispersion consequence by combining the sensor data, GIS data and the diagnostic result of the source term. The result of this study will improve the safety-concerns of residents living next to storage facilities containing hazardous materials by providing the enhanced emergency response plan and monitoring system for toxic gas releases.

• Korean Chemical Engineering Research
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• v.52 no.6
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• pp.720-726
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• 2014

PEM fuel cell vehicles have been getting much attraction due to a sort of highly clean and effective transportation. The onboard fuel processor, however, is inevitably required to supply the hydrogen by conversion from some fuels since there are not enough available hydrogen stations nearby. A lot of studies have been focused on analyses of ATR reactor under the assumption of thermo-neutral condition and those of the optimized process for the minimization of energy consumption using thermal efficiency as an objective function, which doesn't guarantee the maximum hydrogen production. In this study, the analysis of optimization for 100 kW PEMFC onboard fuel processor was conducted targeting various fuels such as gasoline, LPG, diesel using newly defined hydrogen efficiency and keeping simply synthesized heat exchanger network regardless of external utilities leading to compactness and integration. Optimal result of gasoline case shows 9.43% reduction compared to previous study, which shows the newly defined objective function leads to better performance than thermal efficiency in terms of hydrogen production. The sensitivity analysis was also done for hydrogen efficiency, heat recovery of each heat exchanger, and the cost of each fuel. Finally, LPG was estimated as the most economical fuel in Korean market.

• 한국생물공학회:학술대회논문집
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• 2000.04a
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• pp.173-176
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• 2000

A neural network based controller (NN controller) was studied for the control of ammonia concentrations in biological processes. An ammonia FIA has been employed to on-line monitor the concentrations of ammonia in a bioreactor. The optimal neural network structure was investigated by computer simulation and found to be a 3(inputlayer)-2(hidden layer)-1(output layer). The NN controller had advantage over the PID controller, even though the former is more time consuming. The 3-2-1 NN controller has been used to control the ammonia concentrations in a simulated bioprocess and also in a real cultivation process of yeast, and its performance were investigated.

• Journal of Biomedical Engineering Research
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• v.9 no.1
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• pp.17-24
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• 1988

This paper describes a neural network modelling of a vertebrate retina using a discrete-time and discrete-space approach based on neuro-anatomical data, and the computer simulations of the model which approximate the frog/amphibian negro-physiological data. It then compares them and describes how such a model can be beneficially used for confirming the hypothesis of a given neural system and further predict yet unknown experimental data.

• IMMUNE NETWORK
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• v.13 no.2
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• pp.43-54
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• 2013

Over the past 40 years, flow cytometry has emerged as a leading, application-rich technology that supports high-resolution characterization of individual cells which function in complex cellular networks such as the immune system. This brief overview highlights advances in multiparameter flow cytometric technologies and reagent applications for characterization and functional analysis of cells modulating the immune network. These advances significantly support highthroughput and high-content analyses and enable an integrated understanding of the cellular and molecular interactions that underlie complex biological systems.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.608-613
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• 2009

This study aims to examine terrorism by biological agents. These days terrorism evolved so rapidly that more than one terror occurs a day in global society as we are on the edge of so-called New-terrorism. One of new examples of new terrorism is Bioterrorism by biological agents. In order to address Bioterrorism we should conduct a study to examine things to be prepared at ordinary times and future plans. As an effort to develop countermeasures against Bioterrorism, anti-terrorism laws should be made on Prevention phases anti-terrorism funding laws as well. Other Bioterrorism laws need to be made. On Response phases initial reaction task force should be ready for making positive initial reaction. A special hospital for CBR(Chemical, Biological, and Radiological) warfare needs to be designated to practice medicine. Biological-Safety-Levels should be constructed by IV levels. Effective public promotion network should be built. On Recovery phases evaluation system needs to be suggested and international cooperative network should be established.

• Macromolecular Research
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• v.15 no.4
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• pp.363-369
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• 2007

Novel biodegradable elastic hydrogels, based on hydrophilic and hydrophobic polymer blocks, were synthesized via the radical crosslinking reaction of diacrylates of poly(ethylene glycol) (PEG) and poly(${\varepsilon}-caprolactone$) (PCL). PEG and PCL diols were diacrylated with acryloyl chloride in the presence of triethylamine, with the reaction confirmed by FT-IR and $^1H-NMR$ measurements. The diacrylate polymers were used as building-blocks for the syntheses of a series of hydro gels, with different block compositions, by simply varying the feed ratios and molecular weights of the block components. The swelling ratio of the hydrogels was controlled by the balance between the hydrophilic and hydrophobic polymer blocks. Usually, the swelling ratio increases with increasing PEG content and decreasing block length within the network structure. The hydrogels exhibited negative thermo-sensitive swelling behavior due to the coexistence of hydrophilic and hydrophobic polymer components in their network structure, and such thermo-responsive swelling/deswelling behavior could be repeated using a temperature cycle, without any significant change in the swelling ratio. In vitro degradation tests showed that degradation occurred over a 3 to 8 month period. Due to their biodegradability, biocompatibility, elasticity and functionality, these hydrogels could be utilized in various biomedical applications, such as tissue engineering and drug delivery systems.

• Journal of Biomedical Engineering Research
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• v.19 no.1
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• pp.39-46
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• 1998

In this paper, we present a neural network identification and a control of highly complicated nonlinear left ventricular assist device(LVAD) system with a pneumatically driven mock circulation system. Generally, the LVAD system needs to compensate for nonlinearities. It is necessary to apply high performance control techniques. Fortunately, the neural network can be applied to control of a nonlinear dynamic system by learning capability. In this study, we identify the LVAD system with neural network identification(NNI). Once the NNI has learned the dynamic model of the LVAD system, the other network, called neural network controller(NNC), is designed for a control of the LVAD system. The ability and effectiveness of identifying and controlling the LVAD system using the proposed algorithm will be demonstrated by computer simulation.

• Genomics & Informatics
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• v.15 no.1
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• pp.19-27
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• 2017

Understanding complex relationships among heterogeneous biological data is one of the fundamental goals in biology. In most cases, diverse biological data are stored in relational databases, such as MySQL and Oracle, which store data in multiple tables and then infer relationships by multiple-join statements. Recently, a new type of database, called the graph-based database, was developed to natively represent various kinds of complex relationships, and it is widely used among computer science communities and IT industries. Here, we demonstrate the feasibility of using a graph-based database for complex biological relationships by comparing the performance between MySQL and Neo4j, one of the most widely used graph databases. We collected various biological data (protein-protein interaction, drug-target, gene-disease, etc.) from several existing sources, removed duplicate and redundant data, and finally constructed a graph database containing 114,550 nodes and 82,674,321 relationships. When we tested the query execution performance of MySQL versus Neo4j, we found that Neo4j outperformed MySQL in all cases. While Neo4j exhibited a very fast response for various queries, MySQL exhibited latent or unfinished responses for complex queries with multiple-join statements. These results show that using graph-based databases, such as Neo4j, is an efficient way to store complex biological relationships. Moreover, querying a graph database in diverse ways has the potential to reveal novel relationships among heterogeneous biological data.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.04a
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• pp.8-8
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• 2018

Muscle atrophy, known as a sarcopenia, is defined as a loss of muscle mass resulting from a reduction in muscle fiber area or density due to a decrease in muscle protein synthesis and an increase in protein breakdown. Many conditions are associated with muscle atrophy, such as aging, denervation, disuse, starvation, severe injury and inflammation, prolonged bed rest, glucocorticoid treatment, sepsis, cancer, and other cachectic diseases. On the other hand, osteoarthritis (OA) is the most common form of joint disease and is wide spread in the elderly population and is characterized by erosion of articular cartilage, osteophyte formation, and subchondral bone sclerosis. The cytokine network plays an important role in the development and progression of OA with the inflammatory cytokine. Schisandrae Fructus (SF) derived from the ripe fruit of Schisandra chinensis (Turcz.) Baill. (Magnoliaceae) has been extensively used in traditional herbal medicines in Asia. It was originally used as a tonic and has been traditionally used for the treatment of many uncomfortable symptoms, such as cough, dyspnea, dysentery, insomnia, and amnesia for a long time. Previous reports have shown that SF and its related compounds possess various biological activities such as antioxidant, anti-inflammatory, anticancer, anti-microbial, antiseptic, anti-aging, hepatoprotective and immunostimulating effects. However, the therapeutic effects of SF on muscle atrophy and OA has not yet been evaluated. In the present study, we aimed to determine whether extracts of SF, the dried fruit of S. chinensis, mitigates the development of muscle atrophy and OA.