Search results for: Sung Gi Kwon
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 364

Search results for: Sung Gi Kwon

154 Generation of Charged Nanoparticles in the Gas Phase and their Contribution to Deposition of GaN Films and Nanostructures during Atmospheric Pressure Chemical Vapor Deposition

Authors: Jin-Woo Park, Sung-Soo Lee, Nong-Moon Hwang

Abstract:

The generation of charged nanoparticles in the gas phase during the Chemical Vapor Deposition (CVD) process has been frequently reported with their subsequent deposition into films and nanostructures in many systems such as carbon, silicon and zinc oxide. The microstructure evolution of films and nanostructures is closely related with the size distribution of charged nanoparticles. To confirm the generation of charged nanoparticles during GaN, the generation of GaN charged nanoparticles was examined in an atmospheric pressure CVD process using a Differential Mobility Analyser (DMA) combined with a Faraday Cup Electrometer (FCE). It was confirmed that GaN charged nanoparticles were generated under the condition where GaN nanostructures were synthesized on the bare and Au-coated Si substrates. In addition, the deposition behaviour depends strongly on the charge transfer rate of metal substrates. On the metal substrates of a lower CTR such as Mo, the deposition rate of GaN was much lower than on those of a higher CTR such as Fe. GaN nanowires tend to grow on the substrates of a lower CTR whereas GaN thin films tend to be deposited on the substrates of a higher CTR.

Keywords: chemical vapour deposition, charged cluster model, generation of charged nanoparticles, deposition behaviour, nanostructures, gan, charged transfer rate

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153 Effect of Mineral Admixture on Self-Healing Performance in Concrete

Authors: Young-Cheol Choi, Sung-Won Yoo, Bong Chun Lee, Byoungsun Park, Sang-Hwa Jung

Abstract:

Cracks in concrete commonly provide the passages of ingresses of aggressive and harmful ions into concrete inside and thus reduce the durability of concrete members. In order to solve this problem, self-healing concrete based on mineral admixture has become a major issue. Self-healing materials are those which have the ability of autonomously repairing some damages or small cracks in concrete structures. Concrete has an inherent healing potential, called natural healing, which can take place in ordinary concrete elements but its power is limited and is not predictable. The main mechanism of self-healing in cracked concrete is the continued hydration of unreacted binder and the crystallization of calcium carbonate. Some mineral admixtures have been found to promote the self-healing of cementitious materials. The aim of this study is to investigate the effect of mineral admixture on the self-healing performances of high strength concrete. The potential capability of self-healing of cementitious materials was evaluated using isothermal conduction calorimeter. The self-healing efficiencies were studied by means of water flow tests on cracked concrete specimens. The results show a different healing behaviour depending on presence of the crystalline admixture.

Keywords: mineral admixture, self-healing, water flow test, crystallization

Procedia PDF Downloads 336
152 Decision Tree Based Scheduling for Flexible Job Shops with Multiple Process Plans

Authors: H.-H. Doh, J.-M. Yu, Y.-J. Kwon, J.-H. Shin, H.-W. Kim, S.-H. Nam, D.-H. Lee

Abstract:

This paper suggests a decision tree based approach for flexible job shop scheduling with multiple process plans, i. e. each job can be processed through alternative operations, each of which can be processed on alternative machines. The main decision variables are: (a) selecting operation/machine pair; and (b) sequencing the jobs assigned to each machine. As an extension of the priority scheduling approach that selects the best priority rule combination after many simulation runs, this study suggests a decision tree based approach in which a decision tree is used to select a priority rule combination adequate for a specific system state and hence the burdens required for developing simulation models and carrying out simulation runs can be eliminated. The decision tree based scheduling approach consists of construction and scheduling modules. In the construction module, a decision tree is constructed using a four-stage algorithm, and in the scheduling module, a priority rule combination is selected using the decision tree. To show the performance of the decision tree based approach suggested in this study, a case study was done on a flexible job shop with reconfigurable manufacturing cells and a conventional job shop, and the results are reported by comparing it with individual priority rule combinations for the objectives of minimizing total flow time and total tardiness.

Keywords: flexible job shop scheduling, decision tree, priority rules, case study

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151 Grid Based Traffic Vulnerability Model Using Betweenness Centrality for Urban Disaster Management Information

Authors: Okyu Kwon, Dongho Kang, Byungsik Kim, Seungkwon Jung

Abstract:

We propose a technique to measure the impact of loss of traffic function in a particular area to surrounding areas. The proposed method is applied to the city of Seoul, which is the capital of South Korea, with a population of about ten million. Based on the actual road network in Seoul, we construct an abstract road network between 1kmx1km grid cells. The link weight of the abstract road network is re-adjusted considering traffic volume measured at several survey points. On the modified abstract road network, we evaluate the traffic vulnerability by calculating a network measure of betweenness centrality (BC) for every single grid cells. This study analyzes traffic impacts caused by road dysfunction due to heavy rainfall in urban areas. We could see the change of the BC value in all other grid cells by calculating the BC value once again when the specific grid cell lost its traffic function, that is, when the node disappeared on the grid-based road network. The results show that it is appropriate to use the sum of the BC variation of other cells as the influence index of each lattice cell on traffic. This research was supported by a grant (2017-MOIS31-004) from Fundamental Technology Development Program for Extreme Disaster Response funded by Korean Ministry of Interior and Safety (MOIS).

Keywords: vulnerability, road network, beweenness centrality, heavy rainfall, road impact

Procedia PDF Downloads 64
150 The Effect of Remifentanil on Emergence Agitation after Sevoflurane Anesthesia in Children: A Meta-Analysis

Authors: Jong Yeop Kim, Sung Young Park, Dae Hee Kim, Han Bum Joe, Ji Young Yoo, Jong Bum Choi, Sook Young Lee

Abstract:

Emergence agitation (EA) is commonly reported adverse events after sevoflurane anesthesia in pediatric patients. The efficacy of prophylactic remifentanil, one of mu opioid agonist, in preventing EA is controversial. This meta-analysis assessed the effectiveness of remifentanil to decrease the incidence of EA from sevoflurane anesthesia in children. We searched for randomized controlled trials comparing sevoflurane alone anesthesia with sevoflurane and remifentanil anesthesia to prevent EA in the Cochrane Library, Embase, Pubmed, and KoreaMed, and included 6 studies with 361 patients. The number of patients of reporting EA was summarized using risk ratio (RR) with 95% confidence interval (CI), with point estimates and 95CIs derived from a random effects Mantel-Haenszel method. Overall incidence of EA was about 41%. Compared with sevoflurane alone anesthesia, intravenous infusion of remifentanil with sevoflurane significantly reduced the incidence of EA (RR 0.53, 95% CI 0.39-0.73, P < 0.0001), (heterogeneity, I2 = 0, P = 0.42). This meta-analysis suggested that continuous infusion of remifentanil could be effective in decreasing the EA of about 47% after sevoflurane anesthesia. However, considering limitations of the included studies, more randomized controlled studies are required to verify our results.

Keywords: emergence agitation, meta-analysis, remifentanil, pediatrics

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149 Achievement of High L-Cysteine Yield from Enzymatic Conversion Using Eutectic Mixtures of the Substrate ATC

Authors: Deokyeong Choe, Sung Hun Youn, Younggon Kim, Chul Soo Shin

Abstract:

L-Cysteine, a sulfur-containing amino acid, has been often used in the pharmaceutical, cosmetic, food, and feed additive industries. This amino acid has been usually produced by acid-hydrolysis of human hair and poultry feathers. There are many problems, such as avoidance for use of animal hair, low yields, and formation of harmful waste material. As an alternative, the enzymatic conversion of D, L-2-amino-Δ2-thiazoline-4-carboxylic acid (ATC) to L-cysteine has been developed as an environmental-friendly method. However, the substrate solubility was too low to be used in industry. In this study, high concentrations of eutectic substrate solutions were prepared to solve the problem. Eutectic melting occurred at 39°C after mixing ATC and malonic acid at a molar ratio of 1:1. The characteristics of eutectic mixtures were analyzed by FE-SEM, EDS mapping, and XPS. However, since sorbitol, MnSO4, and NaOH should be added as supplements to the substrate mixture for the activation and stabilization of the enzyme, strategies for sequential addition of total five compounds, ATC, malonic acid, sorbitol, MnSO4, and NaOH were established. As a result, eutectic substrate mixtures of 670 mM ATC were successfully formulated. After 6 h of enzymatic reaction, 550 mM L-cysteine was made.

Keywords: D, L-2-amino-Δ2-thiazoline-4-carboxylicacid, enzymatic conversion, eutectic solution, l-cysteine

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148 A Spatial Point Pattern Analysis to Recognize Fail Bit Patterns in Semiconductor Manufacturing

Authors: Youngji Yoo, Seung Hwan Park, Daewoong An, Sung-Shick Kim, Jun-Geol Baek

Abstract:

The yield management system is very important to produce high-quality semiconductor chips in the semiconductor manufacturing process. In order to improve quality of semiconductors, various tests are conducted in the post fabrication (FAB) process. During the test process, large amount of data are collected and the data includes a lot of information about defect. In general, the defect on the wafer is the main causes of yield loss. Therefore, analyzing the defect data is necessary to improve performance of yield prediction. The wafer bin map (WBM) is one of the data collected in the test process and includes defect information such as the fail bit patterns. The fail bit has characteristics of spatial point patterns. Therefore, this paper proposes the feature extraction method using the spatial point pattern analysis. Actual data obtained from the semiconductor process is used for experiments and the experimental result shows that the proposed method is more accurately recognize the fail bit patterns.

Keywords: semiconductor, wafer bin map, feature extraction, spatial point patterns, contour map

Procedia PDF Downloads 347
147 Standardization of the Behavior Assessment System for Children-2, Parent Rating Scales - Adolescent Form (K BASC-2, PRS-A) among Korean Sample

Authors: Christine Myunghee Ahn, Sung Eun Baek, Sun Young Park

Abstract:

The purpose of this study was to evaluate the cross-cultural validity of the Korean version of the Behavioral Assessment System for Children 2nd Edition, Parent Rating Scales - Adolescent Form (K BASC-2, PRS-A). The 150-item K BASC-2, PRS-A questionnaire was administered to a total of 690 Korean parents or caregivers (N=690) of adolescent children in middle school and high school. Results from the confirmatory and exploratory factor analyses indicate that the K BASC-2, PRS-A yielded a 3-factor solution similar to the factor structure found in the original version of the BASC-2. The internal consistencies using the Cronbach’s alpha of the composite scale scores were in the .92~ .98 range. The overall reliability and validity of the K BASC-2, PRS-A seem adequate. Structural equation modeling was used to verify the theoretical relationship among the scales of Adaptability, Withdrawal, Somatization, Depression, and Anxiety, to render additional support for internal validity. Other relevant findings, practical implications regarding the use of the KBASC-2, PRS-A and suggestions for future research are discussed.

Keywords: behavioral assessment system, cross-cultural validity, parent report, screening

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146 Suitability Evaluation of CNW as Scaffold for Osteoblast

Authors: Hoo Cheol Lee, Dae Seung Kim, Sang Myung Jung, Gwang Heum Yoon, Hwa Sung Shin

Abstract:

Loss of bone tissue can occur due to a bone tissue disease and aging or fracture. Renewable formation of bone is mainly made by its differentiation and metabolism. For this reason, osteoblasts have been studied for regeneration of bone tissue. So, tissue engineering has attracted attention as a recovery means. In tissue engineering, a particularly important factor is a scaffold that supports cell growth. For osteoblast scaffold, we used the cellulose nanowhisker (CNW) extracted from marine organism. CNW is one of an abundant material obtained from a number of plants and animals. CNW is polymer consisting of monomer cellulose and this composition offers biodegradability and biocompatibility to CNW. Mechanical strength of CNW is superior to the existing natural polymers. In addition, substances of marine origin have a low risk of secondary infection by bacteria and pathogen in contrast with those of land-derived. For evaluating its suitability as an osteoblast scaffold, we fabricate CNW film for osteoblast culture and performed the MTT assay and ALP assay to confirm its cytotoxicity and effect on differentiation. Taking together these results, we assessed CNW is a potential candidate of a material for bone tissue regeneration.

Keywords: bone regeneration, cellulose nanowhisker, marine derived material, osteoblast

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145 Experimental Study on the Creep Characteristics of FRC Base for Composite Pavement System

Authors: Woo-Tai Jung, Sung-Yong Choi, Young-Hwan Park

Abstract:

The composite pavement system considered in this paper is composed of a functional surface layer, a fiber reinforced asphalt middle layer and a fiber reinforced lean concrete base layer. The mix design of the fiber reinforced lean concrete corresponds to the mix composition of conventional lean concrete but reinforced by fibers. The quasi-absence of research on the durability or long-term performances (fatigue, creep, etc.) of such mix design stresses the necessity to evaluate experimentally the long-term characteristics of this layer composition. This study tests the creep characteristics as one of the long-term characteristics of the fiber reinforced lean concrete layer for composite pavement using a new creep device. The test results reveal that the lean concrete mixed with fiber reinforcement and fly ash develops smaller creep than the conventional lean concrete. The results of the application of the CEB-FIP prediction equation indicate that a modified creep prediction equation should be developed to fit with the new mix design of the layer.

Keywords: creep, lean concrete, pavement, fiber reinforced concrete, base

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144 Urban Big Data: An Experimental Approach to Building-Value Estimation Using Web-Based Data

Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

Abstract:

Current real-estate value estimation, difficult for laymen, usually is performed by specialists. This paper presents an automated estimation process based on big data and machine-learning technology that calculates influences of building conditions on real-estate price measurement. The present study analyzed actual building sales sample data for Nonhyeon-dong, Gangnam-gu, Seoul, Korea, measuring the major influencing factors among the various building conditions. Further to that analysis, a prediction model was established and applied using RapidMiner Studio, a graphical user interface (GUI)-based tool for derivation of machine-learning prototypes. The prediction model is formulated by reference to previous examples. When new examples are applied, it analyses and predicts accordingly. The analysis process discerns the crucial factors effecting price increases by calculation of weighted values. The model was verified, and its accuracy determined, by comparing its predicted values with actual price increases.

Keywords: apartment complex, big data, life-cycle building value analysis, machine learning

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143 A Loop between Victimhood and Women with Choice: Case of Trafficked North Korean Women in China

Authors: Jinah Kwon

Abstract:

Why are there North Korean women who prefer their life in China, living as an undocumented migrant, to legal residence in South Korea? What is the line between choice and coercion in trafficking and how does it relate to family, especially in Asian culture? Is family function as a haven in the unsecured world or a fetter against the better world? Are the current international mechanisms on trafficked victims fully reflecting the voices of the victims? This study is about the paradoxical conditions of North Korean women situated in China as the trafficked victim and as members of their Chinese family. In order to answer the questions above, this study explored the case of trafficked North Korean women in China. This mixed-methods study employed in-depth interviews of 18 trafficked women living in China and a survey of 98 North Korean origin women residing in South Korea. From the survey, 40 out of 98 women from the survey indicated an unexpected function of trafficking, which was used as a channel of supporting the subjectivity of women in the North Korean context. Such results supported the actual observation and narratives of North Korean women who experienced trafficking from the author’s two visits to the Northeastern area of China in 2012 and 2018, respectively. Based on the findings, the last part of the study makes policy implications on international trafficking mechanisms—theories by Gayatri Spivak and Herbert A. Simon was employed to approach the relatively less dealt aspect of trafficking.

Keywords: China, North Korean women, trafficking, victimhood

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142 Performance Comparison of Situation-Aware Models for Activating Robot Vacuum Cleaner in a Smart Home

Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

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141 High Dissolution of ATC by pH Control and Its Enzymatic Conversion to L-Cysteine

Authors: Deokyeong Choe, Sung Hun Youn, Younggon Kim, Chul Soo Shin

Abstract:

L-Cysteine is extensively used as a supplement of pharmaceuticals, cosmetics, food and feed additives. It has obtained industrially by hydrolysis of human hair and poultry feathers. However, there are some problems such as the restriction of using materials from animals and the intractable waste pollution. The enzymatic conversion has been regarded as an environmental-friendly method. Currently, the biggest bottle-neck of enzymatic conversion is the low yield of L-cysteine due to the low substrate solubility. In this study, the method of enhancing the solubility of the substrate D,L-2-amino-Δ2-thiazoline-4-carboxylicacid (ATC) was developed and the enzymatic reaction at high concentration levels was performed. A large amount of substrate in aqueous solutions was dissolved by pH control using salts. As the pH of the solution increased, the solubility of ATC increased. It was thought that a shift of ATC from acid form (-COOH) to dissociated carboxylic group (-COO-) would improve its hydrophilicity leading to solubility increase. The highest solubility of ATC was 610 mM at pH 10.5, whereas the maximum reaction rate was obtained at pH 8.3. As a result, a high L-cysteine yield of 250 mM was achieved at pH 9.1, which was obtained from a combination of optimum pH conditions for ATC solubility and enzymatic conversion. This yield corresponds to approximately 18 times of that in previous reports.

Keywords: D, L-2-amino-Δ2-thiazoline-4-carboxylicacid, enzymatic conversion, high-substrate solubilization, L-Cysteine

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140 Finite-Sum Optimization: Adaptivity to Smoothness and Loopless Variance Reduction

Authors: Bastien Batardière, Joon Kwon

Abstract:

For finite-sum optimization, variance-reduced gradient methods (VR) compute at each iteration the gradient of a single function (or of a mini-batch), and yet achieve faster convergence than SGD thanks to a carefully crafted lower-variance stochastic gradient estimator that reuses past gradients. Another important line of research of the past decade in continuous optimization is the adaptive algorithms such as AdaGrad, that dynamically adjust the (possibly coordinate-wise) learning rate to past gradients and thereby adapt to the geometry of the objective function. Variants such as RMSprop and Adam demonstrate outstanding practical performance that have contributed to the success of deep learning. In this work, we present AdaLVR, which combines the AdaGrad algorithm with loopless variance-reduced gradient estimators such as SAGA or L-SVRG that benefits from a straightforward construction and a streamlined analysis. We assess that AdaLVR inherits both good convergence properties from VR methods and the adaptive nature of AdaGrad: in the case of L-smooth convex functions we establish a gradient complexity of O(n + (L + √ nL)/ε) without prior knowledge of L. Numerical experiments demonstrate the superiority of AdaLVR over state-of-the-art methods. Moreover, we empirically show that the RMSprop and Adam algorithm combined with variance-reduced gradients estimators achieve even faster convergence.

Keywords: convex optimization, variance reduction, adaptive algorithms, loopless

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139 Smart Product-Service System Innovation with User Experience: A Case Study of Chunmi

Authors: Ying Yu, Wen-Chi Kuo, Tung-Jung Sung

Abstract:

The Product-Service System (PSS) has received widespread attention due to the increasing global competition in manufacturing and service markets. Today’s smart products and services are driven by Internet of things (IoT) technologies which will promote the transformation from traditional PSS to smart PSS. Although the smart PSS has some of technological achievements in businesses, it often ignores the real demands of target users when using products and services. Therefore, designers should know and learn the User Experience (UX) of smart products, services and systems. However, both of academia and industry still lack relevant development experience of smart PSS since it is an emerging field. In doing so, this is a case study of Xiaomi’s Chunmi, the largest IoT platform in the world, and addresses the two major issues: (1) why Chunmi should develop smart PSS strategies with UX; and (2) how Chunmi could successfully implement the strategic objectives of smart PSS through the design. The case study results indicated that: (1) the smart PSS can distinguish competitors by their unique UX which is difficult to duplicate; (2) early user engagement is crucial for the success of smart PSS; and (3) interaction, expectation, and enjoyment can be treated as a three-dimensional evaluation of UX design for smart PSS innovation. In conclusion, the smart PSS can gain competitive advantages through good UX design in the market.

Keywords: design, smart PSS, user experience, user engagement

Procedia PDF Downloads 106
138 A Study on Solutions to Connect Distribution Power Grid up to Renewable Energy Sources at KEPCO

Authors: Seung Yoon Hyun, Hyeong Seung An, Myeong Ho Choi, Sung Hwan Bae, Yu Jong Sim

Abstract:

In 2015, the southern part of the Korean Peninsula has 8.6 million poles, 1.25 million km power lines, and 2 million transformers, etc. It is the massive amount of distribution equipments which could cover a round-trip distance from the earth to the moon and 11 turns around the earth. These distribution equipments are spread out like capillaries and supplying power to every corner of the Korean Peninsula. In order to manage these huge power facility efficiently, KEPCO use DAS (Distribution Automation System) to operate distribution power system since 1997. DAS is integrated system that enables to remotely supervise and control breakers and switches on distribution network. Using DAS, we can reduce outage time and power loss. KEPCO has about 160,000 switches, 50%(about 80,000) of switches are automated, and 41 distribution center monitoring&control these switches 24-hour 365 days to get the best efficiency of distribution networks. However, the rapid increasing renewable energy sources become the problem in the efficient operation of distributed power system. (currently 2,400 MW, 75,000 generators operate in distribution power system). In this paper, it suggests the way to interconnect between renewable energy source and distribution power system.

Keywords: distribution, renewable, connect, DAS (Distribution Automation System)

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137 An Experimental Study on the Influence of Mineral Admixtures on the Fire Resistance of High-Strength Concrete

Authors: Ki-seok Kwon, Dong-woo Ryu, Heung-Youl Kim

Abstract:

Although high-strength concrete has many advantages over generic concrete at normal temperatures (around 20℃), it undergoes spalling at high temperatures, which constitutes its structurally fatal drawback. In this study, fire resistance tests were conducted for 3 hours in accordance with ASTM E119 on bearing wall specimens which were 3,000mm x 3,000mm x 300mm in dimensions to investigate the influence the type of admixtures would exert on the fire resistance performance of high-strength concrete. Portland cement, blast furnace slag, fly ash and silica fume were used as admixtures, among which 2 or 3 components were combined to make 7 types of mixtures. In 56MPa specimens, the severity of spalling was in order of SF5 > F25 > S65SF5 > S50. Specimen S50 where an admixture consisting of 2 components was added did not undergo spalling. In 70MPa specimens, the severity of spalling was in order of SF5 > F25SF5 > S45SF5 and the result was similar to that observed in 56MPa specimens. Acknowledgements— This study was conducted by the support of the project, “Development of performance-based fire safety design of the building and improvement of fire safety” (18AUDP-B100356-04) which is under the management of Korea Agency for Infrastructure Technology Advancement as part of the urban architecture research project for the Ministry of Land, Infrastructure and Transport, for which we extend our deep thanks.

Keywords: high strength concrete, mineral admixture, fire resistance, social disaster

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136 Design and Performance Evaluation of Hybrid Corrugated-GFRP Infill Panels

Authors: Woo Young Jung, Sung Min Park, Ho Young Son, Viriyavudh Sim

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This study presents a way to reduce earthquake damage and emergency rehabilitation of critical structures such as schools, high-tech factories, and hospitals due to strong ground motions associated with climate changes. Regarding recent trend, a strong earthquake causes serious damage to critical structures and then the critical structure might be influenced by sequence aftershocks (or tsunami) due to fault plane adjustments. Therefore, in order to improve seismic performance of critical structures, retrofitted or strengthening study of the structures under aftershocks sequence after emergency rehabilitation of the structures subjected to strong earthquakes is widely carried out. Consequently, this study used composite material for emergency rehabilitation of the structure rather than concrete and steel materials because of high strength and stiffness, lightweight, rapid manufacturing, and dynamic performance. Also, this study was to develop or improve the seismic performance or seismic retrofit of critical structures subjected to strong ground motions and earthquake aftershocks, by utilizing GFRP-Corrugated Infill Panels (GCIP).

Keywords: aftershock, composite material, GFRP, infill panel

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135 Ethyl Carbamate in Korean Total Diet Study: Level, Dietary Intake, and Risk Assessment

Authors: Eunmi Koh, Bogyoung Choi, Dayeon Ryu, Jee-Yeon Lee, Sungok Kwon, Cho-Il Kim

Abstract:

Ethyl carbamate(EC) is a probable human carcinogen (Group 2A) found in alcoholic beverages and fermented foods. A total of 351 samples including fermented foods and alcoholic beverages were chosen from 734 foods appeared in the pooled intake data of 2008, 2009, 2010, and 2011 Korea National Health & Nutrition Examination Survey (KNHANES). Sampling was carried out from September 2013 to July 2016 in 18 supermarkets of 9 metropolitan cities in Korea. The samples were pooled, prepared according to various cooking methods, and analyzed. A total of 1245 samples were analyzed using gas chromatograph-mass spectrometer. EC was detected in 13 items (1.0%), which ranged from not-detected to 151 g/kg. Alcoholic beverages (maesilju, whisky, and bokbunjaju) and fermented soy products (soy sauce and soybean paste) were the food items with relatively higher EC levels. Dietary intake of EC in the Korean population was estimated to be 2.11 ng/kg body weight (bw) per day for average population and 8.42 ng/kg bw per day for high consumers (the 97.5th percentile). When the estimated average dietary exposure to EC was compared with the Benchmark Dose Lower Confidence Limit 10% (BMDL10) of 0.3 mg/kg bw per day, margin of exposure (MOE) values of 1420000 to 28000000 were observed. This indicates that there is no health concern for the Korean population.

Keywords: ethyl carbamate, total diet study, dietary exposure, margin of exposure

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134 Cellulose Acetate Nanofiber Modification for Regulating Astrocyte Activity via Simple Heat Treatment

Authors: Sang-Myung Jung, Jeong Hyun Ju, Gwang Heum Yoon, Hwa Sung Shin

Abstract:

Central nervous system (CNS) consists of neuronal cell and supporting cells. Astrocytes are the most common supporting cells and play roles in metabolism between neurons and blood vessel. For this function, engineered astrocytes have been studied as a therapeutic source for CNS injury. In neural tissue engineering, nanofiber has been suggested as an effective scaffold for providing structure and mechanical properties influencing physiology. Cellulose acetate (CA) has been investigated for material to fabricate scaffold because of its biocompatibility, biodegradability and fine thermal stability. In this research, CA nanofiber was modified via heat treatment and its effect on astrocyte activity was evaluated. Adhesion and viability of astrocyte were increased in proportion to stiffness. Additionally, expression of GFAP, a marker of astrocyte activation, was increased via stiffness of scaffold. This research suggests a simple modification method to change stiffness of CA nanofiber and shows cellular behavior affecting stiffness of three-dimensional scaffold independently. For the results, we highlight that the stiffness is a factor to regulate astrocyte activity.

Keywords: astrocyte, cellulose acetate, cell therapy, stiffness of scaffold

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133 A Study of Adaptive Fault Detection Method for GNSS Applications

Authors: Je Young Lee, Hee Sung Kim, Kwang Ho Choi, Joonhoo Lim, Sebum Chun, Hyung Keun Lee

Abstract:

A purpose of this study is to develop efficient detection method for Global Navigation Satellite Systems (GNSS) applications based on adaptive estimation. Due to dependence of radio frequency signals, GNSS measurements are dominated by systematic errors in receiver’s operating environment. Thus, to utilize GNSS for aerospace or ground vehicles requiring high level of safety, unhealthy measurements should be considered seriously. For the reason, this paper proposes adaptive fault detection method to deal with unhealthy measurements in various harsh environments. By the proposed method, the test statistics for fault detection is generated by estimated measurement noise. Pseudorange and carrier-phase measurement noise are obtained at time propagations and measurement updates in process of Carrier-Smoothed Code (CSC) filtering, respectively. Performance of the proposed method was evaluated by field-collected GNSS measurements. To evaluate the fault detection capability, intentional faults were added to measurements. The experimental result shows that the proposed detection method is efficient in detecting unhealthy measurements and improves the accuracy of GNSS positioning under fault occurrence.

Keywords: adaptive estimation, fault detection, GNSS, residual

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132 Characteristics of Oak Mushroom Cultivar, Bambithyang Developed by Golden Seed Project

Authors: Yeongseon Jang, Rhim Ryoo, Young-Ae Park, Kang-Hyeon Ka, Donha Choi, Sung-Suk Lee

Abstract:

Lentinula edodes (Berk.) Pegler, oak mushroom, is one of the most largely produced mushrooms in the world. To increase the competitiveness of Korean oak mushroom, golden seed project is ongoing. In this project, we develop new oak mushroom varieties to increase its productivity, quality, disease resistance, and so on. Through the project, new oak mushroom cultivar, Bambithyang was developed by mono-mono hybridization method. The optimum temperature for mycelial growth was at 25°C on potato dextrose agar (PDA) media. For the mass production test, it was cultivated using sawdust media with sawdust block type for 100 days. The temperature for primordia formation and fruit body production was broad (between 11°C and 20°C) which is good for spring and fall. Each flush period lasted for 6-7 days and the highest fruit body production was recorded in the first flush. The fruiting is sporadic. The pileus was deep brown. Its diameter was 69.2 mm and width was 17.8 mm. The stipe was ivory. It was 14.7 mm thick and 54.7 mm long. We would continue to develop new varieties while increasing the market share of domestic spawn with this variety.

Keywords: Lentinula edodes, mono-mono hybridization, new cultivar, oak mushroom

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131 Development of pm2.5 Forecasting System in Seoul, South Korea Using Chemical Transport Modeling and ConvLSTM-DNN

Authors: Ji-Seok Koo, Hee‑Yong Kwon, Hui-Young Yun, Kyung-Hui Wang, Youn-Seo Koo

Abstract:

This paper presents a forecasting system for PM2.5 levels in Seoul, South Korea, leveraging a combination of chemical transport modeling and ConvLSTM-DNN machine learning technology. Exposure to PM2.5 has known detrimental impacts on public health, making its prediction crucial for establishing preventive measures. Existing forecasting models, like the Community Multiscale Air Quality (CMAQ) and Weather Research and Forecasting (WRF), are hindered by their reliance on uncertain input data, such as anthropogenic emissions and meteorological patterns, as well as certain intrinsic model limitations. The system we've developed specifically addresses these issues by integrating machine learning and using carefully selected input features that account for local and distant sources of PM2.5. In South Korea, the PM2.5 concentration is greatly influenced by both local emissions and long-range transport from China, and our model effectively captures these spatial and temporal dynamics. Our PM2.5 prediction system combines the strengths of advanced hybrid machine learning algorithms, convLSTM and DNN, to improve upon the limitations of the traditional CMAQ model. Data used in the system include forecasted information from CMAQ and WRF models, along with actual PM2.5 concentration and weather variable data from monitoring stations in China and South Korea. The system was implemented specifically for Seoul's PM2.5 forecasting.

Keywords: PM2.5 forecast, machine learning, convLSTM, DNN

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130 Performance Comparison of Resource Allocation without Feedback in Wireless Body Area Networks by Various Pseudo Orthogonal Sequences

Authors: Ojin Kwon, Yong-Jin Yoon, Liu Xin, Zhang Hongbao

Abstract:

Wireless Body Area Network (WBAN) is a short-range wireless communication around human body for various applications such as wearable devices, entertainment, military, and especially medical devices. WBAN attracts the attention of continuous health monitoring system including diagnostic procedure, early detection of abnormal conditions, and prevention of emergency situations. Compared to cellular network, WBAN system is more difficult to control inter- and inner-cell interference due to the limited power, limited calculation capability, mobility of patient, and non-cooperation among WBANs. In this paper, we compare the performance of resource allocation scheme based on several Pseudo Orthogonal Codewords (POCs) to mitigate inter-WBAN interference. Previously, the POCs are widely exploited for a protocol sequence and optical orthogonal code. Each POCs have different properties of auto- and cross-correlation and spectral efficiency according to its construction of POCs. To identify different WBANs, several different pseudo orthogonal patterns based on POCs exploits for resource allocation of WBANs. By simulating these pseudo orthogonal resource allocations of WBANs on MATLAB, we obtain the performance of WBANs according to different POCs and can analyze and evaluate the suitability of POCs for the resource allocation in the WBANs system.

Keywords: wireless body area network, body sensor network, resource allocation without feedback, interference mitigation, pseudo orthogonal pattern

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129 Performance Analysis of Geophysical Database Referenced Navigation: The Combination of Gravity Gradient and Terrain Using Extended Kalman Filter

Authors: Jisun Lee, Jay Hyoun Kwon

Abstract:

As an alternative way to compensate the INS (inertial navigation system) error in non-GNSS (Global Navigation Satellite System) environment, geophysical database referenced navigation is being studied. In this study, both gravity gradient and terrain data were combined to complement the weakness of sole geophysical data as well as to improve the stability of the positioning. The main process to compensate the INS error using geophysical database was constructed on the basis of the EKF (Extended Kalman Filter). In detail, two type of combination method, centralized and decentralized filter, were applied to check the pros and cons of its algorithm and to find more robust results. The performance of each navigation algorithm was evaluated based on the simulation by supposing that the aircraft flies with precise geophysical DB and sensors above nine different trajectories. Especially, the results were compared to the ones from sole geophysical database referenced navigation to check the improvement due to a combination of the heterogeneous geophysical database. It was found that the overall navigation performance was improved, but not all trajectories generated better navigation result by the combination of gravity gradient with terrain data. Also, it was found that the centralized filter generally showed more stable results. It is because that the way to allocate the weight for the decentralized filter could not be optimized due to the local inconsistency of geophysical data. In the future, switching of geophysical data or combining different navigation algorithm are necessary to obtain more robust navigation results.

Keywords: Extended Kalman Filter, geophysical database referenced navigation, gravity gradient, terrain

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128 Periodic Change in the Earth’s Rotation Velocity

Authors: Sung Duk Kim, Kwan U. Kim, Jin Sim, Ryong Jin Jang

Abstract:

The phenomenon of seasonal variations in the Earth’s rotation velocity was discovered in the 1930s when a crystal clock was developed and analyzed in a quantitative way for the first time between 1955 and 1968 when observation data of the seasonal variations was analyzed by an atomic clock. According to the previous investigation, atmospheric circulation is supposed to be a factor affecting the seasonal variations in the Earth’s rotation velocity in many cases, but the problem has not been solved yet. In order to solve the problem, it is necessary to apply dynamics to consider the Earth’s spatial motion, rotation and change of shape of the Earth (movement of materials in and out of the Earth and change of the Earth’s figure) at the same time and in interrelation to the accuracy of post-Newtonian approximation regarding the Earth body as a system of mass points because the stability of the Earth’s rotation angular velocity is in the range of 10⁻⁸~10⁻⁹. For the purpose, the equation was derived, which can consider the 3 kinds of motion above mentioned at the same time by taking the effect of the resultant of external force on the Earth’s rotation into account in a relativistic way to the accuracy of post-Newtonian approximation. Therefore, the equation has been solved to obtain the theoretical values of periodic change in the Earth’s rotation velocity and they have been compared with the astronomical observation data, so to reveal the cause for the periodic change in the Earth’s rotation velocity.

Keywords: Earth rotation, moment function, periodic change, seasonal variation, relativistic change

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127 An Approach for Pattern Recognition and Prediction of Information Diffusion Model on Twitter

Authors: Amartya Hatua, Trung Nguyen, Andrew Sung

Abstract:

In this paper, we study the information diffusion process on Twitter as a multivariate time series problem. Our model concerns three measures (volume, network influence, and sentiment of tweets) based on 10 features, and we collected 27 million tweets to build our information diffusion time series dataset for analysis. Then, different time series clustering techniques with Dynamic Time Warping (DTW) distance were used to identify different patterns of information diffusion. Finally, we built the information diffusion prediction models for new hashtags which comprise two phrases: The first phrase is recognizing the pattern using k-NN with DTW distance; the second phrase is building the forecasting model using the traditional Autoregressive Integrated Moving Average (ARIMA) model and the non-linear recurrent neural network of Long Short-Term Memory (LSTM). Preliminary results of performance evaluation between different forecasting models show that LSTM with clustering information notably outperforms other models. Therefore, our approach can be applied in real-world applications to analyze and predict the information diffusion characteristics of selected topics or memes (hashtags) in Twitter.

Keywords: ARIMA, DTW, information diffusion, LSTM, RNN, time series clustering, time series forecasting, Twitter

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126 Active Islanding Detection Method Using Intelligent Controller

Authors: Kuang-Hsiung Tan, Chih-Chan Hu, Chien-Wu Lan, Shih-Sung Lin, Te-Jen Chang

Abstract:

An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results.

Keywords: distributed generators, probabilistic fuzzy neural network, islanding detection, non-detection zone

Procedia PDF Downloads 360
125 Prognostic and Predictive Value of Tumor: Infiltrating Lymphocytes in Triple Negative Breast Cancer

Authors: Wooseok Byon, Eunyoung Kim, Junseong Kwon, Byung Joo Song, Chan Heun Park

Abstract:

Background/Purpose: Previous preclinical and clinical data suggest that increased lymphocytic infiltration would be associated with good prognosis and benefit from immunogenic chemotherapy especially in triple-negative breast cancer (TNBC). We investigated a single-center experience of TNBC and relationship with lymphocytic infiltration. Methods: From January 2004 to December 2012, at the Department of Surgery, Kangbuk Samsung Hospital, Sungkyunkwan University, School of Medicine, we retrospectively reviewed 897 breast cancer patients-clinical outcomes, clinicopathological characteristics, breast cancer subtypes. And we reviewed lymphocytic infiltration of TNBC specimens by two pathologists. Statistical analysis of risk factors associated with recurrence was performed. Results: A total of 897 patients, 76 were TNBC (8.47%). Mean age of TNBC patients were 50.95 (SD10.42) years, mean follow-up periods was 40.06 months. We reviewed 49 slides, and there were 8 recurrent breast cancer patients (16.32%), and 4 patients were expired (8.16%). There were 9 lymphocytic predominant breast cancers (LPBC)-carcinomas with either intratumoral lymphocytes in >60% of tumor cell nests. 1 patient of LPBC was recurred and 8 were not. In multivariate logistic regression, the odds ratio of lymphocytic infiltration was 0.59 (p=0.643). Conclusion: In a single-center experience of TNBC, the lymphocytic infiltration in tumor cell nest might be a good trend on the prognosis but there was not statistically significant.

Keywords: tumor-infiltrating lymphocytes, triple negative breast cancer, medical and health sciences

Procedia PDF Downloads 384