• International Journal of Oral Biology
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• v.33 no.4
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• pp.163-177
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• 2008

Periodontal disease, a form of chronic inflammatory bacterial infectious disease, is known to be a risk factor for cardiovascular disease (CVD). Porphyromonas gingivalis has been implicated in periodontal disease and widely studied for its role in the pathogenesis of CVD. A previous study demonstrating that periodontopathic P. gingivalis is involved in CVD showed that invasion of endothelial cells by the bacterium is accompanied by an increase in cytokine production, which may result in vascular atherosclerotic changes. The present study was performed in order to further elucidate the role of P. gingivalis in the process of atherosclerosis and CVD. For this purpose, invasion of human aortic smooth muscle cells (HASMC) by P. gingivalis 381 and its isogenic mutants of KDP150 ($fimA^-$), CW120 ($ppk^-$) and KS7 ($relA^-$) was assessed using a metronidazole protection assay. Wild type P. gingivalis invaded HASMCs with an efficiency of 0.12%. In contrast, KDP150 failed to demonstrate any invasive ability. CW120 and KS7 showed relatively higher invasion efficiencies, but results for these variants were still negligible when compared to the wild type invasiveness. These results suggest that fimbriae are required for invasion and that energy metabolism in association with regulatory genes involved in stress and stringent response may also be important for this process. ELISA assays revealed that the invasive P. gingivalis 381 increased production of the proinflammatory cytokine interleukin (IL)-$1{\beta}$ and the chemotactic cytokines (chemokine) IL (interleukin)-8 and monocyte chemotactic (MCP) protein-1 during the 30-90 min incubation periods (P<0.05). Expression of RANTES (regulation upon activation, normal T cell expressed and secreted) and Toll-like receptor (TLR)-4, a pattern recognition receptor (PRR), was increased in HASMCs infected with P. gingivalis 381 by RT-PCR analysis. P. gingivalis infection did not alter interferon-$\gamma$-inducible protein-10 expression in HASMCs. HASMC nonspecific necrosis and apoptotic cell death were measured by lactate dehydrogenase (LDH) and caspase activity assays, respectively. LDH release from HASMCs and HAMC caspase activity were significantly higher after a 90 min incubation with P. gingivalis 381. Taken together, P. gingivalis invasion of HASMCs induces inflammatory cytokine production, apoptotic cell death, and expression of TLR-4, a PRR which may react with the bacterial molecules and induce the expression of the chemokines IL-8, MCP-1 and RANTES. Overall, these results suggest that invasive P. gingivalis may participate in the pathogenesis of atherosclerosis, leading to CVD.

• Journal of Elementary Mathematics Education in Korea
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• v.14 no.3
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• pp.937-957
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• 2010

The purpose of this study is to discover the features of symbol sense. This study tries to sum up the meaning and elements of symbol sense and the measures to improve them through documents. Also based on this, it analyzes the learning conditions about symbol sense for 6th grade mathematically able students and suggests the method that activates symbol sense in the math of elementary schools. Considering various studies on symbol sense, symbol sense means the exact knowledge and essential understanding in a comprehensive way. Symbol sense is an intuition about symbols that grasps the meaning of symbols, understands the situation of question, and realizes the usefulness of symbols in resolving a process. Considering all other scholars' opinions, this study sums up 5 elements of the symbol sense. (The recognition of needs to introduce symbol, ability to read the meaning of symbols, choice of suitable symbols according to the context, pattern guess through visualization, recognize the role of symbols in other context) This study draws the following conclusions after applying the symbol questionnaires targeting 6th grade mathematically able students : First, although they are math talents, there are some differences in terms of the symbol sense level. Second, 5 elements of the symbol sense are not completely separated. They are rather closely related in terms of mainly the symbol understanding, thereby several elements are combined.

• Journal of Sensor Science and Technology
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• v.6 no.6
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• pp.476-482
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• 1997

A portable electronic nose system has been fabricated and characterized using an oxide semiconductor gas sensor array and pattern recognition techniques such as principal component analysis and back-propagation artificial neural network. The sensor array consists of six thick-film gas sensors whose sensing layers are Pd-doped $WO_{3}$, Pt-doped $SnO_{2}$, $TiO_{2}-Sb_{2}O_{5}-Pd$-doped $SnO_{2}$, $TiO_{2}-Sb_{2}O_{5}-Pd$-doped $SnO_{2}$ + Pd coated layer, $Al_{2}O_{3}$-doped ZnO and $PdCl_{2}$-doped $SnO_{2}$. The portable electronic nose system consists of an 16bit Intel 80c196kc as CPU, an EPROM for storing system main program, an EEPROM for containing optimized connection weights of artificial neural network, an LCD for displaying gas concentrations. As an application the system has been used to identify 26 carbon monoxide/hydrocarbon (CO/HC) car exhausting gases in the concentration range of CO 0%/HC 0 ppm to CO 7.6%/HC 400 ppm and the identification has been successfully demonstrated.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.183-190
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• 2016

This paper proposes algorithm to reduce the computing time in a neural network that reduces transmission of data for tracking mobile objects in surveillance networks in terms of detection and communication load. Object Detection can be defined as follows : Given image sequence, which can forom a digitalized image, the goal of object detection is to determine whether or not there is any object in the image, and if present, returns its location, direction, size, and so on. But object in an given image is considerably difficult because location, size, light conditions, obstacle and so on change the overall appearance of objects, thereby making it difficult to detect them rapidly and exactly. Therefore, this paper proposes fast and exact object detection which overcomes some restrictions by using neural network. Proposed system can be object detection irrelevant to obstacle, background and pose rapidly. And neural network calculation time is decreased by reducing input vector size of neural network. Principle Component Analysis can reduce the dimension of data. In the video input in real time from a CCTV was experimented and in case of color segment, the result shows different success rate depending on camera settings. Experimental results show proposed method attains 30% higher recognition performance than the conventional method.

• Korean Journal of Food Science and Technology
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• v.26 no.2
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• pp.162-166
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• 1994

A rapid gas chromatographic (GC) profiling method for the simultaneous analysis of volatile and nonvolatile organic acids was applied to alcoholic beverages (white wine, red wine, brandy, and beer). It involves the solid-phase extraction of organic acids using Chromosorb P as the sorbent and diethyl ether as the eluent with subsequent triethylamine treatment. The resulting triethylammonium salts of acids were directly converted to volatile tert.-butyldimethylsilyl derivatives, which were analyzed by dual-capillary column GC and GC-mass spectrometry. From the alcoholic beverages studied, more than 29 organic acids were detected. When the simplified retention infer (RI) spectra of organic acids, and the direct comparisor method between alcoholic beverages and a test sample were attempted to identify a test sample, it was quickly recognized to be a red wine with the 998 ppt match quality value.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.6
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• pp.37-48
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• 2005

The efficiency of power supply circuits such as DC-DC converters and batteries varies on the trend of the power consumption because their efficiencies are not fixed. To analyze the efficiency of power supply circuits, we need the temporal behavior of the power consumption of the loads, which is dependent on the activity factors of the devices during the operation. Since it is not easy to model every detail of those factors, one of the most accurate power consumption analyses of power supply circuits is measurement of a real system, which is expensive and time consuming. In this paper, we introduce an active load emulator for embedded systems which is capable of power measurement, logging, replaying and synthesis. We adopt a pattern recognition technique for data compression in that long-term behaviors of power consumption consist of numbers of repetitions of short-term behaviors, and the number of short-term behaviors is generally limited to a small number. We also devise a heterogeneous structure of active load elements so that low-speed, high-current active load elements and high-speed, low-current active load elements may emulate large amount and fast changing power consumption of digital systems. For the performance evaluation of our load emulator, we demonstrate power measurement and emulation of a hard drive. As an application of our load emulator, it is used for the analysis of a DC-DC converter efficiency and for the verification of a low-power frequency scaling policy for a real-time task.

• Women's Health Nursing
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• v.7 no.3
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• pp.271-283
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• 2001

The childbearing process is a sociocultural phenomenon of a woman who gives birth to a child as well as a biological phenomenon. The purpose of this ethnographic research study was to explore the experience of childbearing process of mothers with children from pregnancy to the 3 months postpartum in Korea and to understand deeply the perspectives of childbearing women reflected on Korean sociocultural values. A convenient sample of 10 childbearing women were observed from January to October 2000 through field work in Seoul, Korea. Data analysis was accomplished under ongoing process. The results of this study were as follows : The mothers with children experienced self-reflection, family relation, and physical adaptation during pregnancy. In self-reflection, all mothers experienced universality and diversity in their self-discovering process. The universal experiences were maturation, life with family and priority on maternal value between being a mother and a woman. The diverse experiences were taking a dual role of working mother, emotional drift of a resigned mother, and disheartened life of a mother who has two daughters. In family relation, the foundation of the new marital relationship were attained during childbearing process and sexual life were changed for the benefit of a healthy mother and a healthy baby. All mothers established friendly relations with their mothers, but established friendly or conflicting or constraining relations with their mother-in-laws due to husband based family culture. In physical adaptation, the informants endured well the physical discomfort and recognized general appearance change. Also maternal-fetal interaction occurred and mothers realistically felt motherhood and accepted themselves as mother-to-be. The mothers prepared for the best delivery, look for a safe childbirth center, newborn goods, endorsed family coping during hospitalization and responded labor pain to make it more endurable, less painful, fast passed owing to labor recognition of the natural process to be a mother. After childbirth, they felt emancipation, satisfaction, accomplishment, more easiness, actually feeling as mother-to-be, emptiness, and showed response to the sex of newborn. Their Sanhujori practice was different according to the Sanhujori environment including provider, place, time in postpartum and reflected on Sanhubyung. The mothers felt actually mother-to-be and happiness during lactation regardless of feeding pattern. These mothers had a different maternal image about rearing subjecthood through their child-rearing experience. But all mothers felt need for family support and social support. The universal rearing response were actual feeling of mother-to-be, a strenuous experience, a pride on child-rearing, confusion, reflecting marital relationship, and wondering rivalry among children. In conclusion, mother of all with children went through self-discovery, self-reflection and made connections with the family as a mother and as a woman simultaneously during the childbearing process. Therefore it is suggested when harmony and balance between a mother and a woman is accomplished, the woman will lead a healthy and high quality of life. Also, this study sought to confirm the sociocultural factors affecting the childbearing process from the perspectives of the women with children. Therefore health care providers must understand deeply the childbearing women with children based on this finding of and try a integrative approach with new ideology of maternity with biocultural perspectives in a clinical setting.

• Journal of Navigation and Port Research
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• v.41 no.6
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• pp.445-450
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• 2017

It is necessary to set a route to reflect the traffic flow for the safety of the traffic vessels. This ongoing analysis is needed to ensure that the vessels comply with a route. The purpose of this study is to discover the problems of the recommended route vicinity for Wando Harbor and suggest an improvement plan. We used a support vector machine based on the ship's trajectory to establish an efficient route center line. Since the vessels should navigate to the starboard side, with reference to the center line of the recommended route, the trajectories of the vessels were divided into two clusters. The support vector machine is being used in many fields such as pattern recognition, and it is effective for this binary classification. As a result of this study, about 79.5 % of the merchant eastbound ships in a 2.4 NM distance to Jangjuk Sudo did not observe the recommended route, so the risk of collision always existed. The contraflow traffic rate of the route of the eastbound ships decreased from 79.5 % to 30.9 % when the recommended route was reset about 300 meters to the north, from its present position. The support vector machine applied in this study is expected to be applicable, to effectively set the route center line because the ship trajectories can be classified into two clusters.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.4
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• pp.129-134
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• 2018

Recently, the artificial neural network (ANN) model is a promising technique in the prediction, numerical control, robot control and pattern recognition. We predicted the outside temperature of greenhouse using ANN and utilized the model in greenhouse control. The performance of ANN model was evaluated and compared with multiple regression model(MRM) and support vector machine (SVM) model. The 10-fold cross validation was used as the evaluation method. In order to improve the prediction performance, the data reduction was performed by correlation analysis and new factor were extracted from measured data to improve the reliability of training data. The backpropagation algorithm was used for constructing ANN, multiple regression model was constructed by M5 method. And SVM model was constructed by epsilon-SVM method. As the result showed that the RMSE (Root Mean Squared Error) value of ANN, MRM and SVM were 0.9256, 1.8503 and 7.5521 respectively. In addition, by applying the prediction model to greenhouse heating load calculation, it can increase the income by reducing the energy cost in the greenhouse. The heating load of the experimented greenhouse was 3326.4kcal/h and the fuel consumption was estimated to be 453.8L as the total heating time is $10000^{\circ}C/h$. Therefore, data mining technology of ANN can be applied to various agricultural fields such as precise greenhouse control, cultivation techniques, and harvest prediction, thereby contributing to the development of smart agriculture.

• Korean Journal of Food Science and Technology
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• v.34 no.6
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• pp.947-953
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• 2002

Two types of electronic nose were used for investigating the quality of dried lavers stored at 5, 15, and $30^{\circ}C$ RH of 32, 43, and 75%. The electronic nose is composed of metal oxide sensors, and GC is based on SAW sensor. Quality change in dried lavers was described in terms of the sensitivities $(R_{gas}/R_{air})$ of the sensors. Principal component analysis (PCA) was carried out using data obtained from six metal oxide sensors. The first principal component scores were correlated with quality changes of dried lavers. As storage time increased, the stored laver cluster separated from that of fresh lavers. A chromatogram was obtained from GC based on SAW sensor. Olfactory image, A $VaporPrint^{TM}$ image for pattern recognition, showed a significant difference between the stored and the fresh samples. Dried lavers during storage at $30^{\circ}C$ and 75% had bacterial counts of $5.7{\times}10^6\;CFU/g$ after 8 day. Increase of microbial count correlated with the response of electronic nose $(r^2=0.87)$. Whereas, color values showed no correlation.