• Asian Pacific Journal of Cancer Prevention
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• v.16 no.18
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• pp.8553-8557
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• 2016

Background: Accurate dose assessment and correct identification of irradiated from non-irradiated people are goals of biological dosimetry in radiation accidents. Objectives: Changes in the FDXR and the RAD51 gene expression (GE) levels were here analyzed in response to total body exposure (TBE) to a 6 MV x-ray beam in rats. We determined the accuracy for absolute quantification of GE to predict the dose at 24 hours. Materials and Methods: For this in vivo experimental study, using simple randomized sampling, peripheral blood samples were collected from a total of 20 Wistar rats at 24 hours following exposure of total body to 6 MV X-ray beam energy with doses (0.2, 0.5, 2 and 4 Gy) for TBE in Linac Varian 2100C/D (Varian, USA) in Golestan Hospital, in Ahvaz, Iran. Also, 9 rats was irradiated with a 6MV X-ray beam at doses of 1, 2, 3 Gy in 6MV energy as a validation group. A sham group was also included. After RNA extraction and DNA synthesis, GE changes were measured by the QRT-PCR technique and an absolute quantification strategy by taqman methodology in peripheral blood from rats. ROC analysis was used to distinguish irradiated from non-irradiated samples (qualitative dose assessment) at a dose of 2 Gy. Results: The best fits for mean of responses were polynomial equations with a R2 of 0.98 and 0.90 (for FDXR and RAD51 dose response curves, respectively). Dose response of the FDXR gene produced a better mean dose estimation of irradiated "validation" samples compared to the RAD51 gene at doses of 1, 2 and 3 Gy. FDXR gene expression separated the irradiated rats from controls with a sensitivity, specificity and accuracy of 87.5%, 83.5% and 81.3%, respectively, 24 hours after dose of 2 Gy. These values were significantly (p<0.05) higher than the 75%, 75% and 75%, respectively, obtained using gene expression of RAD51 analysis at a dose of 2 Gy. Conclusions: Collectively, these data suggest that absolute quantification by gel purified quantitative RT-PCR can be used to measure the mRNA copies for GE biodosimetry studies at comparable accuracy to similar methods. In the case of TBE with 6MV energy, FDXR gene expression analysis is more precise than that with RAD51 for quantitative and qualitative dose assessment.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.7
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• pp.2745-2749
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• 2015

Objective: To study the PLCE1 gene rs2274223 polymorphism with regard to esophageal cancer and its interaction with diet, lifestyle, psychological and environmental factors in Southwest Shandong province. Materials and Methods: A case series study (case-case) was conducted. Questionnaire data were collected and 3 ml-5ml venous blood was drawn for DNA extraction among the qualified research subjects. PLCE1 gene polymorphism was detected after PCR amplification of DNA. SPSS 13.0 software was used for statistical analysis of the data. Results: The three genotypes A/A, A/G and G/G PLCE1 gene rs2274223 was 31, 16 and 4 cases, accounting for 60.8%, 31.4%, 0.08% respectively. The difference of three genotypes (AA/GA/GG) proportion between negative and positive family history of patients was statistically significant, ${\chi}^2=6.213$, p=0.045. There was no statistically significant relationship between PLCE1 gene rs2274223 polymorphism and smoking, drinking, ${\chi}^2=0.119$, p=0.998, and ${\chi}^2=1.727$, p=0.786. There was no linkage of the three rs2274223 PLCE1 gene genotypes (AA/GA/GG) proportion with eating fried, pickled, hot, mildew, overnight, smoked, excitant food, eat speed, salt taste or not (p>0.05). or with living environment pollution and nine risk factors of occupational exposure (p>0.05). There was no statistically significant difference in TS scores between different genotype of rs2274223 PLCE1 gene. Conclusions: The PLCE1 rs2274223 polymorphism has a relationship with family history of esophageal cancer, but does not have any significant association with age, gender, smoking, alcohol drinking, food hygiene, eating habits, living around the environment and occupation in cases.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.8
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• pp.4175-4179
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• 2016

Background: Oral cavity cancer (OCC) is one of the most common cancers worldwide. No studies have reported on the prevalence and epidemiologic risk factors of oral premalignant lesions (OPLs) in Thailand. The purpose of this study was to investigate the prevalence of OPLs and associated factors in Roi Et Province, Thailand. Materials and Methods: To investigate the prevalence of OPLs, a cross-sectional descriptive study was conducted in which 2,300 subjects over 40 years of age were recruited and screened for the prevalence of OPLs. To identify factors associated with OPLs, a matched case-control study was used in which the subjects were 102 cases with OPL and 102 matched controls without OPLs. The studies were conducted in Roi Et Province during the period 1 February, 2014, to 30 April, 2014, and the data were collected by the use of a structured interview questionnaire and by extraction of information from medical records. Data analyses involved the use of descriptive statistics, McNemar's test, and conditional logistic regression. Results: The overall prevalence of OPLs was 3.8%, and no-one was diagnosed with more than one type of OPL. The factors found to be associated with a statistically significant higher risk of an OPL were betel nut chewing, smoking, and alcohol consumption. The associations with these factors were strong, especially for betel nut chewing and smoking. Conclusions: The habits of betel nut chewing, smoking, and alcohol use are confirmed as factors associated with OPLs in a population of Roi Et Province, Thailand. Campaigns to reduce such risk healthy behaviour are needed, but whether any actual decrease will prevent the eventual transformation of an OPL into an OCC remains an open question.

• The Journal of Society for e-Business Studies
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• v.22 no.1
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• pp.107-122
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• 2017

Nowadays, digital forensic experts are not only computer experts who restore and find deleted files, but also general experts who posses various capabilities including knowledge about processes/laws, communication skills, and ethics. However, there have been few studies about qualifications or competencies required for digital forensic experts comparing with their importance. Therefore, in this study, AHP questionnaires were distributed to digital forensic experts and analyzed to derive priorities of competencies; the first-tier questions which consisted of knowledge, technology, and attitude, and the second-tier ones which have 20 items. Research findings showed that the most important competency was knowledge, followed by technology and attitude but no significant difference was found. Among 20 items of the second-tier competencies, the most important competency was "digital forensics equipment/tool program utilization skill" and it was followed by "data extraction and imaging skill from storage devices." Attitude such as "judgment," "morality," "communication skill," "concentration" were subsequently followed. The least critical one was "substantial law related to actual cases." Previous studies on training/education for digital forensics experts focused on law, IT knowledge, and usage of analytic tools while attitude-related competencies have not given proper attention. We hope this study can provide helpful implications to design curriculum and qualifying exam to foster digital forensic experts.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.3
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• pp.13-22
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• 2008

The objective of this study is to evaluate the applicability of extracted PRMS input parameters by KGIS-Hydrology over Yongdam-Dam watershed. KGIS-Hydrology is a system for automatic extraction and analysis of watershed characteristic data. Input parameters of PRMS were generated from GIS data (DEM, soil, forest type, etc.) using KGIS-Hydrology. Multi-temporal meteorological data from Jangsu station of KMA (Korea Meteorological Administration) were used for all simulation periods. Input parameters of PRMS were optimized using observed runoff data of Yongdam-Dam station (1966-2001) and validated using observed runoff data of Yongdam-Dam station (2002-2006, Yongdam-Dam watershed). The results showed that the simulated flows were much closed to the observed flows of Yongdam-Dam (2002-2006) and Donghyang (2001-2004) station by 0.49~0.83 and 0.57~0.75 model efficiencies, respectively.

• Journal of the Korea Society of Computer and Information
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• v.25 no.7
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• pp.183-191
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• 2020

The purpose of this study is to objectively analyze the trend of media articles related to the 'high school credit system' (2017~2019: 3 years), which has become the biggest concern among Korean education policies, through BIGKinds, a news data big data analysis service for media companies. The main research methodologies were BIGKinds system's specific search term news search, news trend analysis, keyword extraction and wordcloud implementation, network analysis and network picture presentation. The research results are as follows; First, the number of articles related to the high school credit system that appeared in major media outlets in Korea for 3 years from 2017 to 2019 was 3,649. The number of articles was sharply increased at a certain point about 4 times, based on the government's announcement of related policies. It showed an increasing news trend. Second, the top 20 keywords that emerged from the press articles related to the high school credit system for 3 years of analysis were presented, and it was confirmed that the keyword change by year appeared. Third, the network of media articles related to the high school credit system was visualized and presented in different ways by person, institution, and keyword. The results of this study confirmed that the high school credit system education policy was adopted as the representative education policy of the Moon Jae-in government, and is proceeding in the policy decision stage and policy implementation stage.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.6
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• pp.81-89
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• 2004

In this paper, we compare face recognition rate by PCA algorithm using distance change and embedded data being input left side and right side image in stereo images. The proposed method detects face region from RGB color space to YCbCr color space. Also, The extracted face image's scale up/down according to distance change and extracts more robust face region. The proposed method through an experiment could establish standard distance (100cm) in distance about 30∼200cm, and get 99.05% (100cm) as an average recognition result by scale change. The definition of super state is specification region in normalized size (92${\times}$112), and the embedded data extracts the inner factor of defined super state, achieved face recognition through PCA algorithm. The orignal images can receive specification data in limited image's size (92${\times}$112) because embedded data to do learning not that do all learning, in image of 92${\times}$112 size averagely 99.05%, shows face recognition rate of test 1 99.05%, test 2 98.93%, test 3 98.54%, test 4 97.85%. Therefore, the proposed method through an experiment showed that if apply distance change rate could get high recognition rate, and the processing speed improved as well as reduce face information.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.36D no.10
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• pp.9-16
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• 1999

When the conventional IPD (inter-poly-dielctrics) layer with ONO(oxide-nitride-oxide) structure was used in the Flash EEPROM cell, its data retention characteristics were significanfly degraded because the top oxide of the ONO layer was etched off due to the cleaning process used in the gate oxidation process for the peripheral MOSFETs. When the IPD layer with the ONON(oxide-nitride-oxide-nitride) was used there, however, its data retention characteristics were much improved because the top nitride of the ONON layer protected the top oxide from being etched in the cleaning process. For the modelling of the data retention characteristics of the Flash EEPROM cell with the ONON IPD layer, the decrease of the threshold voltage cue to the charge loss during the bake was here given by the empirical relation ${\Delta}V_t\; = \;{\beta}t^me^{-ea/kT}$ and the values of the ${\beta}$=184.7, m=0.224, Ea=0.31 eV were obtained with the experimental measurements. The activation energy of 0.31eV implies that the decrease of the threshold voltage by the back was dur to the movement of the trapped electrons inside the inter-oxide nitride layer. On the other hand, the results of the computer simulation using the model were found to be well consistent with the results of the electrical measurements when the thermal budget of the bake was not high. However, the latter was larger then the former in the case of the high thermal budger, This seems to be due to the leakage current generated by the extraction of the electrons with the bake which were injected into the inter-oxide niride later and were trapped there during the programming, and played the role to prevent the leakage current. To prevent the generation of the leakage current, it is required that the inter-oxide nitride layer and the top oxide layer be made as thin and as thick as possible, respectively.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.3
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• pp.19-29
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• 2011

Until now, many face recognition methods have been proposed, most of them use a 1-dimensional feature vector which is vectorized the input image without feature extraction process or input image itself is used as a feature matrix. It is known that the face recognition methods using raw image yield deteriorated performance in databases whose have severe illumination changes. In this paper, we propose a face recognition method using local statistics of gradients and correlations which are good for illumination changes. BDIP (block difference of inverse probabilities) is chosen as a local statistics of gradients and two types of BVLC (block variation of local correlation coefficients) is chosen as local statistics of correlations. When a input image enters the system, it extracts the BDIP, BVLC1 and BVLC2 feature images, fuses them, obtaining feature matrix by $(2D)^2$ PCA transformation, and classifies it with training feature matrix by nearest classifier. From experiment results of four face databases, FERET, Weizmann, Yale B, Yale, we can see that the proposed method is more reliable than other six methods in lighting and facial expression.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.55-68
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• 2014

Some infrastructure these days is usually constructed under the ground for it to not interfere the foot-traffic of pedestrians, and thus, it is difficult to visually confirm the accurate location of the site where the establishments must be buried. These technical difficulties increase the magnitude of the problems that could arise from over-reliance on the experience of the worker or a mere blueprint. Such problems include exposure to flood and collapse. This paper proposes a constructor-oriented visualization system via mobile gadgets in general construction sites with occluded structures. This proposal is consisted with three stages. First, "Stage of detecting manhole and extracting features" detects and extracts the basis point of occluded structures which is unoccluded manhole. Next, "Stage of tracking features" tracks down the extracted features in the previous stage. Lastly, "Stage of visualizing occluded constructions" analyzes and synthesizes the GPS data and 3D objects obtained from mobile gadgets in the previous stages. This proposal implemented ideal method through parallel analysis of manhole detection, feature extraction, and tracking techniques in indoor environment, and confirmed the possibility through occluded water-pipe augmentation in real environment. Also, it offers a practical constructor-oriented environment derived from the augmented 3D results of occluded water-pipings.