• Progress in Medical Physics
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• v.17 no.1
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• pp.24-31
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• 2006

Automated analysis software was developed to measure the magnitude of the intrafractional and interfractional errors during breast radiation treatments. Error analysis results are important for determining suitable planning target volumes (PTV) prior to Implementing breast-conserving 3-D conformal radiation treatment (CRT). The electrical portal imaging device (EPID) used for this study was a Portal Vision LC250 liquid-filled ionization detector (fast frame-averaging mode, 1.4 frames per second, 256X256 pixels). Twelve patients were imaged for a minimum of 7 treatment days. During each treatment day, an average of 8 to 9 images per field were acquired (dose rate of 400 MU/minute). We developed automated image analysis software to quantitatively analyze 2,931 images (encompassing 720 measurements). Standard deviations ($\sigma$) of intrafractional (breathing motion) and intefractional (setup uncertainty) errors were calculated. The PTV margin to include the clinical target volume (CTV) with 95% confidence level was calculated as $2\;(1.96\;{\sigma})$. To compensate for intra-fractional error (mainly due to breathing motion) the required PTV margin ranged from 2 mm to 4 mm. However, PTV margins compensating for intefractional error ranged from 7 mm to 31 mm. The total average error observed for 12 patients was 17 mm. The intefractional setup error ranged from 2 to 15 times larger than intrafractional errors associated with breathing motion. Prior to 3-D conformal radiation treatment or IMRT breast treatment, the magnitude of setup errors must be measured and properly incorporated into the PTV. To reduce large PTVs for breast IMRT or 3-D CRT, an image-guided system would be extremely valuable, if not required. EPID systems should incorporate automated analysis software as described in this report to process and take advantage of the large numbers of EPID images available for error analysis which will help Individual clinics arrive at an appropriate PTV for their practice. Such systems can also provide valuable patient monitoring information with minimal effort.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.

• Journal of Food Hygiene and Safety
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• v.34 no.4
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• pp.361-366
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• 2019

In this study, microbial contamivation semisulcospira libertine and effect of sedimentation treatment of major bacterial and fungal pathogens were investigated. The total aerobic bacteria, coliforms, Escherichia coli, Staphylococcus aureus, and yeast and mold present in raw and water-dipped Semisulcospira libertine were enumerated using the standard plate count methods on using the standard plate method on potato dextrose agar (PDA), 3M Petrifilm for coliforms / E. coli, 3M Petrifilm for S. aureus, and plate count agar (PCA), respectively. In analysis of microbial contamination of raw Semisulcospira libertine, the total aerobic bacteria, coliforms, and yeast and mold were monitored as 6.40, 2.70, and $6.79{\log}_{10}CFU/g$, respectively. Both E. coli and S. aureus were not detected (detection limit: 10 CFU/g). However, Semisulcospira libertine dipped in ground water for 3 hours had higher contamination levels of all natural indigenous microorganisms than raw Semisulcospira libertine. Especially, E. coli was detected as $2.46{\log}_{10}CFU/g$ in the ground water-dipped Semisulcospira libertine. The total aerobic bacteria in the ground water-dipped Semisulcospira libertine was not significantly reduced (p>0.05) compared to that in the raw Semisulcospira libertine. Moreover, coliforms were significantly increased (p>0.05) in all water-dipped Semisulcospira libertine. Only fungi were slightly reduced (less than 0.2 log) (p>0.05) in the tap water-dipped Semisulcospira libertine by comparison with the raw Semisulcospira libertine. The results of this study suggest that the use of chemical sterilizing agents and other physical methods in the washing stage will be necessary for the microbial reduction in raw Semisulcospira libertine because the use of sediment removal treatment by ground or tap water did not affect the microbiological safety of the raw Semisulcospira libertine.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.5
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• pp.2597-2603
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• 2016

Ovarian cancer is a highly malignant neoplasm with high mortality rates. Research to identify markers facilitating early detection has been pursued for many years. Currently, diagnosis is based on the CA 125 and HE4 markers, as well as the ROMA algorithm. The search continues for new proteins that meet the criteria of good markers A total of 90 patients were included in the present study, allocated into: group 1, ovarian cancer, with 29 patients; group 2, endometrial cysts, with 30s; and group 3, simple ovarian cysts, with 31. Following histopathological verification, the CA 125, HE4, and metalloproteinase 3 (MMP3) levels were determined and the ROMA algorithm was calculated for all patients. The mean concentrations of all determined proteins, CA 125, HE4, and MMP3, as well as the ROMA values, were significantly higher in group 1 (ovarian cancer) compared to group 3 (simple ovarian cysts). The highest significant differences for the CA 125 levels (p<0.000001) and ROMA (p<0.000001) values were observed in postmenopausal women. For HE4, statistical significance was at the level of p=0.00001 compared to p=0.002 for MMP3. For the differentiation between ovarian cancer and endometrial cysts, the respective AUC ratios were obtained for CA 125, HE4, and MMP3 levels, as well as the ROMA values ( 0,93 / 0,96 / 0,75 / 0,98). After removing the post-menopausal patients, the MMP3 AUC value for ovarian cancer vs. benign ovarian cysts increased to 0.814. For post-menopausal women, the MMP3 AUC value for ovarian cancer vs. endometrial cysts was 0.843. As suggested by the results above, both the CA 125 and HE4 markers, as well as the ROMA algorithm, meet the criteria of a good diagnostic test for ovarian cancer. MMP3 seems to meet the criteria of a good diagnostic test, particularly in postmenopausal women; however, it is not superior to the tests used to date.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1247-1247
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• 2001

Constituents of animal biofluids such as milk, blood and urine contain information specifically related to metabolic and health status of the ruminant animals. Some changes in composition of biofluids can be attributed to disease response of the animals. Mastitis is a major problem for the global dairy industry and causes substantial economic losses from decreasing milk production and reducing milk quality. The purpose of this study was to investigate potential of NIRS combined with multivariate analysis for cow's mastitis diagnosis based on NIR spectra of milk, blood and urine. A total of 112 bulk milk, urine and blood samples from 4 Holstein cows were analyzed. The milk samples were collected from morning milking. The urine samples were collected before morning milking and stored at -35$^{\circ}C$ until spectral analysis. The blood samples were collected before morning milking using a catheter inserted into the carotid vein. Heparin was added to blood samples to prevent coagulation. All milk samples were analyzed for somatic cell count (SCC). The SCC content in milk was used as indicator of mastitis and as quantitative parameter for respective urine and blood samples collected at same time. NIR spectra of blood and milk samples were obtained by InfraAlyzer 500 spectrophotometer, using a transflectance mode. NIR spectra of urine samples were obtained by NIR System 6500 spectrophotometer, using 1 mm sample thickness. All samples were divided into calibration set and test set. Class variable was assigned for each sample as follow: healthy (class 1) and mastitic (class 2), based on milk SCC content. SIMCA was implemented to create models of the respective classes based on NIR spectra of milk, blood or urine. For the calibration set of samples, SIMCA models (model for samples from healthy cows and model for samples from mastitic cows), correctly classified from 97.33 to 98.67% of milk samples, from 97.33 to 98.61% of urine samples and from 96.00 to 94.67% of blood samples. From samples in the test set, the percent of correctly classified samples varied from 70.27 to 89.19, depending mainly on spectral data pretreatment. The best results for all data sets were obtained when first derivative spectral data pretreatment was used. The incorrect classified samples were 5 from milk samples,5 and 4 from urine and blood samples, respectively. The analysis of changes in the loading of first PC factor for group of samples from healthy cows and group of samples from mastitic cows showed, that separation between classes was indirect and based on influence of mastitis on the milk, blood and urine components. Results from the present investigation showed that the changes that occur when a cow gets mastitis influence her milk, urine and blood spectra in a specific way. SIMCA allowed extraction of available spectral information from the milk, urine and blood spectra connected with mastitis. The obtained results could be used for development of a new method for mastitis detection.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.3
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• pp.57-69
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• 2004

This study developed an ecological mapping technique with GIS database using the analyses of existing ecological survey reports and the change detection on the Nakdong river estuary. The data which are used to establish GIS DB include 2 Landsat TM images on Nov. 31, 1984 and May 17, 1997, 1:25,000 topographical maps established by National Geography Institution and various ecological survey reports published by Busan metropolitan city government. The details for producing ecological map are as follows. At first, the current methods of ecomapping efforts and previous ecological surveys of Nakdong river estuary were carefully examined. Secondly, the land cover maps were created from the classified Landsat images of 1984 and 1997 for the spatiotemporal ecosystem analysis. Thirdly, the ecosystem was evaluated by using GIS ecological database based on the criteria of botany, zoology and water quality etc. Each criteria was reclassified into 3 stages which describe the overall quality of ecological condition. At last, the comprehensive ecological map was suggested as a prototype of ecosystem assesment and management tool with the discussion of further study. The findings of this study would be a milestone for preserving and managing the ecosystem.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2001.10a
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• pp.61-86
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• 2001

All cancers are caused by abnormalities in DNA sequence. Throughout life, the DNA in human cells is exposed to mutagens and suffers mistakes in replication, resulting in progressive, subtle changes in the DNA sequence in each cell. Since the development of conventional and molecular cytogenetic methods to the analysis of chromosomal aberrations in cancers, more than 1,800 recurring chromosomal breakpoints have been identified. These breakpoints and regions of nonrandom copy number changes typically point to the location of genes involved in cancer initiation and progression. With the introduction of molecular cytogenetic methodologies based on fluorescence in situ hybridization (FISH), namely, comparative genomic hybridization (CGH) and multicolor FISH (m-FISH) in carcinomas become susceptible to analysis. Conventional CGH has been widely applied for the detection of genomic imbalances in tumor cells, and used normal metaphase chromosomes as targets for the mapping of copy number changes. However, this limits the mapping of such imbalances to the resolution limit of metaphase chromosomes (usually 10 to 20 Mb). Efforts to increase this resolution have led to the "new"concept of genomic DNA chip (1 to 2 Mb), whereby the chromosomal target is replaced with cloned DNA immobilized on such as glass slides. The resulting resolution then depends on the size of the immobilized DNA fragments. We have completed the first draft of its Korean Genome Project. The project proceeded by end sequencing inserts from a library of 96,768 bacterial artificial chromosomes (BACs) containing genomic DNA fragments from Korean ethnicity. The sequenced BAC ends were then compared to the Human Genome Project′s publicly available sequence database and aligned according to known cancer gene sequences. These BAC clones were biotinylated by nick translation, hybridized to cytogenetic preparations of metaphase cells, and detected with fluorescein-conjugated avidin. Only locations of unique or low-copy Portions of the clone are identified, because high-copy interspersed repetitive sequences in the probe were suppressed by the addition of unlabelled Cotl DNA. Banding patterns were produced using DAPI. By this means, every BAC fragment has been matched to its appropriate chromosomal location. We have placed 86 (156 BAC clones) cytogenetically defined landmarks to help with the characterization of known cancer genes. Microarray techniques would be applied in CGH by replacement of metaphase chromosome to arrayed BAC confirming in oncogene and tumor suppressor gene: and an array BAC clones from the collection is used to perform a genome-wide scan for segmental aneuploidy by array-CGH. Therefore, the genomic DNA chip (arrayed BAC) will be undoubtedly provide accurate diagnosis of deletions, duplication, insertions and rearrangements of genomic material related to various human phenotypes, including neoplasias. And our tumor markers based on genetic abnormalities of cancer would be identified and contribute to the screening of the stage of cancers and/or hereditary diseases

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.47-54
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• 2017

Recently, there are many studies related aerial mapping project and 3 dimensional shape and model reconstruction using UAV(unmanned aerial vehicle) system and images. In this study, we create 3D reconstruction point data using image matching technology of the UAV overlap images, detect shape change of structure and perform accuracy assessment of area($m^2$) and volume($m^3$) value. First, we build the test structure model data and capturing its images of shape change Before and After. Second, for post-processing the Before dataset is convert the form of raster format image to ensure the compare with all 3D point clouds of the After dataset. The result shows high accuracy in the shape change of more than 30 centimeters, but less is still it becomes difficult to apply because of image matching technology has its own limits. But proposed methodology seems very useful to detect illegal any structures and the quantitative analysis of the structure's a certain amount of damage and management.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.9
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• pp.3981-3990
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• 2015

Background: Breast cancer is the most common type of cancer in Jordan. Current efforts are focused on annual campaigns aimed at increasing awareness about breast cancer and encouraging women to conduct mammogram screening. In the absence of regular systematic screening for breast cancer in Jordan, there is a need to evaluate current mammography screening uptake and its predictors, assess women's knowledge and attitudes towards breast cancer and screening mammograms and to identify barriers to this preventive service. Materials and Methods: This cross-sectional study was conducted in six governorates in Jordan through face-to-face interviews on a random sample of women aged 40 to 69 years. Results: A total of 507 participants with mean age of $46.8{\pm}7.8$ years were interviewed. There was low participation rate in early detection of breast cancer practices. Breast self-examination, doctor examination and periodic mammography screening were reported by 34.9%, 16.8% and 8.6% of study participants, respectively. Additionally 3.8% underwent breast cancer screening at least once but not periodically, while 87.6% had never undergone mammography screening. Reported reasons for conducting the screening were: perceived benefit (50%); family history of breast cancer (23.1%); perceived severity (21.2%); and advice from friend or family member (5.8%). City residents have shown higher probability of undergoing mammogram than those who live in towns or villages. Results revealed negative perceptions and limited knowledge of study participants on breast cancer and breast cancer screening. The most commonly reported barriers for women who never underwent screening were: fear of results (63.8%); no support from surrounding environment (59.7); cost of the test (53.4%); and religious belief, i.e. Qadaa Wa Qadar (51.1%). Conclusions: In the absence of regular systematic screening for breast cancer in Jordan, the uptake of this preventive service is very low. It is essential for the country of Jordan to work on applying regular systematic mammography screening for breast cancer. Additionally, there is a need for improvement in the current health promotion programmes targeting breast cancer screening. Other areas that could be targeted in future initiatives in this field include access to screening in rural areas and removal of current barriers.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.2
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• pp.15-21
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• 2009

Hearing loss is one of the most common birth defects among infants. Most of hearing-impaired children are not diagnosed until 1 to 3 years of age - which is too late for the critical period (6 month) for normal speech and language development. If a hearing impairment is identified and treated in its early stage, child's speech and language skills could be comparable to his or her normal-hearing peers. For these reasons, hearing screening at birth and throughout childhood is extremely important. ABR (Auditory brain-stem response) is nowadays one of the most reliable diagnostic tools in the early detection of hearing impairment. In this study, we have developed the system that automatically detects if there is hearing impairment or not for infants or children. For future studies, it will be developed as a portable system to be able to take a measurement not only in sound proof room but also in nursery for neonates.