• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.314-320
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• 2021

With the increasing age of motherhood in recent years, attributed to late marriages due to social or environmental factors, the Down's syndrome screening test using biochemical markers has become essential for pregnant women. The process of diagnosing Down's syndrome pregnancy in the high-risk group subjects involves chromosomal analysis, which is performed on samples obtained through invasive procedures such as chorionic biopsy or amniotic fluid. Thus, to reduce unnecessary invasive tests and lower the risk to mother and fetus, it is important to identify a screening test with low risk and high Down's syndrome detection rate. Recently, as the average age of mothers has increased, numerous inspection agencies have classified high-risk mothers as women over the age of 35 years. This study evaluated a total of 36,436 pregnant women aged between 17 to 46 years, and who requested prenatal screening at an inspection agency in Yongin in 2018. Test (13,690 people) Four tests were conducted by applying the time-resolved fluoroimmunoassay method using the direct sandwich and indirect sandwich technology, and the immunoassay method using the sandwich method. We aimed to confirm the difference in positivity rate with increasing age of the subjects. We believe that in future, data obtained from this study will be very useful for the prevention and treatment of Down's syndrome risk at varied inspection institutions, and for prospective mothers.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.6
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• pp.2465-2472
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• 2015

Background: The Quality Audit (BQA) program of the Breast Surgeons of Australia and New Zealand (NZ) collects data on early female breast cancer and its treatment. BQA data covered approximately half all early breast cancers diagnosed in NZ during roll-out of the BQA program in 1998-2010. Coverage increased progressively to about 80% by 2008. This is the biggest NZ breast cancer database outside the NZ Cancer Registry and it includes cancer and clinical management data not collected by the Registry. We used these BQA data to compare socio-demographic and cancer characteristics and survivals by ethnicity. Materials and Methods: BQA data for 1998-2010 diagnoses were linked to NZ death records using the National Health Index (NHI) for linking. Live cases were followed up to December $31^{st}$ 2010. Socio-demographic and invasive cancer characteristics and disease-specific survivals were compared by ethnicity. Results: Five-year survivals were 87% for Maori, 84% for Pacific, 91% for other NZ cases and 90% overall. This compared with the 86% survival reported for all female breast cases covered by the NZ Cancer Registry which also included more advanced stages. Patterns of survival by clinical risk factors accorded with patterns expected from the scientific literature. Compared with Other cases, Maori and Pacific women were younger, came from more deprived areas, and had larger cancers with more ductal and fewer lobular histology types. Their cancers were also less likely to have a triple negative phenotype. More of the Pacific women had vascular invasion. Maori women were more likely to reside in areas more remote from regional cancer centres, whereas Pacific women generally lived closer to these centres than Other NZ cases. Conclusions: NZ BQA data indicate previously unreported differences in breast cancer biology by ethnicity. Maori and Pacific women had reduced breast cancer survival compared with Other NZ women, after adjusting for socio-demographic and cancer characteristics. The potential contributions to survival differences of variations in service access, timeliness and quality of care, need to be examined, along with effects of comorbidity and biological factors.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.2
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• pp.60-64
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• 2011

Purpose: The brain perfusion SPECT is the examination which is able to know adversity information related brain disorder. But brain perfusion SPECT has also high failure rates by patient's motions. In this case, we have to use two days method and patients put up with many disadvantages. We think that we don't use two days method in brain perfusion SPECT, if we can use registration method. So this study has led to look over registration method applications in brain perfusion SPECT. Materials and Methods: Jaszczak, Hoffman and cylindrical phantoms were used for acquiring SPECT image data on varying degree in x, y, z axes. The phantoms were filled with $^{99m}Tc$ solution that consisted of a radioactive concentration of 111 MBq/mL. Phantom images were acquired through scanning for 5 sec long per frame by using Triad XLT9 triple head gamma camera (TRIONIX, USA). We painted the ROI of registration image in brain data. So we calculated the ROIratio which was different original image counts and registration image counts. Results: When carring out the experiments under the same condition, total counts differential was from 3.5% to 5.7% (mean counts was from 3.4% to 6.8%) in phantom and patients data. In addition, we also run the experiments in the double activity condition. Total counts differential was from 2.6% to 4.9% (mean counts was from 4.1% to 4.9%) in phantom and patients data. Conclusion: We can know that original and registration data are little different in image analysis. If we use the image registration method, we can improve disadvantage of two days method in brain perfusion SPECT. But we must consider image registration about the distance differences in x, y, z axes.

• The KIPS Transactions:PartD
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• v.15D no.6
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• pp.767-776
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• 2008

Microarray technology is extensively being used in experimental molecular biology field. Microarray experiments generate quantitative expression measurements for thousands of genes simultaneously, which is useful for the phenotype classification of many diseases. One of the two major problems in microarray data classification is that the number of genes exceeds the number of tissue samples. The other problem is that current methods generate classifiers that are accurate but difficult to interpret. Our paper addresses these two problems. We performed a direct integration of individual microarrays with same biological objectives by transforming an expression value into a rank value within a sample and generated rank-comparison decision rules with variable number of genes for cancer classification. Our classifier is an ensemble method which has k top scoring decision rules. Each rule contains a number of genes, a relationship among involved genes, and a class label. Current classifiers which are also ensemble methods consist of k top scoring decision rules. However these classifiers fix the number of genes in each rule as a pair or a triple. In this paper we generalized the number of genes involved in each rule. The number of genes in each rule is in the range of 2 to N respectively. Generalizing the number of genes increases the robustness and the reliability of the classifier for the class prediction of an independent sample. Also our classifier is readily interpretable, accurate with small number of genes, and shed a possibility of the use in a clinical setting.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.409-418
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• 2021

The land cover map is a very important data that is used as a basis for decision-making for land policy and environmental policy. The land cover map is mapped using remote sensing data, and the classification results may vary depending on the acquisition time of the data used even for the same area. In this study, to overcome the classification accuracy limit of single-period data, multi-series satellite images were used to learn the difference in the spectral reflectance characteristics of the land surface according to seasons on a U-Net model, one of the deep learning algorithms, to improve classification accuracy. In addition, the degree of improvement in classification accuracy is compared by comparing the accuracy of single-period data. Seoul, which consists of various land covers including 30% of green space and the Han River within the area, was set as the research target and quarterly Sentinel-2 satellite images for 2020 were aquired. The U-Net model was trained using the sub-class land cover map mapped by the Korean Ministry of Environment. As a result of learning and classifying the model into single-period, double-series, triple-series, and quadruple-series through the learned U-Net model, it showed an accuracy of 81%, 82% and 79%, which exceeds the standard for securing land cover classification accuracy of 75%, except for a single-period. Through this, it was confirmed that classification accuracy can be improved through multi-series classification.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.171-193
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• 2018

LOD(Linked Open Data) cloud is a practical implementation of semantic web. We suggested a new method that provides identity links conveniently in LOD cloud. It also allows changes in LOD to be reflected to searching results without any omissions. LOD provides detail descriptions of entities to public in RDF triple form. RDF triple is composed of subject, predicates, and objects and presents detail description for an entity. Links in LOD cloud, named identity links, are realized by asserting entities of different RDF triples to be identical. Currently, the identity link is provided with creating a link triple explicitly in which associates its subject and object with source and target entities. Link triples are appended to LOD. With identity links, a knowledge achieves from an LOD can be expanded with different knowledge from different LODs. The goal of LOD cloud is providing opportunity of knowledge expansion to users. Appending link triples to LOD, however, has serious difficulties in discovering identity links between entities one by one notwithstanding the enormous scale of LOD. Newly added entities cannot be reflected to searching results until identity links heading for them are serialized and published to LOD cloud. Instead of creating enormous identity links, we propose LOD to prepare its own link policy. The link policy specifies a set of target LODs to link and constraints necessary to discover identity links to entities on target LODs. On searching, it becomes possible to access newly added entities and reflect them to searching results without any omissions by referencing the link policies. Link policy specifies a set of predicate pairs for discovering identity between associated entities in source and target LODs. For the link policy specification, we have suggested a set of vocabularies that conform to RDFS and OWL. Identity between entities is evaluated in accordance with a similarity of the source and the target entities' objects which have been associated with the predicates' pair in the link policy. We implemented a system "Change Acceptable In-Depth Searching System(CAIDS)". With CAIDS, user's searching request starts from depth_0 LOD, i.e. surface searching. Referencing the link policies of LODs, CAIDS proceeds in-depth searching, next LODs of next depths. To supplement identity links derived from the link policies, CAIDS uses explicit link triples as well. Following the identity links, CAIDS's in-depth searching progresses. Content of an entity obtained from depth_0 LOD expands with the contents of entities of other LODs which have been discovered to be identical to depth_0 LOD entity. Expanding content of depth_0 LOD entity without user's cognition of such other LODs is the implementation of knowledge expansion. It is the goal of LOD cloud. The more identity links in LOD cloud, the wider content expansions in LOD cloud. We have suggested a new way to create identity links abundantly and supply them to LOD cloud. Experiments on CAIDS performed against DBpedia LODs of Korea, France, Italy, Spain, and Portugal. They present that CAIDS provides appropriate expansion ratio and inclusion ratio as long as degree of similarity between source and target objects is 0.8 ~ 0.9. Expansion ratio, for each depth, depicts the ratio of the entities discovered at the depth to the entities of depth_0 LOD. For each depth, inclusion ratio illustrates the ratio of the entities discovered only with explicit links to the entities discovered only with link policies. In cases of similarity degrees with under 0.8, expansion becomes excessive and thus contents become distorted. Similarity degree of 0.8 ~ 0.9 provides appropriate amount of RDF triples searched as well. Experiments have evaluated confidence degree of contents which have been expanded in accordance with in-depth searching. Confidence degree of content is directly coupled with identity ratio of an entity, which means the degree of identity to the entity of depth_0 LOD. Identity ratio of an entity is obtained by multiplying source LOD's confidence and source entity's identity ratio. By tracing the identity links in advance, LOD's confidence is evaluated in accordance with the amount of identity links incoming to the entities in the LOD. While evaluating the identity ratio, concept of identity agreement, which means that multiple identity links head to a common entity, has been considered. With the identity agreement concept, experimental results present that identity ratio decreases as depth deepens, but rebounds as the depth deepens more. For each entity, as the number of identity links increases, identity ratio rebounds early and reaches at 1 finally. We found out that more than 8 identity links for each entity would lead users to give their confidence to the contents expanded. Link policy based in-depth searching method, we proposed, is expected to contribute to abundant identity links provisions to LOD cloud.

• Journal of Korea Water Resources Association
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• v.48 no.4
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• pp.291-298
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• 2015

The aim of this study is that a theoretical formula for estimating the one-dimensional longitudinal dispersion coefficient is derived based on a transverse distribution equation for the depth averaged stream-wise velocity in open channel. In "Part I. Theoretical equation for stream-wise velocity" which is the former volume of this article, the velocity distribution equation is derived analytically based on the Shiono-Knight Model (SKM). And then incorporating the velocity distribution equation into a triple integral formula which was proposed by Fischer (1968), the one-dimensional longitudinal dispersion coefficient can be derived theoretically in "Part II. Longitudinal dispersion coefficient" which is the latter volume of this article. SKM has presented an analytical solution to the Navier-Stokes equation to describe the transverse variations, and originally been applied to straight and nearly straight compound channel. In order to use SKM in modeling non-prismatic and meandering channels, the shape of cross-section is regarded as a triangle in this study. The analytical solution for the velocity distribution is verified using Manning's equation and applied to velocity data measured at natural streams. Although the velocity equation developed in this study do not agree well with measured data case by case, the equation has a merit that the velocity distribution can be calculated only using geometric data including Manning's roughness coefficient without any measured velocity data.

• Journal of KIISE
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• v.42 no.8
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• pp.998-1009
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• 2015

In recent years, there has been a growing interest in RDFS Inference to build a rich knowledge base. However, it is difficult to improve the inference performance with large data by using a single machine. Therefore, researchers are investigating the development of a RDFS inference engine for a distributed computing environment. However, the existing inference engines cannot process data in real-time, are difficult to implement, and are vulnerable to repetitive tasks. In order to overcome these problems, we propose a method to construct an in-memory distributed inference engine that uses a parallel graph structure. In general, the ontology based on a triple structure possesses a graph structure. Thus, it is intuitive to design a graph structure-based inference engine. Moreover, the RDFS inference rule can be implemented by utilizing the operator of the graph structure, and we can thus design the inference engine according to the graph structure, and not the structure of the data table. In this study, we evaluate the proposed inference engine by using the LUBM1000 and LUBM3000 data to test the speed of the inference. The results of our experiment indicate that the proposed in-memory distributed inference engine achieved a performance of about 10 times faster than an in-storage inference engine.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.11
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• pp.4623-4627
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• 2014

Background: The epidermal growth factor receptor (EGFR) plays a vital role in the activation and inactivation of receptor tyrosine kinases. Mutations in exons 19 and 21 of EGFR are commonly found to be associated with non small cell lung carcinoma and triple negative breast cancer, enhancing sensitivity to EGFR targeting chemotherapeutic agents. Since amplification and prolonged activation of EGFR molecules have been identified in oral squamous cell carcinomas (OSCC), we investigated whether OSCCs carried mutations in exons 19 and 21 of EGFR to their incidence. Materials and Methods: Tumor chromosomal DNA isolated from forty surgically excised oral squamous cell carcinoma tissues was subjected to PCR amplification with intronic primers flanking exons 19 and 21 of the EGFR gene. The PCR amplicons were subsequently subjected to direct sequencing to elucidate the mutation status. Results: Data analysis of the EGFR exon 19 and 21 coding sequences did not show any mutations in the forty OSCC samples that were analyzed. Conclusions: To the best of our knowledge, this is the first study to have investigated the genetic status of exons 19 and 21 of EGFR in Indian OSCCs and identified that mutation in EGFR exon 19 and 21 may not contribute towards their genesis. The absence of mutations also indicates that oral cancerous lesions may not be as sensitive as other cancers to chemotherapeutic agents targeting EGFR.

• The Research Journal of the Costume Culture
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• v.19 no.2
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• pp.334-345
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• 2011

A study on compressive garments guarantee the required pressure and form depending on the type of disease and the state of injury can be used in the preventive treatment of cardiovascular disease. This research is to provide a preliminary data to develop medical clothing products, especially knitted compression garments. Starting from analyzing knitted structure of imported pressure goods to apply to test samples, 11 kinds of knitted stretchy fabrics were manufactured under the various knitting conditions, then their tensile, mechanical and hand properties were measured. In comparison size changes by knitting structure, tuck stitch applied structure showed an increase in course direction and decrease in wale direction. Float stitch applied structure indicated the contraction of size in width because of unformed loops and floated yarn on the technical back of fabric. As a result of tensile properties in tuck and float applied structure, tensile strength was increased in the course direction. On the other hand, the more loops overlapped due to the tuck and float stitch, the more decreased their elongation and elastic recovery were. In case of mechanical properties, as the tuck and float stitch were overlapped double or triple the bending and shearing properties were risen. Accordingly, the drape of fabric becomes stiff, and its surface becomes rough and uneven. The measurements of hand properties showed that the value of KOSHI, FUKURAMI NUMERI in tuck and float applied structure are higher than the plain structure. This results from the relationship between the mechanical and hand properties.