• Korean Journal of Environmental Biology
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• v.23 no.3 s.59
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• pp.215-220
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• 2005

Through multiple stage analysis, the biochores in Korea were classified and organized as a hierarchy system. In the 1st step, the isopleth lines of warmth index $100^{\circ}C,\;85^{\circ}C,\;55^{\circ}C\;\cdot$ month and the coldness index $-8^{\circ}C,\;or-10^{\circ}C\;\cdot$ month, which indicate the boundaries of plant formation zones (Yim and Kira 1975; Yim 1977), were applied in the determination of major biochores. In the 2nd step, these biochores were subdivided into the five classes based on Thornthwaite's moisture index (Im) and Yim and Kira (1976), as follows: $100{\le}Im,100 In the 3 rd step, the analysis of topographic features yielded three categories of flatlands, gentle slope, and steep slope areas. These were obtained by adopting the $100{\times}100-meter$ gridded DEM and by considering the physical features of the Korean Peninsula. The features of relief in mountainous areas, waters, islands, etc. were converted into climatic indices. This grouping of biochores serves as a useful tool for the interpretation of the distributional patterns of vegetation of vascular plants and similar phenomena.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.625-632
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• 2004

This study presents the NDE (non-destructive evaluation) technique for detecting the loosened bolts on joint steel structures on the basis of TOF (time of flight) and amplitudes of Lamb waves. Probabilistic neural network (PNN) technique which is an effective tool for pattern classification problem was applied to the damage estimation using PZT induced Lamb waves. Two kinds of damages were introduced by dominant damages (DD) which mean loosened bolts within the Lamb waves beam width and minor damages (MD) which mean loosened bolts out of the Lamb waves beam width. They were investigated for the establishment of the optimal decision boundaries which divide each damage class's region including the intact class. In this study, the applicability of the probabilistic neural networks was identified through the test results for the damage cases within and out of wave beam path. It has been found that the present methods are very efficient and reasonable in predicting the loosened bolts on the joint steel structures probabilistically.

• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.327-338
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• 2000

The forest conditions of North Korea has been a great concern since it was known to be closely related to many environmental problems of the disastrous flooding, soil erosion, and food shortage. To assess the long-term changes of forest area as well as the canopy conditions, several sources of multitemporal satellite data were applied to the study area near Kaesung. KOMPSAT-1 EOC data were overlaid with 1981 topographic map showing the boundaries of forest to assess the deforestation area. Delineation of the cleared forest was performed by both visual interpretation and unsupervised classification. For analyzing the change of forest canopy condition, multiple scenes of Landsat and SPOT data were selected. After preprocessing of the multitemporal satellite data, such as image registration and normalization, the normalized difference vegetation index (NDVI) was derived as a representation of forest canopy conditions. Although the panchromatic EOC data had radiometric limitation to classify diverse cover types, they can be effectively used t detect and delineate the deforested area. The results showed that a large portion of forest land has been cleared for the urban and agricultural uses during the last twenty years. It was also found that the canopy condition of remaining forests has not been improved for the last twenty years. It was also found that the canopy condition of remaining forests has not been improved for the last twenty years. Possible causes of the deforestation and the temporal pattern of canopy conditions are discussed.

• Korean Journal of Remote Sensing
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• v.5 no.2
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• pp.109-122
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• 1989

The ISODATA method, which is one of the most famous of the square-error clustering methos, has been applied to two Chungju multivariate data sets in order to evaluate the effectiveness of the regional lithological mapping. One is an airborne radiometric data set and the other is a mixed data set of the airborne radiometric and Landsat TM data. In both cases, the classification of the Bulguksa granite and the Kyemyongsan biotite-quartz gneiss are the most successful. Hyangsanni dolomitic limestone and neighboring Daehyangsan quartzite are also classified by their typical lowness of the radioactive intensities, though it is still confused with some others such as water-covered areas and nearby alluvials, and unaltered limestone areas. Topographically rugged valleys are also classified as the same cluster as above. This could be due to unavoidable variations of flight height and the attitude of the airborne system in such rugged terrains. The regional geological mapping of sedimentary rock units of the Ockchun System is in general confused. This might be due to similarities between different sediments. Considarable discrepancies occurred in mapping some lithological boundaries might also be due to secondary effects such as contamination or smoothing in digitizing process. Further study should be continued in the variable selection scheme as no absolutely superior method claims to exist yet since it seems somewhat to be rather data dependent. Study could also be made on the data preprocessing in order to reduce the erratic effects as mentioned above, and thus hoprfully draw much better result in regional geological mapping.

• Journal of Gastric Cancer
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• v.24 no.1
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• pp.69-88
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• 2024

This review comprehensively examines the diverse spectrum of gastric cancers, focusing on unusual or uncommon histology that presents significant diagnostic and therapeutic challenges. While the predominant form, tubular adenocarcinoma, is well-characterized, this review focuses on lesser-known variants, including papillary adenocarcinoma, micropapillary carcinoma, adenosquamous carcinoma, squamous cell carcinoma (SCC), hepatoid adenocarcinoma, gastric choriocarcinoma, gastric carcinoma with lymphoid stroma, carcinosarcoma, gastroblastoma, parietal cell carcinoma, oncocytic adenocarcinoma, Paneth cell carcinoma, gastric adenocarcinoma of the fundic gland type, undifferentiated carcinoma, and extremely well-differentiated adenocarcinoma. Although these diseases have different nomenclatures characterized by distinct histopathological features, these phenotypes often overlap, making it difficult to draw clear boundaries. Furthermore, the number of cases was limited, and the unique histopathological nature and potential pathogenic mechanisms were not well defined. This review highlights the importance of understanding these rare variants for accurate diagnosis, effective treatment planning, and improving patient outcomes. This review emphasizes the need for ongoing research and case studies to enhance our knowledge of these uncommon forms of gastric cancer, which will ultimately contribute to more effective treatments and better prognostic assessments. This review aimed to broaden the pathological narrative by acknowledging and addressing the intricacies of all cancer types, regardless of their rarity, to advance patient care and improve prognosis.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.663-668
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• 2024

This paper applies statistical analysis methods in the time domain to the fault diagnosis of wafer transfer robots, and proposes a methodology to discern the critical characteristics of vibration and torque signals. Subsequently, principal component analysis (PCA) is applied to diminish the data's dimensionality, followed by the development of a fault diagnosis algorithm utilizing Euclidean distance and Hotelling's T-square statistics. The algorithm establishes decision boundaries to categorize failure states based on the observed data. Our findings indicate that data classification incorporating velocity parameters enhances diagnostic accuracy. This approach serves to enhance the precision and efficacy of fault diagnosis.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.1-14
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• 2012

A river is defined as the watercourse flowing through its channel, and the mapping tasks of a river plays an important role for the research on the topographic changes in the riparian zones and the research on the monitoring of flooding in its floodplain. However, the utilization of the ground surveying technologies is not efficient for the mapping tasks of a river due to the irregular surfaces of the riparian zones and the dynamic changes of water level of a river. Recently, the spatial information data sets are widely used for the coastal mapping tasks due to the acquisition of the topographic information without human accessibility. In this research, we tried to extract a river from the RapidEye imagery by using the ISODATA(Iterative Self_Organizing Data Analysis) classification algorithm with the two different parameters(NIR (Near Infra-Red) band and NDVI(Normalized Difference Vegetation Index)). First, the two different images(the NIR band image and the NDVI image) were generated from the RapidEye imagery. Second, the ISODATA algorithm were applied to each image and each river was generated in each image through the post-processing steps. River boundaries were also extracted from each classified image using the Sobel edge detection algorithm. Ground truths determined by the experienced expert are used for the assessment of the accuracy of an each generated river. Statistical results show that the extracted river using the NIR band has higher accuracies than the extracted river using the NDVI.

• Research in Community and Public Health Nursing
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• v.7 no.2
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• pp.384-399
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• 1996

The concept of parish nursing began in the late 1960s in the United States when increasing numbers of churches employed registered nurses (RNs) to provide holistic, preventive health care to the members of their congregations. Parish nursing role was developed in 1983 by Lutheran chaplain Granger Westberg, and provides care to a variety of church congregation of various denominations. The parish nurse functions as health educator, counselor, group facilitator, client advocate, and liaison to community resources. Since these activities are complementary to the population-focused practice of community health' CNSs, parish nurses either have a strong public health background or work directly with both baccalaureate-prepared public health nurses and CNSs. In a Midwest community in U.S.A., the Healthy People 2000(1991) objectives are being addressed in health ministries through a coalition between public health nurses and parish nurses. Parish nursing is in the beginning state in Korea and up untill now, there has been no research was conducted on concrete role of korean parish nurses. The main purpose of this study was to identify, classify and analyze activities of parish nurses. The other important objective of this study was to establish an effective approach and direction for parish nursing and provide a database for korean parish nursing model through analysis and' classification of the content of the nursing record which included nursing activities. This study was a descriptive survey research. The parish nurses were working in churches where the demonstration project developed on parish nursing. The study was done on all nursing records which were working in churches where the demonstration project developed on parish nursing. The study was done on all nursing records which were documented by parish nurses in three churches from March, 1995 to February, 1996. Namsan, Taegu Jeei and Nedang presbyterian churches in Taegu and Keimyung nursing college incooperated together for the parish nursing demonstration project. The data analysis procedure was as follows: First, a record analysis tool was developed and second, the data was collected, coded and analyzed, the classification for nursing activities was developed through a literature review, from which the basic analysis tool was produced and cotent validity review was also done. The classification of the activities of parish nurses showed 7 activitity categories. 7 activity categories consisted of visitation nursing, health check-ups, health education, referring, attending staff meetings, attending inservices and seminar, volunteers coordinating. The percentage of activities were as follows: Visitation nursing(A: 51.6%, B: 55%, C: 42.6%) Health check-ups(A: 13.5%, B: 12.1%, C: 22.3%) Health education(A: 13.5%, B: 13.2%, C: 18.2%) Referring(A: 1.4%, B: 4.2%, C: 2.4%) Attending staff meeting(A: 18.8%, B: 13.0%, C: 12.2%) Attending inservices and seminar(A: 1.5%, B: 2.2%, C: 2.1%) Volunteers coordinating(A: 0.3%, B: 0.4%, C: 0.0%) To establish and develope parish nursing delivery network in Korea, parish nurses role, activities and boundaries of practice should be continuously monitored and refined every 2 years. Also, It is needed to develope effective nursing recording system based on the need assessment research data of various congregation members. role, activities and boundaries of practice and arrangement of the working structure, continuing education, cooperation with community resources and structuring and organizing parish nursing delivery network. Also, It is needed to develope effective nursing recording system based on the need assessment research data of various congregation members.

• Journal of the Korea Computer Graphics Society
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• v.22 no.3
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• pp.21-29
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• 2016

Cell segmentation is an important but time-consuming and laborious task in biological image analysis. An automated, robust, and fast method is required to overcome such burdensome processes. These needs are, however, challenging due to various cell shapes, intensity, and incomplete boundaries. A precise cell segmentation will allow to making a pathological diagnosis of tissue samples. A vast body of literature exists on cell segmentation in microscopy images [1]. The majority of existing work is based on input images and predefined feature models only - for example, using a deformable model to extract edge boundaries in the image. Only a handful of recent methods employ data-driven approaches, such as supervised learning. In this paper, we propose a novel data-driven cell segmentation algorithm for bright-field microscopy images. The proposed method minimizes an energy formula defined by two dictionaries - one is for input images and the other is for their manual segmentation results - and a common sparse code, which aims to find the pixel-level classification by deploying the learned dictionaries on new images. In contrast to deformable models, we do not need to know a prior knowledge of objects. We also employed convolutional sparse coding and Alternating Direction of Multiplier Method (ADMM) for fast dictionary learning and energy minimization. Unlike an existing method [1], our method trains both dictionaries concurrently, and is implemented using the GPU device for faster performance.

• Journal of Biomedical Engineering Research
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• v.41 no.2
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• pp.67-74
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• 2020

Brain tumors or gliomas are fatal cancer species with high recurrence rates due to their strong invasiveness. Therefore, the goal of surgery is complete tumor resection. However, the surgery is difficult to distinguish the border because tumors and blood vessels have the same color tone and shape. The fluorescein sodium is used as a fluorescence contrast agent for boundary separation. When the external light source is irradiated, yellow fluorescence is expressed in the tumor, which helps distinguish between blood vessels and tumor boundaries. But, the fluorescence expression of fluorescence sodium depends on the concentration of fluorescein sodium and such analytical data is insufficient. The unclear fluorescence can obscure the boundaries between blood vessels and tumors. In addition, reduce the efficiency of fluorescence sodium use. This paper proposes a protocol of concentration range for fluorescence expression conditions. Fluorescent expression was observed using a near-infrared (NIR) color camera with corresponding dilution using normal saline in 1 ml microtube. The flunoresence emission density range is 1.00 mM to 0.15 mM. The fluorescence emission begin to 1.00 mM and the 0.15 mM discolor. The discolor is difficult to fluorescence emission condition obserbation. Thus, the maximum density range of the bright fluoresecein is 0.15 mM to 0.30 mM. When the concentration range of fluorescein sodium is analyzed based on the gradient of fluorescence expression and the power measurement, the brightest fluorescence is expected to facilitate the complete resection of the tumor. For the concentration range protocol, setting concentration ranges and analyzing fluorescence expression image according to saturation and brightness to find optimal fluorescence concentration are important. Concentration range protocols for fluorescence expression conditions can be used to find optimal concentrations of substances whose expression pattern varies with concentration ranges. This study is expected to be helpful in the boundary classification and resection of brain tumors and glioma.