• 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 Korea Robotics Society
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• v.19 no.2
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• pp.221-228
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• 2024

As the importance of cardiovascular health is highlighted, research on its correlation with blood pressure, the most important indicator, is being actively conducted. Therefore, extensive clinical data is essential, but the measurement of the central arterial blood pressure waveform must be performed invasively within the artery, so the quantity and quality are limited. This study suggested a mock circulatory robot and artificial aorta to reproduce the blood pressure waveform generated by the overlap of forward and reflected waves. The artificial aorta was fabricated with biomimetic silicone to mimic the physiological structure and vascular stiffness of the human. A pressurizing chamber was implemented to prevent distortion of the blood pressure waveform due to the strain-softening of biomimetic silicone. The reproduced central arterial blood pressure waveforms have similar magnitude, shape, and propagation characteristics to humans. In addition, changes in blood pressure waveform due to aging were also reproduced by replacing an artificial aorta with various stiffness. It can be expanded to construct a biosignal database and health sensor testing platform, a core technology for cardiovascular health-related research.

• Journal of the Korean Society of Radiology
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• v.16 no.2
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• pp.157-162
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• 2022

Since preclinical positron emission tomography imaging is performed on small animals that are very small compared to the human body, a detector with excellent spatial resolution is required. For this purpose, a system was constructed using a detector using small scintillation pixels. Since the size of the currently developed and used photosensors is limited, excellent spatial resolution can be obtained when the minimum scintillation pixel and maximum array are used. In this study, the size of the photosensor is fixed and various scintillation pixel arrays are configured to match the size of the scintillation pixels, so that no overlap occurs in the flood image and the maximum scintillation pixel array in which all scintillation pixels are distinguished. For this purpose, DETECT2000, which can simulate a detector module composed of a scintillator and an photosensor, was used. A photosensor consisting of a 4 × 4 array of 3 mm × 3 mm pixels was used, and the scintillation pixel array was configured from 8 × 8 to 13 × 13, and simulations were performed. A flood image was constructed using the data obtained from the photosensor pixel, and the maximum scintillation pixel array that does not overlap the image was found through the flood image and the profile. As a result, the size of the scintillation pixel array in which all scintillation pixels are imaged without overlapping each other in the flood image was 11 × 11.

• The Korean Journal of Nuclear Medicine Technology
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• v.28 no.1
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• pp.57-69
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• 2024

Purpose: Quantitative analysis through count measurement in nuclear medicine planar images is limited by analysis techniques that are useful for obtaining various clinical information or by organ overlap or artifacts in actual clinical practice. On the other hand, the use of SPECT tomography images is quantitative analysis using volume rather than planar, which is not only free from problems such as projection overlap, but also has excellent quantitative accuracy. In the use of developing SPECT quantitative analysis technology, this study aims to compare the accuracy of quantitative analysis between ROI of the conventional planar images and VOI of the SPECT tomographic images in evaluating the count change happened by the volume change of the source. Materials and Methods: A ^99mTcO₄^- source(200.17 MBq) was filled with sterilized water in the syringe to create a phantom with an inner diameter volume of 60 cc, and a planar image and a SPECT image were obtained by reducing the volume by 15 cc (25%) respectively. ROI and VOI(threshold: 1~45%, 5% interval) were set for each image obtained to estimate true count and measure the total count, and compared with the preseted volumetric change rate(%). Results: When volume changes of 25%, 50%, and 75% occurred in the initial volume of 60 cc(100%) of the phantom, the average count changes of the measured planar image were 26.8%, 53.2%, 77.5%, and the average count changes of the SPECT image were 24.4%, 50.9%, and 76.8%. In this case, the VOI size(cm³) set showed an average change rate of 25.4%, 51.1%, and 76.6%. The highest threshold value for the accuracy of radioactive concentration by VOI size (average error -1.03%) was 35%, and the VOI size of the same threshold had an error of -17.1% on average compared to the actual volume. Conclusion: On average, the count-based volumetric change rate in nuclear medicine images was able to track changes more accurately using VOI than ROI, but there was no significant difference with relatively similar value. However, the accuracy of radioactive concentration according to individual VOI sizes did not match, but it is considered that a relatively accurate quantitative analysis can be expected when the size of VOI is set smaller than the actual volume.

• Imaging Science in Dentistry
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• v.50 no.2
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• pp.169-174
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• 2020

Purpose: Periodontal disease causes tooth loss and is associated with cardiovascular diseases, diabetes, and rheumatoid arthritis. The present study proposes using a deep learning-based object detection method to identify periodontally compromised teeth on digital panoramic radiographs. A faster regional convolutional neural network (faster R-CNN) which is a state-of-the-art deep detection network, was adapted from the natural image domain using a small annotated clinical data- set. Materials and Methods: In total, 100 digital panoramic radiographs of periodontally compromised patients were retrospectively collected from our hospital's information system and augmented. The periodontally compromised teeth found in each image were annotated by experts in periodontology to obtain the ground truth. The Keras library, which is written in Python, was used to train and test the model on a single NVidia 1080Ti GPU. The faster R-CNN model used a pretrained ResNet architecture. Results: The average precision rate of 0.81 demonstrated that there was a significant region of overlap between the predicted regions and the ground truth. The average recall rate of 0.80 showed that the periodontally compromised teeth regions generated by the detection method excluded healthiest teeth areas. In addition, the model achieved a sensitivity of 0.84, a specificity of 0.88 and an F-measure of 0.81. Conclusion: The faster R-CNN trained on a limited amount of labeled imaging data performed satisfactorily in detecting periodontally compromised teeth. The application of a faster R-CNN to assist in the detection of periodontally compromised teeth may reduce diagnostic effort by saving assessment time and allowing automated screening documentation.

• Asian review of World Histories
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• v.4 no.1
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• pp.3-34
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• 2016

This introduction is both a statement of a research problem and an account of the first research results for its solution. As more historical databases come online and overlap in coverage, we need to discuss the two main issues that prevent 'big' results from emerging so far. Firstly, historical data are seen by computer science people as unstructured, that is, historical records cannot be easily decomposed into unambiguous fields, like in population (birth and death records) and taxation data. Secondly, machine-learning tools developed for structured data cannot be applied as they are for historical research. We propose a complex network, narrative-driven approach to mining historical databases. In such a time-integrated network obtained by overlaying records from historical databases, the nodes are actors, while thelinks are actions. In the case study that we present (the world as seen from Venice, 1205-1533), the actors are governments, while the actions are limited to war, trade, and treaty to keep the case study tractable. We then identify key periods, key events, and hence key actors, key locations through a time-resolved examination of the actions. This tool allows historians to deal with historical data issues (e.g., source provenance identification, event validation, trade-conflict-diplomacy relationships, etc.). On a higher level, this automatic extraction of key narratives from a historical database allows historians to formulate hypotheses on the courses of history, and also allow them to test these hypotheses in other actions or in additional data sets. Our vision is that this narrative-driven analysis of historical data can lead to the development of multiple scale agent-based models, which can be simulated on a computer to generate ensembles of counterfactual histories that would deepen our understanding of how our actual history developed the way it did. The generation of such narratives, automatically and in a scalable way, will revolutionize the practice of history as a discipline, because historical knowledge, that is the treasure of human experiences (i.e. the heritage of the world), will become what might be inherited by machine learning algorithms and used in smart cities to highlight and explain present ties and illustrate potential future scenarios and visionarios.

• Journal of Construction Engineering and Project Management
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• v.9 no.4
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• pp.1-15
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• 2019

Since its adoption by the transportation sector in the early 1990s, partnering has been broadly used with the traditional delivery method by many agencies with significant reported benefits. During the same era, a number of transportation agencies (DOTs) started experimenting with a wide variety of alternative project delivery methods (APDMs) aimed at improving the delivery of highway construction projects. The effect of collaborative working strategies such as partnering, together with the APDMs have become somehow interrelated posing a potential challenge on how to effectively integrate partnering as a concept in the APDMs. The salient question has been if the collaborative nature of these APDMs has affected how partnering is being used by state DOTs. Through an extensive literature review, analysis of 32 CMGC RFPs/RFQs and review of three CMGC case studies, the study found that there is limited information in state DOT documents that show procedures on the usage of partnering with CMGC projects. Majority of DOTs are relying on the inherent nature of the CMGC contract to promote healthy collaborative practices and there is the need to consider partnering during preconstruction and construction separately to cater for any personnel change over. The study also revealed that partnering may become less important at the construction phase due to overlap between partnering and CMGC practices. In support of this finding, a CMGC partnering model was developed that can be adopted by DOTs. This paper contributes to both research and practice by expanding the existing knowledge on partnering on APDMs.

• Korean Journal of Community Nutrition
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• v.22 no.3
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• pp.191-206
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• 2017

Objectives: The present study systematically reviewed previous studies published in Korea regarding obesity status of children and adolescents in order to provide valid directions for future research and to help establish evidence-based prevention strategies. Methods: The articles were selected by searching the primary keyword 'obesity' and the secondary keywords 'children', 'young children', 'adolescents' or 'kids' on the KISS (Korean Studies Information Service System). Out of 503 articles excluding the overlap, 308 articles were selected with inclusion and exclusion criteria. Secular trends of obesity research, distribution of subjects, potential risk factors for obesity, and intervention method for obesity management were documented. The associations between obesity and dietary factors were summarized. Results: The overall number of research studies has increased since 2000 but obesity management studies have decreased in recent years. Most of the studies used a cross-sectional design. Research on preschool children were extremely limited. Intervention studies targeting males were prevalent. The most significant variables relevant to dietary habits were speed of eating, regular breakfast and snacking. The most significant food and nutrient intake factors were thiamin and iron. Intakes of cereals and animal foods were significantly higher in obese children than the counterparts. Conclusions: The present review of locally published articles on the obesity status in children and adolescents suggested the need for well-designed further studies focused on risk factors of obesity and on a range of intervention methods conducive to the development of obesity prevention and management programs.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.182-185
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• 2005

Satellite cameras are calibrated before launch in detail and in general, but it cannot be guaranteed that the geometry is not changing during launch and caused by thermal influence of the sun in the orbit. Modem satellite imaging systems are based on CCD-line sensors. Because of the required high sampling rate the length of used CCD-lines is limited. For reaching a sufficient swath width, some CCD-lines are combined to a longer virtual CCD-line. The images generated by the individual CCD-lines do overlap slightly and so they can be shifted in x- and y-direction in relation to a chosen reference image just based on tie points. For the alignment and difference in scale, control points are required. The resulting virtual image has only negligible errors in areas with very large difference in height caused by the difference in the location of the projection centers. Color images can be related to the joint panchromatic scenes just based on tie points. Pan-sharpened images may show only small color shifts in very mountainous areas and for moving objects. The direct sensor orientation has to be calibrated based on control points. Discrepancies in horizontal shift can only be separated from attitude discrepancies with a good three-dimensional control point distribution. For such a calibration a program based on geometric reconstruction of the sensor orientation is required. The approximations by 3D-affine transformation or direct linear transformation (DL n cannot be used. These methods do have also disadvantages for standard sensor orientation. The image orientation by geometric reconstruction can be improved by self calibration with additional parameters for the analysis and compensation of remaining systematic effects for example caused by a not linear CCD-line. The determined sensor geometry can be used for the generation? of rational polynomial coefficients, describing the sensor geometry by relations of polynomials of the ground coordinates X, Y and Z.

• The KIPS Transactions:PartC
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• v.17C no.5
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• pp.433-440
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• 2010

Energy efficiency, low latency and scalability for wireless sensor networks are important requirements, especially, the wireless sensor network consist of a large number of sensor nodes should be minimized energy consumption of each node to extend network lifetime with limited battery power. An efficient algorithm and energy management technology for minimizing the energy consumption at each sensor node is also required to improve transfer rate. Thus, this paper propose no-overlap multi-pass protocol provides for sensor data transmission in the wireless sensor network environment. The proposed scheme should minimize network overhead through reduced a sensor data translation use to searched multi-path and added the multi-path in routing table. Proposed routing protocol may minimize the energy consumption at each node, thus prolong the lifetime of the sensor network regardless of where the sink node is located outside or inside the received signal strength range. To verify propriety proposed scheme constructs sensor networks adapt to current model using the real data and evaluate consumption of total energy.