• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.28-35
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• 2006

Statistical models of shape variability based on active shape models (ASMs) have been successfully utilized to perform segmentation and recognition tasks in two-dimensional (2D) images. Three-dimensional (3D) model-based approaches are more promising than 2D approaches since they can bring in more realistic shape constraints for recognizing and delineating the object boundary. For 3D model-based approaches, however, building the 3D shape model from a training set of segmented instances of an object is a major challenge and currently it remains an open problem in building the 3D shape model, one essential step is to generate a point distribution model (PDM). Corresponding landmarks must be selected in all1 training shapes for generating PDM, and manual determination of landmark correspondences is very time-consuming, tedious, and error-prone. In this paper, we propose a novel automatic method for generating 3D statistical shape models. Given a set of training 3D shapes, we generate a 3D model by 1) building the mean shape fro]n the distance transform of the training shapes, 2) utilizing a tetrahedron method for automatically selecting landmarks on the mean shape, and 3) subsequently propagating these landmarks to each training shape via a distance labeling method. In this paper, we investigate the accuracy and compactness of the 3D model for the human liver built from 50 segmented individual CT data sets. The proposed method is very general without such assumptions and can be applied to other data sets.

• Journal of Food Hygiene and Safety
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• v.32 no.3
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• pp.179-186
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• 2017

For more efficient and proactive safety control of imported food, new trend in U.S. is emerging, which assesses the food safety control systems of exporting countries using Systems Recognition Assessment Tool and helps ensure safety of imported foods. This study examines trends in development and application of assessmemnt tool and country assessment reports in U.S. where an active discussion on this issue is in progress. The expert interviews were also conducted. U.S. Systems Recognition Assessment Tool was developed by FDA to recognize the potential value in leveraging the expertise of foreign food safety systems and help ensure safety of imported food. The tool is comprised of ten standards and provides an objective framework for determining the robustness of trading partners' overall food safety systems. Using its own tool, the U.S. FDA conducted a preliminary assessment of the food safety control systems of New Zealand and Canada. According to the U.S.-New Zealand and the U.S.-Canada assessment reports, the overall structure of the systems was similar between the countries. In summarizing the opinions of experts, such a trend in National Food Safety Control System Assessment may be utilized in the sanitary assessment and the control of imported food border inspection frequency before importing food. It would contribute to more effective distribution of national budget and increased public trust. Additionally, international collaboration as well as securing of qualified experts and sufficient budget appear to be crucial to further increase the utility of National Food Safety Control Systems Assessment. In conclusion, firstly, it is critically important for the competent authority of South Korea to proactively respond to international trend in National Food Safety Control System Assessment by identifying the details of its background, assessment purpose, core assessment elements, and assessment procedures. Secondly, it is necessary to identify and complement the weaknesses of Korea's food safety control system by reviewing it with U.S. Systems Recognition Assessment Tool. Thirdly, by adapting the assessment results from imported countries' food safety control systems to the imported food inspection intensity, the resources previously used in inspecting the imported food from accredited countries can be redistributed to inspecting the imported food from unaccredited countries, and it would contribute to more efficient imported food safety control. Fourthly, the competent authority of South Korea should also consider developing its own assessment tool designed to reflect the unique characteristics of its food safety control system and international guidelines.

• Journal of Korea Water Resources Association
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• v.53 no.10
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• pp.845-859
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• 2020

Climate change and recent heat waves have drawn public attention toward other environmental issues, such as water pollution in the form of algal blooms, chemical leaks, and oil spills. Water pollution by the leakage of chemicals may severely affect human health as well as contaminate the air, water, and soil and cause discoloration or death of crops that come in contact with these chemicals. Chemicals that may spill into water streams are often colorless and water-soluble, which makes it difficult to determine whether the water is polluted using the naked eye. When a chemical spill occurs, it is usually detected through a simple contact detection device by installing sensors at locations where leakage is likely to occur. The drawback with the approach using contact detection sensors is that it relies heavily on the skill of field workers. Moreover, these sensors are installed at a limited number of locations, so spill detection is not possible in areas where they are not installed. Recently hyperspectral images have been used to identify land cover and vegetation and to determine water quality by analyzing the inherent spectral characteristics of these materials. While hyperspectral sensors can potentially be used to detect chemical substances, there is currently a lack of research on the detection of chemicals in water streams using hyperspectral sensors. Therefore, this study utilized remote sensing techniques and the latest sensor technology to overcome the limitations of contact detection technology in detecting the leakage of hazardous chemical into aquatic systems. In this study, we aimed to determine whether 18 types of hazardous chemicals could be individually classified using hyperspectral image. To this end, we obtained hyperspectral images of each chemical to establish a spectral library. We expect that future studies will expand the spectral library database for hazardous chemicals and that verification of its application in water streams will be conducted so that it can be applied to real-time monitoring to facilitate rapid detection and response when a chemical spill has occurred.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.2
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• pp.23-39
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• 2017

This study began from the question, "is there a way to efficiently apply industrial demand in the university curriculum?" Research focused on how to actively accept and respond to the era of the NCS (National Competency Standards). In order to apply NCS to individual departments of the university, industrial personnel must positively participate to form a practical-level curriculum by the NCS, which can be linked to the work and qualifications. A valid procedure for developing a curriculum based on the NCS of this study is as follows: First, the university must select a specific classification of NCS considering the relevant industry outlook, the speciality of professors in the university, the relationship with regional industries and the prospects for future employment, and the need for industrial manpower. Second, departments must establish a type of human resource that compromises goals for the university education and the missions of the chosen NCS. In this process, a unique competency unit of the university that can support the basic or applied subjects should be added to the task model. Third, the task model based on the NCS should be completed through the verification of each competency unit considering the acceptance or rejection in the curriculum. Fourth, subjects in response to each competency units within the task model should be developed while considering time and credits according to university regulations. After this, a clear subject description of how to operate and evaluate the contents of the curriculum should be created. Fifth, a roadmap for determining the period of operating subjects for each semester or year should be built. This roadmap will become a basis for the competency achievement frame to decide upon the adoption of a Process Evaluation Qualification System. In order for the NCS to be successfully established within the university, a consensus on the necessity of the NCS should be preceded by professors, students and staff members. Unlike a traditional curriculum by professors, the student-oriented NCS curriculum is needed sufficient understanding and empathy for the many sacrifices and commitment of the members of the university.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.137-144
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• 2023

Cyberattack technology is evolving to an unpredictable degree, and it is a situation that can happen 'at any time' rather than 'someday'. Infrastructure that is becoming hyper-connected and global due to cloud computing and the Internet of Things is an environment where cyberattacks can be more damaging than ever, and cyberattacks are still ongoing. Even if damage occurs due to external influences such as cyberattacks or natural disasters, intelligent self-recovery must evolve from a cyber resilience perspective to minimize downtime of cyber assets (OS, WEB, WAS, DB). In this paper, we propose an intelligent self-recovery technology to ensure sustainable cyber resilience when cyber assets fail to function properly due to a cyberattack. The original and updated history of cyber assets is managed in real-time using timeslot design and snapshot backup technology. It is necessary to secure technology that can automatically detect damage situations in conjunction with a commercialized file integrity monitoring program and minimize downtime of cyber assets by analyzing the correlation of backup data to damaged files on an intelligent basis to self-recover to an optimal state. In the future, we plan to research a pilot system that applies the unique functions of self-recovery technology and an operating model that can learn and analyze self-recovery strategies appropriate for cyber assets in damaged states.