• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.1
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• pp.69-74
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• 2019

Purpose $^{18}F$-FDOPA using amino acid is particularly attractive for imaging of brain tumors because of the high uptake in tumor tissue and the low uptake in normal brain tissue. But, on the other hand, $^{18}F$-FDG is highly uptake in both tumor tissue and normal brain tissue. The purpose of study is to evaluate comparison of contrasts in $^{18}F$-FDOPA Brain PET/CT and $^{18}F$-FDG Brain PET/CT and to find out optimal scan time by analysis of variation in SUV with the passage of uptake time. Materials and Methods A region of interest of approximately $350mm^2$ at the center of the tumor and cerebellum in 12 patients ($51.4{\pm}12.8yrs$) who $^{18}F$-FDG Brain PET/CT and $^{18}F$-FDOPA Brain PET/CT were examined more than once each. The $SUV_{max}$ was measured, and the $SUV_{max}$ ratio (T/C ratio) of the tumor cerebellum was calculated. In the analysis of SUV, T/C ratio was calculated for each frame after dividing into 15 frames of 2 minutes each using List mode data in 25 patients ($49.{\pm}10.3yrs$). SPSS 21 was used to compare T/C ratio of $^{18}F$-FDOPA and T/C ratio of $^{18}F$-FDG. Results The T/C ratio of $^{18}F$-FDOPA Brain PET/CT was higher than the T/C ratio of $^{18}F$-FDG Brain, and show a significant difference according to a paired t-test(t=-5.214, p=0.000). As a result of analyzing changes in $SUV_{max}$ and T/C ratio, the peak point of $SUV_{max}$ was $5.6{\pm}2.9$ and appeared in the fourth frame (6 to 8 minutes), and the peak of T/C ratio also appeared in the fourth frame (6 to 8 minutes). Taking this into consideration and comparing the existing 10 to 30 minutes image and 6 to 26 minutes image, the $SUV_{max}$ and T/C ratio increased by 0.2 and 0.1 each, compared to the 10 to 30 minutes image for 6 to 26 minutes image. Conclusion From this study, $^{18}F$-FDOPA Brain PET/CT is effective when reading the image, because the T/C ratio of $^{18}F$-FDOPA Brain PET/CT was higher than T/C ratio of $^{18}F$-FDG Brain PET/CT. In addition, in the case of $^{18}F$-FDOPA Brain PET/CT, there was no difference between the existing 10 to 30 minutes image and 6 to 26 minutes image. Through continuous research, we can find possibility of shortening examination time in $^{18}F$-FDOPA Brain PET/CT. Also, we can help physician to accurate reading using additional scan data.

• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1167-1176
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• 2004

Along the advent of Internet technology, the computing environment has been considerably changed in many application domains. Especially, a lot of researches for e-Logistics have been done for the last 3 years. The e-Logistics means the virtual business activity and service architecture among the logistics companies based on the Internet technology. To construct effectively the e-Logistics framework, researches on the development of the Moving Object Technology(MOT) including GPS and GIS with spatiotemporal databases technique so far has been done The Moving Object Technology stands for the efficient management for the spatiotemporal objects such as vehicles, airplanes, and vessels which change continuously their spatial location along with time flows. However, most systems manage just only the location information detected lately by many reasons so that the uncertainty processing for the past and future location of the moving objects is still very hard. In this paper, we propose the moving object uncertainty model and system design for e-Logistics applications. The MOMS architecture in e-Logistics is suggested and the detailed explain of sub-systems including the uncertainty processor of moving objects is described. We also explain the comprehensive examples of MOMS and uncertainty processing in Delivery Parcel Application that is one of major application of e-Logistics domain.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.63-69
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• 2003

90년대부터 많은 ERP를 도입하여 회사의 전체 업무를 통합시키고 실시간으로 모든 업무를 동시에 처리함에 따라 경영환경과 정보기술의 급격한 변화에 대처하고 있다. 이러한 ERP 시스템을 도입하던 기존의 업무 수행절차와 방법대신 ERP 패키지가 제공하는 프로세스와 기능을 적용하여 기업 내 업무기능을 혁신한다는 특징을 가지고 있어 조직변화를 수반하게 된다. 따라서 효과적인 ERP 구면을 위해서는 기업의 환경에 적절한 구축방법을 정하고 변화관리 이행 프로그램을 필요로 하고 있다. 본 연구에서는 ERP를 구축하는데 어떠한 조직적 환경요인이 영향을 미지고. ERP 구축방법에 따라 변화관리의 특성이 어떻게 달라지며. 변화관리가 ERP 성과에 어떠한 영향을 미치는지 파악하기 위한 프레임워크를 제시하고 이틀 근간으로 하여 상이한 구축방법을 통하여 ERP틀 구면탄 두 기업을 대상으로 심도있게 비교 분석함으로써 ERP 구축환경의 특성과 ERP 구축방법에 따른 변화관리 특성 및 ERP성과를 살펴보았다. 연구결과 ERP 구축방법은 ERP 구축환경에 따라 차이를 보였으며, ERP 구축 방법에 따라서 변화기법이 달라진다는 사실을 알 수 있었다. 그러나 변화관리 방법 중에서도 최고 경영자의 리더십과 현업 직원의 적극적인 참여 및 전사적인 커뮤니케이션은 ERP 구축방법과 관계없이 중요한 요인으로 나타났다. 그리고 ERP 구축방법에 있어서 변화관리 활동은 ERP 성과에 긍정적인 영향을 미쳤다. 본 사례연구로 얻은 시사점은 ERP의 구현하고자 하는 국내 기업들이 ERP 구축방법을 선정하고 적합탄 변화관리 방법의 전개를 위하여 실질적인 도움을 줄 것이다.6 전문가 그룹을 통해 시범적으로 적응하는 것으로 시작해, 학교 및 연구소를 통한 정보지식 공유 그리고 기업 정보화 솔루션으로 활용 될 수 있다.을 제시한다. 이렇게 함으로써 최대한 고객 납기를 만족하도록 계획을 수립할 수 있게 된다. 본 논문에서 제시하는 계획 모델을 사용함으로써 고객 주문에 대한 대응력을 높일 수 있고, 계획의 투명성으로 인한 전체 공급망의Bullwhip effect를 감소시킬 수 있는 장점이 있다. 동시에 이것은 향후 e-Business 시스템 구축을 위한 기본 인프라 역할을 수행할 수 있게 된다. 많았고 년도에 따른 변화는 보이지 않았다. 스키손상의 발생빈도는 초기에 비하여 점차 감소하는 경향을 보였으며, 손상의 특성도 부위별, 연령별로 다양한 변화를 나타내었다.해가능성을 가진 균이 상당수 검출되므로 원료의 수송, 김치의 제조 및 유통과정에서 병원균에 대한 오염방지에 유의하여야 할 것이다. 확인할 수 있었다. 이상의 결과에 의하면 고농도의 유기물이 함유된 음식물쓰레기는 Hybrid Anaerobic Reactor (HAR)를 이용하여 HRT 30일 정도에서 충분히 직접 혐기성처리가 가능하며, 이때 발생된 $CH_{4}$를 회수하여 이용하면 대체에너지원으로 활용 가치가 높은 것으로 판단된다./207), $99.2\%$(238/240), $98.5\%$(133/135) 및 $100\%$ (313)였다. 각각 두 개의 요골동맥과 우내흉동맥에서 부분협착이나 경쟁혈류가 관찰되었다. 결론: 동맥 도관만을 이용한 Off pump CABG를 시행하여

• Journal of the Korea Computer Graphics Society
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• v.23 no.2
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• pp.11-22
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• 2017

This study proposes IMToon(IMage-based carToon) which is an image-based cartoon authoring system using an image processing algorithm. The proposed IMToon allows general users to easily and efficiently produce frames comprising cartoons based on image. The authoring system is designed largely with two functions: cartoon effector and interactive story editor. Cartoon effector automatically converts input images into a cartoon-style image, which consists of image-based cartoon shading and outline drawing steps. Image-based cartoon shading is to receive images of the desired scenes from users, separate brightness information from the color model of the input images, simplify them to a shading range of desired steps, and recreate them as cartoon-style images. Then, the final cartoon style images are created through the outline drawing step in which the outlines of the shaded images are applied through edge detection. Interactive story editor is used to enter text balloons and subtitles in a dialog structure to create one scene of the completed cartoon that delivers a story such as web-toon or comic book. In addition, the cartoon effector, which converts images into cartoon style, is expanded to videos so that it can be applied to videos as well as still images. Finally, various experiments are conducted to verify the possibility of easy and efficient production of cartoons that users want based on images with the proposed IMToon system.

• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.17-36
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• 2022

The purpose of this study is to diagnose problems in the regulation and management of Restricted Development Zone and to prepare a construction plan to convert it to a data-based monitoring system. Unlike other land-use zones, the Restricted Development Zone is a exceptional zone that prohibits all development activities other than the minimum maintenance and must be strictly controlled and managed by the local government. However, the current Restricted Development Zone management is distributed according to the conditions of each local government, and it is not possible to monitor changes in the entire Restricted Development Zone as shown in the survey results. In particular, in this study, by introducing an AI-based monitoring system, MOLIT sends the results of detecting changes across the country at regular time points(monthly and quarterly) to the local governments based on the same regulation standards, and the local governments can be trusted while inputting the regulation results into the system. To propose this methodology, first, a survey and interview were conducted with local government officials and experts. Second, we analyzed cases in which AI analysis was applied to local governments and proposed a plan to improve the efficiency of regulation work according to the introduction of the monitoring system. Third, a plan was prepared to establish a monitoring system based on the advancement of the management information system. This monitoring system can be expanded and applied to land that needs periodic regulation and management in the future, and this study tried to propose a methodology and policy for this.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.119-125
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• 2023

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• The Korean Journal of Nuclear Medicine
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• v.38 no.4
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• pp.318-324
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• 2004

Purpose: Philips GEMINI is a newly introduced whole-body GSO PET/CT scanner. In this study, performance of the scanner including spatial resolution, sensitivity, scatter fraction, noise equivalent count ratio (NECR) was measured utilizing NEMA NU2-2001 standard protocol and compared with performance of LSO, BGO crystal scanner. Methods: GEMINI is composed of the Philips ALLEGRO PET and MX8000 D multi-slice CT scanners. The PET scanner has 28 detector segments which have an array of 29 by 22 GSO crystals ($4{\times}6{\times}20$ mm), covering axial FOV of 18 cm. PET data to measure spatial resolution, sensitivity, scatter fraction, and NECR were acquired in 3D mode according to the NEMA NU2 protocols (coincidence window: 8 ns, energy window: $409[\sim}664$ keV). For the measurement of spatial resolution, images were reconstructed with FBP using ramp filter and an iterative reconstruction algorithm, 3D RAMLA. Data for sensitivity measurement were acquired using NEMA sensitivity phantom filled with F-18 solution and surrounded by $1{\sim}5$ aluminum sleeves after we confirmed that dead time loss did not exceed 1%. To measure NECR and scatter fraction, 1110 MBq of F-18 solution was injected into a NEMA scatter phantom with a length of 70 cm and dynamic scan with 20-min frame duration was acquired for 7 half-lives. Oblique sinograms were collapsed into transaxial slices using single slice rebinning method, and true to background (scatter+random) ratio for each slice and frame was estimated. Scatter fraction was determined by averaging the true to background ratio of last 3 frames in which the dead time loss was below 1%. Results: Transverse and axial resolutions at 1cm radius were (1) 5.3 and 6.5 mm (FBP), (2) 5.1 and 5.9 mm (3D RAMLA). Transverse radial, transverse tangential, and axial resolution at 10 cm were (1) 5.7, 5.7, and 7.0 mm (FBP), (2) 5.4, 5.4, and 6.4 mm (3D RAMLA). Attenuation free values of sensitivity were 3,620 counts/sec/MBq at the center of transaxial FOV and 4,324 counts/sec/MBq at 10 cm offset from the center. Scatter fraction was 40.6%, and peak true count rate and NECR were 88.9 kcps @ 12.9 kBq/mL and 34.3 kcps @ 8.84 kBq/mL. These characteristics are better than that of ECAT EXACT PET scanner with BGO crystal. Conclusion: The results of this field test demonstrate high resolution, sensitivity and count rate performance of the 3D PET/CT scanner with GSO crystal. The data provided here will be useful for the comparative study with other 3D PET/CT scanners using BGO or LSO crystals.