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신부전이 동반된 당뇨병 환자에서 발생된 침습성 모균증 : 수술과 Liposomal amphotericin B 및 GM-CSF 병합 요법에 의한 성공적인 치험 1예
이원영,오기원,임국희,장재혁,이동건,최정현,강무일,신완식,차봉연,이광우,손호영,강성구 대한화학요법학회 1999 대한화학요법학회지 Vol.17 No.4
저자들은 신부전이 동반된 당뇨병 환자에서 발생된 부비동형 모균증에 대하여 수술과 함께 liposomal amphotericin B 및 GM-CSF의 복합치료를 하여 성공적으로 치료한 1예를 경험하였기에 문헌 고찰과 함께 보고하는 바이다. Mucormycosis (zygomycosis) primarily affects diabetic or immunocompromised patients and typically progresses rapidly, necessitating surgical excision and antifungal therapy with amphotericin B. Large doses of amphotericin B are needed for cure, but it has the risk of causing significant renal toxicity. The recent development of liposomal amphotericin B allows antifungal therapy to be administered with potentially improved efficacy and reduced nephrotoxicity. We have experienced a case of paranasal mucormycosis successfully treated with surgery, liposomal amphotericin B and GM-CSF. A 59-year-old male suffering from diabetes mellitus for 6 years was admitted with pain at left maxillary area. He was diagnosed as mucormycosis after cytologic exam on the necrotic nasal mucosa, which showed typical hyphae. He have had diabetic nephropathy with macroproteinuria and had rapidly rising serum creatinine levels with the amphotericin B treatment: creatinine levels reverted to basal level with the use of liposomal amphotericin B. Despite surgical excision and continued antifungal therapy, his infection was not effectively controlled. Therefore, GM-CSF was administered additionally to improve phagocytic activity of leukocytes. He was finally cured after receiving a combination of aggressive surgery, liposomal amphotericin B and GM-CSF. To our knowledge, this is the first detailed clinical description of the treatment of mucormycosis with liposomal amphotericin B in Korea.
Software-based Real-time GNSS Signal Generation and Processing Using a Graphic Processing Unit (GPU)
Im, Sung-Hyuck,Jee, Gyu-In The Institute of Positioning 2014 Journal of Positioning, Navigation, and Timing Vol.3 No.3
A graphic processing unit (GPU) can perform the same calculation on multiple data (SIMD: single instruction multiple data) using hundreds of to thousands of special purpose processors for graphic processing. Thus, high efficiency is expected when GPU is used for the generation and correlation of satellite navigation signals, which perform generation and processing by applying the same calculation procedure to tens of millions of discrete signal samples per second. In this study, the structure of a GPU-based GNSS simulator for the generation and processing of satellite navigation signals was designed, developed, and verified. To verify the developed satellite navigation signal generator, generated signals were applied to the OEM-V3 receiver of Novatel Inc., and the measured values were examined. To verify the satellite navigation signal processor, the performance was examined by collecting and processing actual GNSS intermediate frequency signals. The results of the verification indicated that satellite navigation signals could be generated and processed in real time using two GPUs.
A Highly Efficient and Fast Algorithm for Implementing a Real-Time Software GNSS Receiver
Sung-Hyuck Im,Gyu-In Jee,Hak-Sun Kim,Sang-Do Cho,Sun-Jun Ko 한국항해항만학회 2006 한국항해항만학회 학술대회논문집 Vol.2 No.-
In this paper, for implementing a real-time software GNSS receiver we propose the highly efficient and fast algorithms such as partial down-conversion, phase rotator, composite I&Q accumulation, Virtual DCO technique, and parallel acquisition using FFT. When the proposed algorithms are used, more 30 tracking channels with 3 tracking arm(early-prompt-late) is operated real-time on Intel 2.8GHz personal computer. Also, the partial down-conversion reduces the FFT size, for parallel acquisition, to 1/8 of conventional FFT-size and the program size includes map is not exceed 1Mbyte. Finally, the proposed real-time software GNSS receiver using the proposed algorithms provides the navigation solution with below 10 meter rms error.
3D LIDAR Based Vehicle Localization Using Synthetic Reflectivity Map for Road and Wall in Tunnel
Im, Jun-Hyuck,Im, Sung-Hyuck,Song, Jong-Hwa,Jee, Gyu-In The Institute of Positioning 2017 Journal of Positioning, Navigation, and Timing Vol.6 No.4
The position of autonomous driving vehicle is basically acquired through the global positioning system (GPS). However, GPS signals cannot be received in tunnels. Due to this limitation, localization of autonomous driving vehicles can be made through sensors mounted on them. In particular, a 3D Light Detection and Ranging (LIDAR) system is used for longitudinal position error correction. Few feature points and structures that can be used for localization of vehicles are available in tunnels. Since lanes in the road are normally marked by solid line, it cannot be used to recognize a longitudinal position. In addition, only a small number of structures that are separated from the tunnel walls such as sign boards or jet fans are available. Thus, it is necessary to extract usable information from tunnels to recognize a longitudinal position. In this paper, fire hydrants and evacuation guide lights attached at both sides of tunnel walls were used to recognize a longitudinal position. These structures have highly distinctive reflectivity from the surrounding walls, which can be distinguished using LIDAR reflectivity data. Furthermore, reflectivity information of tunnel walls was fused with the road surface reflectivity map to generate a synthetic reflectivity map. When the synthetic reflectivity map was used, localization of vehicles was able through correlation matching with the local maps generated from the current LIDAR data. The experiments were conducted at an expressway including Maseong Tunnel (approximately 1.5 km long). The experiment results showed that the root mean square (RMS) position errors in lateral and longitudinal directions were 0.19 m and 0.35 m, respectively, exhibiting precise localization accuracy.