The Treatment of Liver Hemangioma Associated with Kasabach-Merritt Syndrome in Neonates.

Hemangioma is the most frequent liver tumor in infancy. The treatment of hepatic hemangioma includes medical, surgical, and non-operative interventional therapy. There are no standard medical regimens currently considered consistently effective. MDMP (megadose methylprednisolone) and α-interferon can be used for medical treatment. Interventional occlusion of feeding arteries in symptomatic hepatic hemangioma is considered a safe and effective alternative to early open surgery. Untreated symptomatic patients with heart failure have a high mortality rate. For this reason symptomatic patients with heart failure may require non-operative treatment such as interventional embolization, because hepatic resection is burdened with high risk. We report our experiences of two patients with neonatal liver hemangiomas whose clinical courses were complicated by cardiac failure to whom medical treatment and/or interventional vascular occlusion were done. Both patients had Kasabach-Merritt syndrome complicated with cardiac failure. Initially, the masses were considered unresectable. In one case, we performed interventional therapy in addition to medical treatment. In another case, we tried medical therapy with megadose steroid and α-interferon. Unfortunately, in spite of the treatments, the patients died of severe hemorrhageope

자율주행 성능 향상을 위한 3차원 객체 증강과 배경 정보의 이해

학위논문(박사) -- 서울대학교대학원 : 융합과학기술대학원 융합과학부(지능정보융합전공), 2024. 2. Wonjong Rhee.In autonomous driving, 3D data augmentation stands as the one of key factors for 3D object detection, enhancing accuracy and adaptability, and fundamentally influencing the success of navigation and safety systems. Recognizing the significance of this task, DR.CPO(Diversified and Realistic 3D Augmentation via Iterative Construction, Random Placement, and HPR Occlusion) adopts a novel approach to enhance detection capabilities through data augmentation, considering various object shapes and occlusions, by employing object separation, complete object shape creation, and hidden point removal. To achieve this goal, the research enriches the training dataset by utilizing data augmentation techniques. By carefully processing available data, the diversity of object shape and size is expanded, widening the range of objects that the model can detect. Additionally, by applying hidden point removal techniques, the model gains the ability to identify objects in occlusion scenarios, effectively overcoming one of the major challenges faced in real autonomous driving situations. EDA(Elastic Deformable Augmentation) employs the deformation of 3D Graphics to augment objects. By altering human movements or the shape of vehicles, it diversified the objects, leading to performance improvement. Beyond object augmentation, BTO(Behind The Object: The Crucial Information of Background Points in Autonomous Driving) provides insight into background augmentation, revealing how different aspects of background information can contribute to performance improvement. By including various realistic backgrounds, the model is shown to improve the ability to adapt to different building shapes, road layouts, local features, and external occlusions in the background arising from LiDAR characteristics. Such background augmentation enhances the models understanding of the driving context, thereby improving detection accuracy and robustness. The proposed methodology has been meticulously evaluated using experiments and performance analysis. The results demonstrate considerable advancement in the 3D object detection field within autonomous driving systems. Enhanced datasets including various object shapes and occlusion scenarios enable trained models to adapt to real environments, accurately detecting and locating objects. The outcomes of this research contribute to the development of autonomous driving technology, facilitating the creation of safer and more efficient self-driving vehicles. These research findings harbor significant potential for paving the way toward a future where intelligent and human-driven vehicles coexist harmoniously, enhancing road safety and offering an improved transportation experience for all users.Chapter 1. Introduction 1 1.1 Thesis Outline 5 1.2 Related Publications 6 Chapter 2. Background 7 2.1 Conventional Data Augmentation 7 2.1.1 Global Data Augmentation 9 2.1.2 Local Data Augmentation 14 2.1.3 Ground Truth Sampling 16 2.2 Research Motivation 20 2.2.1 LiDAR-specific Features 21 2.2.2 The needs for LiDAR-specific Augmentation 24 2.2.3 The needs for understanding the background context information 26 2.2.4 The evaluation metric 26 2.3 Thesis Roadmap 28 Chapter 3. Diversified and Realistic Data augmentation for autonomous driving 29 3.1 Introduction 29 3.2 Contribution 32 3.3 Related Works 34 3.3.1 3D Object Detection 34 3.3.2 Conventional 3D Augmentations 34 3.3.3 Constructing Whole-body Object 35 3.3.4 Occlusion-based Augmentation 36 3.4 Methods 37 3.4.1 Iterative Construction 39 3.4.2 Random Placement 47 3.4.3 HPR Occlusion 49 3.5 Experiments 56 3.5.1 Model and Training Details: 56 3.5.2 Data Efficiency 57 3.5.3 Model-agnostic Effectiveness 59 3.5.4 Comparison with State-of-the-art Models 60 3.5.5 Computational Efficiency 62 3.6 Analysis of DR.CPO 64 3.6.1 Iterative Construction 64 3.6.2 Random Placement 64 3.6.3 HPR Occlusion 66 3.7 Discussion 67 3.8 Conclusion 69 Chapter 4. Elastic Deformable Augmentation for Autonomous Driving 70 4.1 Introduction 70 4.2 Related Works 73 4.2.1 Objects Augmentation for Autonomous Driving 73 4.2.2 3D Graphics Deformation 73 4.3 Methods 75 4.3.1 Free Form Deformation 75 4.3.2 Radial Basis Functions Deformation 77 4.3.3 Pipeline for Elastic Deformation in Autonomous Driving 79 4.4 Experiments 81 4.4.1 The result of Freeform Deformation augmentation 81 4.4.2 The result of RBF Deformation augmentation 82 4.5 Conclusion 83 Chapter 5. The Crucial Information of Background Points in Autonomous Driving 84 5.1 Introduction 84 5.2 Related Works 90 5.2.1 Diversity 90 5.2.2 Domain Information 90 5.2.3 Occlusion Information 91 5.3 Methods 92 5.3.1 Notation 92 5.3.2 Cube Partition Augmentation for Background 93 5.3.3 Regenerated scenes with external background 95 5.3.4 Generating Occlusion in the Background 98 5.4 Experiments 101 5.4.1 Pilot study : The impact of no background 102 5.4.2 The impact of Diversity in Background 103 5.4.3 The impact of Domain Info Constraint 107 5.4.4 The impact of Occlusion Information 109 5.5 Discussion 110 5.6 Conclusion 113 Chapter 6. Discussion 114 6.1 Class-Specific Approaches for Performance 114 6.2 The Discussion about CP Augmentation 115 6.3 The Importance of Domain Information and Class Balance 118 Chapter 7. Conclusion 120 7.1 Limitation 122 7.2 Future Works 123 Bibliography 124 Appendices 134 A Performance Comparison with CAD-based Methods 135 B Full Results of DR.CPO in Chapter 3 136 C Additional KITTI Examples of DR.CPO 137 D Full Results of EDA in Chapter 4 141 E Full Results of BTO in Chapter 5 141 F Full Results of Discussion in Chapter 6 144 Acknowledgement 145박

보험회사 심사자의 직무 관련 스트레스

학위논문 (석사)-- 서울대학교 대학원 : 간호학과 간호학전공, 2015. 8. 최스미.국문초록 보험회사의 지급심사자는 간호사와 간호사가 아닌 심사자로 구분할 수 있으며, 이들은 많은 업무량과 심사결과 통보와 같은 업무로 인해 상당한 직무스트레스가 존재할 수 있다. 또한 의학지식과 임상경험이 있는 간호사와 의학적 지식이 없는 비간호사 심사자의 직무스트레스는 차이가 있을 수 있다. 그러나 아직까지 지급심사자의 직무 스트레스와 심사 업무 특성 스트레스를 비교하고 영향요인을 조사한 연구가 없다. 본 연구는 서술 조사연구로, 일개 생명보험회사의 지급심사자 76명을 대상으로 조사하였다. 설문지를 이용하여 대상자의 일반적 특성과 근무특성을 조사하고 직무스트레스와 심사업무 특성 스트레스를 비교분석하였다. 직무 스트레스는 한국형 직무스트레스 측정도구(KOSS-SF)를 이용하였고, 심사업무 특성 스트레스는 본 연구자가 개발한 도구를 사용하여 조사하였다. 수집된 자료는 Window SPSS 18.0 program을 이용하여 분석하였다. 본 연구의 결과는 다음과 같다. 1) 직무스트레스 정도는 간호사 심사자의 경우 평균 2.46점(±0.54), 비간호사 심사자는 2.45점(±0.69)이었다. 세부 항목 분석 결과 직장에서 내가 힘들 때 내가 힘들다는 것을 알아주고 이해해 주는 사람이 있다. 항목에서 간호사 심사자(2.91±0.47)와 비간호사 심사자(3.14±0.46)의 직무스트레스는 차이가 있었다(p=.036). 2) 심사업무 특성 스트레스 중 업무과정별 스트레스는 간호사 심사자의 경우 5.21점(±1.92), 비간호사 심사자의 경우 4.91점(±2.35)이었고, 업무분야별 스트레스는 간호사 심사자의 경우 6.12점(±1.80), 비간호사 심사자의 경우 5.53점(±2.33)이었으며, 심리적 부담감은 간호사 심사자의 경우 6.92점(±1.65), 비간호사 심사자의 경우 6.32점(±2.33)이었다. 3) 심사업무 특성 스트레스 중 업무분야별 스트레스에서 장해 건(p=.008), 사망 건(p=.004) 처리 시 간호사 심사자와 비간호사 심사자 간의 차이를 보였고, 심리적 부담감에서 민원성향 고객을 응대할 때(p=.019) 간호사 심사자와 비간호사 심사자의 스트레스의 차이가 있었다. 4) 단계적 다중회귀분석 결과, 직무 관련 스트레스 영향요인은 다음과 같다. 직무스트레스는 직무만족(β=.457, p<.001), 성별(β=.256, p=.022)로 나타났으며, 모형의 설명력은 18.7%이었다. 심사업무 특성 스트레스 중 심리적 부담감은 직무만족(β=-.279, p=.015)과 간호사면허 유무(β=-.226, p=.047)이었고, 모형의 설명력은 8.9%였다. 본 연구 결과 간호사 심사자와 비간호사 심사자가 지각하는 직무 관련 스트레스는 차이가 있었다. 특히, 대인관계와 관련하여 간호사 심사자의 직무스트레스는 비간호사 심사자보다 낮게 나타났으며, 심사업무 특성상 업무 분야별로 장해 건과 사망 건 처리시 간호사 심사자의 스트레스는 비간호사 심사자의 스트레스보다 높게 나타났다. 또한 민원성향 고객을 응대할 때 간호사 심사자의 심리적 부담감이 비간호사 심사자의 심리적 부담감보다 더 높았다. 따라서 효율적인 스트레스 관리를 위해서 간호사 심사자와 비간호사 심사자 간의 이러한 차이를 고려한 효과적인 스트레스 감소 중재 개발 및 시행이 필요한 것으로 사료된다. 주요어 : 지급심사, 간호사 심사자, 비간호사 심사자, 직무스트레스, 심사업무 특성 스트레스 학 번 : 2010-20424목 차 국문초록 ........................................................................................... i Ⅰ. 서론 ...................................................................1 1. 연구의 필요성 ..........................................................................1 2. 연구목적 .....................................................................................4 3. 용어정의 .....................................................................................5 Ⅱ. 문헌고찰 ............................................................7 Ⅲ. 연구방법 ............................................................15 1. 연구설계 ......................................................................................15 2. 연구대상 ......................................................................................15 3. 윤리적 고려 ................................................................................16 4. 자료수집도구 ..............................................................................17 5. 자료수집절차 및 방법 ..............................................................19 6. 자료분석방법 ...............................................................................20 Ⅳ. 연구결과 .............................................................21 1. 심사자의 일반적 특성 ...............................................................21 2. 심사자의 근무특성 .....................................................................24 3. 심사자의 직무스트레스 및 영향요인......................................26 4. 심사자의 심사업무 특성 스트레스 및 영향요인..................32 Ⅴ. 논의 .....................................................................46 Ⅵ. 결론 및 제언 .......................................................53 참고문헌 .....................................................................55 부 록 ......................................................................63 Abstract .....................................................................72Maste

유한요소법을 이용한 환자별 교정시스템 구축의 기초 알고리즘 개발과 적용

The purpose of this study is to develop the basic algorithm for the finite element method modeling of individual malocclusions. Usually, a great deal of time is spent in preprocessing. To reduce the time required, we developed a standardized procedure for measuring the position of each tooth and a program to automatically preprocess. The following procedures were carried to complete this study. 1. Twenty-eight teeth morphologies were constructed three-dimensionally for the finite element analysis and saved as separate files. 2. Standard brackets were attached so that the FA points coincide with the center of the brackets. 3. The study model of a patient was made. 4. Using the study model, the crown inclination, angulation, and the vertical distance from the tip of a tooth was measured by using specially designed tools. 5. The arch form was determined from a picture of the model with an image processing technique. 6. The measured data were input as a rotational matrix. 7. The program provides an output file containing the necessary information about the three-dimensional position of teeth, which is applicable to several finite element programs commonly used. The program for a basic algorithm was made with Turbo-C and the subsequent outfile was applied to ANSYS. This standardized model measuring procedure and the program reduce the time required, especially for preprocessing and can be applied to other malocclusions easily