링 마우스 : 손가락 움직임에 의한 컴퓨터 무선 입력 장치

Phan, Ke Hien 한국산업기술대학교 일반대학원 2018 국내석사

국문요약 링 마우스: 손가락 움직임에 의한 컴퓨터 무선 입력 장치 한국산업기술대학교 일반대학원 전자공학과: 판게히엔 지도교수: 정 두 희 이 논문에서는 링과 같이 손가락으로 감싸는 컴퓨터 용 무선 장치를 연구했습니다. Ring Mouse는 Bluetooth를 통해 컴퓨터에 무선으로 연결된 마우스 역할을하는 스마트 장치입니다. 손가락 움직임으로 컴퓨터의 마우스 커서를 제어 할 수 있습니다. 마이크로 컨트롤러 Cortex M4와 함께 nRF52832를 사용함으로써 우리는 전력 효율이 높고 비용 효율적인 회로를 만들었습니다. 모션 데이터는 MPU-9250 모듈을 사용하여 획득합니다. 장치의 기계적 케이스는 3D 인쇄 기술로 설계 및 제작되었습니다. ABSTRACT Ring Mouse: A Wireless Input Device for Computers by Finger Motions By Phan Ke Hien Advisor: Professor Jung Doo Hee Course for Electronics Engineering Graduate School Korea Polytechnic University In this thesis, we studied a wireless device for the computer which is carried on the finger like a ring. Ring Mouse is a smart device that acts as a mouse that is connected wirelessly to a computer via Bluetooth. One can control the mouse cursor on the computer with finger motions. By using nRF52832 with microcontroller Cortex M4, we made a circuit that is power-efficient and cost-effective. Motion data is acquired by using an MPU-9250 module. The mechanical case of the device is designed and made by 3D printing technologies.

Expanding constraint theory to determine well-posedness of large mathematical models

Phan, Phan University of Southern California 2011 해외박사(DDOD)

Mathematical modeling represents one of the major tools for the conception and management of the ever increasing complexity of systems engineering. Unfortunately, present approaches to math modeling suffer from several theoretical problems which include: model consistency, computational allowability, management of the topologically complex flow of software algorithms, rearrangement of independent and dependent variables, distinction between the model structure and software programs and perhaps the most challenging, the exponential explosions resulting from the management of even medium sized models as well as the large models of the thousands of dimensions necessary to define and manage the complex systems of the future. Constraint theory was designed to solve the above problems employing a rigorous application of graph theory and attempts to employ the generalizability of mathematics to extend the math model manager's conceptual understanding from half a dozen dimensions to the desired thousands of dimensions. Constraint theory (CT) went through several stages of detail and maturity, starting with the PhD dissertation in the 1960's and progressing through several papers and two other PhD research programs. CT's present frontier can be characterized by the Constraint Theory book written by Dr. George Friedman and published by Springer in 2005. CT differs from linear programming (LP) in several ways. LP requires a full model of explicit mathematical expressions in linear form whereas CT employs a meta-model based upon relevancy between general (linear or non-linear) relations and variables. CT seeks to determine a model consistency and computational allowability without having to actually solve for a specific solution set whereas LP assumes that the problem is well-posed while attempting to solve for an optimal solution within a given constrained trade space. As mentioned above, the exponential explosions associated with the management of thousand-dimensional models is truly enormous, on the order of 2 N examinations of a model's N equations are required to determine consistency, for example. CT has converged this process---which would take several universe lifetimes even with nanosecond computer cycle times---by a factor of trillions. This convergence is based on an ordered series of graph theoretic steps involving connected-ness, tree-ness, circuit-ness and cluster-ness. A constraint theoretic structure called the "Basic Nodal Square" (BNS) is identified as the kernel of constraint in a math model. An n x n BNS is essentially a complete sub-system of n relations and n variables within the overall model. However, Friedman's book effectively stops at the identification of circuit clusters of approximately 30 relations, and suggests that BNS within these clusters can be found by modern computers in a few hours. It is suggested that perhaps more research can employ the topological property of adjacency to converge the search for BNS within larger circuit clusters. The central contribution resultant from this investigation realizes and improves the computational efficiency of BNS search by factors of trillions, asymptotically (see Figure 10-2). This improvement has been accomplished by innovative application of graph theory, topology, algorithm analysis and linear algebra, which were not addressed to sufficient depth in the original efforts. Leveraging research results in graph theory since the early 1970's, several BNS search methods, based on nodal adjacency, circuit adjacency and nodal degree, have been developed and compared against the baseline (brute-force) approach of 2N. Primary key research findings and enablers include: (a) Decomposition of a model graph into its connected components by employing the graph-theoretic concept of a spanning tree and applying the depth-first search algorithm. (b) Innovation of the edge-centric method, over the legacy approach of vertex-centricity, to identify, and remove, internal trees (or bridges) within a connected component. (c) Further isolation of circuit clusters containing potential BNS by using the graph-theoretic concept of articulation point (or separating vertex). (d) Rigorous proof of circuit vector-based theorems to simplify the computational complexity of constructing unions of adjacent circuits, and thus reduce BNS search space. (e) Application of vectorial dot product to detect adjacency among circuits, and overlapping among nodes or BNSs. (f) Development and demonstration of a meta-meta-model graph to represent overlapping among nodes and to reduce the solution-time for BNS search, from exponential to polynomial. Additional accomplishments further improve the utility of CT by developing an integrated set of efficient computing algorithms to determine model consistency and computational allowability. The output of these algorithms can also advise the model builder of repair alternatives to correct any model inconsistency detected. Such algorithms are necessary to bridge the gap between theoretical abstracts and practical realization of CT in terms of an effective computer-assisted tool for math model management.

Defending denial-of-service attacks in SDNFV-enabled cloud computing

Phan, Van Trung Soongsil University 2017 국내석사

In my thesis, I propose a novel S2eH scheme to tackle Denial-of-Service (DoS) attacks in the Software-Defined Network Functions Virtualization (SDNFV) cloud computing environment. I firstly introduce a new machine learning hybrid model for DoS attack classification based on Support Vector Machine (SVM) and Self Organizing Map (SOM) algorithms to enhance the performance of classification network traffic. The proposed combination mainly focuses on taking advantages of two classification algorithms by utilizing both algorithm advantages that SVM takes a little time to produce outputs with a high accuracy and SOM makes a reliable prediction based on their neurons. Then, I propose an enhanced History-based IP Filtering scheme (eHIPF) to improve attack detection rate and speed. Finally, I propose a novel mechanism combining both the machine learning hybrid model SVMs-SOM and the eHIPF scheme, called S2eH, to make a DoS attack defender in the SDNFV-enabled cloud computing. The S2eH testbed is implemented in the SDNFV cloud environment with Service Function Chaining. Through practical experiments in this testbed, it is proved that the proposed SVMs-SOM combination and eHIPF scheme outperforms existing mechanisms for DoS attack classification and detection. By analyzing comprehensive experiments conducted with various DoS attack levels, I prove that the novel S2eH mechanism is an effective and innovative approach to defend DoS attacks in the SDNFV-based cloud computing. 본 논문에서는 Software-Defined Network Functions Virtualization (SDNFV) Cloud computing 환경에서 서비스 거부 공격을 저지하는 새로운 S2eH 스키마를 제안한다. 먼저, DoS 공격 분류를 위해 Network 분류 성능을 높이는 Support Vector Machine (SVM) 과 Self-Organizing Map(SOM) 알고리즘 기반 새로운 Hybrid Machine Learning을 소개한다. 제안된 결합 시스템은 주로 두 가지 분류 알고리즘의 이점을 가져오는데 초점을 둔다. SVM은 짧은 시간에 높은 정확도로 분류를 하고, SOM은 SOM의 신경망기반으로 신뢰성이 높은 예측을 한다. 또한, 공격 탐지 비율과 속도를 개선하기 위해 History 기반 IP Filtering 스키마(eHIPF)를 제안한다. 본 논문에서는 SDNFV가 가능한 Cloud Computing 에서 DoS공격을 방어하기 위해 SVMs-SOM을 결합한 Hybrid Machine Learning 모델과 eHIPF 스키마를 결합한 새로운 메커니즘 S2eH을 제안한다. S2eH testbed는 Service Function Chaining이 가능한 SDNFV Cloud 환경에서 실험했다. 이 testbed에서 실제 실험을 통해 본 논문에서 제안된 SVMs-SOM 결합과 eHIPF 스키마가 DoS공격 분류와 탐지에 다른 메커니즘보다 좋은 결과 가져오는 것을 증명했다. 다양한 DoS공격 레벨로 수행 된 포괄적인 실험을 분석하여 새로운 S2eH메커니즘이 SDNFV기반 Cloud computing에서 DoS 공격을 방어하기 위한 효과적이고 혁신적인 방법임을 증명했다.

Research on insurance fraud and regulations on prevention of automobile insurance fraud : experiences from the United States of America and proposals for Vietnam

Phan, Thi Huong Giang TLBU Graduate School of Law 2019 국내석사

A Drosophila model for Alzheimer’s disease revealed synaptic neuropathy and biochemical alterations : 초파리 알츠하이머모델의 신경연접의 병리현상과 생화학적인 변화 연구

Phan, Anh Thuc Dang 한림대학교 대학원 2017 국내석사

연구배경: 알츠하이머 병은 시냅스 연결, 신경 세포 죽음, 세포 내 아밀로이드 플라크 및 세포 내 신경원 섬유 엉킴의 존재를 병징으로하는 노화와 관련 퇴행성 신경계 질환입니다. 세포 외 아밀로이드 플라크는 주로 아밀로이드 베타 (Aβ) 펩티드로 구성되어 염증, 산화 스트레스 및 세포사멸을 유발하여 시냅스 및 신경 세포의 손실을 유발한다. 누에(Bombyx mori)는 오래 전부터 혈중 포도당 농도를 조절하여 성기능을 향상시키는 것으로 알려진 아시아 국가의 식품 및 의약품으로 사용되어 왔으며 AD를 비롯한 산화 적 스트레스와 관련된 수많은 신경 질환 치료에 효과가 있다고 알려져 있습니다. 연구방법: 우리는 인간 AD 관련 단백질 APP695, BACE I 및 MAPT를 발현하는 Drosophila melanogaster를 사용하여 애벌레 신경근 접합부의 시냅스 결손, 행동 기능 장애 및 정상 초파리 배지 및 익힌 성숙 누에 유충 분말 포함 배지에서 발생 된 파리의 생화학 적 변이를 조사했다. 연구결과: 우리는 인간 APP, BACE I 및 MAPT의 초파리에서의 발현이 대조군 초파리에 비해 성충의 운동 능력과 수명 단축을 가져왔고, 유충 근육신경연접의 시냅스 감소를 가져왔음을 밝혀냈다. 우리는 익힉 성숙누에가루 포함 배지배양 초파리에서 알츠하이머모델 초파리에서 보이는 수명과 운동 능력 장애를 억제하는데 도움이 된다는 것을 관찰했다. 그리고 익힌 성숙누에 가루 포함배지 배양 초파리의 유충의 경우는 근육신경연접의 시냅스의 감소를 억제함을 확인 하였다. 그리고 알츠하이머모델 초파리에서 감소되는 아세틸콜린 에스터레이즈의 활성을 회복시킴을 확인 하였다. 본 연구결과는 익힌 성숙누에가루가 초파리에서 알츠하이머 발병을 억제함을 알려주고 있다. 익힌성숙누에가루를 이용한 인간 환자에의 적용이 앞으로 수행하여할 연구로 생각이 된다. Backgrounds: Alzheimer’s disease (AD) is an age-related neurodegenerative disease characterized by extensive loss of synaptic connections, neuronal death, and the presence of extracellular amyloid plaques as well as intracellular neurofibrillary tangles (iNFTs). The extracellular amyloid plaques are mainly composed of the amyloid beta (Aβ) peptide which is thought to cause inflammation, oxidative stress and apoptosis, thereby resulting in synaptic and neuronal loss. Silkworm (Bombyxmori) has long been used as food and medicine in Asian countries which is known to control the blood glucose concentrations, improving sexual function and etc. It is believed to have effect on treatment of numerous neurological disorders related to oxidative stress including AD. Methods: We used Drosophila melanogaster expressing the human AD-associated protein APP695 (Amyloid precursor protein), BACE I (β site APP-cleaving enzyme) and MAPT (Microtubule associated – protein Tau) to initially investigate synaptic defects in larvae neuromuscular junction (NMJs), behavior dysfunction as well as biochemical alterations in flies raised on normal food and steamed mature silkworm larval powder food (SMSPF).Results: Our results indicated that the expression of human APP695, BACE I and MAPT led to defective adult locomotion behavior, decreased life expectancy and significantly reduced synaptic boutons compared to control flies. We observed that SMSPF help to extend lifespan and recovery locomotor dysfunction in transgenic flies. Flies reared SMSPF showed a significant increase in number of total synaptic boutons (including synaptic boutons type 1b and 1s) and for transgenic fly, reduced acetylcholinesterase activity, which directly related to AD mechanism in early point of time at 1-day after eclosion. Our data also found that the positive effect of SMSPF is related to the transcriptional regulation of the APP genes which results in decreased the APP levels. Conclusions: The data suggested this model has potential to approach the synaptic dysfunction associated with AD and help to understand AD pathogenesis and its treatment. Our study also suggested that SMSPF had positive effect on improving lifespan and behavioral deficits in AD model.

Improved wavefront reconstruction algorithm for freeform measurement : 자유곡면 측정을 위한 파면재구성 알고리즘의 개선

PHAN HUY PHUC University of Science and Technology 2017 국내석사

With the development of optical systems that used to evaluate the freefrom surface such as lateral shearing interferometer (LSI), deflectometry, and the Shack - Hartmann sensor, the demand of supporting algorithms has risen. They are phase unwrapping algorithm that estimates the absolute (true) phase from the wrapped (measured, principle) phase taken from some captured fringe images, followed by some steps to give the slope measurment data of the surface; then we need a wavefront reconstruction algorithm to reconstruct the surface from these slope data. We propose a wavefront reconstruction algorithm from slope measurements based on a zonal method. In this algorithm, the slope measurement sampling geometry used is the Southwell geometry, in which the phase values and the slope data are measured at the same nodes. The proposed algorithm estimates the phase value at a node point using the slope measurements of eight points around the node, as doing so is believed to result in better accuracy with regard to the wavefront. For optimization of the processing time, a successive over-relaxation method is applied to iteration loops. We use a trial-and-error method to determine the best relaxation factor for each type of wavefront in order to optimize the iteration time and, thus, the processing time of the algorithm. Specifically, for a circularly symmetric wavefront, the convergence rate of the algorithm can be improved by using the result of a Fourier Transform as an initial value for the iteration. Various simulations are presented to demonstrate the improvements realized when using the proposed algorithm. Several experimental measurements of deflectometry are also processed by using the proposed algorithm. Considering PUMA algorithm as one of the most efficient phase unwrapping algorithm with the ability to process various type of phase at high accuracy. However, the drawback of the PUMA lies on computation speed when processing large, complex phase, and the lack of pre-filter make trouble for PUMA processing noisy data. In this paper, we proposed a new algorithm compounding two structures: the incremental breadth-first search (IBFS) which modifies Boykov-Kolmogorov (BK) in the way finding path from source to sink of a graph in max-flow problem in order to help reduce processing time of PUMA algorithm; and a pre-filter by principle of adaptive local denoising. Simulations and experimental implementation used to demonstrate ability of the proposed algorithm.

한국어의 조사에 대한 교육방안 연구 : 초급 단계의 베트남 학습자를 대상으로 :

Phan Thi Hanh 인제대학교 일반대학원 2018 국내석사

한국어와 베트남어의 문법이 완전히 다르기 때문에 베트남인 학습자들이 한국어를 학습할 때 어려움을 많이 겪는다. 특히 한국어의 조사와 어미 활용법에 어려움을 많이 겪는다. 이글은 한국어를 외국어로 하는 초급 수준의 베트남 학습자를 대상으로 조사의 교육방법에 대해 검토하고 조사를 보다 더 쉽게 이해하도록 하기 위한 것이다.

베트남의 외국인 직접투자 구조변화와 정책과제

PHAN HAI TIEN 한밭대학교 대학원 2021 국내석사

외국인 직접투자는 수혜국 입장에서 보면, 제조업, 서비스업 등 산업 활성화를 통하여 경제성장 및 수출 등에 중요한 역할을 한다. 베트남에 대한 외국인투자 활동은 점점 활발해지고 있으며, 많은 다국적기업 및 선진기술을 보유한 대기업이 베트남에 투자하고 있다. 자본 규모의 증가와 함께, 각종 프로젝트의 질이 향상되어 일자리와 소득창출에 크게 기여하고 있다. 2016년부터 베트남에 대한 외국인투자 방식은 변화의 바람이 불고 있다. 과거에는 베트남의 저렴한 토지 사용료와 노동력을 이점으로 활용하였던 그린필드형 투자가 주를 이루고 있었다. 그러나 최근에는 높은 경제성장에 따른 내수시장 확대로 유통망을 확보하고 있는 제조 및 소비재 유통기업 등에 대한 M&A 수요가 증가하고 있다. 미중 무역분쟁으로 인해 불확실성이 증가함에 따라 기존 기업의 인프라와 네트워크를 활용할 수 있는 브라운필드 투자가 급증하고 있는 것이다. 이외에도 베트남 정부의 외국인 지분 제한 비율 완화 및 공기업 민영화 정책 등으로 투자여건이 개선되면서 브라운필드형 투자가 더욱 증가하고 있다. 본 논문에서는 그동안 베트남에 유입된 그린필드형과 브라운필드형 외국인직접투자의 현황 분석과 함께, 경제적 효과 및 사례 분석, 그리고 시사점 및 정책과제에 대하여 연구하였다. 브라운필드형 투자의 경우 국내 기업이 동 투자를 통하여 다국적기업의 글로벌 가치사슬에 바로 편입될 수 있다는 점에서, 해당 기업의 생산성 향상 및 글로벌 시장 확대 등 긍정적인 측면이 크다고 할 수 있다. 따라서 베트남 현지 기업들이 브라운필드형 외국인투자를 통하여 글로벌 가치사슬에 편입하여 글로벌 경쟁력을 제고할 수 있도록 브라운필드형 투자 기회를 적극 제공하는 방향으로 정책적 지원이 필요하다. 인수합병이 이뤄지면 선진 기술과 노하우가 베트남에 이식되고, 일반적으로 거래와 동시에 투자금액 100%가 유입되기에 베트남 내에서도 인수합병 및 지분투자와 같은 브라운필드형 투자를 긍정적으로 바라보고 있다. 또한 기존에 베트남 정부가 지배하고 있던 국영 산업부문에 민간 투자자, 외국계 투자자의 유입을 촉진함으로써 공기업의 투명성, 효율성을 증진하는 동시에 산업 전체의 경쟁력을 국제적 수준으로 끌어올려 글로벌 경쟁력 제고에 기여할 수 있다. 국가의 핵심부문인 공공서비스, 국방, 전력 및 에너지 등을 제외하고 민간 및 외국 투자자에게 개방하여 그동안 방만하게 운영되어왔던 공공 영역을 구조 조정하기 위한 국유기업 민영화가 한편으로 진행되고 있다. 베트남에서 사회경제적 발전전략을 촉진하기 위해서는 외국인 직접투자 자본원을 최대한 활용하는 것이 필요하다. 베트남의 외국인 투자유치 경쟁력이 점점 약화되는 상황으로 베트남 정부는 확실한 비교우위의 투자유치 정책 마련 및 투자환경 개선안을 제시해야 할 것으로 보인다. 한편, 베트남 정부는 베트남 주요 공기업에 대한 외국인 보유 지분 제한 규제를 완화하는 등 관련 법과 제도의 개정을 위해 노력해야 하며, 공기업 민영화 확대 정책 역시 외국기업들의 브라운필드형 투자를 통한 베트남 진출 확대의 기회 요인이 될 것으로 기대된다.

Improved variational methods in medical image enhancement and segmentation

Phan Tran Ho Truc 경희대학교 2009 국내박사

Medical procedures have become a critical application area that makes substantial use of image processing. Medical image processing tasks mainly deal with image enhancement and segmentation, i.e., filtering, sharpening, and bringing out image details, and quantitatively measuring medical conditions such as vessel size, tumor volume, or bone fracture length. Over a long time, medical image processing problems were tackled by a pool of heuristic and low level mathematical operators. Simple heuristic approaches, e.g., histogram equalization, can provide surprisingly good results; however, one cannot know exactly when and why they work or do not work. Recently, the use of variational methods in image processing has emerged as an interesting research topic. Variational methods can be based on either the optimization of a energy functional or the design of a partial differential equation (PDE) whose steady state is the solution of the problem at hand. The advantage of these methods is that the theory behind the concept is well defined. However, the direct application of variational method (as it is) to medical image processing suffers from limited performance since medical images are of very poor quality. It means that purely image-driven methods can hardly work for medical images. In order to find a better solution, one has search on a solution space that is constrained by prior knowledge about the object of interest. In this thesis, I proposed two novel variational algorithms for medical image processing that incorporate knowledge about the structure of interest (vessels, tissues, or bones, etc.) and the imaging modality which is usually known in advance. The first algorithm involved the design of a PDE for curvilinear structure enhancement. Curvilinear structures are targeted as they resemble the image representation of an important organ: blood vessel, which is critical in diagnosis of many injuries in heart, retina, or brain, etc. Here, the prior knowledge is the fact that a vessel has linear elongated structure and a Gaussian proflle across its width (the intensity is highest at the vessel's center and gradually decreased towards its two sides). This is because the blood itself or the contrast agent it carries determines the contrast of the vessel, leading to higher intensity at the vessel's center and lower intensity at its sides. Unlike conventional approaches that use Hessian tensor to detect the elongated structure and suffer from the junction suppression problem, the proposed approach utilizes directional filter bank (DFB). DFB provides more global directional information than the Hessian tensor does. The proposed approach was shown to be able to overcome the junction suppression problem. The second algorithm involved the development of an active contour for inhomogeneous structure segmentation. Here, the prior knowledge resides in the fact that distinct organs shall generate distinct configurations (intensity) in the image. As a result, density function of the foreground (object of interest) should be at far distance from that of the background. Chan-Vese model expresses this "difference" characteristic by only the mean values of the foreground and the background, which is effective for largely homogeneous structures. However, objects in medical images, e.g., bones in CT images, are often inhomogeneous. The proposed model therefore expresses the "difference" characteristic using the whole density function itself and reflects it to the energy functional in the form of a Bhattacharrya distance. Minimization of the proposed energy functional leads to a novel active contour model that can robustly segment inhomogeneous objects. The two proposed models have been extensively evaluated using various synthetic images as well as real medical images such as angiography and CT in comparison with many existing approaches. Experimental results showed that the proposed models provide better performances most of the time.

Simulation of Unsteady Flow Actuation Produced by Surface Plasma Actuator on 2-D Airfoil

Phan Minh Khang 울산대학교 자동차선박기술대학원 2015 국내석사

Effect of flow actuation driven by low current DC surface glow discharge plasma actuator is studied numerically by using OPENFOAM. Numerical model of the source of flow actuation is obtained by physical modeling of ion pressure rise created in DC plasma sheath near the cathode. Modeled plasma flow actuator is tested with NACA0012 airfoil in order to demonstrate the actuation effect in low speed flows. Dynamic situation of the airfoil is obtained by rotating the airfoil within a certain range of angle of attack at a specific rotating speed. In order to simulate the motion of oscillating airfoil, computational domain is split into two parts; far field and near the airfoil. Sliding mesh is applied to a circular domain near the airfoil. To simulate unsteady plasma actuator, plasma actuator is added in Navier Stocke’s equation in term of body force. Simulated plasma actuator is placed on the upper surface of the airfoil at different positions. As the angle of attack changes, flow around the airfoil produces various drag and lift force and dynamic stall may happen. By changing actuation authority according to the change in angle of attach, stabilization of unsteady flow field is achieved and hence constant aerodynamic performance is maintained. The relevant relationship between frequency of plasma actuator and reduced frequency is investigated.