• ETRI Journal
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• 제37권3호
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• pp.512-522
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• 2015

Recent developments in identity-based cryptography (IBC) have provided new solutions to problems related to the security of mobile ad hoc networks (MANETs). Although many proposals to solve problems related to the security of MANETs are suggested by the research community, there is no one solution that fits all. The interdependency cycle between secure routing and security services makes the use of IBC in MANETs very challenging. In this paper, two novel methods are proposed to eliminate the need for this cycle. One of these methods utilizes a key pool to secure routes for the distribution of cryptographic materials, while the other adopts a pairing-based key agreement method. Furthermore, our proposed methods utilize threshold cryptography for shared secret and private key generation to eliminate the "single point of failure" and distribute cryptographic services among network nodes. These characteristics guarantee high levels of availability and scalability for the proposed methods. To illustrate the effectiveness and capabilities of the proposed methods, they are simulated and compared against the performance of existing methods.

• Journal of Electrical Engineering and Technology
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• 제12권3호
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• pp.989-995
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• 2017

As is known to all that the output of wind power generation has a character of randomness and volatility because of the influence of natural environment conditions. At present, the research of wind power prediction mainly focuses on point forecasting, which can hardly describe its uncertainty, leading to the fact that its application in practice is low. In this paper, a wind power range prediction model based on the multiple output property of BP neural network is built, and the optimization criterion considering the information of predicted intervals is proposed. Then, improved Particle Swarm Optimization (PSO) algorithm is used to optimize the model. The simulation results of a practical example show that the proposed wind power range prediction model can effectively forecast the output power interval, and provide power grid dispatcher with decision.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.2
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• pp.91-96
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• 2006

Presently, cycle-slip detection is done between adjacent two points in many cycle-slip methods. Inherently, it is simple wavelet analysis. A new idea is put forward that the number of difference point can adjust by a parameter factor; we study this method to smooth raw data and detect cycle-slip with wavelet analysis. Taking CHAMP satellite data for example, we get some significant conclusions. It is showed that it is valid to detect cycle-slip in GPS phase measurement based on this wavelet function, and it is helpful to improve the precision of GPS data pre-processing and positioning.

• 정보보호학회논문지
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• 제6권3호
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• pp.23-30
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• 1996

본 논문에서는 Diffie-Hellman 방법을 위성을 이용한 다중 방송통신망에 적용하여 키 분배하는 방법을 제안하고 있다.

• Korean Journal of Mathematics
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• 제10권1호
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• pp.5-10
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• 2002

In this paper, we investigate the prefilter base on a fuzzy set and fuzzy net ${\varphi}$ on the fuzzy topological space (X,${\delta}$). And we show that the prefilter base $\mathcal{B}({\varphi})$ determines by the fuzzy net ${\varphi}$ converge to a fuzzy point $p$ iff the fuzzy net ${\varphi}$ converge to a fuzzy point $p$. Also we prove that if the prefilter base $\mathcal{B}$ converge to a fuzzy point $p$, then the $\mathcal{B}$ has the cluster point $p$.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2019년도 춘계학술발표대회
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• pp.482-484
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• 2019

Learning and analyzing 3D point clouds with deep networks is challenging due to the limited and irregularity of the data. In this paper, we present a data-driven point cloud augmentation technique. The key idea is to learn multilevel features per point and to reconstruct to a similar point set. Our network is applied to a projection loss function that encourages the predicted points to remain on the geometric shapes with a particular target. We conduct various experiments using ShapeNet part data to evaluate our method and demonstrate its possibility. Results show that our generated points have a similar shape and are located closer to the object.

• International Journal of Naval Architecture and Ocean Engineering
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• 제12권1호
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• pp.605-616
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• 2020

The construction quality control of hull blocks is of great significance for shipbuilding. The total station device is predominantly employed in traditional applications, but suffers from long measurement time, high labor intensity and scarcity of data points. In this paper, the Terrestrial Laser Scanning (TLS) device is utilized to obtain an efficient and accurate comprehensive construction information of hull blocks. To address the registration problem which is the most important issue in comparing the measurement point cloud and the design model, an automatic registration approach is presented. Furthermore, to compare the data acquired by TLS device and sparse point sets obtained by total station device, a method for key point extraction is introduced. Experimental results indicate that the proposed approach is fast and accurate, and that applying TLS to control the construction quality of hull blocks is reliable and feasible.

• The Journal of Korean Physical Therapy
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• 제15권3호
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• pp.295-345
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• 2003

This study investigated activation of cerebral cortex in patients with hemiplegia that was caused by neural damage. Key-point control movement therapy of Bobath was performed for 9 weeks in 3 subjects with hemiplegia and fMRI was used to compare and analyze activated degree of cerebral cortex in these subjects. fMRI was conducted using the blood oxygen level-dependent(BOLD) technique at 3.0T MR scanner with a standard head coil. The motor activation task consisted of finger flexion-extension exercise in six cycles(one half-cycles = 8 scans = $3\;sec{\times}\;8\;=\;24\;sec$). Subjects performed this task according to visual stimulus that sign of right hand or left hand twinkled(500ms on, 500ms off). After mapping activation of cerebral motor cortex on hand motor function, below results were obtained. 1. Activation decreased in primary motor area, whereas it increased in supplementary motor area and visual association area(p<.001). 2. Activation was observed in bilateral medial frontal gyrus, middle frontal gyrus of left cerebrum, inferior frontal gyrus, inter-hemispheric, fusiform gyrus of right cerebrum, superior parietal lobule of parietal lobe and precuneus in subjedt 1, parahippocampal gyrus of limbic lobe and cingulate gyrus in subject 2, and inferior frontal gyrus of right frontal lobe, middle frontal gyrus, and inferior parietal lobule of left cerebrum in subject 3 (p<.001). 3. Activation cluster extended in declive of right cellebellum posterior lobe in subject 1, culmen of anterior lobe and declive of posterior lobe in subject 2, and dentate gyrus of anterior lobe, culmen and tuber of posterior lobe in subject 3 (p<.001). In conclusion, these data showed that Key-point control movement therapy of Bobath after stroke affect cerebral cortex activation by increasing efficiency of cortical networks. Therefore mapping of brain neural network activation is useful for plasticity and reorganization of cerebral cortex and cortico-spinal tract of motor recovery mechanisms after stroke.

• 한국측량학회지
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• 제34권5호
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• pp.479-493
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• 2016

항공 레이저 스캐너(ALS)로부터 획득한 라이다(LiDAR) 데이터는 지형지물을 모델링하기 위해서 널리 사용되고 있으며, 특히 정밀 3차원 건축물 및 도시모델, 엄밀정사영상 등 고품질의 공간정보를 효율적으로 구축하기 위하여 라이다 데이터를 이용한 3차원 모델링에 관한 연구가 지속적으로 수행되고 있다. 불규칙적으로 분포된 고밀도의 라이다 데이터로부터 객체를 3차원으로 모델링하기 위해서는 시스템 캘리브레이션, 노이즈 제거 및 지면과 객체를 분리하기 위한 필터링, 객체의 종류 및 특성에 따른 데이터 분류, 기하학적 특성 및 동질성에 기반한 데이터 분할, 분할면의 군집화 및 묘사, 분할면의 재구성과 조합에 의한 모델링, 품질검사 등 일련의 복잡한 과정들이 수반된다. 라이다 데이터를 이용한 많은 모델링 방법들은 데이터 분할 과정을 포함하고 있지만, 본 논문에서는 라이다 데이터를 분할하지 않고 객체를 구성하는 중요하고 대표적인 특징점들을 추출하여 건물 모델링에 활용하는 방법을 제안하고 있다. 복잡하고 다양한 건물 형태를 시뮬레이션한 데이터와 실제 데이터에 적용하여 제안한 방법의 타당성 및 정확도를 검증하였다.

• Journal of Power Electronics
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• 제18권6호
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• pp.1791-1804
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• 2018

To achieve a fast dynamic response and to solve the multi-objective control problems of the output currents, capacitor voltages and system constraints, this paper proposes a deadbeat and hierarchical predictive control with space-vector modulation (DB-HPC-SVM) for five-level nested neutral point piloted (NNPP) converters. First, deadbeat control (DBC) is adopted to track the reference currents by calculating the deadbeat reference voltage vector (DB-RVV). After that, all of the candidate switching sequences that synthesize the DB-RVV are obtained by using the fast SVM principle. Furthermore, according to the redundancies of the switch combination and switching sequence, a hierarchical model predictive control (MPC) is presented to select the optimal switch combination (OSC) and optimal switching sequence (OSS). The proposed DB-HPC-SVM maintains the advantages of DBC and SVM, such as fast dynamic response, zero steady-state error and fixed switching frequency, and combines the characteristics of MPC, such as multi-objective control and simple inclusion of constraints. Finally, comparative simulation and experimental results of a five-level NNPP converter verify the correctness of the proposed DB-HPC-SVM.