• 한국운동역학회지
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• 제31권3호
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• pp.199-204
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• 2021

Objective: The purpose of this study was to present a new idea of methodology to evaluate Poomsae performance using inertial measurement unit (IMU) sensors in terms of signal processing techniques. Method: Ten collegian Taekwondo athletes, consisting of five Poomsae elite athletes (age: 21.4 ± 0.9 years, height: 168.4 ± 11.3 cm, weight: 65.0 ± 10.6 kg, experience: 12 ± 0.7 years) and five breaking demonstration athletes (age: 21.0 ± 0.0 years, height: 168.4 ± 4.7 cm, weight: 63.8 ± 8.2 kg, experience: 13.0 ± 2.1 years), voluntarily participated in this study. They performed three different black belt Poomsae such as Goryeo, Geumgang, and Taebaek Poomsae repeatedly twice. Repeated measured motion data on the wrist and ankle were calculated by the methods of cosine similarity and Euclidean distance. Results: The Poomsse athletes showed superior performance in terms of temporal consistency at Goryeo and Taebaek Poomsae, cosine similarity at Geumgang and Taebaek Poomsae, and Euclidian distance at Geumgang Poomsae. Conclusion: IMU sensor would be a useful tool for monitoring and evaluating within-subject temporal variability of Taekwondo Poomsae motions. As well it distinguished spatiotemporal characteristics among three different Poomsae.

• 한국음향학회지
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• 제31권4호
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• pp.266-272
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• 2012

화자 분할 기술은 오디오 데이터로부터 자동적으로 화자 경계 구간을 검출하는 것이다. 화자 분할 방식은 화자에 대한 선행 지식 사용 여부에 따라 거리기반 방식과 모델기반 방식으로 나누어진다. 본 논문에서는 eigenvoice 기반의 화자가중치 거리를 이용한 화자 분할 방식을 도입하고, 이 방식을 대표적인 거리 기반 방식들과 비교한다. 또한, 화자가중치의 거리 측정 함수로 유클리드 거리와 cosine 유사도를 사용하여 화자 분할 성능을 비교하고, eigenvoice 방식에 의해 화자 적응된 모델들 사이의 직접적인 거리를 이용한 화자 분할 방식과의 비교를 통해 화자가중치 거리를 이용한 방식이 계산량면에서 효율적인 점을 검증한다.

• Journal of Information Processing Systems
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• 제20권2호
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• pp.185-199
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• 2024

In this paper, an improved automated spectral clustering (IASC) algorithm is proposed to address the limitations of the traditional spectral clustering (TSC) algorithm, particularly its inability to automatically determine the number of clusters. Firstly, a cluster number evaluation factor based on the optimal clustering principle is proposed. By iterating through different k values, the value corresponding to the largest evaluation factor was selected as the first-rank number of clusters. Secondly, the IASC algorithm adopts a density-sensitive distance to measure the similarity between the sample points. This rendered a high similarity to the data distributed in the same high-density area. Thirdly, to improve clustering accuracy, the IASC algorithm uses the cosine angle classification method instead of K-means to classify the eigenvectors. Six algorithms-K-means, fuzzy C-means, TSC, EIGENGAP, DBSCAN, and density peak-were compared with the proposed algorithm on six datasets. The results show that the IASC algorithm not only automatically determines the number of clusters but also obtains better clustering accuracy on both synthetic and UCI datasets.

• 동력기계공학회지
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• 제21권6호
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• pp.5-12
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• 2017

The steady-state, incompressible and three-dimensional numerical analysis was carried out to investigate the internal flow fields characteristics according to wind tunnel contraction type. The turbulence model used in this study is a realizable $k-{\varepsilon}$ modified from the standard $k-{\varepsilon}$ model. As a results, the distribution of the axial mean velocity components along the central axis of the flow model is very similar to the ASME and BE types, and the cubic and cosine types. When the flow passes through the interior space of the analytical models, the flow resistance at the inlet of the plenum chamber is the largest at BS type contraction, but the smallest at cubic type contraction. The boundary layer thickness is the smallest in the cosine type contraction as the axial distance increases. The maximum turbulent kinetic energy in the test section is the smallest in the order of the contraction of cubic type and cosine type. Comprehensively, cubic type contraction is the best choice for wind tunnel performance, and cosine type contraction can be the next best solution.

• 한국전기전자재료학회논문지
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• 제27권3호
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• pp.162-166
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• 2014

We propose an analysis method of an autostereoscopic display system with lenticular lens array using finite ray-tracing method that is verified by the geometrical optics. In the present work, we adopt the cylinder equation for the mathematical expression of the lenticular lens. For the calculation of the direction cosine of the transmitted ray, we first calculate the refracting point at bottom of the lens and the direction cosine of the incident ray that propagating through the lens by the Snell's law, and then apply to finite ray-tracing method. Finally, we obtain the simulation results for the intensity distribution of the ray at optimal viewing distance. From these results, we confirm the realization of 3D image that exists separately according to the viewing position at an optimal viewing distance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권6호
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• pp.2098-2114
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• 2021

Light intensity variation is one of the key factors which affect the accuracy of vehicle face re-identification, so in order to improve the robustness of vehicle face features to light intensity variation, a Nonnegative Matrix Factorization model with the constraint of image acquisition time difference is proposed. First, the original features vectors of all pairs of positive samples which are used for training are placed in two original feature matrices respectively, where the same columns of the two matrices represent the same vehicle; Then, the new features obtained after decomposition are divided into stable and variable features proportionally, where the constraints of intra-class similarity and inter-class difference are imposed on the stable feature, and the constraint of image acquisition time difference is imposed on the variable feature; At last, vehicle face matching is achieved through calculating the cosine distance of stable features. Experimental results show that the average False Reject Rate and the average False Accept Rate of the proposed algorithm can be reduced to 0.14 and 0.11 respectively on five different datasets, and even sometimes under the large difference of light intensities, the vehicle face image can be still recognized accurately, which verifies that the extracted features have good robustness to light variation.

• Journal of Information Processing Systems
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• 제19권1호
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• pp.17-32
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• 2023

Centralized hierarchical routing protocols are often used to solve the problems of uneven energy consumption and short network life in wireless sensor networks (WSNs). Clustering and cluster head election have become the focuses of WSNs. In this paper, an energy balanced clustering routing algorithm optimized by sine cosine algorithm (SCA) is proposed. Firstly, optimal cluster head number per round is determined according to surviving node, and the candidate cluster head set is formed by selecting high-energy node. Secondly, a random population with a certain scale is constructed to represent a group of cluster head selection scheme, and fitness function is designed according to inter-cluster distance. Thirdly, the SCA algorithm is improved by using monotone decreasing convex function, and then a certain number of iterations are carried out to select a group of individuals with the minimum fitness function value. From simulation experiments, the process from the first death node to 80% only needs about 30 rounds. This improved algorithm balances the energy consumption among nodes and avoids premature death of some nodes. And it greatly improves the energy utilization and extends the effective life of the whole network.

• Journal of Information Processing Systems
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• 제12권3호
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• pp.392-409
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• 2016

The aim of this paper is to examine the effectiveness of combining three popular tools used in pattern recognition, which are the Active Appearance Model (AAM), the two-dimensional discrete cosine transform (2D-DCT), and Kernel Fisher Analysis (KFA), for face recognition across age variations. For this purpose, we first used AAM to generate an AAM-based face representation; then, we applied 2D-DCT to get the descriptor of the image; and finally, we used a multiclass KFA for dimension reduction. Classification was made through a K-nearest neighbor classifier, based on Euclidean distance. Our experimental results on face images, which were obtained from the publicly available FG-NET face database, showed that the proposed descriptor worked satisfactorily for both face identification and verification across age progression.

• 컴퓨터교육학회논문지
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• 제7권5호
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• pp.111-120
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• 2004

영상의 칼라, 텍스쳐, 오브젝트의 형체 등과 같은 하위 수준의 특징을 표현할 수 있는 기술자를 MPEG-7 표준에서 규정하고 있다. 하지만, 각각의 기술자를 따로 분석함으로써는 성능 향상에 불충분한 점이 있었다. 본 논문에서는 칼라 기술자와 텍스쳐 기술자를 결합하여 영상검색의 성능을 향상시키는 방법을 제안한다. MPEG-7 표준에서 정의한 $l_{1}$-norm방법보다, 본 논문에서는 칼라 히스토그램의 경우 코사인 근사도 계수를, 에지 히스토그램의 경우 유클리디언 디스턴스를 적용 실험하여 진일보한 결과를 도출할 수 있었다.

• International Journal of Computer Science & Network Security
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• 제22권1호
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• pp.139-148
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• 2022

Research into wireless sensor networks (WSNs) is a trendy issue with a wide range of applications. With hundreds to thousands of nodes, most wireless sensor networks interact with each other through radio waves. Limited computational power, storage, battery, and transmission bandwidth are some of the obstacles in designing WSNs. Clustering and routing procedures have been proposed to address these concerns. The wireless sensor network's most complex and vital duty is routing. With the Greedy Perimeter Stateless Routing method (GPSR), an efficient and responsive routing protocol is built. In packet forwarding, the nodes' locations are taken into account while making choices. In order to send a message, the GPSR always takes the shortest route between the source and destination nodes. Weighted directed graphs may be constructed utilising four distinct distance metrics, such as Euclidean, city block, cosine, and correlation distances, in this study. NS-2 has been used for a thorough simulation. Additionally, the GPSR's performance with various distance metrics is evaluated and verified. When compared to alternative distance measures, the proposed GPSR with correlation distance performs better in terms of packet delivery ratio, throughput, routing overhead and average stability time of the cluster head.