• Communications for Statistical Applications and Methods
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• v.22 no.4
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• pp.321-331
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• 2015

The K-means clustering algorithm is a popular and widely used method for clustering. For covariance matrices, we consider a geodesic clustering algorithm based on the K-means clustering framework in consideration of symmetric positive definite matrices as a Riemannian (non-Euclidean) manifold. This paper considers a geodesic clustering algorithm for data consisting of symmetric positive definite (SPD) matrices, utilizing the Riemannian geometric structure for SPD matrices and the idea of a K-means clustering algorithm. A K-means clustering algorithm is divided into two main steps for which we need a dissimilarity measure between two matrix data points and a way of computing centroids for observations in clusters. In order to use the Riemannian structure, we adopt the geodesic distance and the intrinsic mean for symmetric positive definite matrices. We demonstrate our proposed method through simulations as well as application to real financial data.

• Journal of Mechanical Science and Technology
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• v.16 no.10
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• pp.1314-1319
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• 2002

A mathematical model and control laws for an Electronic-Vacuum Booster (EVB) for application to vehicle cruise control will be presented. Also this paper includes performance test result of EVB and vehicle cruise control experiments. The pressure difference between the vacuum chamber and the apply chamber is controlled by a PWM-solenoid-valve. Since the pressure at the vacuum chamber is identical to that of the engine intake manifold, the output of the electronic-vacuum booster Is sensitive to engine speed. The performance characteristics of the electronic-vacuum booster have been investigated via computer simulations and vehicle tests. The mathematical model of the electronic-vacuum booster developed in this study and a two-state dynamic engine model have been used in the simulations. It has been shown by simulations and vehicle tests that the EVB-cruise control system can provide a vehicle with good distance control performance in both high speed and low speed stop and go driving situations.

• Journal of Power System Engineering
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• v.3 no.2
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• pp.20-25
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• 1999

Experiments were carried out to investigate the characteristics of formaldehyde emission from the small gasoline engine and its reduction technologies. Catalytic converters used are Pt/Rh, Pd/Rh, Pd/Pt, $62cell/cm^2$ monolith type. The measurement of formaldehyde was conducted by using the method of DNPH-GC. From the experimental results, formaldehyde emission increased in a lean mixture due to incomplete combustion of the hydrocarbons. The order of catalytic activity of formaldehyde oxidation was Pt/Rh > Pd/Rh > Pd/Pt. As the distance from the exhaust manifold to the inlet of the catalyst became far, in spite of lower catalyst temperature, formaldehyde concentration decreased because of the adsorption of formaldehyde.

• International Journal of CAD/CAM
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• v.7 no.1
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• pp.103-112
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• 2007

This paper presents a practical approach for surface reconstruction from unoriented point clouds. Instead of estimating local surface orientation, we first generate a set of depth images from the input point clouds, and a coarse mesh is then generated based on them by space carving techniques. The resultant mesh is progressively refined by local mesh refinement and optimization according to surface distance measure. A manifold mesh approximating the input points within an given tolerance is finally obtained. Our approach is easy to implement, but has the ability to outputs high quality meshes in different resolutions. We show that the proposed approach is not sensitive to several types of data disfigurement and is able to reconstruct models robustly from variance input data.

• Industrial Engineering and Management Systems
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• v.12 no.2
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• pp.161-170
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• 2013

Deployment of green transportation in reverse logistics is a key issue for low carbon technologies. To cope with such logistic innovation, this paper proposes a hybrid approach to solve practical vehicle routing problem (VRP) of pickup type that is common when considering the reverse logistics. Noticing that transportation cost depends not only on distance traveled but also on weight loaded, we propose a hierarchical procedure that can design an economically efficient reverse logistics network even when the scale of the problem becomes very large. Since environmental concerns are of growing importance in the reverse logistics field, we need to reveal some prospects that can reduce $CO_2$ emissions from the economically optimized VRP in the same framework. In order to cope with manifold circumstances, the above idea has been deployed by extending the Weber model to the generalized Weber model and to the case with an intermediate destination. Numerical experiments are carried out to validate the effectiveness of the proposed approach and to explore the prospects for future green reverse logistics.

• The Journal of the Convergence on Culture Technology
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• v.5 no.1
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• pp.385-388
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• 2019

Considering spherically symmetric spacetimes embedded in a 5-dimensional static Lorentzian manifold, within the large distance limit of DGP model, we study null geodesic equations. We discuss possible relations of particles following the geodesics with the gravitational waves detected recently, in comparison with the electromagnetic waves propagaing in these brane spacetimes.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.05a
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• pp.162-163
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• 2018

A risk assessment is performed at the initial design stage of LNG-fuelled ships subject to new fuel supply systems due to marine environmental and emissions regulations. Risk assessment involves a series of logical steps that enable systematic risk analysis and evaluation. LNG-fuelled ships mainly consist of a tank for storing LNG, a gas supply unit for supplying LNG to the engine, an engine using LNG as fuel, and a bunkering manifold for receiving LNG. The components of the LNG fuelled ship are determined according to the characteristics, size, rout, and operating distance. Therefore, the risk factors of each ships are different, and the risk analysis also changes. In this study we consider the systems of ships using LNG as a fuel and analyze the risk assessment of certain cases where the actual risk assessment has been carried out.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2991-3007
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• 2022

Two dimensional locality preserving projections (2D-LPP) is an improved algorithm of 2D image to solve the small sample size (SSS) problems which locality preserving projections (LPP) meets. It's able to find the low dimension manifold mapping that not only preserves local information but also detects manifold embedded in original data spaces. However, 2D-LPP is simple and elegant. So, inspired by the comparison experiments between two dimensional linear discriminant analysis (2D-LDA) and linear discriminant analysis (LDA) which indicated that matrix based methods don't always perform better even when training samples are limited, we surmise 2D-LPP may meet the same limitation as 2D-LDA and propose a novel matrix exponential method to enhance the performance of 2D-LPP. 2D-MELPP is equivalent to employing distance diffusion mapping to transform original images into a new space, and margins between labels are broadened, which is beneficial for solving classification problems. Nonetheless, the computational time complexity of 2D-MELPP is extremely high. In this paper, we replace some of matrix multiplications with multiple multiplications to save the memory cost and provide an efficient way for solving 2D-MELPP. We test it on public databases: random 3D data set, ORL, AR face database and Polyu Palmprint database and compare it with other 2D methods like 2D-LDA, 2D-LPP and 1D methods like LPP and exponential locality preserving projections (ELPP), finding it outperforms than others in recognition accuracy. We also compare different dimensions of projection vector and record the cost time on the ORL, AR face database and Polyu Palmprint database. The experiment results above proves that our advanced algorithm has a better performance on 3 independent public databases.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.415-424
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• 2009

As one of the unsupervised learning neural network methods, self-organizing maps(SOM) are applied to various fields. It reduces the dimension of multidimensional data by representing observations on the low dimensional manifold. On the other hand, the minimal spanning tree(MST) of a graph that achieves the most economic subset of edges connecting all components by a single open loop. In this study, we apply the MST technique to SOM with subnodes. We propose SOM's with embedded MST and a distance measure for optimum choice of the size and shape of the map. We demonstrate the method with Fisher's Iris data and a real gene expression data. Simulated data sets are also analyzed to check the validity of the proposed method.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.3
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• pp.83-89
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• 2011

Diesel engines can produce higher fuel efficiency and lower $CO_2$ emission, they are subject to ever more stringent emission regulation. However, there are two major emission concerns fo diesel engines like such as particulate matter (PM) and nitrogen oxides (NOx). Moreover, it is not easy to satisfy the regulations on the emission of NOx and PM, which are getting more strengthened. One of the solutions is to apply the new combustion concept using multistage injection such as HCCI and PCCI. The other solution is to apply after-treatment systems. For example, lean NOx trap catalyst, Urea-SCR and others have various advantages and disadvantages Especially, Urea-SCR system have advantages such as a high conversion efficiency and a wide operation conditions. Hence the key factor to implementation of Urea-SCR technology, good mixing of urea(Ammonia) and gas, reducing Ammonia slip. Urea mixer components are required to facilitate evaporation and mixing because the liquid state of urea poses significant barriers for evaporation, and the distance to mixer is the most critical that affect mixer performance. In this study, to find out the distance from injector to mixer and simulation factor, a laser diagnostics and high speed camera are used to analyze urea injector spray characteristics and to present a distribution of urea solution in transparent manifold In addition, Droplet Uniformity Index is calculated from the acquired images by using image processing method to clarify the distribution of spray.