• Convergence Security Journal
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• v.23 no.1
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• pp.117-123
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• 2023

To detect advanced ransomware attacks with machine learning-based models, the classification model must train learning data with high-dimensional feature space. And in this case, a 'curse of dimension' phenomenon is likely to occur. Therefore, dimensionality reduction of features must be preceded in order to increase the accuracy of the learning model and improve the execution speed while avoiding the 'curse of dimension' phenomenon. In this paper, we conducted classification of ransomware by applying three machine learning models and two feature extraction techniques to two datasets with extremely different dimensions of feature space. As a result of the experiment, the feature dimensionality reduction techniques did not significantly affect the performance improvement in binary classification, and it was the same even when the dimension of featurespace was small in multi-class clasification. However, when the dataset had high-dimensional feature space, LDA(Linear Discriminant Analysis) showed quite excellent performance.

• Journal of KIISE:Software and Applications
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• v.36 no.11
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• pp.960-966
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• 2009

A manifold is used to represent a relationship between high-dimensional data samples in low-dimensional space. In human pose estimation, it is created in low-dimensional space for processing image and 3D body configuration data. Manifold learning is to build a manifold. But it is vulnerable to silhouette variations. Such silhouette variations are occurred due to view-change, person-change, distance-change, and noises. Representing silhouette variations in a single manifold is impossible. In this paper, we focus a silhouette variation problem occurred by view-change. In previous view invariant pose estimation methods based on manifold learning, there were two ways. One is modeling manifolds for all view points. The other is to extract view factors from mapping functions. But these methods do not support one by one mapping for silhouettes and corresponding body configurations because of unsupervised learning. Modeling manifold and extracting view factors are very complex. So we propose a method based on triple manifolds. These are view manifold, pose manifold, and body configuration manifold. In order to build manifolds, we employ biased manifold learning. After building manifolds, we learn mapping functions among spaces (2D image space, pose manifold space, view manifold space, body configuration manifold space, 3D body configuration space). In our experiments, we could estimate various body poses from 24 view points.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.589-596
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• 2008

Performance of a pulsed heat source high temperature inert gas plasma MHD electrical power generator, which can be one of the candidates of space-based laser-to-electrical power converter, is examined by a time dependent two dimensional numerical simulation. In the present MHD generator, the inert gas is assumed to be ideally heated to about $10^4K$ pulsed-likely within short time(${\sim}1{\mu}s$) in a stagnant energy input volume, and the energy of high temperature inert gas is converted to the electricity with the medium of pure inert gas plasma without seeding. The numerical simulation results show that an enthalpy extraction ratio(=electrical output energy/pulsed heat energy) of several tens of % can be achieved, which is the same level as the conventional seeded non-equilibrium plasma MHD generator. Although there still exist many phenomena to be clarified and many problems to be overcome in order to realize the system, the pulsed heat source high temperature inert gas MHD generator is surely worth examining in more detail.

• Nuclear Engineering and Technology
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• v.52 no.12
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• pp.2709-2716
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• 2020

Compositions of large nuclear cores (e.g. boiling water reactors) are highly heterogeneous in terms of fuel composition, control rod insertions and flow regimes. For this reason, they usually lack high order of symmetry (e.g. 1/4, 1/8) making it difficult to estimate their neutronic parameters for large spaces of possible loading patterns. A detailed hyperparameter optimization technique (a combination of manual and Gaussian process search) is used to train and optimize deep neural networks for the prediction of three neutronic parameters for the Ringhals-1 BWR unit: power peaking factors (PPF), control rod bank level, and cycle length. Simulation data is generated based on half-symmetry using PARCS core simulator by shuffling a total of 196 assemblies. The results demonstrate a promising performance by the deep networks as acceptable mean absolute error values are found for the global maximum PPF (~0.2) and for the radially and axially averaged PPF (~0.05). The mean difference between targets and predictions for the control rod level is about 5% insertion depth. Lastly, cycle length labels are predicted with 82% accuracy. The results also demonstrate that 10,000 samples are adequate to capture about 80% of the high-dimensional space, with minor improvements found for larger number of samples. The promising findings of this work prove the ability of deep neural networks to resolve high dimensionality issues of large cores in the nuclear area.

• The Journal of the Korea Contents Association
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• v.8 no.2
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• pp.91-99
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• 2008

When making a comic film, the comic presentation that uses stress and exaggeration is the important subject among other things. In this study we tried to investigate the comic effect using the movement of three-dimensional shot. To conduct this study, we extracted the shot manufactured through the Flow Motion of a 3D Production Program Virtual Camera and a High Speed Motion Picture Camera. The shot manufactured applying this manufacturing skill and using three-dimensional production method for the video contents efficiently made was classified into several scenes. The focus of this study is to search for the factor that makes the atmosphere of a story comic through three-dimensional production shot. According to the shot analysis, three-dimensional production method plays a role in developing more stories on space and time by visualizing stories in three dimensions, which makes the most use of the movement of camera, lens and the utilization of focus. In addition, in the presentation where many comic and exaggerated factors are provided, we used the technology that stresses a scene using the size of a shot and the lasting time and presented the method that exaggerates space using a 3D Production Program Virtual Camera and a High Speed Motion Picture Camera. By reviewing the qualitative improvement and the efficient method on making comic films through the possibility that the atmosphere of this three-dimensional shot can apply to the effect for comic presentation, we tried to approach the comic presentation.

• Proceedings of the Korean Printing Society Conference
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• 2000.12b
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• pp.17-28
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• 2000

Recently, as the prepress mainstream is changed to the digital workflow, various digital proofing systems such as high price dye sublimation printers and low price ink jet printers are widely used in printing industry. However, most of the digital proofing devices have lower resolutions than analog proofing systems and differ with actual color presses in the color gamuts. Therefore, proper color compensations are needed for digital color proofing in order to match color between the proofs and the press sheets. In this paper, we used 3-dimensional look-up table(LUT) and tetrahedral interpolation method for the color space conversion between the device independent color space(CIEXYZ or Lab) and the device dependent color space(CMY) to reduce the color differences between the original copy and digital color proofs and the press sheets.

• Journal of information and communication convergence engineering
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• v.7 no.3
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• pp.304-308
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• 2009

This paper proposes a new concept of a signal constellation of the recently introduced half-symbol-rate-carrier phase-shift keying (HSRC-PSK) modulations for bandwidth-efficient high speed data communications. Since the HSRC-PSK modulations contain different symbol energies representing the same bit sequences due to the loss of orthogonality of their HSRC signals, it is very hard to represent the symbol using the conventional signal constellation. To resolve the problem, two different energies are assigned to represent one symbol for the HSRC offset quadrature phase shift keying (OQPSK) modulation. Similarly, the different energies exist to display the different symbol for HSRC minimum shift keying (MSK) modulation. With the proposed signal space representation, HSRC-PSK symbol can easily be shown with a two-dimensional scatter plot which provides helpful information of evaluating HSRC-PSK signal's quality.

• Journal of Information Processing Systems
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• v.12 no.4
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• pp.591-611
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• 2016

High dimensional space is the biggest problem when classification process is carried out, because it takes longer time for computation, so that the costs involved are also expensive. In this research, the facial space generated from homogeneous and non-homogeneous polynomial was proposed to extract the facial image features. The homogeneous and non-homogeneous polynomial-based eigenspaces are the second opinion of the feature extraction of an appearance method to solve non-linear features. The kernel trick has been used to complete the matrix computation on the homogeneous and non-homogeneous polynomial. The weight and projection of the new feature space of the proposed method have been evaluated by using the three face image databases, i.e., the YALE, the ORL, and the UoB. The experimental results have produced the highest recognition rate 94.44%, 97.5%, and 94% for the YALE, ORL, and UoB, respectively. The results explain that the proposed method has produced the higher recognition than the other methods, such as the Eigenface, Fisherface, Laplacianfaces, and O-Laplacianfaces.

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.83-90
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• 2004

In this paper, we study the CCD(Clustering with Circular Distance) and the COD(Clustering with Obstructed Distance) problems to be considered when objects are being clustered in a circularly search space and a search space with the presence of obstacles. We also propose a now clustering algorithm for clustering efficiently objects that the insertion or the deletion is occurring frequently in multi-dimensional search space. The distance function for solving the CCD and COD Problems is defined in the Proposed clustering algorithm. This algorithm is included a clustering method to create clusters that have a high spatial locality by minimum computation time.

• International Journal of High-Rise Buildings
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• v.4 no.2
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• pp.153-160
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• 2015

As the predominant mode of vertical urban development in China, mixed-use complexes provide the optimal case for the research of sustainable and vertical urbanism. This paper reviews three typical mixed-use complexes with various vertical space systems in Shanghai via the combination of field observation, questionnaires and software analysis. It then proceeds to determine which vertical space system is most effective for encouraging sustainable vertical urban development from the perspective of spatial efficiency. Finally, it concludes with an evaluation of the relative capabilities of the design features of a mixed-use complex: to create external dimensional-connections, to create multiple internal connections, and to organize overall composite functions.