• Phonetics and Speech Sciences
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• v.4 no.3
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• pp.119-125
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• 2012

This paper describes a new algorithm for encoding spectral shape and envelope in the generic mode of G.718 super-wide band (SWB). In the G.718 SWB coder, generic mode coding and sinusoidal enhancement are used for the quantization of modified discrete cosine transform (MDCT)-based parameters in the high frequency band. In the generic mode, the high frequency band is divided into sub-bands and for every sub-band the most similar match with the selected similarity criteria is searched from the coded and envelope normalized wideband content. In order to improve the quantization scheme in high frequency region of speech/audio signals, the modified generic mode by the improvement of the generic mode in G.718 SWB is proposed. In the proposed generic mode, perceptual vector quantization of spectral envelopes and the resolution increase for spectral copy are used. The performance of the proposed algorithm is evaluated in terms of objective quality. Experimental results show that the proposed algorithm increases the quality of sounds significantly.

• Speech Sciences
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• v.10 no.2
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• pp.15-25
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• 2003

In this paper, we propose an algorithm on OOV(Out-of-Vocabulary) rejection based on two-stage method. In the first stage, the algorithm rejects OOVs using generic word model, and then in the second stage, for further reduction of false acceptance, it rejects words which have low similarity to the candidate by measuring the distance between HMM models. For the experiment, we choose 20 in-vocabulary words out of PBW445 DB distributed by ETRI. In case that the first stage is processed only, the false acceptance is 3% with 100% correct acceptance, and in case both stages are processed, the false acceptance is reduced to 1% with 100% correct acceptance.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.8
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• pp.1187-1193
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• 2013

In this paper, we present realistic 3D head modeling and facial expression systems. For 3D head modeling, we perform generic model fitting to make individual head shape and texture mapping. To calculate the deformation function in the generic model fitting, we determine correspondence between individual heads and the generic model. Then, we reconstruct the feature points to 3D with simultaneously captured images from calibrated stereo camera. For texture mapping, we project the fitted generic model to image and map the texture in the predefined triangle mesh to generic model. To prevent extracting the wrong texture, we propose a simple method using a modified interpolation function. For generating 3D facial expression, we use the vector muscle based algorithm. For more realistic facial expression, we add the deformation of the skin according to the jaw rotation to basic vector muscle model and apply mass spring model. Finally, several 3D facial expression results are shown at the end of the paper.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.56-62
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• 2021

The surge in generic attacks execution against cipher text on the computer network has led to the continuous advancement of the mechanisms to protect information integrity and confidentiality. The implementation of explicit decision tree machine learning algorithm is reported to accurately classifier generic attacks better than some multi-classification algorithms as the multi-classification method suffers from detection oversight. However, there is a need to improve the accuracy and reduce the false alarm rate. Therefore, this study aims to improve generic attack classification by implementing two hybridized decision tree algorithms namely Naïve Bayes Decision tree (NBTree) and Logistic Model tree (LMT). The proposed hybridized methods were developed using the 10-fold cross-validation technique to avoid overfitting. The generic attack detector produced a 99.8% accuracy, an FPR score of 0.002 and an MCC score of 0.995. The performances of the proposed methods were better than the existing decision tree method. Similarly, the proposed method outperformed multi-classification methods for detecting generic attacks. Hence, it is recommended to implement hybridized decision tree method for detecting generic attacks on a computer network.

• Journal of Digital Contents Society
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• v.15 no.3
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• pp.373-380
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• 2014

Malicious codes uses generic unpacking technique to make it hard for analyzers to detect their programs. Recently their has been several researches about generic packet to prevent or detect these techniques. And they try to focus on the codes that repeats while generic packing is doing compression because generic packing technique executes after it is decompressed. And they try to focus on the codes that repeats while generic packing is doing compression because generic packing technique executes after it is decompressed. Therefore, this makes a interesting performance which shows a similar address value from the codes which are repeated several times what is different from the normal program codes. By dividing these codes into regularly separated areas we can find that the generic unpacking codes have a small entropy value compared to normal codes. Using this method, it is possible to identify any program if it is a generic unpacking code or not even though we do not know what kind of algorithm it uses. This paper suggests a way of disarming the generic codes by using the low value entropy value which comes out from the Opcode addresses when generic unpacking codes try to decompress.

• Journal of the Korea Society of Computer and Information
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• v.10 no.3 s.35
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• pp.19-34
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• 2005

The difficulties in implementing of image processing algorithms are a major reason for the lack of research into algorithm comparison. This fact makes an image processing research with difficult. We conclude that it is important to represent algorithms in form of reusable code. Since current image processing systems do not fulfill all requirements we must pose on reusable implementations, we propose to solve the reuse problem by applying generic programming. We define two dimensional iterators, which mediate between image processing algorithms and their underlying data structures, so that the same algorithm implementation can be applied to any number of different image formats. The elegance and efficiency of this approach is illustrated by a number of useful examples and demonstrated by porting in existing image processing algorithm IDE(Integrated Development Environment).

• Journal of Advanced Navigation Technology
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• v.23 no.1
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• pp.77-83
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• 2019

In this paper, we propose an object tracking algorithm based on color histogram and convolutional neural network model. In order to increase the tracking accuracy, we synthesize generic object tracking using regression network algorithm which is one of the convolutional neural network model-based tracking algorithms and a mean-shift tracking algorithm which is a color histogram-based algorithm. Both algorithms are classified through support vector machine and designed to select an algorithm with higher tracking accuracy. The mean-shift tracking algorithm tends to move the bounding box to a large range when the object tracking fails, thus we improve the accuracy by limiting the movement distance of the bounding box. Also, we improve the performance by initializing the tracking start positions of the two algorithms based on the average brightness and the histogram similarity. As a result, the overall accuracy of the proposed algorithm is 1.6% better than the existing generic object tracking using regression network algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.418-422
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• 2005

In this paper, a novel algorithm capable of detecting generic obstacles on a flat surface is proposed. The algorithm fundamentally exploits a distortion phenomena taken place in remapping process of original stereo images to a virtual top-view. Based on the distortion phenomena, we construct stereo polar histograms of edge maps, detect peaks on them, and search for matched peaks on both histograms using a Dynamic Programming (DP). Eventually, the searched corresponding peaks lead to estimate obstacles' positions. The advantages of the proposed algorithm are that it is not largely affected by an intensity difference between a pair of stereo images and does not depend on the typical stereo matching methodologies. Furthermore, the algorithm identifies the obstacles' positions quite robustly.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.25-32
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• 2023

Decision-making refers to identifying the best alternative among a set of alternatives. When a set of criteria are involved, the decision-making is called multi-criteria decision-making (MCDM). In some cases, the involved criteria may be prioritized by the human decision-maker, which determines the importance degree for each criterion; hence, the decision-making becomes prioritized multi-criteria decision-making. The essence of prioritized MCDM is raking the different alternatives concerning the criteria and selecting best one(s) from the ranked list. This paper introduces a generic multi-level algorithm for ranking multiple alternatives in prioritized MCDM problems. The proposed algorithm is implemented by a decision support system for selecting the most critical short-road requests presented to the transportation ministry in the Kingdom of Saudi Arabia. The ranking results show that the proposed ranking algorithm achieves a good balance between the importance degrees determined by the human decision maker and the score value of the alternatives concerning the different criteria.

• Structural Engineering and Mechanics
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• v.34 no.5
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• pp.597-609
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• 2010

A problem formulation and solution methodology for design optimization of laminated thin-walled composite beams of generic section is presented. Objective functions and constraint equations are given in the form of beam stiffness. For two different problems one for open section and the other for closed section, the objective function considered is bending stiffness about x-axis. Depending upon the case, one can consider bending, torsional and axial stiffnesses. The different search and optimization algorithm, known as Evolution Strategies (ES) has been applied to find the optimal fibre orientation of composite laminates. A multi-level optimization approach is also implemented by narrowing down the size of search space for individual design variables in each successive level of optimization process. The numerical results presented demonstrate the computational advantage of the proposed method "Evolution strategies" which become pronounced to solve optimization of thin-walled composite beams of generic section.