• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.537-544
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• 2020

Advances in detection techniques, such as mutation and obfuscation, are being advanced with the development of malware technology. In the malware detection technology, unknown malware detection technology is important, and a method for Malware Authorship Attribution that detects an unknown malicious code by identifying the author through distributed malware is being studied. In this paper, we try to extract the compiler information affecting the binary-based author identification method and to investigate the sensitivity of feature selection, probability and non-probability models, and optimization to classification efficiency between studies. In the experiment, the feature selection method through information gain and the support vector machine, which is a non-probability model, showed high efficiency. Among the optimization studies, high classification accuracy was obtained through feature selection and model optimization through the proposed framework, and resulted in 48% feature reduction and 53 faster execution speed. Through this study, we can confirm the sensitivity of feature selection, model, and optimization methods to classification efficiency.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2382-2390
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• 1999

In this paper, we employed a new quantization scheme called sample-adaptive product quantizer (SAPQ) to quantize image data based on the differential pulse code modulation (DPCM) coder, which has fixed length outputs and high bit rates. In order to improve the performance of traditional DPCM coders, the scalar quantizer should be replaced by the vector quantizer (VQ). As the bit rate increases, it will be nearly impossible to implement a conventional VQ or modified VQ, such as the tree-structured VQ, even if the modified VQ can significantly reduce the encoding complexity. SAPQ has a form of the feed-forward adaptive scalar quantizer having a short adaptation period. However, since SAPQ is a structurally constrained VQ, SAPQ can achieve VQ-level performance with a low encoding complexity. Since SAPQ has a scalar quantizer structure, by using the traditional scalar value predictors, we can easily apply SAPQ to DPCM coders. For synthetic data and real images, by employing SAPQ as the quantizer part of DPCM coders, we obtained a 2~3 dB improvement over the DPCM coders, which are based on the Lloyd-Max scalar quantizers, for data rates above 4 b/point.

• Journal of Energy Engineering
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• v.23 no.4
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• pp.263-271
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• 2014

Corrective thermal performance analysis is required for thermal power plants to determine performance status of turbine cycle. We developed classification method for main feed water flow to make precise correction for performance analysis based on ASME (American Society of Mechanical Engineers) PTC (Performance Test Code). The classification is based on feature identification of status of main water flow. Also we developed predictive algorithms for corrected main feed-water through Support Vector Machine (SVM) Model for each classified feature area. The results was compared to estimations using Neural Network(NN) and Kernel Regression(KR). The feature classification and predictive model of main feed-water flow provides more practical methods for corrective thermal performance analysis of turbine cycle.

• The Journal of the Acoustical Society of Korea
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• v.19 no.4
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• pp.37-44
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• 2000

In this paper, we described the real-time implementation effort of MPEG-4 audio HVXC (Harmonic Vector eXcitation Coding) algorithm for very low bitrates, which has target applications from mobile communications to Internet telephony, on current high performance floating point TMS320C6701 DSP. We adopted a hardware structure for real-time operation. In order for software optimization, we used C- and assembly-language level optimizations for time-critical functional codes. Utilizing the internal program memory of the DSP as the program cache, the internal data memory overlap technique and DMA functionality, we could get a goal of realtime operation of HVXC codec both at 2 kbit/s and at 4 kbit/s. For an encoder at 2 kbit/s, the optimization ratio to original code is about 96 %. Finally, we got the subjective quality of MOS 2.45 at 2 kbit/s from an informal quality test.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.4A
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• pp.330-335
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• 2002

In the direct sequence code division multiple access system, the problem of multiple access interference due to multiple access is generated. A interference cancelling receiver is used to solve this problem. The conventional interference cancelling receiver is structure of successive interference canceller using antenna array. In this structure, the difference of between method I and method II depends on updating weight vector. In this paper, the adaptive blind CMA array interference cancelling receiver using cost function of constant modulus algorithms is proposed to update weight vector at conventional structure. The simulation compared the proposed interference cancelling receiver with two conventional interference cancelling receivers by signal to interference ratio and bit error rate curve under additive white Gaussian noise environment. The simulation results show that the proposed receiver has about the gain of SIR of 1.5[dB] more than method I which is conventional receiver at SIR curve, and about the gain of SIR of 0.5(dB) more than method II. In BER curve, the proposed IC receiver about the gain of SNR of 2[dB] more than method I and about the gain of SNR of 0.5[dB] more than method If, Thus, the proposed interference cancelling receiver has the higher performance than conventional interference cancelling receivers.

• The Transactions of the Korea Information Processing Society
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• v.2 no.5
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• pp.619-625
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• 1995

This paper constructs a feed-forward learning complex algorithm which replaced by the backpropagation learning. This algorithm first attempts to organize the pattern vectors into clusters by Generalized Learning Vector Quantization(GLVQ) clustering algorithm(Nikhil R. Pal et al, 1993), second, regroup the pattern vectors belonging to different clusters, and the last, recognize into regrouping pattern vectors by single layer perceptron. Because this algorithm is feed-forward learning algorithm, time is less than backpropagation algorithm and the recognition rate is increased. We use 250 ASCII code bit patterns that is normalized to 16$\times$8. As experimental results, when 250 patterns devide by 10 clusters, average iteration of each cluster is 94.7, and recognition rate is 100%.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.2
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• pp.49-59
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• 2007

This paper is about an system which can perform automatic semantic annotation to actualize "Semantic Web." Since it is impossible to tag numerous documents manually in the web, it is necessary to gather large Korean web documents as training data, and extract features by using natural language techniques and a thesaurus. After doing these, we constructed concept classifiers through the SVM (support vector machine) teaming algorithm. According to the characteristics of Korean language, morphological analysis and syntax analysis were used in this system to extract feature information. Based on these analyses, the concept code is mapped with Kadokawa thesaurus, which made it possible to map similar words and phrase to one concept code, to make training vectors. This contributed to rise the recall of our system. Results of the experiment show the system has a some possibility of semantic annotation.

• Journal of Korea Multimedia Society
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• v.15 no.4
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• pp.485-491
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• 2012

This paper proposes 'Coding Unit Tree' based on quadtree efficiently with motion vector to represent splitting information of a Coding Unit (CU) in HEVC. The new international video coding, High Efficiency Video Coding (HEVC), adopts various techniques and new unit concept: CU, Prediction Unit (PU), and Transform Unit (TU). The basic coding unit, CU is larger than macroblock of H.264/AVC and it splits to process image-based quadtree with a hierarchical structure. However, in case that there are complex motions in CU, the more signaling bits with motion information need to be transmitted. This structure provides a flexibility and a base for a optimization, but there are overhead about splitting information. This paper analyzes those signals and proposes a new algorithm which removes those redundancy. The proposed algorithm utilizes a type code, a dominant value, and residue values at a node in quadtree to remove the addition bits. Type code represents a structure of an image tree and the two values represent a node value. The results show that the proposed algorithm gains 13.6% bit-rate reduction over the HM-1.0.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.2
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• pp.9-16
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• 2012

In this paper, the beamforming and user scheduling scheme for device-to-device (D2D) underlaying celullar networks with partial channel state information is investigated. In the proposed scheme, cellular users whose channels are nearly orthogonal to the channel between base station and D2D receiver are selected for unitary beamforming so as to minimize the interference to the D2D receiver. The interference caused by underlaying D2D communication can be minimized by reducing the D2D transmitter's transmission power. To enhance the cellular users' throughput further, we also investigate codebook generation method in which each code vector belongs to multiple unitary code matrices. From simulation results, we show that the proposed beamforming and user scheduling scheme mitigates D2D interference to the cellular networks and the codebook generation method improves cellular users' throughput.

• Journal of Korea Game Society
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• v.17 no.6
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• pp.113-120
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• 2017

With the development of virtual reality technology, in recent years, user-friendly hand gesture interface has been more studied for natural interaction with a virtual 3D object. Most earlier studies on the hand-gesture interface are using relatively simple hand gestures. In this paper, we suggest an intuitive hand gesture interface for interaction with 3D object in the virtual reality applications. For hand gesture recognition, first of all, we preprocess various hand data and classify the data through the binary decision tree. The classified data is re-sampled and converted to the chain-code, and then constructed to the hand feature data with the histograms of the chain code. Finally, the input gesture is recognized by MCSVM-based machine learning from the feature data. To test our proposed hand gesture interface we implemented a 'Virtual Block' game. Our experiments showed about 99.2% recognition ratio of 16 kinds of command gestures and more intuitive and user friendly than conventional mouse interface.