• KIPS Transactions on Computer and Communication Systems
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• v.8 no.2
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• pp.35-40
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• 2019

Traditional Malware Detection is susceptible for detecting malware which is modified by polymorphism or obfuscation technology. By learning patterns that are embedded in malware code, machine learning algorithms can detect similar behaviors and replace the current detection methods. Data must collected continuously in order to learn malicious code patterns that change over time. However, the process of storing and processing a large amount of malware files is accompanied by high space and time complexity. In this paper, an HDFS-based distributed processing system is designed to reduce space complexity and accelerate feature extraction time. Using a distributed processing system, we extract two API features based on filtering basis, 2-gram feature and APICFG feature and the generalization performance of ensemble learning models is compared. In experiments, the time complexity of the feature extraction was improved about 3.75 times faster than the processing time of a single computer, and the space complexity was about 5 times more efficient. The 2-gram feature was the best when comparing the classification performance by feature, but the learning time was long due to high dimensionality.

• Journal of Advanced Navigation Technology
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• v.6 no.2
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• pp.138-150
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• 2002

This paper addresses the problem of combining adaptive polarization processing and space-time processing for further performance improvement of radar target detection in clutter and Jammer environments. Since the most straightforward cascade combinations have quite limited performance improvement potentials, we focus on the development of adaptive processing in the joint polarization-space-time domain. Unlike a direct extension of some existing space-time processing algorithms to the joint domain, the processing algorithm developed in this paper does not need a potentially costly polarization filter bank to cover the unknown target polarization parameter. The performance of the new algorithm is derived and evaluated in terms of the probability of detection and the probability of false alarm, and it is compared with other algorithms that do not utilize the polarization information or assume that the target polarization is known.

• Journal of Broadcast Engineering
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• v.17 no.6
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• pp.1048-1060
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• 2012

In this paper, an adaptive temporal and spatial filter (ATSF) based on mean square error (MSE) estimation is proposed. ATSF is a block based de-noising algorithm. Each noisy block is selectively filtered by a temporal filter or a spatial filter. Multi-hypothesis motion compensated filter (MHMCF) and bilateral filter are chosen as the temporal filter and the spatial filter, respectively. Although there is no original video, we mathematically derivate a formular to estimate the real MSE between a block de-noised by MHMCF and its original block and a linear model is proposed to estimate the real MSE between a block de-noised by bilateral filter and its original block. Finally, each noisy block is processed by the filter with a smaller estimated MSE. Simulation results show that our proposed algorithm achieves substantial improvements in terms of both visual quality and PSNR as compared with the conventional de-noising algorithms.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.199-206
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• 2018

This study was to investigate the Influence of smart phone use on gait in healthy adults. Twenty healthy adults were recruited in this study. All subjects performed twice for each normal gait and smart phone gait. The normal gait walked at their chosen speed, and the smart phone gait walked while watching the video. GAITRite system was used to identify the temporal and spatial variables related to the gait pattern during walking. Statistical analysis was analyzed by paired t-test. In comparison of temporal variables, smart phone gait was significantly lower in gait speed and cadence than in normal gait(p<.05), and was significantly longer in single support time and double support time(p<.05). In comparison of spatial variables, smart phone gait was significantly shorter in step length and stride length than in normal gait(p<.05) and significantly longer in step width(p<.05). The results of this study demonstrated that smartphone use can negatively affect the correct gait patterns during walking.

• Journal of the Korea Society of Computer and Information
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• v.16 no.11
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• pp.153-161
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• 2011

As the problem of GOSST building belongs to NP compete domain, heuristics for the problem ask for immense amount execution time and computations in large scale inputs. In this paper, we propose an efficient mechanism for GOSST construction using space locality PTAS. For 40,000 input nodes with maximum weight 100, the proposed space locality PTAS GOSST with 16 unit areas can reduce about 4.00% of connection cost and 89.26% of execution time less than weighted minimum spanning tree method. Though the proposed method increases 0.03% of connection cost more, but cuts down 96.39% of execution time less than approximate GOSST method (SGOSST) without PTAS. Therefore the proposed space locality PTAS GOSST mechanism can work moderately well to many useful applications where a greate number of weighted inputs should be connected in short time with approximate minimum connection cost.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11C
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• pp.929-939
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• 2010

The growth of multimedia technology forces the development of video detection for large database management and illegal copy detection. To meet this demand, this paper proposes a fast video detection method to apply to a large database. The fast video detection algorithm uses spatial features using the gray value distribution from frames and temporal features using the temporal similarity map. We form the video signature using the extracted spatial feature and temporal feature, and carry out a stepwise matching method. The performance was evaluated by accuracy, extraction and matching time, and signature size using the original videos and their modified versions such as brightness change, lossy compression, text/logo overlay. We show empirical parameter selection and the experimental results for the simple matching method using only spatial feature and compare the results with existing algorithms. According to the experimental results, the proposed method has good performance in accuracy, processing time, and signature size. Therefore, the proposed fast detection algorithm is suitable for video detection with the large database.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.2
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• pp.101-111
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• 2021

In general, several computational resources are required to perform multiple-loading transient response analyses. In this paper, we present the procedure for multiple-loading transient response analysis using the Krylov subspace model order reduction and Newmark's time integration scheme. We utilized ANSYS MAPDL, Python, and ANSYS ACT to automate the transient response analysis procedure in the ANSYS Workbench environment and studied several engineering numerical examples to demonstrate the feasibility and efficiency of the proposed approach.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.69-75
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• 2023

Finite field arithmetic operations play an important role in a variety of applications, including modern cryptography and error correction codes. In this paper, we propose an efficient multiplication algorithm over finite fields using the Montgomery multiplication algorithm. Existing multipliers can be implemented using AND and XOR gates, but in order to reduce time and space complexity, we propose an algorithm using NAND and NOR gates. Also, based on the proposed algorithm, an efficient semi-systolic finite field multiplier with low space and low latency is proposed. The proposed multiplier has a lower area-time complexity than the existing multipliers. Compared to existing structures, the proposed multiplier over finite fields reduces space-time complexity by about 71%, 66%, and 33% compared to the multipliers of Chiou et al., Huang et al., and Kim-Jeon. As a result, our multiplier is proper for VLSI and can be successfully implemented as an essential module for various applications.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.62-62
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• 2022

홍수 예보를 위한 강우-유출 분석에서 정확한 예측 강우량 정보는 매우 중요한 인자이다. 이에 따라 강우 예측을 위하여 다양한 연구들이 수행되고 있지만 시·공간적으로 비균일한 특성 또는 변동성을 가진 강우를 정확하게 예측하는 것은 여전히 난제이다. 본 연구에서는 딥러닝 기반 ConvLSTM (Convolutinal Long Short-Term Memory) 모형을 사용하여 위성 강수 자료의 단기 예측을 수행하고 그 정확성을 분석하고자 한다. 대상유역은 메콩강 유역이며, 유역 면적이 넓고 강우 관측소의 밀도가 낮아 시·공간적 강우량 추정에 한계가 있으므로 정확한 강우-유출 분석을 위하여 위성 강수 자료의 활용이 요구된다. 현재 TRMM, GSMaP, PERSIANN 등 많은 위성 강수 자료들이 제공되고 있으며, 우선적으로 ConvLSTM 모형의 강수 예측 활용가능성 평가를 위한 입력자료로 가장 보편적으로 활용되는 TRMM_3B42 자료를 선정하였다. 해당 자료의 특성으로 공간해상도는 0.25°, 시간해상도는 일자료이며, 2001년부터 2015년의 자료를 수집하였다. 모형의 평가를 위하여 2001년부터 2013년 자료는 학습, 2014년 자료는 검증, 2015년 자료는 예측에 사용하였다. 또한 민감도 분석을 통하여 ConvLSTM 모형의 최적 매개변수를 추정하고 이를 기반으로 선행시간(lead time) 1일, 2일, 3일의 위성 강수 예측을 수행하였다. 그 결과 선행시간이 길어질수록 그 오차는 증가하지만, 전반적으로 3가지 선행시간 모두 자료의 강수량뿐만 아니라 공간적 분포까지 우수하게 예측되었다. 따라서 2차원 시계열 자료의 특성을 기억하고 이를 예측에 반영할 수 있는 ConvLSTM 모형은 메콩강과 같은 미계측 대유역에서의 안정적인 예측 강수량 정보를 제공할 수 있으며 홍수 예보를 위한 강우-유출 분석에 활용이 가능할 것으로 판단된다.

• The Journal of the Acoustical Society of Korea
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• v.25 no.8
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• pp.356-361
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• 2006

We present the performance of differential space-time block decoders. which does not require the channel state information. We suggest the structure of the multiple blocks differential space time decoders. which does not require the channel state information, and analyze the Performances. In quasi-static flat fading channels. the Performance of multiple blocks differential detection (MD-STC) outperforms that of 2 blocks(D-STC) by 1.5dB. But in the time-selective fading channels due to Doppler frequency $(f_d)$, the performance of MD-STC degrades as the vehicular speed is greater than 200km/hr in 802.16e systems, where the data transmission rate is 144kbps.