• Title/Summary/Keyword: fast-algorithm

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Implementation Knapsack Problem Algorithm M2M Simulator for Optimal Network (최적 통신망을 위한 Knapsack Problem 알고리즘 M2M 시뮬레이터 구현)

  • Lee, Sun-Sik;Song, Min-Seop;Jang, Jong-Wook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.10a
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    • pp.481-484
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    • 2013
  • Many people today are interested in Machine to Machine (M2M) as the new-generation growth engine of mobile communications service providers in Korea. Its use and application are broadening to various areas and the number of devices used for it is increasing to increase the number of information transmitted for each object. When the traffic reaches its limit while each set of data is transmitted from the devices divided into each group through the mobile network, M2M communications service might not be processed smoothly. This study used the Knapsack Problem algorithm to create a virtual simulator for a smooth M2M service when the mobile network used for the M2M communications reaches its limit. The virtual simulator applies smooth processing of services from the M2M communications that should be processed first to other subsequent services when data comes to each group of devices. As the M2M technology develops to make many objects more compact in size, it would help with smoother processing of M2M services for the mobile network with fast-increasing traffic.

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Metadata Management for E-Commerce Transactions in Digital Library (디지털 도서관에서 전자상거래 트랜잭션을 위한 메타데이타 관리 기법)

  • Choe, Il-Hwan;Park, Seog
    • Journal of KIISE:Databases
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    • v.29 no.1
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    • pp.34-43
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    • 2002
  • Since traditional static metadata set like Dublin Core has static metadata attributes about bibliography information, integration of metadata for various metadata, problems about standard and extension of metadata must be considered for applying it to new environment. Specially, as event-driven metadata write method included the notion of e-commerce come out for interoperability in digital libraries, traditional metadata management which cannot distinguish between different kinds of update operations to new extension of metadata set occurs unsuitable waiting of update operation. So, improvement is needed about it. In this paper, we show whether alleviative transaction consistency can be applied to digital library or not. Also it would divide newer metadata into static metadata attribute connected in read operation within user read-only transaction and dynamic metadata attribute in update operation within dynamic(e-commerce) update transactions. We propose newer metadata management algorithm considered in classfication of metadata attributes and dynamic update transaction. Using two version for minimal maintenance cost and ARU(Appended Refresh Unit) for dynamic update transaction, to minimize conflict between read and write operations shows fast response time and high recency ratio. As a result of the performance evaluation, we show our algorithm is proved to be better than other algorithms in newer metadata environments.

Seismic Traveltime Tomography using Neural Network (신경망 이론을 이용한 탄성파 주시 토모그래피의 연구)

  • Kim, Tae-Yeon;Yoon, Wang-Jung
    • Geophysics and Geophysical Exploration
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    • v.2 no.4
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    • pp.167-173
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    • 1999
  • Since the resolution of the 2-D hole-to-hole seismic traveltime tomography is affected by the limited ray transmission angle, various methods were used to improve the resolution. Linear traveltime interpolation(LTI) ray tracing method was chosen for forward-modeling method. Inversion results using the LTI method were compared with those using the other ray tracing methods. As an inversion algorithm, SIRT method was used. In the iterative non-linear inversion method, the cost of ray tracing is quite expensive. To reduce the cost, each raypath was stored and the inversion was performed from this information. Using the proposed method, fast convergence was achieved. Inversion results are likely to be affected by the initial velocity guess, especially when the ray transmission angle was limited. To provide a good initial guess for the inversion, generalized regression neural network(GRNN) method was used. When the transmitted raypath angle is not limited or the geological model is very complex, the inversion results are not affected by initial velocity model very much. Since the raypath angles, however, are limited in most geophysical tomographic problems, the enhancement of resolution in tomography can be achieved by providing a proper initial velocity model by another inversion algorithm such as GRNN.

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A Real Time Processing Technique for Content-Aware Video Scaling (내용기반 동영상 기하학적 변환을 위한 실시간 처리 기법)

  • Lee, Kang-Hee;Yoo, Jae-Wook;Park, Dae-Hyun;Kim, Yoon
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.1
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    • pp.80-89
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    • 2011
  • In this paper, a new real time video scaling technique which preserved the contents of a movie was proposed. Because in a movie a correlation exists between consecutive frames, in this paper by determining the seam of the current frame considering the seam of the previous frame, it was proposed the real time video scaling technique without the shaking phenomenon of the contents even though the entire video is not analyzed. For this purpose, frames which have similar features in a movie are classified into a scene, and the first frame of a scene is resized by the seam carving at the static images so that it can preserve the contents of the image to the utmost. At this time, the information about the seam extracted to convert the image size is saved, and the sizes of the next frames are controlled with reference to the seam information stored in the previous frame by each frame. The proposed algorithm has the fast processing speed of the extent of being similar to a bilinear method and preserves the main content of an image to the utmost at the same time. Also because the memory usage is remarkably small compared with the existing seam carving method, the proposed algorithm is usable in the mobile terminal in which there are many memory restrictions. Computer simulation results indicate that the proposed technique provides better objective performance and subjective image quality about the real time processing and shaking phenomenon removal and contents conservation than conventional algorithms.

Improvement of Address Pointer Assignment in DSP Code Generation (DSP용 코드 생성에서 주소 포인터 할당 성능 향상 기법)

  • Lee, Hee-Jin;Lee, Jong-Yeol
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.45 no.1
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    • pp.37-47
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    • 2008
  • Exploitation of address generation units which are typically provided in DSPs plays an important role in DSP code generation since that perform fast address computation in parallel to the central data path. Offset assignment is optimization of memory layout for program variables by taking advantage of the capabilities of address generation units, consists of memory layout generation and address pointer assignment steps. In this paper, we propose an effective address pointer assignment method to minimize the number of address calculation instructions in DSP code generation. The proposed approach reduces the time complexity of a conventional address pointer assignment algorithm with fixed memory layouts by using minimum cost-nodes breaking. In order to contract memory size and processing time, we employ a powerful pruning technique. Moreover our proposed approach improves the initial solution iteratively by changing the memory layout for each iteration because the memory layout affects the result of the address pointer assignment algorithm. We applied the proposed approach to about 3,000 sequences of the OffsetStone benchmarks to demonstrate the effectiveness of the our approach. Experimental results with benchmarks show an average improvement of 25.9% in the address codes over previous works.

Computing Algorithm for Genetic Evaluations on Several Linear and Categorical Traits in A Multivariate Threshold Animal Model (범주형 자료를 포함한 다형질 임계개체모형에서 유전능력 추정 알고리즘)

  • Lee, D.H.
    • Journal of Animal Science and Technology
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    • v.46 no.2
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    • pp.137-144
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    • 2004
  • Algorithms for estimating breeding values on several categorical data by using latent variables with threshold conception were developed and showed. Thresholds on each categorical trait were estimated by Newton’s method via gradients and Hessian matrix. This algorithm was developed by way of expansion of bivariate analysis provided by Quaas(2001). Breeding values on latent variables of categorical traits and observations on linear traits were estimated by preconditioned conjugate gradient(PCG) method, which was known having a property of fast convergence. Example was shown by simulated data with two linear traits and a categorical trait with four categories(CE=calving ease) and a dichotomous trait(SB=Still Birth) in threshold animal mixed model(TAMM). Breeding value estimates in TAMM were compared to those in linear animal mixed model (LAMM). As results, correlation estimates of breeding values to parameters were 0.91${\sim}$0.92 on CE and 0.87${\sim}$0.89 on SB in TAMM and 0.72~0.84 on CE and 0.59~0.70 on SB in LAMM. As conclusion, PCG method for estimating breeding values on several categorical traits with linear traits were feasible in TAMM.

Face recognition using PCA and face direction information (PCA와 얼굴방향 정보를 이용한 얼굴인식)

  • Kim, Seung-Jae
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.10 no.6
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    • pp.609-616
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    • 2017
  • In this paper, we propose an algorithm to obtain more stable and high recognition rate by using left and right rotation information of input image in order to obtain a stable recognition rate in face recognition. The proposed algorithm uses the facial image as the input information in the web camera environment to reduce the size of the image and normalize the information about the brightness and color to obtain the improved recognition rate. We apply Principal Component Analysis (PCA) to the detected candidate regions to obtain feature vectors and classify faces. Also, In order to reduce the error rate range of the recognition rate, a set of data with the left and right $45^{\circ}$ rotation information is constructed considering the directionality of the input face image, and each feature vector is obtained with PCA. In order to obtain a stable recognition rate with the obtained feature vector, it is after scattered in the eigenspace and the final face is recognized by comparing euclidean distant distances to each feature. The PCA-based feature vector is low-dimensional data, but there is no problem in expressing the face, and the recognition speed can be fast because of the small amount of calculation. The method proposed in this paper can improve the safety and accuracy of recognition and recognition rate faster than other algorithms, and can be used for real-time recognition system.

Energy-Efficient Signal Processing Using FPGAs (FPGA 상에서 에너지 효율이 높은 병렬 신호처리 기법)

  • Jang Ju-wook;Hwang Yunil;Scrofano Ronald;Prasanna Viktor K.
    • The KIPS Transactions:PartA
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    • v.12A no.4 s.94
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    • pp.305-312
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    • 2005
  • In this paper, we present algorithm-level techniques for energy-efficient design at the algorithm level using FPGAs. We then use these techniques to create energy-efficient designs for two signal processing kernel applications: fast Fourier transform(FFT) and matrix multiplication. We evaluate the performance, in terms of both latency and energy efficiency, of FPGAs in performing these tasks. Using a Xilinx Virtex-II as the target FPGA, we compare the performance of our designs to those from the Xilinx library as well as to conventional algorithms run on the PowerPC core embedded in the Virtex-II Pro and the Texas Instruments TMS320C6415. Our evaluations are done both through estimation based on energy and latency equations on high-level and through low-level simulation. For FFT, our designs dissipated an average of $50\%$ less energy than the design from the Xilinx library and $56\%$ less than the DSP. Our designs showed an EAT factor of 10 times improvement over the embedded processor. These results provide a concrete evidence to substantiate the idea that FPGAs can outperform DSPs and embedded processors in signal processing. Further, they show that PFGAs can achieve this performance while still dissipating less energy than the other two types of devices.

Design and Implementation of Sequential Pattern Miner to Analyze Alert Data Pattern (경보데이터 패턴 분석을 위한 순차 패턴 마이너 설계 및 구현)

  • Shin, Moon-Sun;Paik, Woo-Jin
    • Journal of Internet Computing and Services
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    • v.10 no.2
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    • pp.1-13
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    • 2009
  • Intrusion detection is a process that identifies the attacks and responds to the malicious intrusion actions for the protection of the computer and the network resources. Due to the fast development of the Internet, the types of intrusions become more complex recently and need immediate and correct responses because the frequent occurrences of a new intrusion type rise rapidly. Therefore, to solve these problems of the intrusion detection systems, we propose a sequential pattern miner for analysis of the alert data in order to support intelligent and automatic detection of the intrusion. Sequential pattern mining is one of the methods to find the patterns among the extracted items that are frequent in the fixed sequences. We apply the prefixSpan algorithm to find out the alert sequences. This method can be used to predict the actions of the sequential patterns and to create the rules of the intrusions. In this paper, we propose an extended prefixSpan algorithm which is designed to consider the specific characteristics of the alert data. The extended sequential pattern miner will be used as a part of alert data analyzer of intrusion detection systems. By using the created rules from the sequential pattern miner, the HA(high-level alert analyzer) of PEP(policy enforcement point), usually called IDS, performs the prediction of the sequence behaviors and changing patterns that were not visibly checked.

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Estimating Stability Indices from the MODIS Infrared Measurements over the Korean Peninsula (MODIS 적외 자료를 이용한 한반도 지역의 대기 안정도 지수 산출)

  • Park, Sung-Hee;Chung, Eui-Seok;Koenig, Marianne;Sohn, B.J.
    • Korean Journal of Remote Sensing
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    • v.22 no.6
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    • pp.469-483
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    • 2006
  • An algorithm was developed to estimate stability indices (SI) over the Korean peninsula using Terra Moderate Resolution Imaging Spectroradiometer (MODIS) infrared brightness temperatures (TBs). The SI is defined as the stability of the atmosphere in the hydrostatic equilibrium with respect to the vertical displacements and is used as an index for the potential severe storm development. Using atmosphere temperature and moisture profiles from Regional Data Assimilation and Prediction System (RDAPS) as initial guess data for a nonlinear physical relaxation method, K index (KI), KO Index (KO), lifted index (LI), and maximum buoyancy (MB) were estimated. A fast radiative transfer model, RTTOV-7, is utilized for reducing the computational burden related to the physical relaxation method. The estimated TBs from the radiative transfer simulation are in good agreement with observed MODIS TBs. To test usefulness for the short-term forecast of severe storms, the algorithm is applied to the rapidly developed convective storms. Compared with the SIs from the RDAPS forecasts and NASA products, the MODIS SI obtained in this research predicts the instability better over the pre-convection areas. Thus, it is expected that the nowcasting and short-term forecast can be improved by utilizing the algorithms developed in this study.