Earticle

근사문자열매칭문제는 오랫동안 활발히 연구되어 왔다. 대표적인 근사문자열매칭문제로 편집거리문제와 k-오차문 제가 잘 알려져 있다. 알파벳 Σ에 대해 길이가 각각 m, n인 두 문자열 P와 T가 주어졌을 때, 편집거리문제는 P와 T사이의 편집거리를 계산하는 문제이며, k-오차문제는 T내에서 P가 k이내의 편집거리로 발생하는 모든 위치를 찾는 문제이다. 편집거리문제와 k-오차문제는 동적프로그래밍을 이용하여 O(mn) 시간과 공간을 이용하여 해결할 수 있으며, 접미사트리를 이용하면 k-오차문제는 O(kn) 시간과 공간을 이용하여 해결할 수 있다. 편집 거리 문제는 4-러시안 알고리즘을 이용해서도 해결할 수 있다. 4-러시안 알고리즘은 블록 크기를 t라 할 때, 전처리 단 계에서 O((3lΣl)2tt2) 시간과 O((3lΣl)2tt) 공간, 계산 단계에서 O(mm/t) 시간과 O(mn) 공간을 이용하여 편집거 리를 계산한다. 본 논문에서는 4-러시안 알고리즘의 계산 단계를 m/t 개의 쓰레드를 사용하여 O(m+n) 시간에 수 행하도록 병렬화하여 k-오차문제를 해결하는 알고리즘을 제시한다. 실험결과, 제시된 4-러시안 병렬알고리즘은 기존의 4-러시안 순차알고리즘보다 DNA알파벳(lΣl = 4)의 경우 t = 2일 때 약 41배, t = 4일 때 약 19배 빠른 결과를 보였고, 이진알파벳(lΣl = 2)의 경우 t = 2일 때 약 45배, t = 5일 때 약 15배 빠른 결과를 보였다.

Approximate string matching problems have been studied extensively for a long time. Two of the most well-known approximate string matching problems are the edit distance problem and the k -difference problem. Given two strings P(lPl=m) and T(lTl=n) over an alphabet Σ , the edit distance problem is to compute the edit distance between P and T . The k-difference problem is to find all the occurrences of P in T with at most k edit distances. The edit distance problem and the k-difference problem can be solved in O(mn) time using dynamic programming technique. If suffix trees are used, the k-difference problem can be solved in O(kn) time and space. The edit distance problem also can be solved using Four-Russians’ algorithm whose preprocessing step runs in O((3lΣl)2tt2) time and O((3lΣl)2tt) space and the computation step runs in O(mn/t) time and O(mn) space where t is the size of the block. In this paper, we propose a parallelized version of the computation step of the Four-Russians’ algorithm for the k-difference problem which runs in O(m+n) time using m/t threads. For DNA alphabet, experimental results show that our parallel algorithm is about 41 times and 19 times faster than the (sequential) Four-Russians’ algorithm when t=2 and t=4, respectively. For binary alphabet, our parallel algorithm is about 45 times and 15 times faster than the (sequential) Four-Russians’ algorithm when t=2 and t=5, respectively.

최근 실내 위치측위 기술을 이용하여 다양한 서비스가 이루어지고 있다. 실내 위치측위 방식에는 대표적으로 fingerprinting 방식과 삼변측량 방식이 있으나 활용의 제한성 및 위치추정 오차 등의 문제점이 있다. 이러한 문제점을 해결하기 위해 기존의 측위 방식인 AOA, TOA, TDOA 등의 측위 기술을 응용한 연구가 진행되고 있다. 본 논문에서는 실내 환경에서 RSSI 차이를 이용한 AOA 기반 위치 추정 알고리즘에 대해 연구한다. 4개의 안테나를 가지는 하나의 AP를 가정하여 연구를 진행하며, RSSI를 기반으로 도래각을 추정 후 AOA 알고리즘에 적용한다. RSSI의 보정을 위해 재귀식 평균 필터를 이용하며, 도래각 추정을 위해 보정된 RSSI와 피타고라스 정리를 이용한다. 실험 결과 좁은 간격으로 배치된 4개의 무지향성 안테나의 방사 패턴으로 인하여 18%의 오차율을 보였으며, 지향성 안테나를 이용할 경우 실내 환경에서 AOA 알고리즘을 활용할 수 있을 것으로 판단된다.

There have recently been various services that use indoor location estimation technologies. Representative methods of location estimation include fingerprinting and triangulation, but they lack accuracy. Various kinds of research which apply existing location estimation methods like AOA, TOA, and TDOA are being done to solve this problem. In this paper, we study the location estimation algorithm based on AOA using a RSSI difference in indoor environments. We assume that there is a single AP with four antennas, and estimate the angle of arrival based on the RSSI value to apply the AOA algorithm. To compensate for RSSI, we use a recursive averaging filter, and use the corrected RSSI and the Pythagorean theorem to estimate the angle of arrival. The results of the experiment, show an error of 18% because of the radiation pattern of the four non-directional antennas arranged at narrow intervals.

There are still problems such as low detection accuracy and poor noise immunity in the application of the standard threshold difference algorithm in the signal detection of electrocardiosignal (ECG), in this paper, a medical monitoring model based on the adaptive threshold difference is proposed. First we use a nonlinear filter to filter the P wave and T wave which are low frequency in ECG signal. Then complex wave QRS will be tested. Then the algorithm will be more accuracy through the detection of the R-R interval length and the adjustment of threshold. Finally, the ECG signal will be test with quadratic spline wavelet twice, and the error judgment will be known through adaptive threshold difference. In the simulation experiments, after judging error by wavelet transformation and making the standard threshold difference algorithm optimize adaptively, algorithm showed excellent detection accuracy with and without noise.

In order to solve such problems as the difficult realization of accurate positioning and multidimensional dynamic elastic range measurement and the poor reading of positioning data caches during the range measurement process in wireless sensor network, a wireless sensor network positioning algorithm based on neighbor spin-hop iteration mechanism. Firstly, the neighbor clustering process is executed for the nodes in the wireless sensor network, namely: the first-order neighbor nodes and the second-order neighbor nodes are taken as the network neighborhood. Secondly, other network nodes are positioned according to the rejection and attraction conditions of the neighborhood radius, and meanwhile the iteration mechanism is adopted to realize error minimization so as to obtain the accurate position coordinate of the node. The simulation result shows: compared with currently widely applied two-dimensional non-iterative accurate positioning algorithms, such as RSLM algorithm and SOCP algorithm, the new algorithm is provided with clustering mechanism for accurate positioning and the error correction method based on iteration mechanism, thus to not only effectively reduce the node position error and improve positioning accuracy during multidimensional range measurement, but also improve network packet delivery ratio and reduce network control overhead.

In this paper, a difference expansion based reversible data hiding approach which achieves the low distortion requirement under the same embedding capacity is proposed. An edge-oriented prediction method and a modified overflow/underflow prevention method are proposed to achieve the requirement. For each pixel, the prediction method uses edge information to get a better predicted value in an attempt to reduce the image distortion. Experimental results have demonstrated that the proposed reversible data hiding method yields lower distortion than several well-known expansion-based reversible data hiding methods.

Stencils are finite-difference algorithms for solving large-scale and high-dimension partial differential equations. Due to the data dependences among the iterative statements in Stencils, traditional Stencil computations are be executed serially, rather than in parallel. It’s challenging to design an effective and scalable Stencil parallelized method. To address the issue of 3D data space computing, we present a serial execution model based on multi-layers symmetric Stencil method and time skewing techniques. Within this model, the iteration space is divided to multiple tiles based on time skewing, where the executive process is ordered by the sequence of tiles, and the nodes in each individual tile can be swept repeatedly to improve the data locality. In addition, we propose a novel 3D iterative space alternate tiling Stencil parallel method, which subdivides the iteration space along high dimension, and changes the execution sequence of tiles to reduce the data dependency and communication cost, where the partial order of tiles is still guaranteed. Experimental results demonstrate our proposed alternative tiling parallel method achieves better parallel efficiency and scalability compared with the domain-decomposition methods.

A CGH (Computer-Generated Hologram) is produced by calculating the interference pattern between the object wave and the reference wave. Thus it has been developed to get some ideal characteristics of CGH that are not possible in reality or to test the characteristics of a hologram. To generate a CGH with the hologram resolution of (M×N) for a 3D object having K light source, basically (N×N×K) calculational iterations are necessary. This paper proposes an algorithm that increases the speed of generating a digital hologram using a depth different temporal filtering (DDTF) of a depth video sequence. The proposed algorithm is a technique that performs CGH operation with only calculation the different depth values between the depth video frames. The experimental results showed that the proposed algorithm increased operation speed by 65% over the technique using the conventional CGH equation.

Aiming at the problem of the dim target real-time detection in Infrared search and track (IRST) systems, a fusion detection algorithm for infrared dim target based on temporal-spatial domain accumulation and difference is proposed. The proposed algorithm suppresses background and enhances targets by template filtering and difference processing in space domain, and the image sequences are processed by multi-frame energy accumulation and frame difference methods according to the target’s moving characteristics in time domain. After the fusion segmentation of the temporal and spatial processing results with definite rule, the target can be detected by the relation of the possible target’s position in adjoining frames according to target’s moving continuity and regularity. Experimental results show that the proposed algorithm enormously increases the target's SNR after the temporal-spatial fusion enhancement, and it has high detection probability and high detecting speed. In the meantime, the algorithm is easy to realize in hardware and can be applied effectively in the real-time target detection of the IRST systems.

일반적으로 워터마킹은 오디오, 비디오, 이미지, 그리고 텍스트 등의 콘텐트의 저작권을 위해서 사용되고 있다. 인터넷의 발달로 어플리케이션과 연동되는 관계형 데이터베이스는 악의적인 공격자들에 의한 데이터베이스 복제, 유출 등이 빈번히 발생하고 있다. 따라서 데이터베이스의 저작권보호 역시 필요성이 증대되고 있다. 또한 데이터베이스에는 민감한 개인정보에서 산업기밀 정보까지 다양한 정보고 포함되어 있다. 따라서 관계형 데이터베이스의 보호는 데이터베 이스 분야에서 매우 중요한 연구 영역이 되고 있다. 본 논문에서는 관계형 데이터를 보호할 수 있는 다양한 방안의 기 존의 연구를 살펴보고, 이들 데이터를 보호할 수 있는 새로운 방법을 제안하고자 한다. 특히 본 논문에서는 가역적인 방법으로 데이터베이스에 워터마크를 삽입하는 방법을 제안하고자 한다. 실험결과 제안한 기술은 악의적인 공격에 강함 을 보였다. 또한, 제안한 방법이 실제 어플리케이션에 적용 가능함을 보였다.

Generally, watermarking can be used copyright for contents such as audios, videos, images, and texts. With the development of Internet, many malicious attackers illegally copy relational databases synchronized applications Therefore, it is needed for the protection of databases copyright, because databases involve various sensitive information such as personal information, information industry, and secret national intelligence. Thus, the protection of relational databases is a major research field in the databases research topics. In this paper, we will review previous researches related the protection of relational databases and propose new method for relational data. Especially, we propose watermarking scheme for databases using reversible method in this paper. As an experimental result, the proposed scheme is very strong to malicious attacks. In addition, we proved our proposed scheme is to apply real application.

This article presents a new global-local hybrid coarse-mesh finite difference (HCMFD) method for efficient parallel calculation of pin-by-pin heterogeneous core analysis. In the HCMFD method, the one-node coarse-mesh finite difference (CMFD) scheme is combined with a nodal expansion method (NEM)-based two-node CMFD method in a nonlinear way. In the global-local HCMFD algorithm, the global problem is a coarse-mesh eigenvalue problem, whereas the local problems are fixed source problems with boundary conditions of incoming partial current, and they can be solved in parallel. The global problem is formulated by one-node CMFD, in which two correction factors on an interface are introduced to preserve both the surface-average flux and the net current. Meanwhile, for accurate and efficient pin-wise core analysis, the local problem is solved by the conventional NEM-based two-node CMFD method. We investigated the numerical characteristics of the HCMFD method for a few benchmark problems and compared them with the conventional two-node NEM-based CMFD algorithm. In this study, the HCMFD algorithm was also parallelized with the OpenMP parallel interface, and its numerical performances were evaluated for several benchmarks.

The power efficiency of a full-color OLED display decreases with long-term operation because of the material characteristics. The lifetime of the OLED display also decreases as the power efficiency declines. Therefore, this work provides a novel color difference algorithm to improve the power consumption and extend the OLED lifetime.

Unlabeled examples are easier and less expensive to obtain than labeled examples. Semisupervised approaches are used to utilize such examples in an eort to boost the predictive performance. This paper proposes a novel semisupervised classication method named transductive least squares support vector machine (TLS-SVM), which is based on the least squares support vector machine. The proposed method utilizes the dierence convex algorithm to derive nonconvex minimization solutions for the TLS-SVM. A generalized cross validation method is also developed to choose the hyperparameters that aect the performance of the TLS-SVM. The experimental results conrm the successful performance of the proposed TLS-SVM.

Reversible data embedding theory has marked a new epoch for data hiding and information security. Being reversible, the original data and the embedded data as well should be completely restored. Difference expansion transform is a remarkable breakthrough in reversible data hiding scheme. The difference expansion method achieves high embedding capacity and keeps the distortion low. This paper shows that the difference expansion method with simplified location map, and new expandability and changeability can achieve more embedding capacity while keeping the distortion almost the same as the original expansion method.

블럭 정합 알고리즘의 VLSI 구현시 복잡도를 줄이고, 수행 속도를 높이기 위하여 새로운 정합 기준인 적응적 비트 축소 MAD(adaptive bit-reduced mean absolute difference:ABRMAD)를 제안한다. ABRMAD는 기존의 MAD에서 화소의 모든 비트를 비교하는 대신, 화소를 구성하는 중요한 비트만을 고려하여 축소된 화소 값을 비교하여 움직임 벡터를 찾는다. 실험을 통하여, 제안한 정합 기준은 기존의 MAD 정합 기준에 비하여 낮은 하드웨어 복잡도를 가지면서 MSE(mean square error) 측면에서 유사한 성능을 가짐을 보인다. 또한 기존의 비트 수 축소형 정합 기준인 DPC(difference pixel counting), BBME(binary-matching with edge-map), 그리고 BPM(bit-plane matching)과 비교하여 같은 수의 비트를 사용하였을 경우 좋은 MSE 성능을 가짐을 보인다.

An adaptive bit-reduced mean absolute difference (ABRMAD) is presented as a criterion for the block-matching algorithm (BMA) to reduce the complexity of the VLSI Implementation and to improve the processing time. The ABRMAD uses the lower pixel resolution of the significant bits instead of full resolution pixel values to estimate the motion vector (MV) by examining the pixels Ina block. Simulation results show that the 4-bit ABRMAD has competitive mean square error (MSE)results and a half less hardware complexity than the MAD criterion, It has also better characteristics in terms of both MSE performance and hardware complexity than the Minimax criterion and has better MSE performance than the difference pixel counting(DPC), binary block-matching with edge-map(BBME), and bit-plane matching(BPM) with the same number of bits.

In this paper, a new scheme to calculate the weighting factor of the 2-D isotropic-dispersion finite difference time domain(ID-FDTD) is proposed. The weighting factor in [1] was formulated in free space, so that it may not be optimal in dielectric media. Therefore, the weighting factor was reformulated by considering the material properties and using the least mean square method. As a result, a minimum numerical dispersion error for any dielectric media is guaranteed.

In this paper, an efficient and robust localization algorithm using Receiver Signal Strength Difference (RSSD) for a non-cooperative RF emitter is given. The proposed algorithm firstly calculate the center point and radius of Apollonius's circles and then estimate the intersection point of the circles based on Time of Arrival concept. And this paper also compares the performance of RSSD localization algorithms such as Non-linear Least Squares and Linearized Least Squares by Lines of Position (LOP) with the proposed algorithm. And some conclusions have been reached regarding the relative accuracy, robustness and computational cost of these algorithms.

The accurate estimation of a fault location is desired in distance protection schemes for transmission lines in order to selectively deactivate a faulted line. However, a typical method to estimate a fault location by calculating impedances with voltages and currents at relaying points may have errors due to various factors such as the mutual impedances of lines, fault impedances, or effects of parallel circuits. The proposed algorithm in this paper begins by extracting the fundamental phasor of the positive sequence currents from the three phase currents. The second-order difference of the phasor is then calculated based on the fundamental phasor of positive sequence currents. The traveling times of the waves generated by a fault are derived from the second-order difference of the phasor. Finally, the distance from the relaying point to the fault is estimated using the traveling times. To analyze the performance of the algorithm, a power system with EHV(Extra High Voltage) untransposed double-circuit transmission lines is modeled and simulated under various fault conditions, such as several fault types, fault locations, and fault inception angles. The results of the simulations show that the proposed algorithm has the capability to estimate the fault locations with high speed and accuracy.

Recently, pirates are infesting on the sea and they have been hijacking the several vessels for example Samho Dream and Samho Jewelry of Korea. One of the items to reduce the risk is to adopt the invader detection system. If the pirates break in to the ship, the detection system can monitor the pirates and then call the security alarm. The crew can gain time to hide to the safe room and the report can be automatically sent to the control room to cope with the situation. For the invader detection, an unmanned observation system was proposed using the image detection algorithm that extracts the invader image from the recording image. To detect the motion area, the difference value was calculated between the current image and the prior image of the invader, and the 'AND' operator was used in calculated image and edge line. The image noise was reduced based on the morphology operation and then the image was transformed into morphological information. Finally, a neural network model was applied to recognize the invader. In the experimental results, it was confirmed that the proposed approach can improve the performance of the recognition in the invader monitoring system.