• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8B
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• pp.745-756
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• 2006

The general packet filtering system using TCAM has some limitations such as range and negation rules filtering, so this paper proposes efficient searching schemes than existing methods. CRG(Converting Range rules using Gray code) algorithm, in the case of range rules, that takes advantage of the gray code and TCAM characteristics to save a number of TCAM entries is proposed, and a nTCAM(TCAM with negation) architecture for negation rules is proposed, implemented using a FPGA design tool, and verified through the wave simulation. According to the simulation with the SNORT rules, the CRG algorithm and nTCAM save TCAM entries about 93% in IPv4 and 98% in IPv6 than the existing method.

• Journal of electromagnetic engineering and science
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• v.17 no.2
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• pp.108-110
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• 2017

The global positioning system (GPS) is a useful system in civilian and military applications. However, because of the weak signal, GPS receivers are vulnerable to interference caused by unwanted signals or intentional jammers. To alleviate this issue, a controlled reception pattern antenna (CRPA) array can be employed to adaptively place radiation pattern nulls toward the direction of the signal interference. The performance of the CRPA array improves as the number of antenna elements increases. Therefore, antenna miniaturization is highly desirable for CRPA applications. We designed a compact CRPA array based on seven electrically miniaturized microstrip patch antennas (MPAs) on a 5-inch ground platform. We used a non-Foster matching circuit to match efficiently miniaturized MPAs on an FR-4 substrate. Experimental results show that the non-Foster matching circuit significantly improves such elements of antenna performance as return loss and antenna gain. In addition, we confirmed that the mutual coupling of the proposed CRPA array is less than -45 dB.

• Journal of Satellite, Information and Communications
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• v.7 no.1
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• pp.53-58
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• 2012

In this paper, we evaluate and analyze representative estimation methods for the sparse channel. In order to evaluate error performance of matching pursuit(MP) and minimum mean square error(MMSE) algorithm, lower bound of MMSE is determined by Cramer-Rao bound and compared with upper bound of MP. Based on analysis of those bounds, mean square error of MP which is effective in the estimation of sparse channel can be larger than that of MMSE according to the number of estimated tap and signal-to-noise ratio. Simulation results show that the performances of both algorithm are reversed on the sparse channel with Rayleigh fading according to signal-to-noise ratio.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.10
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• pp.1258-1263
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• 1999

본 논문에서는 CRCW(Concurrent Read Concurrent Write)와 CREW(Concurrent Read Exclusive Write) PRAM(Parallel Random Access Machine) 모델에서 무방향성 그래프 G=(V, E)의 극대 매칭을 구하기 위해 간결한 랜덤 병렬 알고리즘을 제안한다. CRCW PRAM 모델에서 m개의 선을 가진 그래프에 대해, 제안된 매칭 알고리즘은 m개의 프로세서 상에서 {{{{ OMICRON (log m)의 기대 수행 시간을 가진다. 또한 CRCW 알고리즘을 CREW PRAM 모델에서 구현한 CREW 알고리즘은 OMICRON (log^2 m)의 기대 수행 시간을 가지지만,OMICRON (m/logm) 개의 프로세서만을 가지고 수행될 수 있다.Abstract This paper presents simple randomized parallel algorithms for finding a maximal matching in an undirected graph G=(V, E) for the CRCW and CREW PRAM models. The algorithm for the CRCW model has {{{{ OMICRON (log m) expected running time using m processors, where m is the number of edges in G We also show that the CRCW algorithm can be implemented on a CREW PRAM. The CREW algorithm runs in {{{{ OMICRON (log^2 m) expected time, but it requires only OMICRON (m / log m) processors.

• Journal of Internet Computing and Services
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• v.11 no.1
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• pp.59-69
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• 2010

With the growing number of web services, there arise issues of finding suitable services. But, the traditional keyword search method is insufficient for two reasons: (1) this does not capture the underlying semantics of web services. (2) this does not suffice for accurately specifying users' information needs. In order to overcome limitations of this keyword search method, we propose a novel syntactic analysis and ontology learning method. The syntactic analysis method gives us a breadth of coverage for common terms, while the ontology learning method gives a depth of coverage by providing relationships. By combining these two methods, we hope to improve both the recall and the precision. We describe an experimental study on a collection of 508 web services that shows the high recall and precision of our method.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.949-954
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• 2010

Computing the rotation-invariant distance between image time-series is a time-consuming process that incurs a lot of Euclidean distances for all possible rotations. In this paper we propose an innovative solution that significantly reduces the number of Euclidean distances using the triangular inequality. To this end, we first present the notion of self rotation distance and show that, by using the self rotation distance with the triangular inequality, we can prune many unnecessary distance computations. We next present that only one self-rotation is enough for all self-rotation distances required. Experimental results show that our self rotation distance-based methods outperform the existing methods by up to an order of magnitude.

• Steel and Composite Structures
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• v.36 no.1
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• pp.17-29
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• 2020

This paper presents experimental and numerical studies on the seismic responses of the steel cabinet facility considering the nonlinear behavior of connections and site-response effects. Three finite element (FE) models with differences of type and number of connections between steel plates and frame members have been developed to demonstrate adequately dynamic responses of structures. The screw connections with the bilinear force-deformation relationship are proposed to represent the inelastic behavior of the cabinet. The experiment is carried out to provide a verification with improved FE models. It shows that the natural frequencies of the cabinet are sensitive to the plate and frame connectors. The screw connections reduce the free vibration compared to the weld one, with decreased values of 2.82% and 4.87% corresponding to front-to-back and side-to-side directions. Additionally, the seismic responses are investigated for various geological configurations. Input time histories are generated so that their response spectrums are compatible with a required response spectrum via the time-domain spectral matching. The results indicate that both site effects and nonlinear behavior of connections affect greatly on the seismic response of structures.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.457-462
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• 2006

Sequential Pattern Mining is the mining approach which addresses the problem of discovering the existent maximal frequent sequences in a given databases. In the daily and scientific life, sequential data are available and used everywhere based on their representative forms as text, weather data, satellite data streams, business transactions, telecommunications records, experimental runs, DNA sequences, histories of medical records, etc. Discovering sequential patterns can assist user or scientist on predicting coming activities, interpreting recurring phenomena or extracting similarities. For the sake of that purpose, the core of sequential pattern mining is finding the frequent sequence which is contained frequently in all data sequences. Beside the discovery of frequent itemsets, sequential pattern mining requires the arrangement of those itemsets in sequences and the discovery of which of those are frequent. So before mining sequences, the main task is checking if one sequence is a subsequence of another sequence in the database. In this paper, we implement the subsequence matching method as the preprocessing step for sequential pattern mining. Matched sequences in our implementation are the normalized sequences as the form of number chain. The result which is given by this method is the review of matching information between input mapped sequences.

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.629-644
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• 2010

A real-time image georeferencing system requires all inputs to be determined in real-time. The intrinsic camera parameters can be identified in advance from a camera calibration process while other control information can be derived instantaneously from real-time GPS/INS data. The bottleneck process is tie point acquisition since manual operations will be definitely obstacles for real-time system while the existing extraction methods are not fast enough. In this paper, we present a fast-and-automated image matching technique based on the KLT tracker to obtain a set of tie-points in real-time. The proposed work accelerates the KLT tracker by supplying the initial guessed tie-points computed using the GPS/INS data. Originally, the KLT only works effectively when the displacement between tie-points is small. To drive an automated solution, this paper suggests an appropriate number of depth levels for multi-resolution tracking under large displacement using the knowledge of uncertainties the GPS/INS data measurements. The experimental results show that our suggested depth levels is promising and the proposed work can obtain tie-points faster than the ordinary KLT by 13% with no less accuracy. This promising result suggests that our proposed algorithm can be effectively integrated into the real-time image georeferencing for further developing a real-time surveillance application.

• Smart Media Journal
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• v.11 no.8
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• pp.84-92
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• 2022

Precision livestock monitoring promises greater management efficiency for farmers and higher welfare standards for animals. Recent studies on video-based animal activity recognition and tracking have shown promising solutions for understanding animal behavior. To achieve that, surveillance cameras are installed diagonally above the barn in a typical cattle farm setup to monitor animals constantly. Under these circumstances, tracking individuals requires addressing challenges such as occlusion and visual appearance, which are the main reasons for track breakage and increased misidentification of animals. This paper presents a framework for multi-cattle tracking in closed barns with appearance and motion models. To overcome the above challenges, we modify the DeepSORT algorithm to achieve higher tracking accuracy by three contributions. First, we reduce the weight of appearance information. Second, we use an Ensemble Kalman Filter to predict the random motion information of cattle. Third, we propose a supplementary matching algorithm that compares the absolute cattle position in the barn to reassign lost tracks. The main idea of the matching algorithm assumes that the number of cattle is fixed in the barn, so the edge of the barn is where new trajectories are most likely to emerge. Experimental results are performed on our dataset collected on two cattle farms. Our algorithm achieves 70.37%, 77.39%, and 81.74% performance on HOTA, AssA, and IDF1, representing an improvement of 1.53%, 4.17%, and 0.96%, respectively, compared to the original method.