• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.8
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• pp.781-789
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• 2010

In the GPS/INS integrated system fault detection, algorithm based on a chi-square distribution is commonly used. In this paper, it has been proposed simplified GPS/INS fault detection algorithm that is combined conventional RAIM (Receiver Autonomous Integrity Monitor) and algorithm based on chi-square distribution for UAV using row-grade processor. It use a fault model to verify the proposed algorithm and produced the result.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8A
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• pp.805-814
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• 2008

Both EPCglobal Generation-2 (Gen2) for passive RFID systems and Intelleflex for semi-passive RFID systems use probabilistic slotted ALOHA with Q algorithm, which is a kind of dynamic framed slotted ALOHA (DFSA), as the tag anti-collision algorithm. A better tag anti-collision algorithm can reduce collisions so as to increase the efficiency of tag identification. In this paper, we introduce and analyze the estimation methods of the number of slots and tags for DFSA. To increase the efficiency of tag identification, we propose two new tag anti-collision algorithms, which are Chebyshev's inequality (CHI) algorithm and hybrid Q algorithm, and compare them with the conventional Q algorithm and adaptive adjustable framed Q (AAFQ) algorithm, which is mentioned in Part I. The simulation results show that AAFQ performs the best in Gen2 scenario. However, in Intelleflex scenario the proposed hybrid Q algorithm is the best. That is, hybrid Q provides the minimum identification time, shows the more consistent collision ratio, and maximizes throughput and system efficiency in Intelleflex scenario.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.439-451
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• 2021

We propose a deep learning-based beamformer combined with spectral subtraction for continuous speech recognition operating in noisy environments. Conventional beamforming systems were mostly evaluated by using pre-segmented audio signals which were typically generated by mixing speech and noise continuously on a computer. However, since speech utterances are sparsely uttered along the time axis in real environments, conventional beamforming systems degrade in case when noise-only signals without speech are input. To alleviate this drawback, we combine online beamforming algorithm and spectral subtraction. We construct a Continuous Speech Enhancement (CSE) evaluation set to evaluate the online beamforming algorithm in noisy environments. The evaluation set is built by mixing sparsely-occurring speech utterances of the CHiME3 evaluation set and continuously-played CHiME3 background noise and background music of MUSDB. Using a Kaldi-based toolkit and Google web speech recognizer as a speech recognition back-end, we confirm that the proposed online beamforming algorithm with spectral subtraction shows better performance than the baseline online algorithm.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.167-174
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• 2022

In metaheuristic algorithms such as Genetic Algorithm (GA), initial population has a significant impact as it affects the time such algorithm takes to obtain an optimal solution to the given problem. In addition, it may influence the quality of the solution obtained. In the machine learning field, feature selection is an important process to attaining a good performance model; Genetic algorithm has been utilized for this purpose by scientists. However, the characteristics of Genetic algorithm, namely random initial population generation from a vector of feature elements, may influence solution and execution time. In this paper, the use of a statistical algorithm has been introduced (Chi2) for feature relevant checks where p-values of conditional independence were considered. Features with low p-values were discarded and subject relevant subset of features to Genetic Algorithm. This is to gain a level of certainty of the fitness of features randomly selected. An ensembled-based learning model for Hepatitis has been developed for Hepatitis C stage classification. 1385 samples were used using Egyptian-dataset obtained from UCI repository. The comparative evaluation confirms decreased in execution time and an increase in model performance accuracy from 56% to 63%.

• Proceedings of the IEEK Conference
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• 2003.07b
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• pp.959-962
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• 2003

At the processing capabilities and operating frequency of embedded system are growing, so is the needed data bandwidth to fully utilize the processing capability. The ability to transfer huge amount of data between the embedded core and external devices is required for efficient system operation. In this paper, the data communication architecture for the mixed-clock system is proposed. The dynamic priority adaptation algorithm for bus arbitration is proposed for bandwidth guarantee. The communication architecture that incorporates the proposed arbitration algorithm adapts the priority of communication components dynamically based on the information from FIFO. The experiments show that the measured bandwidth of each component traces the required bandwidth well compared to the other arbitration algorithms

• Proceedings of the IEEK Conference
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• 2003.07b
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• pp.823-826
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• 2003

FPGA-based logic emulator with lane gate capacity generally comprises a large number of FPGAs connected in mesh or crossbar topology. However, gate utilization of FPGAs and speed of emulation are limited by the number of signal pins among FPGAs and the interconnection architecture of the logic emulator. The time-multiplexing of interconnection wires is required for multi-FPGA system incorporating several state-of-the-art FPGAs. This paper proposes a circuit partitioning algorithm called SCATOMi(SCheduling driven Algorithm for TOMi)for multi-FPGA system incorporating four to eight FPGAs where FPGAs are interconnected through TOMi(Time-multiplexed, Off-chip, Multicasting interconnection). SCATOMi improves the performance of TOMi architecture by limiting the number of inter-FPGA signal transfers on the critical path and considering the scheduling of inter-FPGA signal transfers. The performance of the partitioning result of SCATOMi is 5.5 times faster than traditional partitioning algorithms. Architecture comparison show that the pin count is reduced to 15.2%-81.3% while the critical path delay is reduced to 46.1%-67.6% compared to traditional architectures.

• 한국데이터정보과학회:학술대회논문집
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• 2004.04a
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• pp.39-50
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• 2004

The decision tree approach is most useful in classification problems and to divide the search space into rectangular regions. Decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud dection, data reduction and variable screening, category merging, etc. CHAID(Chi-square Automatic Interaction Detector) uses the chi-squired statistic to determine splitting and is an exploratory method used to study the relationship between a dependent variable and a series of predictor variables. In this paper we propose CHAID algorithm by cube-based proportional sampling and explore CHAID algorithm in view of accuracy and speed by the number of variables.

• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.85-93
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• 2011

The Vertex Coloring Problem hasn't been solved in polynomial time, so this problem has been known as NP-complete. This paper suggests linear time algorithm for Vertex Coloring Problem (VCP). The proposed algorithm is based on assumption that we can't know a priori the minimum chromatic number ${\chi}(G)$=k for graph G=(V,E) This algorithm divides Vertices V of graph into two parts as independent sets $\overline{C}$ and cover set C, then assigns the color to $\overline{C}$. The element of independent sets $\overline{C}$ is a vertex ${\upsilon}$ that has minimum degree ${\delta}(G)$ and the elements of cover set C are the vertices ${\upsilon}$ that is adjacent to ${\upsilon}$. The reduced graph is divided into independent sets $\overline{C}$ and cover set C again until no edge is in a cover set C. As a result of experiments, this algorithm finds the ${\chi}(G)$=k perfectly for 26 Graphs that shows the number of selecting ${\upsilon}$ is less than the number of vertices n.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.51-54
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• 2005

Clustering analysis is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their attributes. In this paper we propose a new algorithm for K-medoids clustering which runs like the K-means algorithm. The new algorithm calculates distance matrix once and uses it for finding new medoids at every iterative step. We evaluate the proposed method using real and synthetic data and compare with the results of other algorithms. The proposed algorithm takes reduced time in computation and better performance than others.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.65-74
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• 2005

This Paper Propose a robust scene change detection technique that use the weighted chi-square test and the automated threshold-decision algorithm. The weighted chi-test can subdivide the difference values of individual color channels by calculating the color intensities according to mSC standard, and it can detect the scene change by joining the weighted color intensities to the predefined chi-test which emphasize the comparative color difference values. The automated decision algorithm uses the difference values of frame-to-frame that was obtained by the weighted chi-test. In the first step, The average of total difference value and standard deviation value is calculated and then, subtract the mean value from the each difference values. In the next step, the same process is performed on the remained difference value. The propose method is tested on various sources and in the experimental results, it is shown that the Proposed method is efficiently estimates the thresholds and reliably detects scene changes.