• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.51-57
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• 2008

We present a modeling of constraint satisfaction problems and provide heuristic algorithms of backtracking search to optimize the frequency assignment. Our research objective is to find a frequency assignment that satisfies all the constraints using minimum number of frequencies while maximizing the number of community radio stations served for a given area. In order to get a effective solution, some ordering heuristics such as variable orderings and value orderings are provided to minimize the backtracking in finding all solutions within a limited time. To complement the late detection of inconsistency in the backtracking, we provide the consistency enforcing technique or constraint propagation to eliminate the values that are inconsistent with some constraints. By integrating backtracking search algorithms with consistency enforcing techniques, it is possible to obtain more powerful and effective algorithms of constraint satisfaction problems. We also provide the performance evaluation of proposed algorithms by comparing the theoretical lower bound and our computed solution.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.215-217
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• 2008

The most widely used method for searching contents of mot ion picture compares contents by extracted cuts. The cut extract ion methods, such as CHD(Color Histogram Difference) or ECR(Edge Change Ratio), are very weak at modifications such as cropping, resizing and low bit rate. The suggested method uses audio contents for indexing and searching to make search be robust against these modification. Scenes of audio contents are extracted for modification-robust search. And based on these scenes, make spectral powers binary on each frequency bin. in the time-frequency domain. The suggested method shows failure rate less than 1% on the false positive error and the true negative error to the modified(using cropping, clipping, row bit rate, addtive frame) contents.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.123-136
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• 2014

Recently, online shopping has further developed as the use of the Internet and a variety of smart mobile devices becomes more prevalent. The increase in the scale of such shopping has led to the creation of many Internet shopping malls. Consequently, there is a tendency for increasingly fierce competition among online retailers, and as a result, many Internet shopping malls are making significant attempts to attract online users to their sites. One such attempt is keyword marketing, whereby a retail site pays a fee to expose its link to potential customers when they insert a specific keyword on an Internet portal site. The price related to each keyword is generally estimated by the keyword's frequency of appearance. However, it is widely accepted that the price of keywords cannot be based solely on their frequency because many keywords may appear frequently but have little relationship to shopping. This implies that it is unreasonable for an online shopping mall to spend a great deal on some keywords simply because people frequently use them. Therefore, from the perspective of shopping malls, a specialized process is required to extract meaningful keywords. Further, the demand for automating this extraction process is increasing because of the drive to improve online sales performance. In this study, we propose a methodology that can automatically extract only shopping-related keywords from the entire set of search keywords used on portal sites. We define a shopping-related keyword as a keyword that is used directly before shopping behaviors. In other words, only search keywords that direct the search results page to shopping-related pages are extracted from among the entire set of search keywords. A comparison is then made between the extracted keywords' rankings and the rankings of the entire set of search keywords. Two types of data are used in our study's experiment: web browsing history from July 1, 2012 to June 30, 2013, and site information. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The original sample dataset contains 150 million transaction logs. First, portal sites are selected, and search keywords in those sites are extracted. Search keywords can be easily extracted by simple parsing. The extracted keywords are ranked according to their frequency. The experiment uses approximately 3.9 million search results from Korea's largest search portal site. As a result, a total of 344,822 search keywords were extracted. Next, by using web browsing history and site information, the shopping-related keywords were taken from the entire set of search keywords. As a result, we obtained 4,709 shopping-related keywords. For performance evaluation, we compared the hit ratios of all the search keywords with the shopping-related keywords. To achieve this, we extracted 80,298 search keywords from several Internet shopping malls and then chose the top 1,000 keywords as a set of true shopping keywords. We measured precision, recall, and F-scores of the entire amount of keywords and the shopping-related keywords. The F-Score was formulated by calculating the harmonic mean of precision and recall. The precision, recall, and F-score of shopping-related keywords derived by the proposed methodology were revealed to be higher than those of the entire number of keywords. This study proposes a scheme that is able to obtain shopping-related keywords in a relatively simple manner. We could easily extract shopping-related keywords simply by examining transactions whose next visit is a shopping mall. The resultant shopping-related keyword set is expected to be a useful asset for many shopping malls that participate in keyword marketing. Moreover, the proposed methodology can be easily applied to the construction of special area-related keywords as well as shopping-related ones.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.1
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• pp.8-13
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• 2008

The high peak-to-average power ratio(PAPR) of the transmitted signals is one of the major drawbacks of the orthogonal frequency division multiplexing(OFDM). The partial transmit sequences(PTS) technique can improve the PAPR statistics of the OFDM signals. However, in the PTS technique, the computational complexity to select phase weighting factors increases exponentially with the number of sub-blocks. In this paper, a search algorithm that has no limit on the values of phase weighting factors and requires no additional operations for the search is presented. To evaluate the performance, the proposed search algorithm is compared with the full search algorithm in terms of the complementary cumulative distribution function(CCDF) of the PAPR and the computational complexity. It is shown through simulations that the proposed technique can achieve significant reductions in the computational complexity with little performance degradation compared with the full search algorithm.

• MALSORI
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• no.51
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• pp.151-165
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• 2004

For educational and research purposes, a Korean speech recognition platform is designed. It is based on an object-oriented architecture and can be easily modified so that researchers can readily evaluate the performance of a recognition algorithm of interest. This platform will save development time for many who are interested in speech recognition. The platform includes the following modules: Noise reduction, end-point detection, met-frequency cepstral coefficient (MFCC) and perceptually linear prediction (PLP)-based feature extraction, hidden Markov model (HMM)-based acoustic modeling, n-gram language modeling, n-best search, and Korean language processing. The decoder of the platform can handle both lexical search trees for large vocabulary speech recognition and finite-state networks for small-to-medium vocabulary speech recognition. It performs word-dependent n-best search algorithm with a bigram language model in the first forward search stage and then extracts a word lattice and restores each lattice path with a trigram language model in the second stage.

• Journal of Magnetics
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• v.13 no.1
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• pp.34-36
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• 2008

For the measurement of the magnetic field distribution with high spatial resolution and high accuracy, the magnetic field sensing probe must be non-magnetic, but the MFM probe and sub-millimeter-meter size Hall probe use a ferromagnetic tip and block, respectively, to increase the sensitivity. To overcome this drawback, we developed a micro-size search coil magnetometer which consists of a single turn search coil, Terfenol-D actuator, scanning system, and control software. To reduce the noise generated by the stray ac magnetic field of the actuator driving coil, we employed an even function $\lambda$-H magnetostriction curve and lock-in technique. Using the developed magnetometer, we were able to measure the magnetic field distribution with a magnetic field resolution of 1 mT and spatial resolution of $0.1mm{\times}0.2mm$ at a coil vibration frequency of 1.8 kHz.

• Journal of Families and Better Life
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• v.15 no.4
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• pp.41-54
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• 1997

The purpose of this study is to analyze information search according to consumer's prior knowledge and degree of importance of products. Questionnare survey method was used in this research. The sample was taken from 548 university students in Seoul from 19th of June to 26th of June in 1997. Statistical methods used in this study were Frequency, Percentage, Regression and path Analysis. The major findings are summarized as follows; 1) The level of Consumer's prior knowledge showed somewhat middle. 2) Degree of importance of products showed in order of quality, A/S extension exchange price reliance of a manufacturing company a design etc. 3) Information search for the consumer's prior knowledge and importance showed high on the whole. The more prior knowledge consumer have the better they recognize for the importance of products. Therefore consumers are more likely to search information.

• The Journal of the Acoustical Society of Korea
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• v.15 no.2
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• pp.90-94
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• 1996

Code Excited Linear Prediction(CELP) vocoder exhibits good performance at data rates below 8 kbps. The major drawback of CELP type coders is a large amount of computation. In this paper, we propose a new pitch searching method that preserves the quality of the CELP vocoder reducing computational complexity. The basic idea is that grasps preliminary pitches using the first formant of speech signal and performs pitch search only about the preliminary pitches. As applying the proposed method to the CELP vocoder, we can reduce complexity by 64% in the pitch search.

• Structural Engineering and Mechanics
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• v.69 no.1
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• pp.21-31
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• 2019

Optimizing composite structures to exploit their maximum potential is a realistic application with promising returns. In this research, simultaneous maximization of the fundamental frequency and frequency separation between the first two modes by optimizing the fiber angles is considered. A high-fidelity design optimization methodology is developed by combining the high-accuracy of finite element method with iterative improvement capability of metaheuristic algorithms. Three powerful nature-inspired optimization algorithms viz. a genetic algorithm (GA), a particle swarm optimization (PSO) variant and a cuckoo search (CS) variant are used. Advanced memetic features are incorporated in the PSO and CS to form their respective variants-RPSOLC (repulsive particle swarm optimization with local search and chaotic perturbation) and CHP (co-evolutionary host-parasite). A comprehensive set of benchmark solutions on several new problems are reported. Statistical tests and comprehensive assessment of the predicted results show CHP comprehensively outperforms RPSOLC and GA, while RPSOLC has a little superiority over GA. Extensive simulations show that the on repeated trials of the same experiment, CHP has very low variability. About 50% fewer variations are seen in RPSOLC as compared to GA on repeated trials.

• Smart Media Journal
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• v.9 no.4
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• pp.170-175
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• 2020

It is important to select the most appropriate channel for efficient transmission of massive multimedia data between smart devices in wireless sensor network. In the fixed channel method, sensor nodes can restrict usefulness of frequency and may be a major constraint to support frequency at various environments. In this paper, we propose a modified efficient channel search algorithm that determines available channel and tolerance of interference of links between two nodes. From the results of computer simulation, the proposed method shows that the link of channel can be set efficiently than the other methods even if the number of interference links increases and the beacon packet waiting time caused by interference is reduced remarkably.