• Journal of the Institute of Convergence Signal Processing
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• v.11 no.3
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• pp.189-196
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• 2010

In this paper, we proposed the adaptive local sigma filter reducing noises generated by an image sensor. The small noises generated by the image sensor are amplified by increased an analog gain and an exposure time of the image sensor together with information. And the goal of this work was the system design that is reduce the these amplified noises. Edge data are extracted by Flatness Index Map algorithm. We made the threshold adaptively changeable by the luminance average in this algorithm that extracts the edge data not in high luminance, but just low luminance. The Local Sigma Filter performed only about the edge pixel that were extracted by Flatness Index Map algorithm. To verify the performance of the designed filter, we made the Window test program. The hardware was designed with HDL language. We verified the hardware performance of Local Sigma Filter system using FPGA Demonstration board and HD image sensor, $1280{\times}720$ image size and 30 frames per second.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.8
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• pp.76-85
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• 2000

Effects of the random fluctuation in grating half-period have been studied by an effective index transfer matrix method in DFB lasers. The laser facets are assumed to be perfectly antireflection coated, and the period fluctuation is modeled as a Gaussian random variable. The random fluctuation breaks spectral symmetry in both uniform-grating and quarter-wavelength -shifted(QWS) DFB lasers, and decreases the effective coupling coefficient. This leads to increased average mirror loss of ${\pm}$1 modes and reduced stopband width in uniform grating DFB lasers, and degradation in the wavelength accuracy and the single mode stability in QWS-DFB lasers. Threshold gain difference decreases with increasing period fluctuation irrespective of grating coupling coefficient in QWS-DFB lasers, while spatial hole-burning effect is exacerbated or alleviated when the normalized coupling coefficient is lower and higher than 1.5, respectively.

• The Journal of the Acoustical Society of Korea
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• v.24 no.5
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• pp.238-247
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• 2005

In this Paper. we Presents subband design techniques of a compensating filter and adaptive feedback canceller for the digital hearing aid. The sensorineural hearing loss has a hearing threshold that shows a nonlinear characteristic in frequency domain. and its compensation suffers from an echo that produced by an undesired time varying feedback path. Therefore. the digital hearing aid requires the compensator that can adjust gains nonlinearly in frequency bands and eliminate the echo rapidly In the Proposed digital hearing aid. the compensating filter is designed by the adaptive system identification method in subband structure, and the adaptive feedback canceller is designed by the subband affine projection algorithm. The designed compensation filter can control the nonlinear gain in each subband respectively, therefore precise compensation is possible. And the feedback canceller using the subband adaptive filter achieves fast convergence rate. The Performances of the Proposed method are verified by computer simulations as comparing with the behaviors of the previous trials.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.344-352
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• 2020

Covertness and performance are very important design goals in the underwater communications. To satisfy both of them, we proposed efficient underwater communication model which combined multiband and direct sequence spread spectrum method in order to improve performance and covertness simultaneously. Turbo coding method with 1/3 coding rates is used for channel coding algorithm, and turbo equalization method which iterately exchange probabilistic information between equalizer and decoder is used for receiver side. After optimal threshold value was set in Rake processing, this paper analyzed the performance by varying the number of chips were 8, 16, 32 and the number of bands were from 1 to 4. Through the simulation results, we confirmed that the performance improvement was obtained by increasing the number of bands and chips. 2~3 dB of performance gain was obtained when the number of chips were increased in same number of bands.

• Korean Journal of Otorhinolaryngology-Head and Neck Surgery
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• v.61 no.12
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• pp.663-668
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• 2018

Background and Objectives The main objectives of this study were to determine the clinical usefulness of the program-assisted and real ear measurement (REM)-assisted fitting of hearing aids. Subjects and Method Fifteen participants with moderate to moderately severe hearing loss were enrolled in this study. Objective and subjective fitting results were assessed to compare the benefits between the program-assisted fitting (using a software fitting program) and the REM-assisted fitting. Real ear insertion gain (REIG), sound-field audiometry using warble tone, and Korean Hearing in Noise Test (K-HINT) were performed as objective tests. Sound quality rating was performed as a subjective test. Results In the program fitting, 48.89% of fitting points failed to come within ${\pm}10dB$ of the REIG target. In the REM fitting, however, the percentage of failure significantly decreased to 23.33% (p=0.013). In K-HINT test, the reception threshold for speech in quiet situation significantly decreased from 50.1 dB HL with the program fitting to 44.7 dB HL after the REM fitting (p<0.001). In front noise condition, signal-to-noise ratio improved from 4.53 dB to 3.50 dB with the REM fitting without statistical significance (p=0.099). In the sound quality rating, the REM fitting ($4.27{\pm}0.56$) showed a significantly better sound quality ratings than the program fitting ($3.69{\pm}0.74$) (p=0.017). Conclusion The REM fitting showed better results in both subjective and objective measurements than the program fitting.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.203-209
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• 2019

We will be establish the new $q(1{\leq}q{\leq}p-1)$ stores of firm $F_B$ to gain pop/(p+q) over rival firm $F_A$ that has already operate with p stores in a city of population pop. Han proposes inclusion-exclusion algorithm(IEA) that searches maximal pop top 5 location and select the maximum location take account of locate variation with increasing of $q=1,2,{\cdots},p-1$. This paper reduced the orignal graph into partial graph initially and search only q=1 node continually reduced in accordance with increasing $q=1,2,{\cdots},p-1$. If the final result is shown in the case of steel customer between q, the q locations farther separate in order to improve of solution. For the eleven experimental data, this algorithm is a relative simplicity and more optimal solution than Han's IEA.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.8
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• pp.1077-1083
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• 2019

Objective: Sow longevity is important for efficient and profitable pig farming. Recently, there has been an increasing interest in social genetic effect (SGE) of pigs on stress-tolerance and behavior. The present study aimed to estimate genetic correlations among average daily gain (ADG), stayability (STAY), and number of piglets born alive at the first parity (NBA1) in Korean Yorkshire pigs, using a model including SGE. Methods: The phenotypic records of ADG and reproductive traits of 33,120 and 11,654 pigs, respectively, were evaluated. The variances and (co) variances of the studied traits were estimated by a multi-trait animal model applying the Bayesian with linear-threshold models using Gibbs sampling. Results: The direct and SGEs on ADG had a significantly negative (-0.30) and neutral (0.04) genetic relationship with STAY, respectively. In addition, the genetic correlation between the social effects on ADG and NBA1 tended to be positive (0.27), unlike the direct effects (-0.04). The genetic correlation of the total effect on ADG with that of STAY was negative (-0.23) but non-significant, owing to the social effect. Conclusion: These results suggested that total genetic effect on growth in the SGE model might reduce the negative effect on sow longevity because of the growth potential of pigs. We recommend including social effects as selection criteria in breeding programs to obtain satisfactory genetic changes in both growth and longevity.

• Structural Engineering and Mechanics
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• v.80 no.6
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• pp.701-709
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• 2021

The paper aims at improving the understanding and mitigating the effects of tunnel fires that may breakout due to the burning fuel and/or explosion within the tunnel. This study particularly focuses on the behavior of the commonly used horse shoe geometry of tunnel systems. The problem has been obtained using an adequate well-established program incorporating the Lagrangian approach. A transient-thermo-coupled static structural analysis is carried out. The effects of radiation and convection to the outer walls of the tunnel is studied. The paper also presents the impact of the hazard on the structural integrity of the tunnel. A methodology is proposed to study the tunnel fire using a model which uses equivalent steel sheet to represent the presence of reinforcements to improve the computational efficiency with adequate validation. A parametric study has been carried out and the effect of suitable lining property for mitigating the fire hazard is arrived at. Detailed analysis is done for the threshold limits of the properties of the lining material to check if it is acceptable in all aspects for the integrity of the tunnel. The study may prove useful for developing insights for ensuring tunnel fire safety. To conduct such studies experimentally are tremendously costly but are required to gain confidence. But, scaled models, as well as loading and testing conditions, cannot be studied by many trials experimentally as the cost will shoot up sharply. In this context, the results obtained from such computational studies with a feasible variation of various combinations of parameters may act as a set of guidelines to freeze the adequate combination of various parameters to conduct one or two costly experiments for confidence building.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.129-142
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• 2016

Customer product reviews have become one of the important factors for purchase decision makings. Customers believe that reviews written by others who have already had an experience with the product offer more reliable information than that provided by sellers. However, there are too many products and reviews, the advantage of e-commerce can be overwhelmed by increasing search costs. Reading all of the reviews to find out the pros and cons of a certain product can be exhausting. To help users find the most useful information about products without much difficulty, e-commerce companies try to provide various ways for customers to write and rate product reviews. To assist potential customers, online stores have devised various ways to provide useful customer reviews. Different methods have been developed to classify and recommend useful reviews to customers, primarily using feedback provided by customers about the helpfulness of reviews. Most shopping websites provide customer reviews and offer the following information: the average preference of a product, the number of customers who have participated in preference voting, and preference distribution. Most information on the helpfulness of product reviews is collected through a voting system. Amazon.com asks customers whether a review on a certain product is helpful, and it places the most helpful favorable and the most helpful critical review at the top of the list of product reviews. Some companies also predict the usefulness of a review based on certain attributes including length, author(s), and the words used, publishing only reviews that are likely to be useful. Text mining approaches have been used for classifying useful reviews in advance. To apply a text mining approach based on all reviews for a product, we need to build a term-document matrix. We have to extract all words from reviews and build a matrix with the number of occurrences of a term in a review. Since there are many reviews, the size of term-document matrix is so large. It caused difficulties to apply text mining algorithms with the large term-document matrix. Thus, researchers need to delete some terms in terms of sparsity since sparse words have little effects on classifications or predictions. The purpose of this study is to suggest a better way of building term-document matrix by deleting useless terms for review classification. In this study, we propose neutrality index to select words to be deleted. Many words still appear in both classifications - useful and not useful - and these words have little or negative effects on classification performances. Thus, we defined these words as neutral terms and deleted neutral terms which are appeared in both classifications similarly. After deleting sparse words, we selected words to be deleted in terms of neutrality. We tested our approach with Amazon.com's review data from five different product categories: Cellphones & Accessories, Movies & TV program, Automotive, CDs & Vinyl, Clothing, Shoes & Jewelry. We used reviews which got greater than four votes by users and 60% of the ratio of useful votes among total votes is the threshold to classify useful and not-useful reviews. We randomly selected 1,500 useful reviews and 1,500 not-useful reviews for each product category. And then we applied Information Gain and Support Vector Machine algorithms to classify the reviews and compared the classification performances in terms of precision, recall, and F-measure. Though the performances vary according to product categories and data sets, deleting terms with sparsity and neutrality showed the best performances in terms of F-measure for the two classification algorithms. However, deleting terms with sparsity only showed the best performances in terms of Recall for Information Gain and using all terms showed the best performances in terms of precision for SVM. Thus, it needs to be careful for selecting term deleting methods and classification algorithms based on data sets.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.8 s.338
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• pp.33-40
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• 2005

This paper presents a structure of the searcher using a diversity in array antenna systems operating in the cdma2000 1x signal environments. The new technique exploits the fact that the In-phase and quadrature components of interferers can respectively be viewed as an independent gaussian noise at each antnna element in most practical cdma signal environments. The proposed PN acquisition scheme is a singles-dwell PN acquisition system consisting of two stages, that is, the searching stage and the verification stage. The searching stage independently correlates the receiver multiple signals with PN generator of each antenna element for obtaining the synchronous energy at the entire region. Then, the searching results of each antenna element are non-coherently combinind. The verification stage compares the searching energy with the optimal threshold, which is predesigned in the lock detector, and decides whether the acquisition is successful or fail. In this paper, we analyzed the effect of tile diversity order to determine the mean acquisition time. In general, it is known that the mean acquisition time significantly decrease as the number of antenna elements increases. But, as the diversity order goes up, the enhancement of the performance is saturated. Therefore, to decrease the mean acquisition time of the searcher, we must design the optimal array antenna systems by considering the operating SNR range of the receiver, the probability of detection $P_D$ and that of false alarm $P_{FA}$ . The Performance of the proposed PN acquisition scheme is analyzed in frequency selective Rayleigh fading channels. In this paper, the effect of the number of antenna elements on PN acquisition scheme is shown according to the probability of detection $P_D$ and that of false alarm $P_{FA}$.