• Korean Journal of Fisheries and Aquatic Sciences
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• v.48 no.5
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• pp.798-804
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• 2015

The distributions of demersal fish along the coast of the South Sea, Korea, were estimated from a hydroacoustic survey and bottom trawl catches in April of 2015. Acoustic data were collected at 38 kHz, and converted into the nautical area scattering coefficient (NASC, m²/n·mile²) for 0.1 n∙mile along eight transects during day and nighttime. Various demersal fish species were collected and the dominant species comprised no more than half of the catch. The estimated acoustic density of demersal fish compared well with the cumulative catch weight from bottom trawl catches in daytime, but showed a low correlation at nighttime. The NASC of pelagic fish determined for anchovy was correlated with water temperature. The combined hydroacoustic and trawl method can be used to understand the spatial/temporal structure and estimate the density of demersal fish in coastal areas.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.47 no.5
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• pp.671-681
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• 2014

The distribution and abundance of coastal fish species in Asan Bay, Korea, were estimated from hydroacoustic survey and net catches. Acoustic data were collected with 38 and 200 kHz from July to October of 2012, and converted to the nautical area scattering coefficient (NASC, $m^2/mile^2$) for $0.25n{\cdot}mile$ along ten transects. Japanese anchovy Engraulis japonicus was the dominant specie in the net catches. The virtual echogram technique was used to distinguish E. japonicus from other species based on the differences in the mean volume backscattering strength (${\Delta}MVBS$) at 38 and 200 kHz. Engraulis japonicus and other fishes are mainly distributed in the center channel and outer part of Asan Bay. E. japonicus tends to move from inner to outer Asan Bay in summer and fall. From NASC data, the target strength and length-weight function of E. japonicus and other fishes were used to estimate the E. japonicus stock at 24.1-93.3 tons, and other fish at 40.6-88.4 tons from July to October 2012. The estimated anchovy biomass compared well with the cumulative catch weight from stow net catches. The hydroacoustic method offers an approach to understanding spatial/temporal structure and estimating the biomass of fish aggregations in coastal areas.

• Journal of the Korean Wood Science and Technology
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• v.39 no.2
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• pp.163-171
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• 2011

Because Japanese cedar shows lower mechanical performance, glued-laminated timber (glulam) can be a better way to utilize Japanese cedar for structural purpose. However, low yield of higher grade lamination from log makes it difficult to design structural glulam. This study was aimed to increase the yield of higher grade lamination and provide higher efficiency of manufacturing structural lamination by ultrasonic log sorting technology. Logs were sorted by an existing log grading rule regulated by Korea Forest Research Institute (KFRI). It was found that the KFRI log grading rule contributed to finding better logs in viewpoint of the volumetric yield and it can reduce the number of rejected lumber by visual grading. However, it could not identify better logs to produce higher-grade products. To find an appropriate log-sorting-method for structural products, log diameter and ultrasonic time of flight (TOF) for the log were considered as factors to affect mechanical performance of resulting products. However, it was found that influence of log diameter on mechanical performance of resulting products was very small. The TOF showed a possibility to sort logs by mechanical performance of resulting products even though a coefficient of correlation was not strong (R = 0.6). In a case study, the log selection based on the ultrasonic TOF of the log increased the yield of the outermost tension lamination (E8 or better grade, KS F 3021) from 2.6% to 12.5% and reduced LTE5 (lower than E5 grade) lamination from 43.6% to 10.3%, compared with the existing KFRI log grading rule.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1539-1544
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• 2005

The gauge control of the fishing mill is very important because more and more accurately sized hot rolled coils are demanded by customers recently. Because the mill constant and the plasticity coefficient vary with the specifications of the mill, the classification of steel, the strip width, the strip thickness and the slab temperature, the variation of these parameters should be considered in the automatic gauge control system(AGC). Generally, the AGC gain is used to minimize the effect of the uncertain parameters. In a practical field, operators set the AGC gain as a constant value calculated by FSU (Finishing-mill Set-Up model) and it is not changed during the operating time. In this paper, the thickness data signals that occupy different frequency bands are respectively extracted by adaptive filters and then the main cause of the thickness variation is analyzed. Additionally, the AGC gain is adaptively tuned to reduce this variation using the online tuning model. Especially ANFIS(Adaptive-Neuro-based Fuzzy Interface System) which unifies both fuzzy logics and neural networks, is used for this gain adjustment system because fuzzy logics use the professionals' experiences about the uncertainty and the nonlinearity of the system. Simulation is performed by using POSCO's data and the results show that proposed on-line gain adjustment algorithm has a good performance.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.2 s.48
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• pp.63-71
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• 2006

In the companion paper (II, Development of Site Classification System), new size classification system based on site periods $(T_G)$ was recommended for legions of shallow bedrock depth in Korea. Despite the site classification method was improved, the response spectrum would be required to be modified by adjusting the integration interval to calculate the site coefficients because the response spectra did not match well the average spectral accelerations obtained by site response analyses in the range of long periods. In this paper, new response spectra for each site categories were determined by adjusting the integration interval of long period site coefficient $F_v\;from\;0.4{\sim}2.0\;to\;0.4{\sim}1.5$ second. It matched well the average spectral accelerations and new response spectrum, and it was also improved compared to the current she classification system.

• Journal of The Korean Association For Science Education
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• v.32 no.3
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• pp.524-531
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• 2012

Categorization is an important human function used to process different stimuli. It is also one of the most important factors affecting measurement of a person's classification ability. Explicit categorization, the representative system by which categorization ability is measured, can verbally describe the categorization rule. The purpose of this study was to develop a prediction model for categorization ability as it relates to the classification process of living organisms using fMRI. Fifty-five participants were divided into two groups: a model generation group, comprised of twenty-seven subjects, and a model verification group, made up of twenty-eight subjects. During prediction model generation, functional connectivity was used to analyze temporal correlations between brain activation regions. A classification ability quotient (CQ) was calculated to identify the verbal categorization ability distribution of each subject. Additionally, the connectivity coefficient (CC) was calculated to quantify the functional connectivity for each subject. Hence, it was possible to generate a prediction model through regression analysis based on participants' CQ and CC values. The resultant categorization ability regression model predictor was statistically significant; however, researchers proceeded to verify its predictive ability power. In order to verify the predictive power of the developed regression model, researchers used the regression model and subjects' CC values to predict CQ values for twenty-eight subjects. Correlation between the predicted CQ values and the observed CQ values was confirmed. Results of this study suggested that explicit categorization ability differs at the brain network level of individuals. Also, the finding suggested that differences in functional connectivity between individuals reflect differences in categorization ability. Last, researchers have provided a new method for predicting an individual's categorization ability by measuring brain activation.

• Physical Therapy Korea
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• v.19 no.4
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• pp.46-54
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• 2012

Ely's test is commonly used to assess rectus femoris muscle flexibility. however, a reliability limit of this test was demonstrated by a previous study. In this study, we present an alternative method using an application for a digital horizontal level in a smartphone (DHLS) to complement the reliability limit of Ely's test. The aim of this study was to examine the reliability of Ely's test using DHLS on the pelvis, compared to using visual observation (VO) of pelvic and hip motions. Nineteen patients with lumbar extension-rotation syndrome were recruited for this study. An examiner examined the rectus femoris flexibility (both pass/fail and goniometer scoring) through Ely's test using both DHLS and VO. A retest session was completed two hours later for within-day reliability and seven days later for between-day intra-rater test-retest reliability. Results showed higher Kappa values for pass/fail scoring and higher intraclass correlation coefficient values for goniometer scoring in Ely's test using DHLS, compared to using VO. Measurement error and Bland and Altman plots further demonstrated the degree of intra-rater variance during Ely's test using DHLS in a clinical setting, compared to using VO. These results demonstrated that Ely's test using DHLS showed acceptable reliability compared to using VO. Ely's test using DHLS could be widely used for measuring the rectus femoris muscle flexibility in patients with lumbar extension-rotation syndrome, although the inter-rater reliability needs to be established first.

• Korean Chemical Engineering Research
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• v.47 no.2
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• pp.179-184
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• 2009

Recent evolution of computer technology enhances the effectiveness of CFD(Computational Fluid Dynamics) analysis for the 3-dimensional complex transport phenomena including turbulent flows. Cheaper and easier than laser and ultra-sonic methods, the windows simulator name by CAMSI(Computer-Aided Management of Stereo Images) has been developed in order to implement the 3-dimensional image using a disparity histogram extracted from left and right stereo images. In our program using the area-based method, the matching pixel finding methods consist of SSD(Sum of Squared Distance), SAD(Sum of Absolute Distance), NCC(Normalized Correlation Coefficient) and MPC(Matching Pixel Count). On performing the program, stereo images on different window sizes for various matching pixel finding methods are compared reasonably. When the image has a small noise, SSD on small window size is more effective. Whereas there is much noise, NCC or MPC is more effective than SSD. CAMSI from the present study will be much helpful to implement the complex objects and to analyze 3-dimensional CFD around them.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.1
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• pp.16-22
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• 2010

Electrocardiogram(ECG) analysis and arrhythmia recognition are critical for diagnosis and treatment of ill patients. Cardiac arrhythmia is a condition in which heart beat may be irregular and presents a serious threat to the patient recovering from ventricular tachycardia (VT) and ventricular fibrillation (VF). Other arrhythmias like atrial premature contraction (APC), Premature ventricular contraction (PVC) and superventricular tachycardia (SVT) are important in diagnosing the heart diseases. This paper presented new method to classify various arrhythmias contrary to other techniques which are limited to only two or three arrhythmias. ECG is decomposed into Intrinsic Mode Functions (IMFs) by Empirical Mode Decomposition (EMD). Burg algorithm was performed on IMFs to obtain AR coefficients which can reduce the dimension of feature vector and utilized as Multi-class SVM inputs which is basically extended from binary SVM. We chose optimal parameters for SVM classifier, applied to arrhythmias classification and achieved the accuracies of detecting NSR, APC, PVC, SVT, VT and VP were 96.8% to 99.5%. The results showed that EMD was useful for the preprocessing and feature extraction and multi-class SVM for classification of cardiac arrhythmias, with high usefulness.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.681-684
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• 2015

Power amplifier is an essential component for transmitting signals to a remote receiver in wireless communication systems. Power amplifier is a non-linear device in general, and the nonlinear distortion becomes severer as the output power increases. The nonlinearity results in spectral regrowth, which leads to adjacent channel interference, and decreases the transmit signal quality. To linearize power amplifiers, many techniques have been developed so far. Among the techniques, digital pre-distortion is known as the most cost and performance effective technique. However, the linearization performance falls down abruptly when the power amplifier operates in its saturation region. This is because of the severe nonlinearity. To relieve this problem, this paper proposes a new adaptive predistortion technique. The proposed technique controls the adaptive algorithm based on the power amplifier input level. Specifically, for small signals, the adaptive predistortion algorithm works normally. On the contrary, for large signals, the adaptive algorithm stops until small signals occur again. By doing this, wrong coefficient update by severe nonlinearity can be avoided. Computer simulation results show that the proposed method can improve the linearization performance compared with the conventional digital predistortion algorithms.