• Asian-Australasian Journal of Animal Sciences
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• v.17 no.7
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• pp.924-929
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• 2004

The objective of this study were to investigate the effect of ejaculation frequency on semen characteristics and to establish a method for quick assessment of sperm concentration in TCC using packed cell volume (PCV) as the parameter (Trial 1). Eighty senior roosters, averaging 61 wk-old, were used and the sperm concentrations were determined using a hemacytometer. The PCV value was measured in a capillary (0.75 mm in inner diameter) by centrifugation. A simple linear regression analysis suggested that the sperm concentrations were significantly correlated with PCV values (r=0.62, p<0.001). Trial 2 was conducted to determine the optimal ejaculation frequency of TCC roosters in a weekly semen collection program. The male birds were subjected to 1, 2, 3 or 6 ejaculations per week for four consecutive weeks and semen characteristics including ejaculation volume (EV, mL), sperm motility (%), PCV (%), sperm concentration (ESC, $\times$10$^{9}$/mL), weekly sperm production (WSP, $\times$10$^{9}$/wk) and average motile sperm numbers (AMSN, $\times$10$^{9}$/ejac) were determined. Average EV was greater in the group with 3 ejac/wk than with only 1 ejac/wk in weeks 1 and 3 of the collection period. WSP increased with ejaculation frequency during the first 3 weeks of collection (p<0.05). Sperm motility was better in the birds with 6 ejac/wk than in single ejaculation group for the first 2 wk and no significant differences were found for the last 2 wk of study. In contrast, the PCV value showed a trend of reduction for the first 2 wks in the 6 ejac/wk group. Surprisingly, no significant differences were detected in the AMSN among treatment groups. The weekly motile sperm production (WMSP) increased with ejaculation frequency. Based on our observation, PCV values could be used for a quick estimation of sperm concentration and an intensive semen collection program enhanced weekly sperm production in TCC roosters.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.3
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• pp.93-100
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• 2007

Since Koblitz and Miller suggested the use of elliptic curves in cryptography, there has been an extensive literature on elliptic curve cryptosystem (ECC). The use of ECC is based on the observation that the points on an elliptic curve form an additive group under point addition operation. To realize secure cryptosystems using these groups, it is very important to find an elliptic curve whose group order is divisible by a large prime, and also to find a base point whose order equals this prime. While there have been many dramatic improvements on finding an elliptic curve and computing its group order efficiently, there are not many results on finding an adequate base point for a given curve. In this paper, we propose an efficient method to find a random base point on an elliptic curve defined over $GF(p^m)$. We first show that the critical operation in finding a base point is exponentiation. Then we present efficient algorithms to accelerate exponentiation in $GF(p^m)$. Finally, we implement our algorithms and give experimental results on various practical elliptic curves, which show that the new algorithms make the process of searching for a base point 1.62-6.55 times faster, compared to the searching algorithm based on the binary exponentiation.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.245-248
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• 1997

Operative interventions for the management of osteonecrosis of the femoral head (ONFH) include core drilling, with or without vascularized fibular bone grafting. Nevertheless, their clinical results have not been consistently satisfactory. Recently, a new surgical procedure that incorporates cementation with polymethylmethacrylate (PMMA) after core drilling has been tried clinically. In this study, a biomechanical analysis using a finite element method(FEM) was undertaken to evaluate surgical methods and their underlying surgical parameter. Our finite element models included five types. They were (1) normal model (Type I), (2) necrotic model (Type II), (3) core decompressed model (Type III). (4) fibular bone grafted model (Type IV), and (5) cemented with PMMA model (Type V). The geometric dimensions of the femur were based on digitized CT-scan data of a normal person. Various physiological loading conditions and surgical penetration depths by the core were used as mechanical variables to study their biomechanical contributions in stress transfer within the femoral head region. In addition. the peak von Mises stress(PVMS) within the necrotic cancellous bone of the femoral head was obtained. The fibular bone grafted method and cementation method provided optimal stress transfer behaviors. Here. substantial increase in the low stress level was observed when the penetration depth was extended to 0mm and 5mm from the subchondral region. Moreover, significant decrease in PVMS due to surgery was observed in the fibular bone grafted method and the cementation method when the penetration depths were extended up to 0 and 5mm from the subchondral region. The drop in PVMS was greater during toe-off than during heel-strike (57% vs. 28% in Type IV and 49% vs. 22% in Type V). Both the vascularized fibular bone grafting method (Type IV) and the new PMMA technique (Type V) appear to be very effective in providing good stress transfer and reducing the peak Von-Mises stress within the necrotic region. Overall results show that fibular bone grafting and cementation methods are quite similar. In light of above results, the new cementation method appears to be a promising surgical alternative or the treatment of ONFH. The use of PMMA for the core can be less prone to surgical complication as opposed to preparation of fibular bone graft and can achieve more immediate fixation between the core and the surrounding region.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.6
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• pp.607-614
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• 2013

Nowadays, automotive manufacturers have developed various technologies to improve fuel economy and reduce harmful emissions. The ultra-lean direct injection engine is a promising technology because it has the advantage of improving thermal efficiency through the deliberate control of fuel and ignition. This study aims to investigate the development of a spray-guided-type lean-burn LPG direct injection engine through the redesign of the combustion system. This engine uses a central-injection-type cylinder head in which the injector is installed adjacent to the spark plug. Fuel consumption and combustion stability were estimated depending on the ignition timing and injection timing at various air-fuel ratios. The optimal injection timing and ignition timing were based on the best fuel consumption and combustion stability.

• Applied Biological Chemistry
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• v.43 no.2
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• pp.95-99
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• 2000

A series of hetero ring (X) substitued chalcone derivatives with farnesyl protein transferase (FPTase) inhibition activities $(pI_{50})$ values determined in vitro is analyzed by modified Free-Wilson (F-W) and Hansch method for quantitative structure activity relationship (QSARs). On the basis of F-W analysis on the FPTase inhibitory activity of a training set of the compounds, none of the (X)-substituents were not contribute the activity. But the net charge of ${\alpha}$ carbon atom is contribute the activity than that of ${\beta}$ carbon atom. And the relative orders of the (Y)-substituents on the activity are ortho>meta>para-substituents. According to Hansch approach, the activities would depend largely on the optimal, $(R_{opt.}=-0.35)$ resonance effect with ortho substituted $(I_o>0)$ electron donating group (R<0) and STERIMOL parameter, $B_1$ constant. The inhibition activity between hetro ring substituents have been a proportioned with each others and none substituent(H), 45 showed the highest FPTase inhibition $(pI_{50}=4.30)$ activity.

• The Korean Journal of Applied Statistics
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• v.33 no.5
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• pp.615-625
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• 2020

The document-term frequency matrix is a term extracted from documents in which the group information exists in text mining. In this study, we generated the document-term frequency matrix for document classification according to research field. We applied the traditional term weighting function term frequency-inverse document frequency (TF-IDF) to the generated document-term frequency matrix. In addition, we applied term frequency-inverse gravity moment (TF-IGM). We also generated a document-keyword weighted matrix by extracting keywords to improve the document classification accuracy. Based on the keywords matrix extracted, we classify documents using a deep neural network. In order to find the optimal model in the deep neural network, the accuracy of document classification was verified by changing the number of hidden layers and hidden nodes. Consequently, the model with eight hidden layers showed the highest accuracy and all TF-IGM document classification accuracy (according to parameter changes) were higher than TF-IDF. In addition, the deep neural network was confirmed to have better accuracy than the support vector machine. Therefore, we propose a method to apply TF-IGM and a deep neural network in the document classification.

• Journal of Environmental Impact Assessment
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• v.23 no.4
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• pp.296-314
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• 2014

In recent years, Ministry of Environment (MOE) has been implementing a phased strengthening of the effluent standards for sewage treatment plants. In this regard, a comprehensive system should be developed to help check the appropriateness of such standards by specifying the grounds for standard-setting and investigating the current operation of sewage treatment plants clearly. It is necessary to establish a new standard-setting system for the effluent that is in a closer connection with the environmental criteria and rating systems. In the United States, the federal government provides guidelines on the least provisions and requirements for the Publicly Owned Treatment Works (POTWs). Local governments set the same or stricter guidelines that reflect the characteristics of each state. In Japan, the sewage treatment plants are subject to both the effluent standards and the discharge acceptable limits to pubic waters under the sewerage law. Specific requirements and limits are set in accordance with local government regulations. The European Union imposes sewage treatment plants with different provisions for effluent standards, depending on the sensitivity of public waters to eutrophication. The effluent standards for sewage treatment plants are classified by pollutant loads discharged to receiving waters. MOE also needs to introduce systems for setting new parameter standards on a POTW effluent by applying statistical means and treatment efficiencies or optimal treatment techniques, as seen in the cases of the US National Pollutant Discharge Elimination System (NPDES) or the EU Integrated Pollution Prevention and Control (IPPC).

• The Journal of the Acoustical Society of Korea
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• v.24 no.3
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• pp.141-149
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• 2005

Tn general. Gaussian mixture model (GMM) is used to estimate the speaker model from the speech for speaker identification. The parameter estimates of the GMM are obtained by using the Expectation-Maximization (EM) algorithm for the maximum likelihood (ML) estimation. However the EM algorithm has such drawbacks that it depends heavily on the initialization and it needs the number of mixtures to be known. In this paper, to solve the above problems of the EM algorithm. we propose an EM algorithm with the initialization based on incremental ${\cal}k-means$ for GMM. The proposed method dynamically increases the number of mixtures one by one until finding the optimum number of mixtures. Whenever adding one mixture, we calculate the mutual relationship between it and one of other mixtures respectively. Finally. based on these mutual relationships. we can estimate the optimal number of mixtures which are statistically independent. The effectiveness of the proposed method is shown by the experiment for artificial data. Also. we performed the speaker identification by applying the proposed method comparing with other approaches.

• Journal of the Korea Society of Computer and Information
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• v.5 no.2
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• pp.30-36
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• 2000

The hidden node plays a role of the functional units that classifies the features of input pattern in the given question. Therefore, a neural network that consists of the number of a suitable optimum hidden node has be on the rise as a factor that has an important effect upon a result. However there is a problem that decides the number of hidden nodes based on back-propagation learning algorithm. If the number of hidden nodes is designated very small perfect learning is not done because the input pattern given cannot be classified enough. On the other hand, if designated a lot, overfitting occurs due to the unnecessary execution of operation and extravagance of memory point. So, the recognition rate is been law and the generality is fallen. Therefore, this paper suggests a method that decides the number of neural network node with feature information consisted of the parameter of learning algorithm. It excludes a node in the Pruning target, that has a maximum value among the feature value obtained and compares the average of the rest of hidden node feature value with the feature value of each hidden node, and then would like to improve the learning speed of neural network deciding the optimum structure of the multi-layer neural network as pruning the hidden node that has the feature value smaller than the average.

• Journal of Korea Water Resources Association
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• v.50 no.12
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• pp.827-836
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• 2017

The most important parameters of the Muskingum method, widely used in hydrologic river routing, are the storage coefficient and the weighting factor. The Muskingum method does not consider the lateral inflow from the upstream to the downstream, but the lateral inflow actually occurs due to the rainfall on the watershed. As a result, it is very difficult to estimate the storage coefficient and the weighting factor by using the actual data of upstream and downstream. In this study, the flow without the lateral inflow was calculated from the river flow through the hydraulic flood routing by using the HEC-RAS one-dimensional unsteady flow model, and the method of the storage coefficient and the weighting factor calculation is presented. Considering that the storage coefficient relates to the travel time, the empirical travel time formulas used in the establishment of the domestic river basin plan were applied as the storage coefficient, and the simulation results were compared and analyzed. Finally, we have developed a formula for calculating the travel time considering the flow rate, and proposed a method to perform flood routing by updating the travel time according to the inflow change. The rise and fall process of the flow rate, the peak flow rate, and the peak time are well simulated when the travel time in consideration of the flow rate is applied as the storage coefficient.