• Korean Journal of Applied Biomechanics
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• v.20 no.1
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• pp.67-73
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• 2010

The purpose of this study was to compare the differences in kinematic and kinetic parameters of the ankle and knee joint according to three landing direction(central, left, right). Fifteen collegiate male athletes(age: $22.7{\pm}3.5$ years, height: $174.9{\pm}7.1\;cm$, weight: $69.4{\pm}6.7\;kg$) with the right leg as dominant were chosen. The subjects performed series of drop landings in three directions. In terms of the three different landing directions, plantar flexion was the greatest during the central drop landings. For each initial contact of the landing direction, plantar flexion of the ankle was greatest at the central drop landing, inversion of the ankle was greatest at the right landing and valgus of the knee was greatest at the left drop landing. Regarding the peak force, the greatest was at the 1st peak force during the central drop landing. For the time-span of the 2nd peak force and the 2-1 peak force, both right sides resulted as the greatest. Therefore, with the appropriate training in landing techniques and developing neuromuscular training for proprioception by taking the injury mechanisms on ankle and knee during drop landings into account, it will assist in preventing such injuries.

• International Journal of Industrial Entomology and Biomaterials
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• v.13 no.1
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• pp.15-22
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• 2006

An experiment was conducted to study the efficiency of cyanobacterial biofertilizer (CBB) with chemical (NPK) fertilizer on quantitative and qualitative characters of mulberry variety Kanva-2. Their influences on silkworm growth and cocoon characters were also studied. Ten different CBB and NPK fertilizer treatments were given to 5000 plants of established mulberry garden. Treatments were of four types viz., (i) T1 to T7: single and combination dose of CBB+50% NPK (ii) T8: combination dose of CBB + 25%NPK, (iii) T9: CBB only and (iv) T10: control-l00% NPK. Soil pH decreased and nutrients status increased in CBB (T1- T9) treated plots. Average of ten crops data on quantitative traits revealed that T7 (CBB [N. muscorum (1.0 g), A. variahilis (1.0) and S. millei (1.0 g)] + 50% NPK) was very effective in improving growth parameters. Leaf yield was also found high in treatment T7 (32.12 tons/ha/yr.) followed by T10 (31.17 tons/ha/yr.) and T8 (27.67 tons/ha/yr.). Leaf quality characters were found high in T7 and low in T9. Most of the quality traits in T7 are on par with control no. The results revealed that reduction in the dose of chemical fertilizers in T7 did not affect the leaf yield and leaf quality traits of mulberry. This clearly indicates that the efficiency of CBB (T7) provides nitrogen, increases essential nutrients available in soil, maintain soil pH and supply growth substances required for the improvement of leaf yield and leaf quality of mulberry. Bioassay study also revealed no significant difference in silkworm growth and cocoon characters between treatments T7 and T10. Economics calculated revealed that T7 is highly economical and beneficial over T10 by gaining an amount of Rs. 660/-/acre/crop. Thus, treatment T7 containing N. muscorum (1.0 g), A. variahilis (1.0 g) and S. millei (1.0 g) + 50% NPK fertilizers can be recommended to sericulturists mainly to reduce the use of NPK fertilizers, by saving 50% of its cost and to improve soil fertility conditions, which in turn improves leaf yield and quality of mulberry.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.12
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• pp.1865-1870
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• 2010

We develop an IPMC actuator with self-sensing behavior based on an accurate neural network model (NNM). The supplied voltage and voltage signals measured at two determined points on both sides of the IPMC sheet are used as inputs to the NNM. A CCD laser displacement sensor is installed in the rig for accurate measurement of the IPMC tip displacement that is used as the training output of the proposed NNM. Consequently, the NNM model is used to estimate the IPMC tip displacement; the NNM parameters are optimized by the collected input/output training data. The effectiveness of the model for the IPMC actuator is then verified by modeling results.

• International Journal of Industrial Entomology and Biomaterials
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• v.14 no.1
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• pp.15-21
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• 2007

Three newly authorized bivoltine silkworm hybrids namely, $CSR2{\times}CSR4$ (productive single hybrid), $(CSR6{\times}CSR26){\times}(CSR2{\times}CSR27)$ (productive double hybrid) and $CSR18{\times}CSR19$ (robust single hybrid) were chosen for the present study. These hybrids were subjected to different temperature and humidity treatments i.e., $25{\pm}$1^{\circ}C and RH $65{\pm}5%$ (control), $30{\pm}1^{\circ}C$, with combinations of low relative humidity (RH $65{\pm}5%$) and high RH ($85{\pm}5%$) at different stages during rearing and spinning of silkworm larvae. The larvae of after 3rd moult were subjected to different thermal and humidity stress till the assessment of cocoon traits. The comparative rearing and reeling performance clearly indicated that the deleterious effect of high temperature and high RH was more pronounced for the majority of traits such as cocoon uniformity, cocoon weight, shell weight, shell percentage, reelability, filament length, raw silk percentage raw silk recovery denier and waste percentage on silk weight than other temperature and RH treatments and this effect was almost similar for all three silkworm hybrids studied. The present investigation clearly indicate that the deleterious effect of high temperature and high RH was more pronounced on rearing and spinning of silkworm larvae than other temperature and RH treatments and similar effect was noticed for all the three silkworm hybrids studied. The cocoon characters can be improved by providing ideal environmental conditions even during spinning stage of larvae affected with high temperature and RH. The study also suggest that high temperature and low humidity has greater effect during rearing stage than spinning stage.

• Asian-Australasian Journal of Animal Sciences
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• v.7 no.4
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• pp.571-582
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• 1994

Three livestock/crop demonstration-cum-training farms have been established on plots of half, one and two acres, typical of the "Kandyan Forest Garden System" Vegetables, bananas, pepper, coffee, coconut and fruit trees are widely spaced, for intercropping with grass, and have been surrounded with live fences that also provide fodder for livestock to increase the family income. Each unit is operated by a selected employee and his family under a monthly incentive scheme based upon the gross margin. On these farms the technical parameters in dairying are better than elsewhere in the Mid-Country. Economic performance over 1985-1992 showed that dairying contributed most to the total gross margin of the half, one and two acre units, i.e. 31, 63 and 69%, respectively. Next came crops (29%, 37% and 19%), poultry (22%, 0% and 9%), and goats (18%, 0% and 3%). In the three farms the cash income per Sri Lankan Rupee spent was 1.5, 4.6 and 2.1, respectively. The overall ratio was 3.2 for dairying, 1.1 for poultry, 4.5 for goats and 9.9 for crops. Actual family labour in the three farms was 548, 548 and 639 days, compared to the 270, 330 and 440 days anticipated in the initial feasibility study. The average incentive payments, which were 20% (half acre), 61% (one acre) and 133% (two acres) of the parastatal salary of the employee, were only insufficient for the extra labour applied in the half acre unit. Dairying and goats proved to be attractive cash earners with a domestic fuel were important benefits. Poultry did little to improve farm income.

• Journal of Biomedical Engineering Research
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• v.38 no.1
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• pp.25-31
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• 2017

Testing TB in chest X-ray images is a typical method to diagnose presence and magnitude of PTB lesion. However, the method has limitation due to inter-reader variability. Therefore, it is essential to overcome this drawback with automatic interpretation. In this study, we propose a novel method for detection of PTB using SegNet, which is a deep learning architecture for semantic pixel wise image labelling. SegNet is composed of a stack of encoders followed by a corresponding decoder stack which feeds into a soft-max classification layer. We modified parameters of SegNet to change the number of classes from 12 to 2 (TB or none-TB) and applied the architecture to automatically interpret chest radiographs. 552 chest X-ray images, provided by The Korean Institute of Tuberculosis, used for training and test and we constructed a receiver operating characteristic (ROC) curve. As a consequence, the area under the curve (AUC) was 90.4% (95% CI:[85.1, 95.7]) with a classification accuracy of 84.3%. A sensitivity was 85.7% and specificity was 82.8% on 431 training images (TB 172, none-TB 259) and 121 test images (TB 63, none-TB 58). This results show that detecting PTB using SegNet is comparable to other PTB detection methods.

• The Journal of the Acoustical Society of Korea
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• v.15 no.6
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• pp.59-65
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• 1996

This paper proposes a 4 kbps PSI-VSELP(Pitch Synchronous Innovation-Vector Sum Excited Linear Prediction) speech coder which produces speech equivalent to that of the conventional 4.8 kbps VSELP. Since the 'half-rate' is differently defined from country to country, there may be a need to reduce the bit rate of conventional half-rate coder. To minimize the degradation of speech quality caused by bit-rate reduction, it is desirable to perform bit-allocation based on the carefull consideration of the effect of various transmission parameters. This paper adopts this analytical approach for bit-allocation at 4 kbps. To improve the quality of the VSELP coder at 4 kbps, basis vectors which play the most important role in the performance, are optimized by an iterative closed-loop training process and the PSI technique is employed in the VSELP performance, are optimized by an iterative closed-loop training process and the PSI technique is employed in the VSELP coder. To demonstrate the performance of the proposed speech coder, we peformed experiments under the noiseless and error free conditions. From experimental results, even though the proposed 4 kbps PSI-VSELP coder showed lower scores in the objective measure, higher scores in subjective measure was obtained compared with those of the conventional 4.8 kbps VSELp.

• Journal of the Korean Society for information Management
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• v.33 no.2
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• pp.33-59
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• 2016

This study examined the factors affecting the performance of automatic classification for the domestic conference papers based on machine learning techniques. In particular, In view of the classification performance that assigning automatically the class labels to the papers in Proceedings of the Conference of Korean Society for Information Management using Rocchio algorithm, I investigated the characteristics of the key factors (classifier formation methods, training set size, weighting schemes, label assigning methods) through the diversified experiments. Consequently, It is more effective that apply proper parameters (${\beta}$, ${\lambda}$) and training set size (more than 5 years) according to the classification environments and properties of the document set. and If the performance is equivalent, I discovered that the use of the more simple methods (single weighting schemes) is very efficient. Also, because the classification of domestic papers is corresponding with multi-label classification which assigning more than one label to an article, it is necessary to develop the optimum classification model based on the characteristics of the key factors in consideration of this environment.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.18 no.10
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• pp.965-975
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• 2005

In the case of the fault in stator windings of a high voltage motor. it facilitates certain destructive characteristics in insulations. This will result in a decreased reliability in power supplies and will prevent the generation of electricity, which will result in huge economic losses. This study simulates motor windings using normal windings and four faulty windings for an actual fault in stator winding of a high voltage motor. The partial discharge signals produced in each faulty winding were measured using an 80 PF epoxy/mica coupler sensor. In order to quantified signal waves its a way of feature extraction for each faulty signal, the signal wave of winding was quantified to measure the degree of skewness shape and kurtosis, which are both types of statistical parameters, using a discrete wavelet transformation method for each faulty type. Wave types present different types lot each faulty type, and the skewness and kurtosis also present different quantified values. The result of feature extraction was used as a preprocessing stage to identify a certain fault in stater windings. It is evident that the type of faulty signals can be classified from the test results using faulty signals that were randomly selected from the signal, which was not applied in the training after the training and learning period, by applying it to a back-propagation algorithm due to the supervising and learning method in a neural network in order to classify the faulty type. This becomes an important basis for studying diagnosis methods using the classification of faulty signals with a feature extraction algorithm, which can diagnose the fault of stator windings in the future.

• Journal of the Society of Naval Architects of Korea
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• v.51 no.4
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• pp.274-282
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• 2014

Time series of the dynamic response of a slender marine structure was predicted using quadratic Volterra series. The wave-structure interaction system was identified using the NARX(Nonlinear Autoregressive with Exogenous Input) technique, and the network parameters were determined through the supervised training with the prepared datasets. The dataset used for the network training was obtained by carrying out the nonlinear finite element analysis on the freely standing riser under random ocean waves of white noise. The nonlinearities involved in the analysis were both large deformation of the structure under consideration and the quadratic term of relative velocity between the water particle and structure in Morison formula. The linear and quadratic frequency response functions of the given system were extracted using the multi-tone harmonic probing method and the time series of response of the structure was predicted using the quadratic Volterra series. In order to check the applicability of the method, the response of structure under the realistic ocean wave environment with given significant wave height and modal period was predicted and compared with the nonlinear time domain simulation results. It turned out that the predicted time series of the response of structure with quadratic Volterra series successfully captures the slowly varying response with reasonably good accuracy. It is expected that the method can be used in predicting the response of the slender offshore structure exposed to the Morison type load without relying on the computationally expensive time domain analysis, especially for the screening purpose.