• International Journal of Industrial Entomology and Biomaterials
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• v.17 no.2
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• pp.205-209
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• 2008

Impact of food plant on reproductive and commercial parameters in Antheraea mylitta, a polyphagous insect of economic importance was studied upon feeding the insect larvae on the same host plants for six continuous generations. A. mylitta larvae were fed upon Terminalia tomentosa, Terminalia arjuna and Zizyphus jujuba and restricted them to the same host plant for six generations to document the quantitative improvement in reproductive and commercial parameters. The parameters showed significant improvement in all the host plants studied over their respective controls. Fecundity among the reproductive parameters was highly improved than others (85.9% in T. tomentosa; 58% in T. arjuna and 49.7% in Z. jujuba). Likewise in commercial parameters, the shell weight in male showed the highest improvement (by 52.9%, 45.8% and 42.1% in T. tomentosa; T. arjuna and Z. jujuba respectively). On the other hand, the shell ratio percentage in female recorded the lowest improvement. The values for all characters were recorded a decline in T. arjuna and Z. jujuba fed ones over T. tomentosa, except that of shell ratio percentage in female has registered an increase in Z jujuba fed. The study thus revealed the comparative superiority of T. tomentosa over T. arjuna and Z. jujuba.

• International Journal of Industrial Entomology and Biomaterials
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• v.7 no.2
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• pp.191-195
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• 2003

The impact of antibiotic (Norfloxacin) administration ,at different concentration (50 ppm and 100 ppm) on commercial characters of bivoltine $({CSR_2}{\times}{CR_4})$ and the cross breed race $({BL_67}{\times}{CSR_101})$ was studied. The result indicated that antibiotic administration with different concentrations significantly improved the rearing and cocoon parameters like larval duration, larval weight, growth index, single cocoon weight, single shell weight and shell ratio. The post cocoon parameters like average filament length, non-breakable filament length, raw silk percentage, raw silk recovery percentage, denier, reelability and neatness were recorded significantly higher in antibiotic treated batches. The better performances of these parameters were recorded with the increase of antibiotic concentration.

• Journal of Korean Physical Therapy Science
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• v.10 no.2
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• pp.17-28
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• 2003

The aim of this study was to investigate the effects of treadmill gait training on the functional characteristics and the temporal-distance parameters of gait in hemiplegic patients, as compared with conventional gait training. The subjects of this study were 32 hemiplegic patients who had been admitted or were visited out-patients at Kangdong Sacred Heart Hospital, Hallym University, from March 3 through April 25, 2003. These subjects were randomly divided into treadmill gait training group or conventional gait training group. We evaluated the gait ability, motor functions, muscle strength, spasticity, physiological cost index, and temporal-distance parameters. We analyzed the changes between pre and post training in each groups, and the difference between two groups. Temporal-distance parameters were obtained using the ink footprint method and then energy consumption using physiological cost index. The results were as follows: 1. After a six-week training, treadmill gait training group significantly improved, as. compared to pre-training, in gait ability, motor functions for the leg and trunk and gross function, muscle strength of the lower limb, gait speed, cadence, step length both on the affected and on the unaffected side, step length symmetry, and energy consumption(p<0.05). 2. After a six-week training, conventional gait training group significantly improved, as compared to pretraining, in gait ability, motor functions for the leg and trunk, muscle strength of the lower limb, spasticity the upper limb, gait speed, cadence, step length both on the affected and on the unaffected side, and energy consumption(p<0.05). 3. After a six-week training, the treadmill gait training group significantly improved, as compared to the conventional gait, training, in gait speed and step length on the unaffected side. These results show that treadmill gait training was improved gait speed and step length on the unaffected side of hemiplegic patients, as compared with conventional gait training. Further research is needed to confirm the generalization of these findings and to identify which hemiplegic patients might benefit from treadmill gait training.

• The Journal of Korean Physical Therapy
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• v.26 no.3
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• pp.196-201
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• 2014

Purpose: The novelty of intensive mobility training (IMT) is its intensive nature. The purpose of this study was to examine the effect of IMT in patients with Parkinson's disease. Methods: Subjects participated in 3 hours/day for ten days (30 hours). Gait parameters of interest were the timed up-and-go test, 10-m walk test, and step length and width. Measures were made at baseline before commencement of training (pre-training) and at the end of the two-week training period (post-training). Results: Seven patients with Parkinson's disease enrolled in the study. On average, participants are able to tolerate 141 minutes of activity during a 180-minute session. Results showed that, after 10 consecutive days training, subjects significantly improved for all parameters; the timed up-and-go test, 10-m walk test, and stride length and step width. Conclusion: This study's findings show that gait properties in patients with Parkinson's disease can be improved with IMT.

• Speech Sciences
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• v.11 no.4
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• pp.43-52
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• 2004

Model parameters in HMM based speech recognition systems are normally estimated using Maximum Likelihood Estimation(MLE). The MLE method is based mainly on the principle of statistical data fitting in terms of increasing the HMM likelihood. The optimality of this training criterion is conditioned on the availability of infinite amount of training data and the correct choice of model. However, in practice, neither of these conditions is satisfied. In this paper, we propose a training algorithm, MCE(Minimum Classification Error), to improve the performance of a speech recognizer detecting mispronunciation of a foreign language. During the conventional MLE(Maximum Likelihood Estimation) training, the model parameters are adjusted to increase the likelihood of the word strings corresponding to the training utterances without taking account of the probability of other possible word strings. In contrast to MLE, the MCE training scheme takes account of possible competing word hypotheses and tries to reduce the probability of incorrect hypotheses. The discriminant training method using MCE shows better recognition results than the MLE method does.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.2
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• pp.200-206
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• 2012

The changes in physiologic parameters by swim exercise duration were examined in five female well-trained Jeju crossbred riding horses that had riding experience of more than three years without swim training experience. The horses were performed with swim exercise for 10 min (60.0 m/min) once a day for 14 days. Physiologic characteristics and haematic parameters were measured before swimming, immediately after swimming, and after a 10 min rest at first day ($D_0$), 7 days ($D_7$), and 14 days ($D_{14}$) of training. After 14 days of swim training, heart rate (p<0.05), blood glucose (p<0.05), lactate concentration (p<0.001), packed cell volume (p<0.01), and hemoglobin (p<0.01) measured immediately after swim and after 10 min rest showed significant lower values than those of $D_0$. The results illustrate the benefits of swim training for riding horses and the need for the establishment of swimming routines of appropriate duration and intensity to maximize the advantages of swim training.

• Journal of IKEEE
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• v.22 no.1
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• pp.14-20
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• 2018

The purpose of training a convolutional neural network (CNN) is to obtain weight factors that give high classification accuracies. The initial values of hyper-parameters affect the training results, and it is important to train a CNN with a suitable hyper-parameter set of a learning rate, a batch size, the initialization of weight factors, and an optimizer. We investigate the effects of a single hyper-parameter while others are fixed in order to obtain a hyper-parameter set that gives higher classification accuracies and requires shorter training time using a proposed VGG-like CNN for training since the VGG is widely used. The CNN is trained for four datasets of CIFAR10, CIFAR100, GTSRB and DSDL-DB. The effects of the normalization and the data transformation for datasets are also investigated, and a training scheme using merged datasets is proposed.

• The Journal of Korean Physical Therapy
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• v.27 no.5
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• pp.364-368
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• 2015

Purpose: Walking in the dual-task condition is a critical skill for hemiplegic patients to live in real-life situations. The purpose of this study was to compare the effect of dual-task gait training and general gait training on gait parameters and cognitive function in patients with chronic stroke during dual-task walking. Methods: The study included 23 patients with chronic hemiparetic stroke who were randomly divided into experimental (dual-task gait training) and control (general walking training) groups. The 11 subjects in the experimental group and nine subjects in the control group received dual-task gait training (walking while handling a ball, crossing obstacles, picking up various objects, and problem solving simple cognitive tasks and general over-ground gait training, respectively, for 30 minutes per day 5 days per week for 4 weeks. Spatiotemporal parameters and cognitive tasks in the dual-task gait condition were measured. Statistical analysis of the changes between the pre- and post-intervention measurement variables was performed using ANCOVA. Results: In the gait condition under cognitive tasks, the changes pre- and post-intervention in gait velocity, stride length, double support limb, and step symmetry were significantly greater in the dual-task gait training group; however, the dual-task gait training group showed no significant improvement compared to the general gait training group in terms of the assessment of cognitive tasks. Conclusion: The findings suggest that dual-task gait training may be beneficial for walking ability in dual-task walking condition.

• Tuberculosis and Respiratory Diseases
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• v.38 no.4
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• pp.379-383
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• 1991

To evaluate the effect of intensive training on ventilatory functions in soccer players, comparisons of various ventilatory parameters were made before and after 5-5.5 months of intensive training. The subjects were 15 members of a university soccer team with mean age and career of 19.9 and 8.3 years, respectively. Ventilatory parameters studied were those obtained by the analyses of forced expiratory volume and maximal expiratory flow-volume curves, as well as spirometric measurements of VC and MVV. After intensive training, volume parameters, such as VC, FVC and $FEV_{1&3}$ as well as flow parameters, effort-dependent and effort-independent, such as MVV, FEF200-1200, FEF25-75%, PEF, FEF25%, FEF50%, FEF75% showed significant increase. However, when the observed values of flow parameters were volume-adjusted to FVC, the differences before and after intensive training became insignificant. This suggests that enhanced ventilatory functions in soccer players after intensive training are primarily due to increase in FVC caused by increase in respiratory musle strength.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.51-59
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• 2019

Due to the exponential growth of access information on the web, the need for predicting web users' next access has increased. Various models such as markov models, deep neural networks, support vector machines, and fuzzy inference models were proposed to handle web access prediction. For deep learning based on neural network models, training time on large-scale web usage data is very huge. To address this problem, deep neural network models are trained on cluster of computers in parallel. In this paper, we investigated impact of several important spark parameters related to data partitions, shuffling, compression, and locality (basic spark parameters) for training Multi-Layer Perceptron model on Spark standalone cluster. Then based on the investigation, we tuned basic spark parameters for training Multi-Layer Perceptron model and used it for tuning Spark when training Multi-Layer Perceptron model for web access prediction. Through experiments, we showed the accuracy of web access prediction based on our proposed web access prediction model. In addition, we also showed performance improvement in training time based on our spark basic parameters tuning for training Multi-Layer Perceptron model over default spark parameters configuration.