• Journal of Information Processing Systems
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• v.13 no.4
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• pp.893-913
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• 2017

The handwriting based person identification systems use their designer's perceived structural properties of handwriting as features. In this paper, we present a system that uses those structural properties as features that graphologists and expert handwriting analyzers use for determining the writer's personality traits and for making other assessments. The advantage of these features is that their definition is based on sound historical knowledge (i.e., the knowledge discovered by graphologists, psychiatrists, forensic experts, and experts of other domains in analyzing the relationships between handwritten stroke characteristics and the phenomena that imbeds individuality in stroke). Hence, each stroke characteristic reflects a personality trait. We have measured the effectiveness of these features on a subset of handwritten Devnagari and Latin script datasets from the Center for Pattern Analysis and Recognition (CPAR-2012), which were written by 100 people where each person wrote three samples of the Devnagari and Latin text that we have designed for our experiments. The experiment yielded 100% correct identification on the training set. However, we observed an 88% and 89% correct identification rate when we experimented with 200 training samples and 100 test samples on handwritten Devnagari and Latin text. By introducing the majority voting based rejection criteria, the identification accuracy increased to 97% on both script sets.

• International Journal of Industrial Entomology and Biomaterials
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• v.8 no.2
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• pp.201-205
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• 2004

During the routine survey, the mortality of mulberry seedlings was noticed due to damping-off disease. The disease recognized by rotting of emerged seedlings near the soil line (just below the soil level) resulting in collapse of the seedlings. Two fungi were isolated from affected samples and identified as Alternaria alternata (Fr.) Keissler and Fusarium solani (Mart.) Sacc. Both the fungi were found to be responsible in causing pre and post emergence damping-off of seedlings in mulberry. For management of the disease, an experiment was conducted using fungicides. These fungicides were applied as seed treatment; soil drenching and foliar spray alone and in combination. Among the different treatments, integration of seed treatment and soil application of Dithane M-45 (Mancozeb 75% WP) + Bavistin (Carbendazim 50% WP) followed by foliar spray of these fungicides (after 35 days of sowing) resulted in better survivability of seedlings (93.3 %) on $90^th$ day and controlled the pre and post emergence damping off by 100 and 89.5%, respectively over the check.

• Korean Journal of Remote Sensing
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• v.20 no.5
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• pp.353-359
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• 2004

This study proposes an approach to unsupervisedly estimate the number of classes and the parameters of defining the classes in order to train the classifier. In the proposed method, the image is segmented using a spatial region growing based on hierarchical clustering, and fuzzy training is then employed to find the sample classes that well represent the ground truth. For cluster validation, this approach iteratively estimates the class-parameters in the fuzzy training for the sample classes and continuously computes the log-likelihood ratio of two consecutive class-numbers. The maximum ratio rule is applied to determine the optimal number of classes. The experimental results show that the new scheme proposed in this study could be used to select the regions with different characteristics existed on the scene of observed image as an alternative of field survey that is so expensive.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.123-124
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• 2019

This paper proposes an improved deep learning method based on small data sets for animal image classification. Firstly, we use a CNN to build a training model for small data sets, and use data augmentation to expand the data samples of the training set. Secondly, using the pre-trained network on large-scale datasets, such as VGG16, the bottleneck features in the small dataset are extracted and to be stored in two NumPy files as new training datasets and test datasets. Finally, training a fully connected network with the new datasets. In this paper, we use Kaggle famous Dogs vs Cats dataset as the experimental dataset, which is a two-category classification dataset.

• Korean Journal of Exercise Nutrition
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• v.13 no.2
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• pp.141-145
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• 2009

The purpose of this study was to investigate the effect of endurance training and Rooibos-tea treatment during 12 week on lipid peroxidation(MDA), oxidative DNA damage(8-hydroxyguanine), and antioxidant enzymes(SOD, GPX) in human. The subjects were divided into three groups; Train+Rooi, Train, and Rooi groups. The Train+Rooi and Rooi group took 3 g of Rooibos-tea for 12 weeks. Blood samples were taken from antecubital vein at before training, after 6week, and after 12 week training. Data were analyzed by two-way ANOVA with repeated measures using the SPSS/PC⁺. The results are summarized as follows: MDA and 8-hydroxyguanine concentration were no significantly differences between group(p>.05). SOD and GPX concentration were significantly increased in Train+Rooi, Rooi group than Train group(p<.05). This results suggested that effects of Rooibos-tea treatment has associated with improve scavenger of antioxidant.

• Korean Journal of Environmental Biology
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• v.29 no.3
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• pp.208-211
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• 2011

The lowest amount of heavy metals was found outside the city (25 km away), the highest amount was found near the thermoelectric power plant, and the average amount was discovered in the central part of the city. The presence of heavy metals in soil samples resulted in reduction of several important soil characteristics (pH, humus content, soil "breathing"). Use of simple and quick methods to examine soil with high heavy metals pollution resulted in the discovery of a pedobiota group, consisting of nematodes, fungi (genus Fusarium) and Protozoa which indicated the toxicity of the Almaty city soils.

• Journal of Dairy Science and Biotechnology
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• v.27 no.2
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• pp.37-41
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• 2009

Sensory analysis of milk and milk products is widely appreciated, and there is a demand for experts with these skills in the dairy industry. To this end, it is important to understand the basic principles of sensory analysis and impart training to facilitate the development of dairy food industry. This paper addresses the ISO 22935/IDF 99 guidelines on the methodology of sensory analysis of milk and milk products, training procedures and monitoring of selected assessors, and criteria for sampling and preparation of dairy samples and their assessment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2A
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• pp.85-90
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• 2009

In this paper, as an alternative to constant modulus algorithm based on MSE, maximization of the probability that equalizer output power is equal to the constant modulus of the transmitted symbols is introduced. The proposed algorithm using the gradient ascent method to the maximum probability criterion has superior convergence and steady-state MSE performance, and the error samples of the proposed algorithm exhibit more concentrated density functions in blind equalization environments. Simulation results indicate that the proposed training has a potential advantage versus MSE training for the constant modulus approach to blind equalization.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.995-1004
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• 2020

This study aims to analyze the effect of transformational leadership (TL), procedural justice (PJ), and training (T) on employee performance (EP) mediated by self-efficacy (SE). The object of this research is Rumah Sakit Umum Daerah (RSUD) M.Th. Djaman, a hospital in Sanggau Regency, while the subjects are the institution's staff. Data collection search uses purposive sampling with a total of 120 samples. Data are obtained through questionnaires distributed directly to respondents using the Google Form application. Data analysis techniques used in this study include standard error of mean (SEM) with AMOS software version 24.00. Methods use to test validity and reliability of data include Confirmatory Factor Analysis (CFA), Construct Reliability (CR) and VE. The results of the analysis show that only training has a significant effect on self-efficacy, and self-efficacy has a significant effect on employee performance. Also, self-efficacy is proven to mediate the role of training on employee performance; the other hypotheses are not significant. Training is the most prominent positive factor affecting self-efficacy and self-efficacy has a significant effect on employee performance at RSUD M.Th. Djaman. The results of this study can be used as a reference by management in determining what policy priorities should take precedence.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.443-450
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• 2020

This study aims to add insight into the effectiveness of e-training, e-leadership, work-life balance, and work motivation on millennial generation employees' performance in today's work life amid the outbreak of the COVID-19 pandemic that requires to work more online. Unlike previous generations, millennials are technology-literate, intent on succeeding quickly, give up easily, and seek instantaneous gratification. The population in this study are millennial generation employees at one of Honda motorcycle dealers in Jakarta, Indonesia. The number of samples collected was 200. The sampling technique used is the side probability method, with proportional random sampling technique. The research method used is an associative quantitative approach through survey methods and Structural Equation Modeling. Data were collected through questionnaires distributed to millennial generation employees, with results then processed through the Lisrel 8.5 program. The results of this study show, first, that e-training, e-leadership, and work-life balance have positive effect on work motivation. Second, e-training, e-leadership, work-life balance, and work motivation have positive effect on employees' performance. The findings indicate that companies must pay attention to the factors of e-training, e-leadership, and work-life balance to keep employees motivated and to maintain optimal employee performance, especially during the COVID-19 pandemic through working online.