• IE interfaces
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• v.25 no.3
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• pp.283-289
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• 2012

M/G/1 queue with server vacations period depending on the previous vacation and customer's arrival is considered. Most existing studies on M/G/1 queue with server vacations assume that server vacations are independent of customers' arrival. However, some vacations are terminated by some class of customers' arrival in certain queueing systems. In this paper, therefore, we investigate M/G/1 queue with server vacations where each vacation period has different distribution and vacation length is influenced by customers' arrival. Laplace-Stieltjes transform of the waiting time distribution and the distribution of number of customers waiting for each class of customers are respectively derived. As performance measures, mean waiting time and average number of customers waiting for each class of customers are also derived.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.675-679
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• 2001

In this paper, we present a new competitive learning algorithm called Dynamic Competitive Learning (DCL). DCL is a supervised learning method that dynamically generates output neurons and initializes automatically the weight vectors from training patterns. It introduces a new parameter called LOG (Limit of Grade) to decide whether an output neuron is created or not. If the class of at least one among the LOG number of nearest output neurons is the same as the class of the present training pattern, then DCL adjusts the weight vector associated with the output neuron to learn the pattern. If the classes of all the nearest output neurons are different from the class of the training pattern, a new output neuron is created and the given training pattern is used to initialize the weight vector of the created neuron. The proposed method is significantly different from the previous competitive learning algorithms in the point that the selected neuron for learning is not limited only to the winner and the output neurons are dynamically generated during the learning process. In addition, the proposed algorithm has a small number of parameters, which are easy to be determined and applied to real-world problems. Experimental results for pattern recognition of remote sensing data and handwritten numeral data indicate the superiority of DCL in comparison to the conventional competitive learning methods.

• 전기의세계
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• v.16 no.2
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• pp.1-8
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• 1967

From the discovery of Alago's disk, a number of trials and efforts have been concentrated on a small-sized and light-weighted induction motor. They have devoted themseleves, however, mainly to a improvement of cooling effect, a proper weight-distribution of copper and iron and desirable number of slots. In consequence, such an effort restricted only to the field of design, has resulted in unsatisfactory developments in the insulating materials consisting of the main parts of an induction motor. The quality of fibre and paper which are used as class-A insulation materials with their "compound" and "varnish" has been increased to some extent. Similarly Class-B insulation materials like asbest mica has been almost a combination of inorganic and binding materials. But nowadays synthesic chemistry is making a remarkable progress. So it comes possible for us to have silicon resin and other good ones of similar charateristics. And even a thin silicon resin insures us to get excellent heat-pro f and insulation, so a better space factor and cost-down in motor design have come possible in most advanced nations of the world, but not in our country. Furthermore, a consideration of productivity and economy in manufacturing process has been neglected by a majority of engineers. This is more unpleasant und more undesirable. I think this rational method of induction motor design using new synthesic resin will devote in making your productivity and economy better. And the nation-wide standard value of electric motor size is sited here. size is sited here.

• Korean Journal of Remote Sensing
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• v.18 no.3
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• pp.155-162
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• 2002

Neural networks have been focused on as a robust classifier for the remotely sensed imagery due to its statistical independency and teaming ability. Also the artificial neural networks have been reported to be more tolerant to noise and missing data. However, unlike the conventional statistical classifiers which use the statistical parameters for the classification, a neural network classifier uses individual training sample in teaming stage. The training performance of a neural network is know to be very sensitive to the discrepancy of the number of the training samples of each class. In this paper, the effect of the population discrepancy of training samples of each class was analyzed with three layered feed forward network. And a method for reducing the effect was proposed and experimented with Landsat TM image. The results showed that the effect of the training sample size discrepancy should be carefully considered for faster and more accurate training of the network. Also, it was found that the proposed method which makes teaming rate as a function of the number of training samples in each class resulted in faster and more accurate training of the network.

• Acta Via Serica
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• v.6 no.1
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• pp.31-54
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• 2021

Radicalisation has become an important issue for the Kyrgyz Republic with an increasing number of individuals leaving the country for conflict zones. The government of the Kyrgyz Republic adopted a number of policies to prevent radicalisation and violent extremism among youth. One of these measures is piloting a new subject, titled, History of Religious Culture, (История религиозной культуры) in public schools. The analysis in this paper aims to explore the experiences of teachers, who have taught the new class. The article also examines any differences in the level of resilience of pupils in schools, piloting and not piloting the new subject, towards radicalisation and violent extremism. Data used in this article comes from a survey with 760 adolescents across public schools in six regions of the country and key informant interviews with teachers who have taught the new class. Qualitative findings showed a positive experience of teachers who reported expanding their pupils' and their own knowledge of various religions. Quantitative findings indicate that the new class, History of Religious Culture, may have had a positive impact on violence-related beliefs in pilot schools that reported views less supportive of violence. The study concludes that the government's response to radicalisation and violent extremism has expanded beyond a security approach by including education. This, however, poses a risk of securitising education.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.591-609
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• 2024

In this study, preprocessings with all combinations were examined in terms of the effects on decreasing word number, shortening the duration of the process and the classification success in balanced and imbalanced datasets which were unbalanced in different ratios. The decreases in the word number and the processing time provided by preprocessings were interrelated. It was seen that more successful classifications were made with Turkish datasets and English datasets were affected more from the situation of whether the dataset is balanced or not. It was found out that the incorrect classifications, which are in the classes having few documents in highly imbalanced datasets, were made by assigning to the class close to the related class in terms of topic in Turkish datasets and to the class which have many documents in English datasets. In terms of average scores, the highest classification was obtained in Turkish datasets as follows: with not applying lowercase, applying stemming and removing stop words, and in English datasets as follows: with applying lowercase and stemming, removing stop words. Applying stemming was the most important preprocessing method which increases the success in Turkish datasets, whereas removing stop words in English datasets. The maximum scores revealed that feature selection, feature size and classifier are more effective than preprocessing in classification success. It was concluded that preprocessing is necessary for text classification because it shortens the processing time and can achieve high classification success, a preprocessing method does not have the same effect in all languages, and different preprocessing methods are more successful for different languages.

• Korean Journal of Environment and Ecology
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• v.20 no.4
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• pp.415-424
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• 2006

This study was carried out to analyze the characteristics of forest watershed factors by using the quantification theory(I) for evaluation and prediction of the failure hazard area. Present $sediment(m^3/yr/ha)$ of erosion control dams were investigated in 95 sites of erosion control dam constructed during 1986 to 1999 in Gyeongnam province. The results obtained from this study were summarized as follows; General condition of class I(Very hazard area) were as follow; Igneous rock in parent rock, coniferous in forest type, below 20year in stand age, below 30cm in soil depth, SCL in soil texture, $31{\sim}40%$ in gravel contents, $S{\sim}E$ in aspect, $2,501{\sim}3,600m$ in length of main stream, $26{\sim}30$ in number of total streams, $6,601{\sim}10,000m$ in length of total streams, over 3 in stream order, over 16 in number of first streams order and over $31^{\circ}$ of slope gradient. General condition of class IIl(hazard area) were as follow; Metamorphic rock in parent rock, hardwood in forest type, over $21{\sim}24year$ in stand age, $31{\sim}40cm$ in soil depth, SiCL or SCL in soil texture, $11{\sim}20%$ in gravel contents, $S{\sim}W$ in aspect, $1,501{\sim}2,600m$ in length of main stream, $6{\sim}10$ in number of total streams, $3,501{\sim}5,500m$ in length of total streams, 2 in stream order, $6{\sim}10$ in number of first streams order and over $31^{\circ}$ of slope gradient. General condition of class III(Un hazard area) were as follow; Sedimentary rock in parent rock, mixed in forest type, over 25year in stand age, $41{\sim}50cm$ in soil depth, SiCL in soil texture, below 10% in gravel contents, $N{\sim}W$ in aspect, below 500m in length of main stream, below 5 in number of total streams, below 1,000m in length of total treams, below 1 in stream order, below 2 in number of first streams order and below $25^{\circ}$ of slope gradient. The prediction method of suitable for failure hazard area divided into class I, II, and III for the convenience of use. The score of class I evaluated as a very hazard area was over 4.8052. A score of class II was 4.8051 to 2.5602, it was evaluated as a hazard area, and class III was below 2.5601, it was evaluated as a un hazard area.

• Journal of Korean Elementary Science Education
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• v.36 no.1
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• pp.95-112
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• 2017

The competence of teachers, comes out through their lesson, is one of the key factors of school education. The purpose of this study is comparing the viewpoints on the science lessons in the elementary classrooms between pre-service teachers and highly experienced teachers in order to draw implications on pre-service teacher educating system. The participants of the study are 14 junior students in a university of education and 9 elementary school teachers who are highly educated and have much career experience. Each student participant observed one video clip with science lesson of their classmate. The total number of the video subject to observation is 4. Meanwhile experienced teachers observed 1 or 2 videos which are the same to those the students watched. The participants made a class criticism according to the General Standards for Class Critique made by KICE. The in-depth analysis of the criticism yielded the following conclusions; First, pre-service teachers had narrow views on the science class mainly limited in the practical part of class, but experienced teachers had wide views covered to class-knowledge, plan, and practice. Second, most experienced teachers thought that learning is the process by which students acquire knowledge or concepts by themselves, and the main purpose of the class is to help students' learning. Meanwhile, there were many pre-service teachers who thought that conveying knowledge or concepts to students was the main purpose of the class. Third, experienced teachers thought that a good science class should maintain consistency around the learning goals from the planning, implementation, and evaluation. However, many pre-service teachers did not take the learning objectives so seriously.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.4
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• pp.788-797
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• 2003

Class library is one of the most crucial element of Java runtime environment in addition to Java virtual machine. In particular, embedded Java system depends heavily on the class library due to having a low bandwidth communication link and a small amount of memory which are a common restriction of embedded system. It is therefore quite necessary to find the characteristic of the class library for embedded Java system to build an efficient Java runtime environment. In this paper we have analyzed the characteristic of the class library for embedded system. The analysis includes sorts of classes in the library, typical size of the file which contains the class, and the composition of constant pool which is a major part of the file. We also have found typical number of field and method a class contains, the sizes of stack and local variable array each method requires, and the length of bytecode in the method. The result of this study can be used to estimate the startup time for class loading and the size of memory to create an instance of class which are a mandatory information to design an efficient embedded Java virtual machine.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.4
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• pp.1371-1376
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• 2012

Background: Economic status is known to be directly or indirectly related to cancer incidence since it affects accessibility to health-related social resources, preventive medical checkups, and lifestyle. This study investigates the relationship between cancer incidence and family income in Korea. Methods:Using the Korean National Health Insurance cancer registration data in 2009, the relationship between their family income class and cancer risk was analyzed. The age-standardized incidence rates of the major cancers were calculated for men and women separately. After adjusting for age, residential area, and number of family members, cancer risks for major cancers according to family income class were estimated using a logistic regression model. Results: In men, the risk of stomach cancer for Income Class 5 (lowest) was 1.12 times (95% CI 1.02-1.23) higher than that of Income Class 1 (highest), for lung cancer 1.61 times (95% CI 1.43-1.81) higher, for liver cancer 1.22 times (95% CI 1.08-1.37) higher, and for rectal cancer 1.37 times higher (95% CI 1.18-1.59). In women, the risk of stomach cancer for Income Class 5 was 1.22 times higher (95% CI 1.08-1.37) than that for Income Class 1, while for cervical cancer it was 2.47 times higher (95% CI 2.08-2.94). In contrast, in men, Income Class 1 showed a higher risk of thyroid cancer and prostate cancer than that of Income Class 5, while, in women the same was the case for thyroid cancer. Conclusions: The results show the relationship between family income and cancer risk differs according to type of cancer.