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The Actual Combat of Military Vehicle Structure Melt Teaching Pattern Discuss
Issue:
Volume 2, Issue 2, June 2017
Pages:
51-53
Received:
4 September 2016
Accepted:
9 March 2017
Published:
10 March 2017
DOI:
10.11648/j.mlr.20170202.11
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Abstract: It is melted that now, the firm decision intention of the Central Military Commission on whole army carries military affairs forward vigorously to train actual combat, actual combat melt teaching train research is just unfolding. However as automobile professional foundation, It is military program that masses of automobile professional educational need to study and discuss urgently.
Abstract: It is melted that now, the firm decision intention of the Central Military Commission on whole army carries military affairs forward vigorously to train actual combat, actual combat melt teaching train research is just unfolding. However as automobile professional foundation, It is military program that masses of automobile professional educational...
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Data Mining of Access to Tetanus Toxoid Immunization Among Women of Childbearing Age in Ethiopia
Kedir Hussein Abegaz,
Emiru Merdassa Atomssa
Issue:
Volume 2, Issue 2, June 2017
Pages:
54-60
Received:
7 February 2017
Accepted:
21 February 2017
Published:
9 March 2017
DOI:
10.11648/j.mlr.20170202.12
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Abstract: Tetanus toxoid (TT) vaccine is given to women of childbearing age to prevent neonatal tetanus and maternal mortality attributed to tetanus. Globally, tetanus is responsible for 5% of maternal deaths and 14% of neonatal deaths annually. Data mining is the process of discovering interesting patterns and knowledge from large amounts of data. Thus, the aim of this study was to identify the best classifier, and to predict the pattern from the TT data set using the data mining algorithms technique. The data for this study were the Tetanus Toxoid data set from the Ethiopian Demographic and Health Survey (EDHS) 2011, and analyzed using the Knowledge discovery process of Selection, Processing, Transforming, mining, and interpretation. The WEKA 3.6.1 tool was used for classification, clustering, association and attribute selection. The accuracy rate of the classifiers on training data is relatively higher than on test data and the multilayer perceptron is the best classifier in our data set on Tetanus toxoid. In the cross-validation with 10 folds, correctly classified best are by naïve Bayesian 63.30% and the least accurate were by k-nearest neighbor 60.52%. Single data instance test using Naïve Bayesian was done by creating test 1, test 2, test 3, and test 4 data test instance, three of them are correctly predicted but one of them incorrectly classified. The maximum confidence attained in the general association is 0.98. But, in the class attribute, it is 0.72. The literacy status of the mother has high information gain with the value 0.046. As a conclusion, the best algorithm based on the TT vaccination data is multilayer perceptron classifier with an accuracy of 67.28% and the total time taken to build the model is at 0.01 seconds. Multilayer perceptron classifier has the lowest average error at 32.72% compared to others. These results suggest that among the machine learning algorithm tested, multilayer perceptron classifier has the potential to significantly improve the conventional classification methods for use in EDHS data of Tetanus toxoid.
Abstract: Tetanus toxoid (TT) vaccine is given to women of childbearing age to prevent neonatal tetanus and maternal mortality attributed to tetanus. Globally, tetanus is responsible for 5% of maternal deaths and 14% of neonatal deaths annually. Data mining is the process of discovering interesting patterns and knowledge from large amounts of data. Thus, the...
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Optimization of the Launching Process in the Electric Drive with the Help of Genetic Algorithm
Issue:
Volume 2, Issue 2, June 2017
Pages:
61-65
Received:
31 January 2017
Accepted:
21 February 2017
Published:
9 March 2017
DOI:
10.11648/j.mlr.20170202.13
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Abstract: In the terms of limited resources and rise of energy prices, one of the most priority directions of modern research is increasing the energy efficiency of electric drives, which are widely used in industrial enterprises. The present methods of minimizing losses are designed for stationary modes. Little attention is paid to the development of algorithms of reducing losses in transition modes. Owing to high complexity of multivariate dynamic processes of optimal control laws, it is advisable to carry out with the help of stochastic optimization techniques. The particularity of the proposed method of optimization is multiple simulation of the used drive in order to find the start-up characteristics, where minimum of energy losses is provided. Automation of search was performed with the help of developed program, which contains the genetic algorithm module and linking module with the electric drive model in Matlab/Simulink environment. The program allows you to select the parameters of the genetic algorithm and control process of optimization.
Abstract: In the terms of limited resources and rise of energy prices, one of the most priority directions of modern research is increasing the energy efficiency of electric drives, which are widely used in industrial enterprises. The present methods of minimizing losses are designed for stationary modes. Little attention is paid to the development of algori...
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Lean Production Planning for 5 Axes CNC Driven Milling Machine
Sandor Bodzas,
Bela Krakko
Issue:
Volume 2, Issue 2, June 2017
Pages:
66-72
Received:
29 January 2017
Accepted:
3 March 2017
Published:
15 March 2017
DOI:
10.11648/j.mlr.20170202.14
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Abstract: The aim of this publication is to determine the OEE (Overall Equipment Efficiency) indicator for a 5 axes milling machine found at Diehl Aircabin Hungary Ltd. for the present and future state. Based on this value, the utilization of the machine for the given production amount can be calculated. With the optimal choice of the right production parameters (the number of cuts, feeding, depth of cut, etc.) greater productivity can be achieved i.e the machine main time (time of cutting) will be less. The possibilities of the reduction of the machine time will be analyzed and calculated.
Abstract: The aim of this publication is to determine the OEE (Overall Equipment Efficiency) indicator for a 5 axes milling machine found at Diehl Aircabin Hungary Ltd. for the present and future state. Based on this value, the utilization of the machine for the given production amount can be calculated. With the optimal choice of the right production parame...
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The Improvement of Negative Sentences Translation in English-to-Korean Machine Translation
Jang Chung-Hyok,
Kim Kwang-Hyok
Issue:
Volume 2, Issue 2, June 2017
Pages:
73-77
Received:
2 February 2017
Accepted:
25 February 2017
Published:
15 March 2017
DOI:
10.11648/j.mlr.20170202.15
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Abstract: This paper describes the translation algorithm of English negative sentences in rule-based English-Korean Machine Translation (EKMT). The proposed algorithm is based on the comparative study of the linguistic characteristics of English and Korean negative sentences. The earlier versions of machine translation system which is under development by our research team, failed to translate English negative sentences into accurate Korean equivalents. On the basis of the comparative linguistic research on negation in English and Korean, a new translation algorithm of the English negative sentences was established and evaluated.
Abstract: This paper describes the translation algorithm of English negative sentences in rule-based English-Korean Machine Translation (EKMT). The proposed algorithm is based on the comparative study of the linguistic characteristics of English and Korean negative sentences. The earlier versions of machine translation system which is under development by ou...
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