• International journal of advanced smart convergence
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• v.6 no.3
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• pp.22-28
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• 2017

With the recent development of technologies to manage vast amounts of data, data mining technology has had a major impact on all industries.. Data mining is the process of discovering useful correlations hidden in data, extracting executable information for the future, and using it for decision making. In other words, it is a core process of Knowledge Discovery in data base(KDD) that transforms input data and derives useful information. It extracts information that we did not know until now from a large data base. In the decision tree, c4.5 algorithm was used. In addition, the C4.5 algorithm was used in the decision tree to analyze the difference between frequency and mortality in the region. In this paper, the frequency and mortality of percutaneous coronary intervention for patients with heart disease were divided into regions.

• Journal of Power Electronics
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• v.14 no.5
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• pp.926-936
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• 2014

A simplified and effective space vector pulse-width modulation (SVPWM) algorithm with two and three levels for three-phase voltage-source converters is proposed in this study. The proposed SVPWM algorithm only uses several linear calculations on three-phase modulated voltages without any complicated trigonometric calculations adopted by conventional SVPWM. This simplified SVPWM also avoids choosing the vector sector required by conventional SVPWM. A two-level overmodulation scheme is integrated into the proposed two-level SVPMW to generate the output voltage that increases from a linear region to a six-step state with a smoothly linear transition characteristic and a simple overmodulation process without a lookup table and complicated nonlinear functions. The three-level SVPWM with a proportional-integral controller effectively balances the neutral point potential of the neutral point clamped converter. Results from the simulation in MATLAB/Simulink and the experiment based on a digital signal processor are provided to clearly demonstrate the validity and effectiveness of the proposed strategies.

• Geomechanics and Engineering
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• v.35 no.1
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• pp.67-80
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• 2023

Due to the nature of the conjunctive Cone Penetration Test(CPT), which does not verify the actual sample directly, geotechnical engineers commonly classify the underground geomaterials using CPT results with the classification diagrams proposed by various researchers. However, such classification diagrams may fail to reflect local geotechnical characteristics, potentially resulting in misclassification that does not align with the actual stratification in regions with strong local features. To address this, this paper presents an objective method for more accurate local CPT soil classification criteria, which utilizes C4.5 decision tree models trained with the CPT results from the clay-dominant southern coast of Korea and the sand-dominant region in South Carolina, USA. The results and analyses demonstrate that the C4.5 algorithm, in conjunction with oversampling, outlier removal, and pruning methods, can enhance and optimize the decision tree-based CPT soil classification model.

• Advances in nano research
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• v.14 no.3
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• pp.225-234
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• 2023

In this study, we aim to use big data resources and statistical analysis to obtain a reliable instruction to reach high-quality and high yield agricultural yields. In this regard, soil type data, raining and temperature data as well as wheat production in each year are collected for a specific region. Using statistical methodology, the acquired data was cleaned to remove incomplete and defective data. Afterwards, using several classification methods in machine learning we tried to distinguish between different factors and their influence on the final crop yields. Comparing the proposed models' prediction using statistical quantities correlation factor and mean squared error between predicted values of the crop yield and actual values the efficacy of machine learning methods is discussed. The results of the analysis show high accuracy of machine learning methods in the prediction of the crop yields. Moreover, it is indicated that the random forest (RF) classification approach provides best results among other classification methods utilized in this study.

• Journal of Microbiology and Biotechnology
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• v.28 no.6
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• pp.957-967
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• 2018

A novel $g-C_3N_4$/ZnO/stellerite (CNZOS) hybrid photocatalyst, which was synthesized by coupled hydro thermal-thermal polymerization processing, was applied as an efficient visible-light-driven photocatalyst against Staphylococcus aureus. The optimum synthesized hybrid photocatalyst showed a sandwich structure morphology with layered $g-C_3N_4$ (doping amount: 40 wt%) deposited onto micron-sized ZnO/stellerite particles (ZnO average diameter: ~18 nm). It had a narrowing band gap (2.48 eV) and enlarged specific surface area ($23.05m^2/g$). The semiconductor heterojunction effect from ZnO to $g-C_3N_4$ leads to intensive absorption of the visible region and rapid separation of the photogenerated electron-hole pairs. In this study, CNZOS showed better photocatalytic disinfection efficiency than $g-C_3N_4/ZnO$ powders. The disinfection mechanism was systematically investigated by scavenger-quenching methods, indicating the important role of $H_2O_2$ in both systems. Furthermore, $h^+$ was demonstrated as another important radical in oxidative inactivation of the CNZOS system. In respect of the great disinfection efficiency and practicability, the CNZOS heterojunction photocatalyst may offer many disinfection applications.

• Steel and Composite Structures
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• v.34 no.1
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• pp.17-34
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• 2020

This paper investigates the flexural behavior of concrete beams reinforced longitudinally with either steel bars, molded glass-fiber reinforced polymer (GFRP) grating mesh or pultruded glass-fiber reinforced polymer (GFRP) grating mesh, under four-point bending. The variables included in this study were the type of concrete (normal weight concrete, perlite concrete and vermiculite concrete), type of the longitudinal reinforcement (steel bars, molded and pultruded GFRP grating mesh) and the longitudinal reinforcement ratio (between 0.007 and 0.035). The influences of these variables on the load-midspan deflection curves, bending stiffness, energy absorption and failure modes were investigated. A total of fifteen beams with a cross-sectional dimension of 160 mm × 210 mm and an overall length of 2400 mm were cast and divided into three groups. The first group was constructed with normal weight concrete and served as a reference concrete. The second and third groups were constructed with perlite concrete and vermiculite concrete, respectively. An innovative type of stirrup was used as shear reinforcement for all beams. The results showed that the ultimate load of the beams reinforced with pultruded GFRP grating mesh ranged between 19% and 38% higher than the ultimate load of the beams reinforced with steel bars. The bending stiffness of all beams was influenced by the longitudinal reinforcement ratio rather than the type of concrete. Failure occurred within the pure bending region which means that the innovative stirrups showed a significant resistance to shear failure. Good agreement between the experimental and the analytical ultimate load was obtained.

• Economic and Environmental Geology
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• v.29 no.6
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• pp.665-676
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• 1996

Domestic metal mines have contributed to the national industrialization of Japan for over a century through their stable supply of raw materials. However, due to the changes which have taken place in the industries structure, mining industry has been shifted to downstream industries. At present, only three major mines are in production. In recent times, changing economic conditions have made it increasingly difficult to develop new base metal mines. Subsequently, the deposit type targeted has shifted from base metals to epithermal associated gold deposits which, if of sufficient grade and tonnage, can be economical. Accompanying the dramatic rise in the price of gold during the late 1970's, has been an increase in the geological information and our understanding of epithermal gold deposits around the Pacific rim region. In particular, the common acceptance of the plate tectonic theory and the correlation's between modem geothermal systems and fossil epithermal systems were most important developments. In 1988, the Mining Council authorized the domestic exploration of 19 districts, targeting epithermal gold mineralization. Since 1989 the Metal Mining Agency of Japan, semi-government organization, has been conducted gold exploration in such area. With new genetic concepts and new technologies, promising gold mineralization has been discovered. Two such areas which are at an advanced stage of exploration are Seta, in northern Hokkaido, and Noya, in central Kyushu.

• Safety and Health at Work
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• v.5 no.4
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• pp.203-209
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• 2014

Background: Coal mining is of significant economic importance to the Australian economy. Despite this fact, the related workforce is subjected to a number of psychosocial risks and musculoskeletal injury, and various psychological disorders are common among this population group. Because only limited research has been conducted in this population group, we sought to examine the relationship between physical (pain) and psychological (distress) factors, as well as the effects of various demographic, lifestyle, and fatigue indicators on this relationship. Methods: Coal miners (N = 231) participated in a survey of musculoskeletal pain and distress on-site during their work shifts. Participants also provided demographic information (job type, age, experience in the industry, and body mass index) and responded to questions about exercise and sleep quality (on-and off-shift) as well as physical and mental tiredness after work. Results: A total of 177 workers (80.5%) reported experiencing pain in at least one region of their body. The majority of the sample population (61.9%) was classified as having low-level distress, 28.4% had scores indicating mild to moderate distress, and 9.6% had scores indicating high levels of distress. Both number of pain regions and job type (being an operator) significantly predicted distress. Higher distress score was also associated with greater absenteeism in workers who reported lower back pain. In addition, perceived sleep quality during work periods partially mediated the relationship between pain and distress. Conclusion: The study findings support the existence of widespread musculoskeletal pain among the coal-mining workforce, and this pain is associated with increased psychological distress. Operators (truck drivers) and workers reporting poor sleep quality during work periods are most likely to report increased distress, which highlights the importance of supporting the mining workforce for sustained productivity.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.217-229
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• 2018

This paper aims at applying the data mining such as decision tree, neural network, and logistic regression to an unsold apartment complex in Wirye new town and developing the model forecasting the result of initial sale contract by house unit. Raw data are divided into training data and test data. The order of predictability in training data is neural network, decision tree, and logistic regression. On the contrary, the results of test data show that logistic regression is the best model. This means that logistic regression has more data adaptability than neural network which is developed as the model optimized for training data. Determinants of initial sale are the location of floor, direction, the location of unit, the proximity of electricity and generator room, subscriber's residential region and the type of subscription. This suggests that using two models together is more effective in exploring determinants of initial sales. This paper contributes to the development of convergence field by expanding the scope of data mining.

• Imaging Science in Dentistry
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• v.50 no.4
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• pp.323-330
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• 2020

Purpose: The mastoid region is ideal for studying sexual dimorphism due to its anatomical position at the base of the skull. This study aimed to determine sex in the Iranian population based on measurements of the mastoid process using different data mining algorithms. Materials and Methods: This retrospective study was conducted on 190 3-dimensional cone-beam computed tomographic (CBCT) images of 105 women and 85 men between the ages of 18 and 70 years. On each CBCT scan, the following 9 landmarks were measured: the distance between the porion and the mastoidale; the mastoid length, height, and width; the distance between the mastoidale and the mastoid incision; the intermastoid distance (IMD); the distance between the lowest point of the mastoid triangle and the most prominent convex surface of the mastoid (MF); the distance between the most prominent convex mastoid point (IMSLD); and the intersecting angle drawn from the most prominent right and left mastoid point (MMCA). Several predictive models were constructed and their accuracy was compared using cross-validation. Results: The results of the t-test revealed a statistically significant difference between the sexes in all variables except MF and MMCA. The random forest model, with an accuracy of 97.0%, had the best performance in predicting sex. The IMSLD and IMD made the largest contributions to predicting sex, while the MMCA variable had the least significant role. Conclusion: These results show the possibility of developing an accurate tool using data mining algorithms for sex determination in the forensic framework.