• International journal of advanced smart convergence
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• 제6권3호
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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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• 제14권5호
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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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• 제35권1호
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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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• 제14권3호
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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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• 제28권6호
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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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• 제34권1호
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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.

• 자원환경지질
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• 제29권6호
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• pp.665-676
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• 1996

안정적인 천연자원의 공급을 통해 오랫동안 국가산업화에 이바지해온 일본의 광산산업은 산업구조의 개편에 따라 하향추세를 맞아 현재는 세 곳의 주요 광산만이 가행중이다. 최근 경제사정의 변화로 새로운 비금속광상의 개발이 어려워짐에 따라 매장량과 품위에 있어 경제적 가치를 갖는 천열수금광상으로 관심이 옮겨가고 있는 추세이다. 1970년대 후반의 급격한 금가격 상승은 환태평양 지역의 천열수금광상에 대한 지질학적 정보와 이해를 증가시키는 역할을 했으며, 특히 판구조론의 확립과 더불어 지열수계와 화석천열수계의 대비라는 가장 중요한 발전이 이루어졌다. 1988년에는 광산협회에서 천열수금광상의 개발을 목표로 일본내 19개 지역의 탐사를 인가했으며, 1989년부터는 준정부기관인 금속광업국에서 이 지역들의 금탐사를 수행해왔다. 광상성인에 관한 신개념과 새로운 탐사기술로 유망한 금광화대가 발견되어 왔으며 개발이 진척된 곳은 홋카이도 북부의 세타지역과 큐슈 중부의 노야지역이다.

• Safety and Health at Work
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• 제5권4호
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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.

• 디지털융복합연구
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• 제16권12호
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• pp.217-229
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• 2018

이 연구에서는 미분양 아파트 단지의 세대별 계약 자료에 데이터 마이닝 기법인 의사결정나무, 신경망, 로지스틱 모형을 적용하여 세대별 초기계약을 예측하는 모형을 개발한다. 모형 개발에는 위례신도시 미분양 아파트 단지의 계약 자료가 이용되며, 이 자료는 훈련용 자료와 검정용 자료로 분할되어 분석에 투입된다. 훈련용 자료에서는 신경망, 의사결정나무, 로지스틱 모형 순으로 예측력이 뛰어났지만 검정용 자료에서는 로지스틱 모형이 가장 우수하게 나타났다. 이 같은 결과는 신경망이 훈련용 자료에 최적화된 모형으로 구축되면서 검정용 자료에 대한 적응성이 떨어져 나타난 결과로 판단된다. 의사결정나무와 로지스틱 모형을 병행 적용한 결과, 층수, 향, 세대 위치, 전기 및 발전기실의 소음, 청약자 거주지, 청약 종류가 초기계약에 영향을 주는 것으로 나타났다. 이는 두 가지 모형을 같이 사용하는 것이 초기계약 결정요인 발굴에 더 효과적이라는 것을 의미한다. 이 연구는 데이터 마이닝의 적용 범위를 주택 분양 예측까지 확장함으로써 융복합 분야 발전에 기여하고 있다.

• Imaging Science in Dentistry
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• 제50권4호
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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.