• Title/Summary/Keyword: Mining design

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Estimation of geomechanical parameters of tunnel route using geostatistical methods

  • Aalianvari, Ali;Soltani-Mohammadi, Saeed;Rahemi, Zeynab
    • Geomechanics and Engineering
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    • v.14 no.5
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    • pp.453-458
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    • 2018
  • Geomechanical parameters are important factors for engineering projects during design, construction and support stages of tunnel and dam projects. Geostatistical estimation methods are known as one of the most significant approach at estimation of Geomechanical parameters. In this study, Azad dam headrace tunnel is chosen to estimate Geomechanical parameters such as Rock Quality Designation (RQD) and uniaxial compressive strength (UCS) by ordinary kriging as a geostatistical method. Also Rock Mass Rating (RMR) distribution is presented along the tunnel. Main aim in employment of geostatistical methods is estimation of points that unsampled by sampled points.To estimation of parameters, initially data are transformed to Gaussian distribution, next structural data analysis is completed, and then ordinary kriging is applied. At end, specified distribution maps for each parameter are presented. Results from the geostatistical estimation method and actual data have been compared. Results show that, the estimated parameters with this method are very close to the actual parameters. Regarding to the reduction of costs and time consuming, this method can use to geomechanical estimation.

Occupational Health and Safety and Organizational Commitment: Evidence from the Ghanaian Mining Industry

  • Amponsah-Tawiah, Kwesi;Mensah, Justice
    • Safety and Health at Work
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    • v.7 no.3
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    • pp.225-230
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    • 2016
  • Background: This study seeks to examine the relationship and impact of occupational health and safety on employees' organizational commitment in Ghana's mining industry. The study explores occupational health and safety and the different dimensions of organizational commitment. Methods: A cross-sectional survey design was used for this study. The respondents were selected based on simple random sampling. Out of 400 questionnaires administered, 370 were returned (77.3% male and 22.7% female) and used for the study. Correlation and multiple regression analysis were used to determine the relationship and impact between the variables. Results: The findings of this study revealed positive and significant relationship between occupational health and safety management, and affective, normative, and continuance commitment. Additionally, the results revealed the significant impact of occupational health and safety on affective, normative, and continuance commitment. Conclusion: Management within the mining sector of Ghana must recognize the fact that workers who feel healthy and safe in the performance of their duties, develop emotional attachment and have a sense of obligation to their organization and are most likely committed to the organization. Employees do not just become committed to the organization; rather, they expect management to first think about their health and safety needs by instituting good and sound policy measures. Thus, management should invest in the protection of employees' health and safety in organizations.

An Intelligent Agent System using Multi-View Information Fusion (다각도 정보융합 방법을 이용한 지능형 에이전트 시스템)

  • Rhee, Hyun-Sook
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.12
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    • pp.11-19
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    • 2014
  • In this paper, we design an intelligent agent system with the data mining module and information fusion module as the core components of the system and investigate the possibility for the medical expert system. In the data mining module, fuzzy neural network, OFUN-NET analyzes multi-view data and produces fuzzy cluster knowledge base. In the information fusion module and application module, they serve the diagnosis result with possibility degree and useful information for diagnosis, such as uncertainty decision status or detection of asymmetry. We also present the experiment results on the BI-RADS-based feature data set selected form DDSM benchmark database. They show higher classification accuracy than conventional methods and the feasibility of the system as a computer aided diagnosis system.

Modeling time-dependent behavior of hard sandstone using the DEM method

  • Guo, Wen-Bin;Hu, Bo;Cheng, Jian-Long;Wang, Bei-Fang
    • Geomechanics and Engineering
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    • v.20 no.6
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    • pp.517-525
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    • 2020
  • The long-term stability of rock engineering is significantly affected by the time-dependent deformation behavior of rock, which is an important mechanical property of rock for engineering design. Although the hard rocks show small creep deformation, it cannot be ignored under high-stress condition during deep excavation. The inner mechanism of creep is complicated, therefore, it is necessary to investigate the relationship between microscopic creep mechanism and the macro creep behavior of rock. Microscopic numerical modeling of sandstone creep was performed in the investigation. A numerical sandstone sample was generated and Parallel Bond contact and Burger's contact model were assigned to the contacts between particles in DEM simulation. Sensitivity analysis of the microscopic creep parameters was conducted to explore how microscopic parameters affect the macroscopic creep deformation. The results show that the microscopic creep parameters have linear correlations with the corresponding macroscopic creep parameters, whereas the friction coefficient shows power function with peak strength and Young's modulus, respectively. Moreover, the microscopic parameters were calibrated. The creep modeling curve is in good agreement with the verification test result. Finally, the creep curves under one-step loading and multi-step loading were compared. This investigation can act as a helpful reference for modeling rock creep behavior from a microscopic mechanism perspective.

Investigation of mechanical behaviour of non-persistent jointed blocks under uniaxial compression

  • Asadizadeh, Mostafa;Moosavi, Mahdi;Hossaini, Mohammad Farouq
    • Geomechanics and Engineering
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    • v.14 no.1
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    • pp.29-42
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    • 2018
  • This paper presents the results of an empirical study in which square rock-like blocks containing two parallel pre-existing rough non-persistent joints were subjected to uniaxial compression load. The main purpose of this study was to investigate uniaxial compressive strength and deformation modulus of jointed specimens. Response Surface Method (RSM) was utilized to design experiments and investigate the effect of four joint parameters, namely joint roughness coefficient (JRC), bridge length (L), bridge angle (${\gamma}$), and joint inclination (${\theta}$). The interaction of these parameters on the uniaxial compressive strength (UCS) and deformation modulus of the blocks was investigated as well. The results indicated that an increase in joint roughness coefficient, bridge length and bridge angle increased compressive strength and deformation modulus. Moreover, increasing joint inclination decreased the two mechanical properties. The concept of 'interlocking cracks' which are mixed mode (shear-tensile cracks) was introduced. This type of cracks can happen in higher level of JRC. Initiation and propagation of this type of cracks reduces mechanical properties of sample before reaching its peak strength. The results of the Response Surface Methodology showed that the mutual interaction of the joint parameters had a significant influence on the compressive strength and deformation modulus.

Development of Customized Strategy for Enhancing Automobile Repurchase Using Data Mining Techniques (자동차 재구매 증진을 위한 데이터 마이닝 기반의 맞춤형 전략 개발)

  • Lee, Dong-Wook;Choi, Keun-Ho;Yoo, Dong-Hee
    • The Journal of Information Systems
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    • v.26 no.3
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    • pp.47-61
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    • 2017
  • Purpose Although automobile production has increased since the development of the Korean automobile industry, the number of customers who can purchase automobiles decreases relatively. Therefore, automobile companies need to develop strategies to attract customers and promote their repurchase behaviors. To this end, this paper analyzed customer data from a Korean automobile company using data mining techniques to derive repurchase strategies. Design/methodology/approach We conducted under-sampling to balance the collected data and generated 10 datasets. We then implemented prediction models by applying a decision tree, naive Bayesian, and artificial neural network algorithms to each of the datasets. As a result, we derived 10 patterns consisting of 11 variables affecting customers' decisions about repurchases from the decision tree algorithm, which yielded the best accuracy. Using the derived patterns, we proposed helpful strategies for improving repurchase rates. Findings From the top 10 repurchase patterns, we found that 1) repurchases in January are associated with a specific residential region, 2) repurchases in spring or autumn are associated with whether it is a weekend or not, 3) repurchases in summer are associated with whether the automobile is equipped with a sunroof or not, and 4) a customized promotion for a specific occupation increases the number of repurchases.

Design of Efficient Query Language to support Local information administration environment (지역정보 관리 환경을 지원하기 위한 효율적인 질의 언어의 설계)

  • Kang, Sung-Kwan;Rhee, Phill-Kyu
    • Proceedings of the Korean Information Science Society Conference
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    • 2008.06c
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    • pp.36-40
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    • 2008
  • SIMS manages data for various spatial and non-spatial as integral management system to support space information administration environment and support several application works. Without being limited to spatial data that existent spatial Data Mining question language advances handling in this paper, did so that can find useful information from various data connected with automatically data collection, artificial satellite side upside service, remote sensing, GPS. Mobile Computing and data about Spatio-Temporal. Also, we designed spatial Data Mining query language that support a spatial Data Mining exclusive use system based on SIMS.

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Ethical Fashion Research Trend Using Text Mining: Network Analysis of the Published Literature 2009-2019 (텍스트 마이닝을 활용한 윤리적 패션 연구동향: 2009-2019 연구 네트워크 분석)

  • Choi, Yeong-Hyeon;Lee, Kyu-Hye
    • Fashion & Textile Research Journal
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    • v.22 no.2
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    • pp.181-191
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    • 2020
  • The fashion industry has faced environmental, social, and ethical issues due to increased interest in ethical consumption. Numerous ethical studies have been conducted in the fashion industry. This study looked at the current state of research by year, academic journal, and detail in major related papers published in Scopus, KCI and KCI between 2009 and 2019. Ethical fashion studies began to appear in 2009 and were concentrated in certain academic journals and focused on fashion marketing and fashion design. Topics in ethical fashion were terms such as sustainable, eco-friendly, up-cycling, recycling, eco, zero-waist, and organic. In ethical fashion studies, environmental studies were conducted most often; in addition, the terms used along with ethical fashion tend to be frequently used for each particular major. Looking at key words used in research by period, the study showed that research was most diverse between 2016 and 2019. In particular, environmental and social issues of ethical fashion and convergence with animal protection, new distribution, science and technology sectors were newly added between 2016 and 2019. This study used text mining and network analysis to understand the overall trends of ethical fashion studies in Korea. In conclusion it is important to realize the relationship between the main words along with the current status analysis.

An Implementation of Recommender System using Data Mining Techniques (데이터 마이닝 기법을 이용한 추천 시스템의 구현)

  • Lee, Ki-Wook;Sung, Chang-Gyu
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.1 s.39
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    • pp.293-300
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    • 2006
  • The Recommender systems help users to find and evaluate items of interest. Such systems have become powerful tools in the domains from electronic commerce to digital libraries and knowledge management. Sellers can recommend products to customers with the prediction of future buying behavior on the basis of the consumer's population statistics and past selling behavior. In this paper, we are describing the design and the development of personalization recommender system which increases satisfaction level of customers by searching products to reflect the pattern and propensity of customers properly. The suggested system supplies the real-time analysis service to predict the customers purchase situation by applying the association rule of the data mining.

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A Design of false alarm analysis framework of intrusion detection system by using incremental mining method (점진적 마이닝 기법을 적용한 침입탐지 시스템의 오 경보 분석 프레임워크 설계)

  • Kim Eun-Hee;Ryu Keun-Ho
    • The KIPS Transactions:PartC
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    • v.13C no.3 s.106
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    • pp.295-302
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    • 2006
  • An intrusion detection system writes a lot of alarms against attack behaviors in real time. These alarms contain not only actual attack alarms, but also false alarms that are mistakes made by the intrusion detection system. False alarms are the main reason that reduces the efficiency of the intrusion detection system, and we propose framework for false alarms analysis in the paper. Also, we apply an incremental data mining method for pattern analysis of false alarms increasing continuously. The framework consists of GUI, DB Manager, Alert Preprocessor, and False Alarm Analyzer. We analyze the false alarms increasingly through the experiment of the proposed framework and show that false alarms are reduced by applying the analyzed false alarm rules in the intrusion detection system.