Search results for: gold Mining

Authors: M. L. Dinis, M. C. Vila, A. Fiúza, A. Futuro, C. Nunes

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The present paper describes the study of paste tailings prepared in laboratory using gold tailings, produced in a Finnish gold mine with the incorporation of coal ash. Natural leaching tests were conducted with the original materials (tailings, fly and bottom ashes) and also with paste mixtures that were prepared with different percentages of tailings and ashes. After leaching, the solid wastes were physically and chemically characterized and the results were compared to those selected as blank – the unleached samples. The tailings and the coal ash, as well as the prepared mixtures, were characterized, in addition to the textural parameters, by the following measurements: grain size distribution, chemical composition and pH. Mixtures were also tested in order to characterize their mechanical behavior by measuring the flexural strength, the compressive strength and the consistency. The original tailing samples presented an alkaline pH because during their processing they were previously submitted to pressure oxidation with destruction of the sulfides. Therefore, it was not possible to ascertain the effect of the coal ashes in the acid mine drainage. However, it was possible to verify that the paste reactivity was affected mostly by the bottom ash and that the tailings blended with bottom ash present lower mechanical strength than when blended with a combination of fly and bottom ash. Surface paste disposal offer an attractive alternative to traditional methods in addition to the environmental benefits of incorporating large-volume wastes (e.g. bottom ash). However, a comprehensive characterization of the paste mixtures is crucial to optimize paste design in order to enhance engineer and environmental properties.

Keywords: coal ash, mine tailings, paste blends, surface disposal

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Authors: Paballo M. Moshupya, Tamiru A. Abiye, Ian Korir

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Mining and processing of naturally occurring radioactive materials could result in elevated levels of natural radionuclides in the environment. The aim of this study was to evaluate the radioactivity levels on a large scale in the West Rand District in South Africa, which is dominated by abandoned gold mine tailings and the consequential radiological exposures to members of the public. The activity concentrations of ²³⁸U, ²³²Th and 40K in mine tailings, soil and rocks were assessed using the BGO Super-Spec (RS-230) gamma spectrometer. The measured activity concentrations for ²³⁸U, ²³²Th and 40K in the studied mine tailings were found to range from 209.95 to 2578.68 Bq/kg, 19.49 to 108.00 Bq/kg and 31.30 to 626.00 Bq/kg, respectively. In surface soils, the overall average activity concentrations were found to be 59.15 Bq/kg, 34.91 and 245.64 Bq/kg for 238U, ²³²Th and 40K, respectively. For the rock samples analyzed, the mean activity concentrations were 32.97 Bq/kg, 32.26 Bq/kg and 351.52 Bg/kg for ²³⁸U, ²³²Th and 40K, respectively. High radioactivity levels were found in mine tailings, with ²³⁸U contributing significantly to the overall activity concentration. The external gamma radiation received from surface soil in the area is generally low, with an average of 0.07 mSv/y. The highest annual effective doses were estimated from the tailings dams and the levels varied between 0.14 mSv/y and 1.09 mSv/y, with an average of 0.51 mSv/y. In certain locations, the recommended dose constraint of 0.25 mSv/y from a single source to the average member of the public within the exposed population was exceeded, indicating the need for further monitoring and regulatory control measures specific to these areas to ensure the protection of resident members of the public.

Keywords: activity concentration, gold mine tailings, in-situ gamma spectrometry, radiological exposures

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Authors: Odinah Cuartero-Enteria, Kyla Rita Mercado, Jason Salamanes, Aian Pecasales, Sherwin Sabado

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The northern part of Mindanao Island, Philippines has sizable reserve of mineral resources. Years ago, mining activities have been flourishing which resulted to both local economic gain but with environmental concerns. This study investigates the prevalent diseases by mining activities in these areas. The study was done using the secondary data gathered from the Rural Health Units (RHU) of the selected areas. The study further determined the prevalent diseases that existed in the three areas from years 2005, 2010 and 2015 indicating before the mining activities and when mining activities are present. The results show that areas which are far from mining activities have fewer cases of patients suffering from air-borne diseases. The top ten most common diseases such as pneumonia, tuberculosis, influenza, upper respiratory tract infection (URTI) and skin diseases were caused by air-borne due to air pollution. Hence, the places where mining activities are present contribute to the prevalent diseases. Thus, addressing the air pollution caused by mining activities is very important.

Keywords: Philippines, Mindanao Island, mining activities, pollution, prevalent diseases

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Authors: Bingjie Wang, Su-Yeon Kwon, Ik-Joong Kang

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A Surface-enhanced Raman Scattering (SERS) as the principle for enhancing Raman scattering by molecules adsorbed on rough metal surfaces or by nanostructures is used to detect the concentration change of γ-Aminobutyric Acid (GABA). As for the gold-chitosan nanoshell, it is made by using chitosan nanoparticles crosslinking with sodium tripolyphosphate(TPP) for the first step to form the chitosan nanoparticles, which would be covered with the gold sequentially. The size of the fabricated product was around 100nm. Based on the method that the sulfur end of the MPA linked to gold can form the very strong S–Au bond, and the carboxyl group, the other end of the MPA, can easily absorb the GABA. GABA is the mainly inhibitory neurotransmitter in the mammalian central nervous system in the human body. It plays such significant role in reducing neuronal excitability throughout the nervous system. When the system formed, it generated SERS, which made a clear difference in the intensity of Raman scattering within the range of GABA concentration. So it is obtained from the experiment that the calibration curve according to the GABA concentration relevant with the SERS scattering. In this study, DLS, SEM, FT-IR, UV, SERS were used to analyze the products to obtain the conclusion.

Keywords: chitosan-gold nanoshell, mercaptopropionic acid, γ-aminobutyric acid, surface-enhanced Raman scattering

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Authors: Sonali Agarwal

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The investor perception about investment avenues is affected to a great degree by the current happenings, within the country, and on the global stage. The influencing events can range from government policies, bilateral trade agreements, election agendas, to changing exchange rates, appreciation and depreciation of currency, recessions, meltdowns, bankruptcies etc. The current research attempts to discover and unravel the effect of various macroeconomic variables (crude oil price, gold price, silver price and USD exchange rate) on the Indian mutual fund industry in general and the chosen funds (Axis Gold Fund, BSL Gold Fund, Kotak Gold Fund & SBI gold fund) in particular. Cointegration tests and Vector error correction equations prove that the chosen variables have strong effect on the NAVs (net asset values) of the mutual funds. However, the greatest influence is felt from the fund’s own past and current information and it is found that when an innovation of fund’s own lagged NAVs is given, variance caused is high that changes the current NAVs markedly. The study helps to highlight the interplay of macroeconomic variables and their repercussion on mutual fund industry.

Keywords: cointegration, Granger causality, impulse response, macroeconomic variables, mutual funds, stationarity, unit root test, variance decomposition, VECM

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Authors: Ghaemi Reza, Abdollahi Hamid, Dashti Elham

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Cloud computing poses a diversity of challenges in data mining operation arising out of the dynamic structure of data distribution as against the use of typical database scenarios in conventional architecture. Due to immense number of users seeking data on daily basis, there is a serious security concerns to cloud providers as well as data providers who put their data on the cloud computing environment. Big data analytics use compute intensive data mining algorithms (Hidden markov, MapReduce parallel programming, Mahot Project, Hadoop distributed file system, K-Means and KMediod, Apriori) that require efficient high performance processors to produce timely results. Data mining algorithms to solve or optimize the model parameters. The challenges that operation has to encounter is the successful transactions to be established with the existing virtual machine environment and the databases to be kept under the control. Several factors have led to the distributed data mining from normal or centralized mining. The approach is as a SaaS which uses multi-agent systems for implementing the different tasks of system. There are still some problems of data mining based on cloud computing, including design and selection of data mining algorithms.

Keywords: cloud computing, data mining, computing models, cloud services

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Authors: Gabriel K. Nzulu, Lina Rostorm, Hans Högberg, Jun Liu, per Eklund, Lars Hultman, Martin Magnuson

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Altered and gangue quartz in hydrothermal veins from the Kubi Gold deposit in Dunkwa on Offin in the central region of Ghana are investigated for possible Au associated pathfinder minerals and to provide understanding and increase the knowledge of the mineral hosting and alteration processes in quartz. X-ray diffraction, air annealing furnace, differential scanning calorimetry, energy dispersive X-ray spectroscopy, and transmission electron microscopy have been applied on different quartz types outcropping from surface and bed rocks at the Kubi Gold Mining to reveal the material properties at different temperatures. From the diffraction results of the fresh and annealed quartz samples, we find that the samples contain pathfinder and the impurity minerals FeS₂, biotite, TiO₂, and magnetite. These minerals, under oxidation process between 574-1400 °C temperatures experienced hematite alterations and a transformation from α-quartz to β-quartz and further to cristobalite as observed from the calorimetry scans for hydrothermally exposed materials. The energy dispersive spectroscopy revealed elemental species of Fe, S, Mg, K, Al, Ti, Na, Si, O, and Ca contained in the samples and these are attributed to the impurity phase minerals observed in the diffraction. The findings also suggest that during the hydrothermal flow regime, impurity minerals and metals can be trapped by voids and faults. Under favorable temperature conditions the trapped minerals can be altered to change color at different depositional stages by oxidation and reduction processes leading to hematite alteration which is a useful pathfinder in mineral exploration.

Keywords: quartz, hydrothermal, minerals, hematite, x-ray diffraction, crystal-structure, defects

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Authors: Tetsuo Okutsu

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We have developed a crystallization plate with the function of promoting protein crystallization. A gold thin film is deposited on the crystallization plate. A protein solution is dropped thereon, and crystallization is promoted when the protein is irradiated with light of a wavelength that protein does not absorb. Protein is densely adsorbed on the gold thin film surface. The light excites the surface plasmon resonance of the gold thin film, the protein is excited by the generated enhanced electric field induced by surface plasmon resonance, and the amino acid residues are radicalized to produce protein dimers. The dimers function as templates for protein crystals, crystallization is promoted.

Keywords: lysozyme, plasmon, protein, crystallization, RNaseA

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Authors: Sohail Imran, Tariq Mahmood

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In complex healthcare diagnostic investigation process, medical practitioners have to focus on ways to standardize their processes to perform high quality care and optimize the time and costs. Process mining techniques can be applied to extract process related knowledge from data without considering causal and dynamic dependencies in business domain and processes. The application of process mining is effective in diagnostic investigation. It is very helpful where a treatment gives no dispositive evidence favoring it. In this paper, we applied process mining to discover important process flow of diagnostic investigation for hepatitis patients. This approach has some benefits which can enhance the quality and efficiency of diagnostic investigation processes.

Keywords: process mining, healthcare, diagnostic investigation process, process flow

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Authors: Bingjie Wang, Su-Yeon Kwon, Ik-Joong Kang

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The goal of this experiment is to develop a sensor that can quickly check the concentration by using the nanoparticles made by chitosan and gold. Using chitosan nanoparticles crosslinking with sodium tripolyphosphate(TPP) is the first step to form the chitosan nanoparticles, which would be covered with the gold sequentially. The size of the fabricated product was around 100nm. Based on the method that the sulfur end of the MPA linked to gold can form the very strong S–Au bond, and the carboxyl group, the other end of the MPA, can easily absorb the GABA. As for the GABA, what is the primary inhibitory neurotransmitter in the mammalian central nervous system in the human body. It plays such significant role in reducing neuronal excitability pass through the nervous system. A Surface-enhanced Raman Scattering (SERS) as the principle for enhancing Raman scattering by molecules adsorbed on rough metal surfaces or by nanostructures is used to detect the concentration change of γ-Aminobutyric Acid (GABA). When the system is formed, it generated SERS, which made a clear difference in the intensity of Raman scattering within the range of GABA concentration. So it is obtained from the experiment that the calibration curve according to the GABA concentration relevant with the SERS scattering. In this study, DLS, SEM, FT-IR, UV, SERS were used to analyze the products to obtain the conclusion.

Keywords: mercaptopropionic acid, chitosan-gold nanoshell, γ-aminobutyric acid, surface-enhanced raman scattering

Procedia PDF Downloads 247

Authors: Anurag Savarnya

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The reliability of the various parts of electric mining shovel has been assessed through the application of Weibull Model. The study was initiated to find reliability of components of electric mining shovel. The paper aims to optimize the reliability of components and increase the life cycle of component. A multilevel decomposition of the electric mining shovel was done and maintenance records were used to evaluate the failure data and appropriate system characterization was done to model the system in terms of reasonable number of components. The approach used develops a mathematical model to assess the reliability of the electric mining shovel components. The model can be used to predict reliability of components of the hydraulic mining shovel and system performance. Reliability is an inherent attribute to a system. When the life-cycle costs of a system are being analyzed, reliability plays an important role as a major driver of these costs and has considerable influence on system performance. It is an iterative process that begins with specification of reliability goals consistent with cost and performance objectives. The data were collected from an Indian open cast coal mine and the reliability of various components of the electric mining shovel has been assessed by following a Weibull Model.

Keywords: reliability, Weibull model, electric mining shovel

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Authors: Adewale O. Ogunde, Olusegun Folorunso, Adesina S. Sodiya

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Most existing Distributed Association Rule Mining (DARM) systems are still facing several challenges. One of such challenges that have not received the attention of many researchers is the inability of existing systems to adapt to constantly changing databases and mining environments. In this work, an Adaptive Incremental Mining Algorithm (AIMA) is therefore proposed to address these problems. AIMA employed multiple mobile agents for the entire mining process. AIMA was designed to adapt to changes in the distributed databases by mining only the incremental database updates and using this to update the existing rules in order to improve the overall response time of the DARM system. In AIMA, global association rules were integrated incrementally from one data site to another through Results Integration Coordinating Agents. The mining agents in AIMA were made adaptive by defining mining goals with reasoning and behavioral capabilities and protocols that enabled them to either maintain or change their goals. AIMA employed Java Agent Development Environment Extension for designing the internal agents’ architecture. Results from experiments conducted on real datasets showed that the adaptive system, AIMA performed better than the non-adaptive systems with lower communication costs and higher task completion rates.

Keywords: adaptivity, data mining, distributed association rule mining, incremental mining, mobile agents

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Authors: Narmina Ismayilova, Shamil Zabitov, Fuad Askerzadeh, Raqif Seyfullayev

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Tulallar volcano-tectonic structure is located in the conjugation zone of the Gekgel horst-uplift, Dashkesan, and Agzhakend synclinorium. Regionally, these geological structures are an integral part of the Lok-Karabakh island arc system. Tulallar field is represented by three areas (Central, East, West). The area of the ore field is located within a partially eroded oblong volcano-tectonic depression. In the central part, the core is divided by the deep Tulallar-Chiragdara-Toganalinsky fault with arcuate fragments of the ring structure into three blocks -East, Central, and West, within which the same areas of the Tulallar field are located. In general, for the deposit, the position of both ore-bearing vein zones and ore-bearing blocks is controlled by fractures of two systems - sub-latitudinal and near-meridional orientations. Mineralization of gold-sulfide ores is confined to these zones of disturbances. The zones have a northwestern and northeastern (near-meridian) strike with a steep dip (70-85◦) to the southwest and southeast. The average thickness of the zones is 35 m; they are traced for 2.5 km along the strike and 500 m along with the dip. In general, for the indicated thickness, the zones contain an average of 1.56 ppm Au; however, areas enriched in noble metal are distinguished within them. The zones are complicated by postore fault tectonics. Gold mineralization is localized in the Kimmeridgian volcanics of andesi-basalt-porphyritic composition and their vitrolithoclastic, agglomerate tuffs, and tuff breccias. For the central part of the Tulallar ore field, a map of geochemical anomalies was built on the basis of analysis data carried out in an international laboratory. The total gold content ranges from 0.1-5 g/t, and in some places, even more than 5 g/t. The highest gold content is observed in the monoquartz facies among the secondary quartzites with quartz veins. The smallest amount of gold content appeared in the quartz-kaolin facies. And also, anomalous values of gold content are located in the upper part of the quartz vein. As a result, an en-echelon arrangement of anomalous values of gold along the strike and dip was revealed.

Keywords: geochemical anomaly, gold deposit, mineralization, Tulallar

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Authors: Umar Sambo Umar, Ahmad Isah Haruna, Abubakar Sadik Maigari, Muhammad Bello Abubakar

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Schist belts in Nigeria occur prominently west of longitude 80 E and sporadic to the east, they are upper Proterozioc low-medium grade deformed metasediments and metavolcanics that were intruded by Pan-African granitoids. The Wonaka schist belt, though reportedly distinctive in composition and metamorphism, is the least understood; the host for primary gold were not defined, structures which may control primary enrichment have not been delineated. The aim of this work is to determine the relationship between litho-structures and the gold around Wonaka schist belt through geological field mapping, petrographic studies and structural data analysis via ArcGis 10.2, Surfer 11.0 and Stereopro 2.0. The results show that the major rock types are mica schist and migmatites, muscovites detected during microstructural analysis suggests low-grade metamorphism in the metapelites. The shear zones identified were trending North Northeast – South Southwest (NNE-SSW), fractures trend mostly Northeast-Southwest (NE-SW) perpendicular to planes of gneissic foliations, these conform to the late Pan-African deformational episode. Pegmatite lodes, net self-cross cutting quartz veins as well as the quartz stringers hosted by both migmatites and schist are delineated as targets for primary gold mineralization, while major confluences of the streams serve as zones for secondary (placer) gold targets since the streams are dendritic and intermittent.

Keywords: gold mineralization, Nigeria, migmatites, Wonaka schist belt

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Authors: B. Suraj Aravind, M. H. M. Krishna Prasad

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There exist emerging applications of data streams that require association rule mining, such as network traffic monitoring, web click streams analysis, sensor data, data from satellites etc. Data streams typically arrive continuously in high speed with huge amount and changing data distribution. This raises new issues that need to be considered when developing association rule mining techniques for stream data. This paper proposes to introduce an improved data stream association rule mining algorithm by eliminating the limitation of resources. For this, the concept of cloud computing is used. Inclusion of this may lead to additional unknown problems which needs further research.

Keywords: data stream, association rule mining, cloud computing, frequent itemsets

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Authors: Maram Saleh

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Knowledge has become an essential resource in today’s economy and become the most important asset of maintaining competition advantage in organizations. The importance of knowledge has made organizations to manage their knowledge assets and resources through all multiple knowledge management stages such as: Knowledge Creation, knowledge storage, knowledge sharing and knowledge use. Researches on data mining are continues growing over recent years on both business and educational fields. Data mining is one of the most important steps of the knowledge discovery in databases process aiming to extract implicit, unknown but useful knowledge and it is considered as significant subfield in knowledge management. Data miming have the great potential to help organizations to focus on extracting the most important information on their data warehouses. Data mining tools and techniques can predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. This review paper explores the applications of data mining techniques in supporting knowledge management process as an effective knowledge discovery technique. In this paper, we identify the relationship between data mining and knowledge management, and then focus on introducing some application of date mining techniques in knowledge management for some real life domains.

Keywords: Data Mining, Knowledge management, Knowledge discovery, Knowledge creation.

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Authors: Adarsh Shroff

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Big data is a collection of dataset so large and complex that it becomes difficult to process using data base management tools. To perform operations like search, analysis, visualization on big data by using data mining; which is the process of extraction of patterns or knowledge from large data set. In recent years, the data mining applications become stale and obsolete over time. Incremental processing is a promising approach to refreshing mining results. It utilizes previously saved states to avoid the expense of re-computation from scratch. This project uses i2MapReduce, an incremental processing extension to Map Reduce, the most widely used framework for mining big data. I2MapReduce performs key-value pair level incremental processing rather than task level re-computation, supports not only one-step computation but also more sophisticated iterative computation, which is widely used in data mining applications, and incorporates a set of novel techniques to reduce I/O overhead for accessing preserved fine-grain computation states. To optimize the mining results, evaluate i2MapReduce using a one-step algorithm and three iterative algorithms with diverse computation characteristics for efficient mining.

Keywords: big data, map reduce, incremental processing, iterative computation

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Authors: Nhleko Monique Chiloane

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The gold mining industry has predominantly used ammonium nitrate fuel oil (ANFO) explosives for decades, although these are known to be “gassier” and their detonation results in toxic fumes, for example, carbon monoxide (CO), nitrogen oxides (NOx) and ammonia. Re-entry into underground workings too soon after blasting can lead to fatal exposure to toxic fumes. It is, therefore, required that the polluted air be removed from the affected areas within a reasonable period before employees' re-entry into the working area. Post-blast re-entry times have therefore been described as a productivity bottleneck. The known causes of post-blast fumes are water ingress, incorrect fuel to oxygen ratio, confinement, explosive additives etc. To prevent or minimize post-blast fumes, some researchers have used neutralization, re-burning technique and non-explosive products or different oxidizing agents. The use of commercial explosives without nitrate oxidizing agents can also minimize the production of blasting fumes and thereby reduce the time needed for the clearance of these fumes to allow workers to re-enter the underground workings safely. The reduction in non-production time directly contributes to an increase in the available time per shift for productive work, thus leading to continuous mining. However, owing to its low cost and ease of use, ANFO is still widely used in South African underground blasting operations.

Keywords: post-blast fumes, continuous mining, ammonium nitrate explosive, non-explosive blasting, re-entry period

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Authors: Sajjad Baghernezhad, Saeideh Baghernezhad

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Nowadays considering human involved in increasing data development some methods such as data mining to extract science are unavoidable. One of the discussions of data mining is inherent distribution of the data usually the bases creating or receiving such data belong to corporate or non-corporate persons and do not give their information freely to others. Yet there is no guarantee to enable someone to mine special data without entering in the owner’s privacy. Sending data and then gathering them by each vertical or horizontal software depends on the type of their preserving type and also executed to improve data privacy. In this study it was attempted to compare comprehensively preserving data methods; also general methods such as random data, coding and strong and weak points of each one are examined.

Keywords: data mining, distributed data mining, privacy protection, privacy preserving

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Authors: O. S. Adeyemi, C. G. Whiteley

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The present study determined the toxic potential of metal nanoparticles in cell culture system. Silver and gold nanoparticles were synthesized and characterized following established "green" protocols. The synthesized nanoparticles, in varying concentrations ranging from 0.1–100 µM were evaluated for toxicity in metastatic MDA-MB-231 cells. The nanoparticles promoted a generation of reactive oxygen species and reduced cell viability to less than 50% in the demonstration of cellular toxicity. The nanoparticles; gold and the silver-gold mixture had IC50 values of 56.65 and 18.44 µM respectively. The IC50 concentration for silver nanoparticles could not be determined. Furthermore, the probe of the cell death using flow cytometry and confocal microscopy revealed the partial involvement of apoptosis as well as necrosis. Our results revealed cellular toxicity caused by the nanoparticles but the mechanism remains yet undefined.

Keywords: cell death, nanomedicine, nanotoxicology, toxicity

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Authors: Suzan Wedyan

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Data mining is one of the main phases in the Knowledge Discovery Database (KDD) which is responsible of finding hidden and useful knowledge from databases. There are many different tasks for data mining including regression, pattern recognition, clustering, classification, and association rule. In recent years a promising data mining approach called associative classification (AC) has been proposed, AC integrates classification and association rule discovery to build classification models (classifiers). This paper surveys and critically compares several AC algorithms with reference of the different procedures are used in each algorithm, such as rule learning, rule sorting, rule pruning, classifier building, and class allocation for test cases.

Keywords: associative classification, classification, data mining, learning, rule ranking, rule pruning, prediction

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Authors: M. Sai Veerendra

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Today, money laundering (ML) poses a serious threat not only to financial institutions but also to the nation. This criminal activity is becoming more and more sophisticated and seems to have moved from the cliché of drug trafficking to financing terrorism and surely not forgetting personal gain. Most of the financial institutions internationally have been implementing anti-money laundering solutions (AML) to fight investment fraud activities. However, traditional investigative techniques consume numerous man-hours. Recently, data mining approaches have been developed and are considered as well-suited techniques for detecting ML activities. Within the scope of a collaboration project on developing a new data mining solution for AML Units in an international investment bank in Ireland, we survey recent data mining approaches for AML. In this paper, we present not only these approaches but also give an overview on the important factors in building data mining solutions for AML activities.

Keywords: data mining, clustering, money laundering, anti-money laundering solutions

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Authors: Ali Mortazavi

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The main objective of this research project is to delve into a multitude of geomechanical risks associated with various mining methods employed within the underground mining industry. Controlling geotechnical design parameters and operational factors affecting the selection of suitable mining techniques for a given underground mining condition will be considered from a risk assessment point of view. Important geomechanical challenges will be investigated as appropriate and relevant to the commonly used underground mining methods. Given the complicated nature of rock mass in-situ and complicated boundary conditions and operational complexities associated with various underground mining methods, the selection of a safe and economic mining operation is of paramount significance. Rock failure at varying scales within the underground mining openings is always a threat to mining operations and causes human and capital losses worldwide. Geotechnical design is a major design component of all underground mines and basically dominates the safety of an underground mine. With regard to uncertainties that exist in rock characterization prior to mine development, there are always risks associated with inappropriate design as a function of mining conditions and the selected mining method. Uncertainty often results from the inherent variability of rock masse, which in turn is a function of both geological materials and rock mass in-situ conditions. The focus of this research is on developing a methodology which enables a geomechanical risk assessment of given underground mining conditions. The outcome of this research is a geotechnical risk analysis algorithm, which can be used as an aid in selecting the appropriate mining method as a function of mine design parameters (e.g., rock in-situ properties, design method, governing boundary conditions such as in-situ stress and groundwater, etc.).

Keywords: geomechanical risk assessment, rock mechanics, underground mining, rock engineering

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Authors: Linus O. Asuquo

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Mining in Nigeria and development effort of metallurgical technologies at National Metallurgical Development Centre Jos has been addressed in this paper. The paper has looked at the history of mining in Nigeria, the impact of mining on social and industrial development, and the contribution of the mining sector to Nigeria’s Gross Domestic Product (GDP). The paper clearly stated that Nigeria’s mining sector only contributes 0.5% to the nation’s GDP unlike Botswana that the mining sector contributes 38% to the nation’s GDP. Nigeria Bureau of Statistics has it on record that Nigeria has about 44 solid minerals awaiting to be exploited. Clearly highlighted by this paper is the abundant potentials that exist in the mining sector for investment. The paper made an exposition on the extensive efforts made at National Metallurgical Development Center (NMDC) to develop metallurgical technologies in various areas of the metals sector; like mineral processing, foundry development, nonferrous metals extraction, materials testing, lime calcination, ANO (Trade name for powder lubricant) wire drawing lubricant, refractories and many others. The paper went ahead to draw a conclusion that there is a need to develop the mining sector in Nigeria and to give a sustainable support to the efforts currently made at NMDC to develop metallurgical technologies which are capable of transforming the metals sector in Nigeria, which will lead to industrialization. Finally the paper made some recommendations which traverse the topic for the best expectation.

Keywords: mining, minerals, technologies, value addition

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Authors: Sarra Senhadji, Imene Benzeguimi, Zohra Yagoub

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Big Data represents the recent technology of manipulating voluminous and unstructured data sets over multiple sources. Therefore, NOSQL appears to handle the problem of unstructured data. Association rules mining is one of the popular techniques of data mining to extract hidden relationship from transactional databases. The algorithm for finding association dependencies is well-solved with Map Reduce. The goal of our work is to reduce the time of generating of frequent itemsets by using Map Reduce and NOSQL database oriented document. A comparative study is given to evaluate the performances of our algorithm with the classical algorithm Apriori.

Keywords: Apriori, Association rules mining, Big Data, Data Mining, Hadoop, MapReduce, MongoDB, NoSQL

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Authors: Lisa Shambare, Jean Mulopo, Sehliselo Ndlovu

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One of the major challenges of sustainable development is promoting an industry which is both ecologically durable and economically viable. This requires processes that are material and energy efficient whilst also being able to limit the production of waste and toxic effluents through effective methods of process synthesis and intensification. In South Africa and globally, both miniaturisation and technological advances have substantially increased the amount of electronic wastes (e-waste) generated annually. Vast amounts of e-waste are being generated yearly with only a minute quantity being recycled officially. The passion for electronic devices cannot ignore the scarcity and cost of mining the noble metal resources which contribute significantly to the efficiency of most electronic devices. It has hence become imperative especially in an African context that sustainable strategies which are environmentally friendly be developed for recycling of the noble metals from e-waste. This paper investigates the recovery of gold, silver and palladium from electronic wastes, which consists of a vast array of metals, using ionic liquids which have the potential of reducing the gaseous and aqueous emissions associated with existing hydrometallurgical and pyrometallurgical technologies while also maintaining the economy of the overall recycling scheme through solvent recovery. The ionic liquids 1-butyl-3-methyl imidazolium hydrogen sulphate (BmimHSO4) which behaves like a protic acid and was used in the present research for the selective leaching of gold and silver from e-waste. Different concentrations of the aqueous ionic liquid were used in the experiments ranging from 10% to 50%. Thiourea was used as the complexing agent in the investigation with Fe3+ as the oxidant. The pH of the reaction was maintained in the range of 0.8 to 1.5. The preliminary investigations conducted were successful in the leaching of silver and palladium at room temperature with optimum results being at 48hrs. The leaching results could not be explained because of the leaching of palladium with the absence of gold. Hence a conclusion could not be drawn and there was the need for further experiments to be run. The leaching of palladium was carried out with hydrogen peroxide as oxidant and 1-butyl-3-methyl imidazolium chloride (BmimCl) as the solvent. The experiments at carried out at a temperature of 60 degrees celsius and a very low pH. The chloride ion was used to complex with palladium metal. From the preliminary results, it could be concluded that pretreatment of the treatment e-waste was necessary to improve the efficiency of the metal recovery process. A conclusion could not be drawn for the leaching experiments.

Keywords: BmimCl, BmimHSO4, gold, palladium, silver

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Authors: Awatef Hicheur Cairns, Billel Gueni, Hind Hafdi, Christian Joubert, Nasser Khelifa

Abstract:

Given the ever changing needs of the job markets, education and training centers are increasingly held accountable for student success. Therefore, education and training centers have to focus on ways to streamline their offers and educational processes in order to achieve the highest level of quality in curriculum contents and managerial decisions. Educational process mining is an emerging field in the educational data mining (EDM) discipline, concerned with developing methods to discover, analyze and provide a visual representation of complete educational processes. In this paper, we present our distributed computation platform which allows different education centers and institutions to load their data and access to advanced data mining and process mining services. To achieve this, we present also a comparative study of the different clustering techniques developed in the context of process mining to partition efficiently educational traces. Our goal is to find the best strategy for distributing heavy analysis computations on many processing nodes of our platform.

Keywords: educational process mining, distributed process mining, clustering, distributed platform, educational data mining, ProM

Procedia PDF Downloads 423

Authors: Emmanuel Agunloye, Asterios Gavriilidis, Luca Mazzei

Abstract:

Gold nanoparticles are commonly synthesized by reducing chloroauric acid with sodium citrate. This method, referred to as the citrate method, can produce spherical gold nanoparticles (NPs) in the size range 10-150 nm. Gold NPs of this size are useful in many applications. However, the NPs are usually polydisperse and irreproducible. A better understanding of the synthesis mechanisms is thus required. This work thoroughly investigated the only model that describes the synthesis. This model combines mass and population balance equations, describing the NPs synthesis through a sequence of chemical reactions. Chloroauric acid reacts with sodium citrate to form aurous chloride and dicarboxy acetone. The latter organizes aurous chloride in a nucleation step and concurrently degrades into acetone. The unconsumed precursor then grows the formed nuclei. However, depending on the pH, both the precursor and the reducing agent react differently thus affecting the synthesis. In this work, we investigated the model for different conditions of pH, temperature and initial reactant concentrations. To solve the model, we used Parsival, a commercial numerical code, whilst to test it, we considered various conditions studied experimentally by different researchers, for which results are available in the literature. The model poorly predicted the experimental data. We believe that this is because the model does not account for the acid-base properties of both chloroauric acid and sodium citrate.

Keywords: citrate method, gold nanoparticles, Parsival, population balance equations, Turkevich organizer theory

Procedia PDF Downloads 166

Authors: Seema Vaidya

Abstract:

Mining association rule is a key issue in data mining. In any case, the standard models ignore the distinction among the exchanges, and the weighted association rule mining does not transform on databases with just binary attributes. This paper proposes a novel continuous example and executes a tree (FP-tree) structure, which is an increased prefix-tree structure for securing compacted, discriminating data about examples, and makes a fit FP-tree-based mining system, FP enhanced capacity algorithm is used, for mining the complete game plan of examples by illustration incessant development. Here, this paper handles the motivation behind making remarkable and weighted item sets, i.e. rare weighted item set mining issue. The two novel brightness measures are proposed for figuring the infrequent weighted item set mining issue. Also, the algorithm are handled which perform IWI which is more insignificant IWI mining. Moreover we utilized the rare item set for choice based structure. The general issue of the start of reliable definite rules is troublesome for the grounds that hypothetically no inciting technique with no other person can promise the rightness of influenced theories. In this way, this framework expects the disorder with the uncommon signs. Usage study demonstrates that proposed algorithm upgrades the structure which is successful and versatile for mining both long and short diagnostics rules. Structure upgrades aftereffects of foreseeing rare diseases of patient.

Keywords: association rule, data mining, IWI mining, infrequent item set, frequent pattern growth

Procedia PDF Downloads 377

Authors: T. P. Oladele, C. A. Snyders, S. M. Bradshaw, G. Akdogan

Abstract:

The effect of temperature, contact time and agitation during pre-treatment was investigated on the elution of gold from granular activated carbon at fixed caustic-cyanide concentration and elution conditions. It was shown that there are interactions between parameters during pre-treatment. At 80oC, recovery is independent of the contact time while the maximum recovery is obtained in the absence of agitation (0rpm). Increase in agitation speed from 0 rev/min to 1200 rev/min showed a decrease in recovery of approximately 20 percent at 80°C. Recovery with increased time from 15 minutes to 45 minutes is only pronounced at 25°C with approximately 4 percent increase at all agitation speeds. The results from elution recovery are aimed to give insight into the mechanisms of pre-treatment under the combinations of the chosen parameters.

Keywords: gold, temperature, contact time, agitation speed, recovery

Procedia PDF Downloads 446