Search results for: data stream mining

Authors: Vivian W. L. Tsang, Karen Lockhart, Samuel Spiegel, Annalee Yassi

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Background: Workers in the informal economy often incur exposure to well-documented occupational health hazards. Insufficient attention has been afforded to rigorously evaluating intervention programs to reduce the risks, especially in artisanal and small-scale gold mining (ASGM). Objectives: This systematic review, conducted as part of the World Health Organization’s Global Plan of Action for Workers’ Health, sought to assess the state of knowledge on occupational health programs and interventions for the informal artisanal and small-scale gold mining (ASGM) sector, an occupation which directly employs at least 50 million people. Methods: We used a comprehensive search strategy for four well-known databases relevant to health outcomes: PubMed, Engineering Village, OVID Medline, and Web of Science, and employed the PRISMA framework for our analysis. Findings: Ten studies met the inclusion criteria of a primary study focused on assessing the impact of interventions addressing occupational health concerns in ASGM. There were no studies evaluating or even identifying comprehensive occupational health and safety programs for this sector, although target interventions addressing specific hazards exist. Major areas of intervention –education and introduction of mercury-reducing/eliminating technology were identified, and the challenges and limitations of each intervention taken into the assessment. Even for these, however, there was a lack of standardization for measuring outcome or impact, let alone long-term health outcomes for miners and mining communities. Conclusion: There is an urgent need for research on comprehensive occupational health programs addressing the array of hazards faced by artisanal and small-scale miners.

Keywords: informal economy, artisanal and small-scale gold mining, occupational health, health and safety, workplace safety

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Authors: I. Inthanongsone, C. Drebenstedt, J. C. Bongaerts, P. Sontamino

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The major concern in evaluating the value of mining projects related to the deficiency of the traditional discounted cash flow (DCF) method. This method does not take uncertainties into account and, hence it does not allow for an economic assessment of managerial flexibility and operational adaptability, which are increasingly determining long-term corporate success. Such an assessment can be performed with the real options valuation (ROV) approach, since it allows for a comparative evaluation of unforeseen uncertainties in a project life cycle. This paper presents an economic evaluation model for open pit mining projects based on real options valuation approach. Uncertainties in the model are caused by metal prices and cost uncertainties and the system dynamics (SD) modeling method is used to structure and solve the real options model. The model is applied to a case study. It can be shown that that managerial flexibility reacting to uncertainties may create additional value to a mining project in comparison to the outcomes of a DCF method. One important insight for management dealing with uncertainty is seen in choosing the optimal time to exercise strategic options.

Keywords: DCF methods, ROV approach, system dynamics modeling methods, uncertainty

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Authors: Doug Specht

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This research project sought to explore the links between digital media, PGIS and social movement organisations in Tolima, Colombia. The primary aim of the research was to examine how knowledge is created and disseminated through digital media and GIS in the region, and whether there exists the infrastructure to allow for this. The second strand was to ascertain if this has had a significant impact on the way grassroots movements work and produce collective actions. The third element is a hypothesis about how digital media and PGIS could play a larger role in activist activities, particularly in reference to the extractive industries. Three theoretical strands have been brought together to provide a basis for this research, namely (a) the politics of knowledge, (b) spatial management and inclusion, and (c) digital media and political engagement. Quantitative data relating to digital media and mobile internet use was collated alongside qualitative data relating to the likelihood of using digital media in activist campaigns, with particular attention being given to grassroots movements working against extractive industries in the Tolima region of Colombia. Through interviews, surveys and GIS analysis it has been possible to build a picture of online activism and the role of PPGIS within protest movement in the region of Tolima, Colombia. Results show a gap between the desires of social movements to use digital media and the skills and finances required to implement programs that utilise it. Maps and GIS are generally reserved for legal cases rather than for informing the lay person. However, it became apparent that the combination of digital/social media and PPGIS could play a significant role in supporting the work of grassroots movements.

Keywords: PGIS, GIS, social media, digital media, mining, colombia, social movements, protest

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Authors: Ajit Singh, Waliur Rahaman, Parmanand Sharma, Laluraj C. M., Lavkush Patel, Bhanu Pratap, Vinay Kumar Gaddam, Meloth Thamban

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The Himalayan glaciers are the potential source of perennial water supply to Asia’s major river systems like the Ganga, Brahmaputra and the Indus. In order to improve our understanding about the source of precipitation and hydrograph components in the interior Himalayan glaciers, it is important to decipher the sources of moisture and their contribution to the glaciers in this river system. In doing so, we conducted an extensive pilot study in a Sutri Dhaka glacier, western Himalaya during 2014-15. To determine the moisture sources, rain, surface snow, ice, and stream meltwater samples were collected and analyzed for stable oxygen (δ¹⁸O) and hydrogen (δD) isotopes. A two-component hydrograph separation was performed for the glacier stream using these isotopes assuming the contribution of rain, groundwater and spring water contribution is negligible based on field studies and available literature. To validate the results obtained from hydrograph separation using above method, snow and ice melt ablation were measured using a network of bamboo stakes and snow pits. The δ¹⁸O and δD in rain samples range from -5.3% to -20.8% and -31.7% to -148.4% respectively. It is noteworthy to observe that the rain samples showed enriched values in the early season (July-August) and progressively get depleted at the end of the season (September). This could be due to the ‘amount effect’. Similarly, old snow samples have shown enriched isotopic values compared to fresh snow. This could because of the sublimation processes operating over the old surface snow. The δ¹⁸O and δD values in glacier ice samples range from -11.6% to -15.7% and -31.7% to -148.4%, whereas in a Sutri Dhaka meltwater stream, it ranges from -12.7% to -16.2% and -82.9% to -112.7% respectively. The mean deuterium excess (d-excess) value in all collected samples exceeds more than 16% which suggests the predominant moisture source of precipitation is from the Western Disturbances. Our detailed estimates of the hydrograph separation of Sutri Dhaka meltwater using isotope hydrograph separation and glaciological field methods agree within their uncertainty; stream meltwater budget is dominated by glaciers ice melt over snowmelt. The present study provides insights into the sources of moisture, controlling mechanism of the isotopic characteristics of Sutri Dhaka glacier water and helps in understanding the snow and ice melt components in Chandra basin, Western Himalaya.

Keywords: D-excess, hydrograph separation, Sutri Dhaka, stable water isotope, western Himalaya

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Authors: Sergio Zabala-Vargas, Miguel Jiménez-Barrera, Luz VArgas-Sánchez

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In recent years, information related to project management in organizations has been increasing exponentially. Performance data, management statistics, indicator results have forced the collection, analysis, traceability, and dissemination of project managers to be essential. In this sense, there are current trends to facilitate efficient decision-making in emerging technology projects, such as: Machine Learning, Data Analytics, Data Mining, and Big Data. The latter is the most interesting in this project. This research is part of the thematic line Construction methods and project management. Many authors present the relevance that the use of emerging technologies, such as Big Data, has taken in recent years in project management in the construction sector. The main focus is the optimization of time, scope, budget, and in general mitigating risks. This research was developed in the northeastern region of Colombia-South America. The first phase was aimed at diagnosing the use of emerging technologies (Big-Data) in the construction sector. In Colombia, the construction sector represents more than 50% of the productive system, and more than 2 million people participate in this economic segment. The quantitative approach was used. A survey was applied to a sample of 91 companies in the construction sector. Preliminary results indicate that the use of Big Data and other emerging technologies is very low and also that there is interest in modernizing project management. There is evidence of a correlation between the interest in using new data management technologies and the incorporation of Building Information Modeling BIM. The next phase of the research will allow the generation of guidelines and strategies for the incorporation of technological tools in the construction sector in Colombia.

Keywords: big data, building information modeling, tecnology, project manamegent

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Authors: E Tambo, O. O. Olalubi, E. C. Ugwu, J. Y. Ngogang

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Despite the World Health Organization (WHO) declaration of international health emergency concern, the status quo of responses and efforts to stem the worst-recorded Ebola epidemic Ebola outbreak is still precariously inadequate in most of the affected in West. Mining natural resources have been shown to play a key role in both motivating and fuelling ethnic, civil and armed conflicts that have plagued a number of African countries over the last decade. Revenues from the exploitation of natural resources are not only used in sustaining the national economy but also armies, personal enrichment and building political support. Little is documented on the mining and ecological impact on the emergence and geographical distribution of Ebola in Africa over time and space. We aimed to provide a better understanding of the interconnectedness among issues of mining natural, resource management, mining conflict and post-conflict on Ebola outbreak and how wealth generated from abundant natural resources could be better managed in promoting research and development towards strengthening environmental, socioeconomic and health systems sustainability on Ebola outbreak and other emerging diseases surveillance and responses systems prevention and control, early warning alert, durable peace and sustainable development rather than to fuel conflicts, resurgence and emerging diseases epidemics in the perspective of community and national/regional approach. Our results showed the first assessment of systematic impact of all major minerals conflict events diffusion over space and time and mining activities on nine Ebola genesis and geo-distribution in affected countries across Africa. We demonstrate how, where and when mining activities in Africa increase ecological degradation, conflicts at the local level and then spreads violence across territory and time by enhancing the financial capacities of fighting groups/ethnics and diseases onset. In addition, led process of developing minimum standards for natural resource governance; improving governmental and civil society capacity for natural resource management, including the strengthening of monitoring and enforcement mechanisms; understanding the post-mining and conflicts community or national reconstruction and rehabilitation programmes in strengthening or developing community health systems and regulatory mechanisms. In addition the quest for the control over these resources and illegal mining across the landscape forest incursion provided increase environmental and ecological instability and displacement and disequilibrium, therefore affecting the intensity and duration of mining and conflict/wars and episode of Ebola outbreaks over time and space. We highlight the key findings and lessons learnt in promoting country or community-led process in transforming natural resource wealth from a peace liability to a peace asset. The imperative necessity for advocacy and through facilitating intergovernmental deliberations on critical issues and challenges affecting Africa community transforming exploitation of natural resources from a peace liability to outbreak prevention and control. The vital role of mining in increasing government revenues and expenditures, equitable distribution of wealth and health to all stakeholders, in particular local communities requires coordination, cooperative leadership and partnership in fostering sustainable developmental initiatives from mining context to outbreak and other infectious diseases surveillance responses systems in prevention and control, and judicious resource management.

Keywords: mining, mining conflicts, mines, ecological, Ebola, outbreak, mining companies, miners, impact

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Authors: Saeidreza Radpour, Md. Ahiduzzaman, Amit Kumar

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Alberta’s mining sector consumed 871.3 PJ in 2012, which is 67.1% of the energy consumed in the industry sector and about 40% of all the energy consumed in the province of Alberta. Natural gas, petroleum products, and electricity supplied 55.9%, 20.8%, and 7.7%, respectively, of the total energy use in this sector. Oil sands mining and upgrading to crude oil make up most of the mining energy sector activities in Alberta. Crude oil is produced from the oil sands either by in situ methods or by the mining and extraction of bitumen from oil sands ore. In this research, the factors affecting oil sands production have been assessed and a framework has been developed for market penetration of new efficient technologies in this sector. Oil sands production amount is a complex function of many different factors, broadly categorized into technical, economic, political, and global clusters. The results of developed and implemented statistical analysis in this research show that the importance of key factors affecting on oil sands production in Alberta is ranked as: Global energy consumption (94% consistency), Global crude oil price (86% consistency), and Crude oil export (80% consistency). A framework for modeling oil sands energy technologies’ market penetration (OSETMP) has been developed to cover related technical, economic and environmental factors in this sector. It has been assumed that the impact of political and social constraints is reflected in the model by changes of global oil price or crude oil price in Canada. The market share of novel in situ mining technologies with low energy and water use are assessed and calculated in the market penetration framework include: 1) Partial upgrading, 2) Liquid addition to steam to enhance recovery (LASER), 3) Solvent-assisted process (SAP), also called solvent-cyclic steam-assisted gravity drainage (SC-SAGD), 4) Cyclic solvent, 5) Heated solvent, 6) Wedge well, 7) Enhanced modified steam and Gas push (emsagp), 8) Electro-thermal dynamic stripping process (ET-DSP), 9) Harris electro-magnetic heating applications (EMHA), 10) Paraffin froth separation. The results of the study will show the penetration profile of these technologies over a long term planning horizon.

Keywords: appliances efficiency improvement, diffusion models, market penetration, residential sector

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Authors: Stellina Jolly

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July 18th to August 19th 2013 has gone down in the history of India for undertaking the country’s first environment referendum. The Supreme Court had ruled that the Vedanta Group's bauxite mining project in the Niyamgiri Hills of Orissa will have to get clearance from the gram sabha, which will consider the cultural and religious rights of the tribals and forest dwellers living in Rayagada and Kalahandi districts. In the Niyamgiri hills, people of small tribal hamlets were asked to voice their opinion on bauxite mining in their habitat. The ministry has reiterated its stand that mining cannot be allowed on the Niyamgiri hills because it will affect the rights of the Dongria Kondhs. The tribal person who occupies the Niyamgiri Hills in Eastern India accomplished their first success in 2010 in their struggle to protect and preserve their existence, culture and land against Vedanta a London-based mining giant. In August, 2010 Government of India revoked permission for Vedanta Resources to mine bauxite from hills in Orissa State where the Dongria Kondh live as forest dwellers. This came after various protests and reports including amnesty report wherein it highlighted that an alumina refinery in eastern India operated by a subsidiary of mining company. Vedanta was accused of causing air and water pollution that threatens the health of local people and their access to water. The abuse of human rights by corporate is not a new issue it has occurred in Africa, Asia and other parts of the world. Paper focuses on the instances and extent of human right especially in terms of environment violations by corporations. Further Paper details on corporations and sustainable development. Paper finally comes up with certain recommendation including call for a declaration by United Nations on Corporate environment Human Rights Liability.

Keywords: environment, corporate, human rights, sustainable development

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Authors: Amir Bak Khoshnevis, Mahdieh Khodadadi, Aghil Lotfi

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For a bluff body, roughness elements in simulating a turbulent boundary layer, leading to delayed flow separation, a smaller wake, and lower form drag. In the present work, flow past a circular cylinder with using tripping wires is studied experimentally. The wind tunnel used for modeling free stream is open blow circuit (maximum speed = 30m/s and maximum turbulence of free stream = 0.1%). The selected Reynolds number for all tests was constant (Re = 25000). The circular cylinder selected for this experiment is 20 and 400mm in diameter and length, respectively. The aim of this research is to find the optimal operation mode. In this study installed some tripping wires 1mm in diameter, with a different number of wires on the circular cylinder and the wake characteristics of the circular cylinder is studied. Results showed that by increasing number of tripping wires attached to the circular cylinder (6, 8, and 10, respectively), The optimal angle for the tripping wires with 1mm in diameter to be installed on the cylinder is 60̊ (or 6 wires required at angle difference of 60̊). Strouhal number for the cylinder with tripping wires 1mm in diameter at angular position 60̊ showed the maximum value.

Keywords: wake of circular cylinder, trip wire, velocity defect, strouhal number

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Authors: Khaled Benyounes

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Determination of the rock mechanical properties such as unconfined compressive strength UCS, Young’s modulus E, and tensile strength by the Brazilian test Rtb is considered to be the most important component in drilling and mining engineering project. Research related to establishing correlation between strength and physical parameters of rocks has always been of interest to mining and reservoir engineering. For this, many rock blocks of limestone were collected from the quarry located in Meftah (Algeria), the cores were crafted in the laboratory using a core drill. This work examines the relationships between mechanical properties and some physical properties of limestone. Many empirical equations are established between UCS and physical properties of limestone (such as dry bulk density, velocity of P-waves, dynamic Young’s modulus, alteration index, and total porosity). Other correlations, UCS - tensile strength, dynamic Young’s modulus - static Young’s modulus have been find. Based on the Mohr-Coulomb failure criterion, we were able to establish mathematical relationships that will allow estimating the cohesion and internal friction angle from UCS and indirect tensile strength. Results from this study can be useful for mining industry for resolve range of geomechanical problems such as slope stability.

Keywords: limestone, mechanical strength, Young’s modulus, porosity

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Authors: Ebuwa Osagie, Chet Biliyok, Yeung Hoi

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Regeneration energy requirement and ways to reduce it is the main aim of most CO2 capture researches currently being performed and thus, post-combustion carbon capture (PCC) option is identified to be the most suitable for the natural gas-fired power plants. From current research and development (R&D) activities worldwide, two main areas are being examined in order to reduce the regeneration energy requirement of amine-based PCC, namely: (a) development of new solvents with better overall performance than 30wt% monoethanolamine (MEA) aqueous solution, which is considered as the base-line solvent for solvent-based PCC, (b) Integration of the PCC Plant to the power plant. In scaling-up a PCC pilot plant to the size required for a commercial-scale natural gas-fired power plant, process modelling and simulation is very essential. In this work, an integrated process made up of a 482MWe natural gas-fired power plant, an MEA-based PCC plant which is developed and validated has been modelled and simulated. The PCC plant has four absorber columns and a single stripper column, the modelling and simulation was performed with Aspen Plus® V8.4. The gas turbine, the heat recovery steam generator and the steam cycle were modelled based on a 2010 US DOE report, while the MEA-based PCC plant was modelled as a rate-based process. The scaling of the amine plant was performed using a rate based calculation in preference to the equilibrium based approach for 90% CO2 capture. The power plant was integrated to the PCC plant in three ways: (i) flue gas stream from the power plant which is divided equally into four stream and each stream is fed into one of the four absorbers in the PCC plant. (ii) Steam draw-off from the IP/LP cross-over pipe in the steam cycle of the power plant used to regenerate solvent in the reboiler. (iii) Condensate returns from the reboiler to the power plant. The integration of a PCC plant to the NGCC plant resulted in a reduction of the power plant output by 73.56 MWe and the net efficiency of the integrated system is reduced by 7.3 % point efficiency. A secondary aim of this study is the parametric studies which have been performed to assess the impacts of natural gas on the overall performance of the integrated process and this is achieved through investigation of the capture efficiencies.

Keywords: natural gas-fired, power plant, MEA, CO2 capture, modelling, simulation

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Authors: Jalal Soleimannejad, Mohammad Asadizeidabadi, Mahmoud Koorki, Mojtaba Azarpira

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A significant percentage of production costs is the maintenance costs, and analysis of maintenance costs could to achieve greater productivity and competitiveness. With this is mind, the maintenance of machines and installations is considered as an essential part of organizational functions and applying effective strategies causes significant added value in manufacturing activities. Organizations are trying to achieve performance levels on a global scale with emphasis on creating competitive advantage by different methods consist of RCM (Reliability-Center-Maintenance), TPM (Total Productivity Maintenance) etc. In this study, increasing the capacity of Concentration Plant of Golgohar Iron Ore Mining & Industrial Company (GEG) was examined by using of reliability and maintainability analyses. The results of this research showed that instead of increasing the number of machines (in order to solve the bottleneck problems), the improving of reliability and maintainability would solve bottleneck problems in the best way. It should be mention that in the abovementioned study, the data set of Concentration Plant of GEG as a case study, was applied and analyzed.

Keywords: bottleneck, golgohar iron ore mining & industrial company, maintainability, maintenance costs, reliability

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Authors: Obed Asamoah

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Forests are very vital for human survival and our well-being. During the past years, the world has taken an increasingly significant role in the modification of the global environment. The high rate of deforestation in Ghana is of primary national concern as the forests provide many ecosystem services and functions that support the country’s predominantly agrarian economy and foreign earnings. Ghana forest is currently major source of carbon sink that helps to mitigate climate change. Ghana forests, both the reserves and off-reserves, are under pressure of deforestation. The causes of deforestation are varied but can broadly be categorized into anthropogenic and natural factors. For the anthropogenic factors, increased wood fuel collection, clearing of forests for agriculture, illegal and poorly regulated timber extraction, social and environmental conflicts, increasing urbanization and industrialization are the primary known causes for the loss of forests and woodlands. Mineral exploitation in the forest areas is considered as one of the major causes of deforestation in Ghana. Mining activities especially mining of gold by both the licensed mining companies and illegal mining groups who are locally known as "gallantly mining" also cause damage to the nation's forest reserves. Several works have been conducted regarding the causes of the high rate of deforestation in Ghana, major attention has been placed on illegal logging and using forest lands for illegal farming and mining activities. Less emphasis has been placed on the timber production companies on their harvesting methods in the forests in Ghana and other activities that are carried out in the forest. The main objective of the work is to find out the harvesting methods and the activities of the timber production companies and their effects on the forests in Ghana. Both qualitative and quantitative research methods were engaged in the research work. The study population comprised of 20 Timber industries (Sawmills) forest areas of Ghana. These companies were selected randomly. The cluster sampling technique was engaged in selecting the respondents. Both primary and secondary data were employed. In the study, it was observed that most of the timber production companies do not know the age, the weight, the distance covered from the harvesting to the loading site in the forest. It was also observed that old and heavy machines are used by timber production companies in their operations in the forest, which makes the soil compact prevents regeneration and enhances soil erosion. It was observed that timber production companies do not abide by the rules and regulations governing their operations in the forest. The high rate of corruption on the side of the officials of the Ghana forestry commission makes the officials relax and do not embark on proper monitoring on the operations of the timber production companies which makes the timber companies to cause more harm to the forest. In other to curb this situation the Ghana forestry commission with the ministry of lands and natural resources should monitor the activities of the timber production companies and sanction all the companies that make foul play in their activities in the forest. The commission should also pay more attention to the policy “fell one plant 10” to enhance regeneration in both reserves and off-reserves forest.

Keywords: companies, deforestation, forest, Ghana, timber

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Authors: Sharmin Sultana, Nicolas Nuns, Pardis Simon, Jean-Marc Giraudon, Jean-Francois Lamonior, Nathalie D. Geyter, Rino Morent

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Environmental issues, especially air pollution, have become a huge concern of environmental legislation as a consequence of growing awareness in our global world. In this regard, control of volatile organic compounds (VOCs) emission has become an important issue due to their potential toxicity, carcinogenicity, and mutagenicity. The research of innovative technologies for VOC abatement is stimulated to accommodate the new stringent standards in terms of VOC emission. One emerging strategy is the coupling of 2 existing complementary technologies, namely here non-thermal plasma (NTP) and heterogeneous catalysis, to get a more efficient process for VOC removal in air. The objective of this current work is to investigate the abatement of trichloroethylene (TCE-highly toxic chlorinated VOC) from moist air (RH=15%) as a function of time by combined use of multi-pin-to-plate negative DC corona/glow discharge with Fe-doped cryptomelanes catalyst downstream i.e. post plasma-catalysis (PPC) process. For catalyst alone case, experiments reveal that, initially, Fe doped cryptomelane (regardless the mode of Fe incorporation by co-precipitation (Fe-K-OMS-2)/ impregnation (Fe/K-OMS-2)) exhibits excellent activity to decompose TCE compared to cryptomelane (K-OMS-2) itself. A maximum obtained value of TCE abatement after 6 min is as follows: Fe-KOMS-2 (73.3%) > Fe/KOMS-2 (48.5) > KOMS-2 (22.6%). However, with prolonged operation time, whatever the catalyst under concern, the abatement of TCE decreases. After 111 min time of exposure, the catalysts can be ranked as follows: Fe/KOMS-2 (11%) < K-OMS-2 (12.3%) < Fe-KOMS-2 (14.5%). Clearly, this phenomenon indicates catalyst deactivation either by chlorination or by blocking the active sites. Remarkably, in PPC configuration (energy density = 60 J/L, catalyst temperature = 150°C), experiments reveal an enhanced performance towards TCE removal regardless the type of catalyst. After 6 min time on stream, the TCE removal efficiency amount as follows: K-OMS-2 (60%) < Fe/K-OMS-2 (79%) < Fe-K-OMS-2 (99.3%). The enhanced performances over Fe-K-OMS-2 catalyst are attributed to its high surface oxygen mobility and structural defects leading to high O₃ decomposition efficiency to give active species able to oxidize the plasma processed hazardous\by-products and the possibly remaining VOC into CO₂. Moreover, both undoped and doped catalysts remain strongly capable to abate TCE with time on stream. The TCE removal efficiencies of the PPC processes with Fe/KOMS-2 and KOMS-2 catalysts are not affected by time on stream indicating an excellent catalyst stability. When using the Fe-K-OMS-2 as catalyst, TCE abatement slightly reduces with time on stream. However, it is noteworthy to stress that still a constant abatement of 83% is observed during at least 30 minutes. These results prove that the combination of NTP with catalysts not only increases the catalytic activity but also allows to avoid, to some extent, the poisoning of catalytic sites resulting in an enhanced catalyst stability. In order to better understand the different surface processes occurring in the course of the total TCE oxidation in PPC experiments, a detailed X-ray Photoelectron Spectroscopy (XPS) and Time of Flight-Secondary Ion Mass Spectrometry (ToF-SIMS) study on the fresh and used catalysts is in progress.

Keywords: Fe doped cryptomelane, non-thermal plasma, plasma-catalysis, stability, trichloroethylene

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Authors: K. Jahani, J. Razavi

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Nowadays, to decrease the number of downtimes in the industries such as metal mining, petroleum and chemical industries, predictive maintenance is crucial. In order to have efficient predictive maintenance, knowing the performance of critical equipment of production line such as pumps and hydro-cyclones under variable operating parameters, selecting best indicators of this equipment health situations, best locations for instrumentation, and also measuring of these indicators are very important. In this paper, computer aided engineering (CAE) tools are implemented to study some important elements of copper process line, namely slurry pumps and cyclone to predict the performance of these components under different working conditions. These modeling and simulations can be used in predicting, for example, the damage tolerance of the main shaft of the slurry pump or wear rate and location of cyclone wall or pump case and impeller. Also, the simulations can suggest best-measuring parameters, measuring intervals, and their locations.

Keywords: computer aided engineering, predictive maintenance, fault detection, mining process line, slurry pump, hydrocyclone

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Authors: Amir B. Khoshnevis, Morteza Mirhosseini

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The paper deals with a sub-part of an extensive research program on the wake survey method in various Reynolds numbers and angles of attack. This research experimentally investigates the wake flow characteristics behind S823 and S822 airfoils in which designed for small wind turbines. Velocity measurements determined by using hot-wire anemometer. Data acquired in the wake of the airfoil at locations(c is the chord length): 0.01c - 3c. Reynolds number increased due to increase of free stream velocity. Results showed that mean velocity profiles depend on the angle of attack and location of data collections. Data acquired at the low Reynolds numbers (smaller than 10^5). Effects of Reynolds numbers on the mean velocity profiles are more significant in near locations the trailing edge and these effects decrease by taking distance from trailing edge toward downstream. Mean velocity profiles region increased by increasing the angle of attack, except for 7°, and also the maximum velocity deficit (velocity defect) increased. The difference of mean velocity in and out of the wake decreased by taking distance from trailing edge, and mean velocity profile become wider and more uniform.

Keywords: angle of attack, Reynolds number, velocity deficit, separation

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Authors: Halkiopoulos Constantinos, Gkintoni Evgenia, Koutsopoulou Ioanna, Antonopoulou Hera

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E-sports and e-gaming have emerged in recent years since the increase in internet use have become universal and e-gamers are the new reality in our homes. The excessive involvement of young adults with e-sports has already been revealed and the adverse consequences have been reported in researches in the past few years, but the issue has not been fully studied yet. The present research is conducted in Greece and studies the psychological profile of video game players and provides information on personality traits, habits and emotional status that affect online gamers’ behaviors in order to help professionals and policy makers address the problem. Three standardized self-report questionnaires were administered to participants who were young male and female adults aged from 19-26 years old. The Profile of Mood States (POMS) scale was used to evaluate people’s perceptions of their everyday life mood; the personality features that can trace back to people’s habits and anticipated reactions were measured by Eysenck Personality Questionnaire (EPQ), and the Trait Emotional Intelligence Questionnaire (TEIQue) was used to measure which cognitive (gamers’ beliefs) and emotional parameters (gamers’ emotional abilities) mainly affected/ predicted gamers’ behaviors and leisure time activities?/ gaming behaviors. Data mining techniques were used to analyze the data, which resulted in machine learning algorithms that were included in the software package R. The research findings attempt to designate the effect of personality traits, emotional status and emotional intelligence influence and correlation with e-sports, gamers’ behaviors and help policy makers and stakeholders take action, shape social policy and prevent the adverse consequences on young adults. The need for further research, prevention and treatment strategies is also addressed.

Keywords: e-sports, e-gamers, personality traits, POMS, emotional intelligence, data mining, R

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Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

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In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

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Authors: Rajkumar Ghosh

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The industrialization of coal mining and related activities has a significant impact on groundwater in the surrounding areas of the Damodar River. The Damodar River basin, located in eastern India, is known as the "Ruhr of India" due to its abundant coal reserves and extensive coal mining and industrial operations. One of the major consequences of collieries on groundwater is the contamination of water sources. Coal mining activities often involve the excavation and extraction of coal through underground or open-pit mining methods. These processes can release various pollutants and chemicals into the groundwater, including heavy metals, acid mine drainage, and other toxic substances. As a result, the quality of groundwater in the Damodar River region has deteriorated, making it unsuitable for drinking, irrigation, and other purposes. The high concentration of heavy metals, such as arsenic, lead, and mercury, in the groundwater has posed severe health risks to the local population. Prolonged exposure to contaminated water can lead to various health problems, including skin diseases, respiratory issues, and even long-term ailments like cancer. The contamination has also affected the aquatic ecosystem, harming fish populations and other organisms dependent on the river's water. Moreover, the excessive extraction of groundwater for industrial processes, including coal washing and cooling systems, has resulted in a decline in the water table and depletion of aquifers. This has led to water scarcity and reduced availability of water for agricultural activities, impacting the livelihoods of farmers in the region. Efforts have been made to mitigate these issues through the implementation of regulations and improved industrial practices. However, the historical legacy of coal industrialization continues to impact the groundwater in the Damodar River area. Remediation measures, such as the installation of water treatment plants and the promotion of sustainable mining practices, are essential to restore the quality of groundwater and ensure the well-being of the affected communities. In conclusion, the coal industrialization in the Damodar River surrounding has had a detrimental impact on groundwater. This research focuses on soil subsidence induced by the over-exploitation of ground water for dewatering open pit coal mines. Soil degradation happens in arid and semi-arid regions as a result of land subsidence in coal mining region, which reduces soil fertility. Depletion of aquifers, contamination, and water scarcity are some of the key challenges resulting from these activities. It is crucial to prioritize sustainable mining practices, environmental conservation, and the provision of clean drinking water to mitigate the long-lasting effects of collieries on the groundwater resources in the region.

Keywords: coal mining, groundwater, soil subsidence, water table, damodar river

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Authors: Kyoungrean Kim

Abstract:

Importance of deep-sea mineral resources is dramatically increasing due to the depletion of land mineral resources corresponding to increasing human’s economic activities. Korea has acquired exclusive exploration licenses at four areas which are the Clarion-Clipperton Fracture Zone in the Pacific Ocean (2002), Tonga (2008), Fiji (2011) and Indian Ocean (2014). The preparation for commercial mining of Nautilus minerals (Canada) and Lockheed martin minerals (USA) is expected by 2020. The London Protocol 1996 (LP) under International Maritime Organization (IMO) and International Seabed Authority (ISA) will set environmental guidelines for deep-sea mining until 2020, to protect marine environment. In this research, the applicability of washing/extraction treatment for the remediation of deep-sea mining tailings was mainly evaluated in order to present preliminary data to develop practical remediation technology in near future. Polymetallic nodule samples were collected at the Clarion-Clipperton Fracture Zone in the Pacific Ocean, then stored at room temperature. Samples were pulverized by using jaw crusher and ball mill then, classified into 3 particle sizes (> 63 µm, 63-20 µm, < 20 µm) by using vibratory sieve shakers (Analysette 3 Pro, Fritsch, Germany) with 63 µm and 20 µm sieve. Only the particle size 63-20 µm was used as the samples for investigation considering the lower limit of ore dressing process which is tens to 100 µm. Rhamnolipid and sodium alginate as biosurfactant and aluminum sulfate which are mainly used as flocculant were used as environmentally friendly additives. Samples were adjusted to 2% liquid with deionized water then mixed with various concentrations of additives. The mixture was stirred with a magnetic bar during specific reaction times and then the liquid phase was separated by a centrifugal separator (Thermo Fisher Scientific, USA) under 4,000 rpm for 1 h. The separated liquid was filtered with a syringe and acrylic-based filter (0.45 µm). The extracted heavy metals in the filtered liquid were then determined using a UV-Vis spectrometer (DR-5000, Hach, USA) and a heat block (DBR 200, Hach, USA) followed by US EPA methods (8506, 8009, 10217 and 10220). Polymetallic nodule was mainly composed of manganese (27%), iron (8%), nickel (1.4%), cupper (1.3 %), cobalt (1.3%) and molybdenum (0.04%). Based on remediation standards of various countries, Nickel (Ni), Copper (Cu), Cadmium (Cd) and Zinc (Zn) were selected as primary target materials. Throughout this research, the use of rhamnolipid was shown to be an effective approach for removing heavy metals in samples originated from manganese nodules. Sodium alginate might also be one of the effective additives for the remediation of deep-sea mining tailings such as polymetallic nodules. Compare to the use of rhamnolipid and sodium alginate, aluminum sulfate was more effective additive at short reaction time within 4 h. Based on these results, sequencing particle separation, selective extraction/washing, advanced filtration of liquid phase, water treatment without dewatering and solidification/stabilization may be considered as candidate technologies for the remediation of deep-sea mining tailings.

Keywords: deep-sea mining tailings, heavy metals, remediation, extraction, additives

Procedia PDF Downloads 139

Authors: Safa Adi

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This paper will consider the problem of sequential mining patterns embedded in a database by handling the time constraints as defined in the GSP algorithm (level wise algorithms). We will compare two previous approaches GTC and PSP, that resumes the general principles of GSP. Furthermore this paper will discuss PG-hybrid algorithm, that using PSP and GTC. The results show that PSP and GTC are more efficient than GSP. On the other hand, the GTC algorithm performs better than PSP. The PG-hybrid algorithm use PSP algorithm for the two first passes on the database, and GTC approach for the following scans. Experiments show that the hybrid approach is very efficient for short, frequent sequences.

Keywords: database, GTC algorithm, PSP algorithm, sequential patterns, time constraints

Procedia PDF Downloads 362

Authors: Jia Li, Xing Wei, Yuchen Hong, Yang Lu

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Detecting vehicle behavior has always been the focus of intelligent transportation, but with the explosive growth of the number of vehicles and the complexity of the road environment, the vehicle behavior videos captured by traditional surveillance have been unable to satisfy the study of vehicle behavior. The traditional method of manually labeling vehicle behavior is too time-consuming and labor-intensive, but the existing object detection and tracking algorithms have poor practicability and low behavioral location detection rate. This paper proposes a vehicle behavior detection algorithm based on the dual-stream convolution network and the multi-dimensional video dynamic detection network. In the videos, the straight-line behavior of the vehicle will default to the background behavior. The Changing lanes, turning and turning around are set as target behaviors. The purpose of this model is to automatically mark the target behavior of the vehicle from the untrimmed videos. First, the target behavior proposals in the long video are extracted through the dual-stream convolution network. The model uses a dual-stream convolutional network to generate a one-dimensional action score waveform, and then extract segments with scores above a given threshold M into preliminary vehicle behavior proposals. Second, the preliminary proposals are pruned and identified using the multi-dimensional video dynamic detection network. Referring to the hierarchical reinforcement learning, the multi-dimensional network includes a Timer module and a Spacer module, where the Timer module mines time information in the video stream and the Spacer module extracts spatial information in the video frame. The Timer and Spacer module are implemented by Long Short-Term Memory (LSTM) and start from an all-zero hidden state. The Timer module uses the Transformer mechanism to extract timing information from the video stream and extract features by linear mapping and other methods. Finally, the model fuses time information and spatial information and obtains the location and category of the behavior through the softmax layer. This paper uses recall and precision to measure the performance of the model. Extensive experiments show that based on the dataset of this paper, the proposed model has obvious advantages compared with the existing state-of-the-art behavior detection algorithms. When the Time Intersection over Union (TIoU) threshold is 0.5, the Average-Precision (MP) reaches 36.3% (the MP of baselines is 21.5%). In summary, this paper proposes a vehicle behavior detection model based on multi-dimensional dynamic detection network. This paper introduces spatial information and temporal information to extract vehicle behaviors in long videos. Experiments show that the proposed algorithm is advanced and accurate in-vehicle timing behavior detection. In the future, the focus will be on simultaneously detecting the timing behavior of multiple vehicles in complex traffic scenes (such as a busy street) while ensuring accuracy.

Keywords: vehicle behavior detection, convolutional neural network, long short-term memory, deep learning

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Authors: Philip T. Broughton, Mark P. Bettney, Isla L. Smail

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Effective treatment of ground instability is essential when managing the impacts associated with historic mining. A field trial was undertaken by the Coal Authority to investigate the geotechnical performance and potential use of composite materials comprising resin and fill or stone to safely treat surface collapses, such as crown-holes, associated with shallow mining. Test pits were loosely filled with various granular fill materials. The fill material was injected with commercially available silicate and polyurethane resin foam products. In situ and laboratory testing was undertaken to assess the geotechnical properties of the resultant composite materials. The test pits were subsequently excavated to assess resin permeation. Drilling and resin injection was easiest through clean limestone fill materials. Recycled building waste fill material proved difficult to inject with resin; this material is thus considered unsuitable for use in resin composites. Incomplete resin permeation in several of the test pits created irregular ‘blocks’ of composite. Injected resin foams significantly improve the stiffness and resistance (strength) of the un-compacted fill material. The stiffness of the treated fill material appears to be a function of the stone particle size, its associated compaction characteristics (under loose tipping) and the proportion of resin foam matrix. The type of fill material is more critical than the type of resin to the geotechnical properties of the composite materials. Resin composites can effectively support typical design imposed loads. Compared to other traditional treatment options, such as cement grouting, the use of resin composites is potentially less disruptive, particularly for sites with limited access, and thus likely to achieve significant reinstatement cost savings. The use of resin composites is considered a suitable option for the future treatment of shallow mining collapses.

Keywords: composite material, ground improvement, mining legacy, resin

Procedia PDF Downloads 333

Authors: Hasan G. Elmazoghi, Aisha I. Alzayani, Lubna S. Bentaher

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Rainfall is a highly non-linear phenomena, which requires application of powerful supervised data mining techniques for its accurate prediction. In this study the Artificial Neural Network (ANN) technique is used to predict the mean monthly historical rainfall data collected from BENINA station in Benghazi for 31 years, the period of “1977-2006” and the results are compared against the observed values. The specific objective to achieve this goal was to determine the best combination of weather variables to be used as inputs for the ANN model. Several statistical parameters were calculated and an uncertainty analysis for the results is also presented. The best ANN model is then applied to the data of one year (2007) as a case study in order to evaluate the performance of the model. Simulation results reveal that application of ANN technique is promising and can provide reliable estimates of rainfall.

Keywords: neural networks, rainfall, prediction, climatic variables

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Authors: María R. Contreras, Diana Endara

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Cyanide leaching is the most used technology for gold mining industry, which produces large amounts of effluents requiring treatment. In Ecuador the development of gold mining industry has increased, causing significant environmental impacts due to the highly use of cyanide, it is estimated that 10 gr of extracted gold generates 7000 liters of water contaminated with 300mg/L of free cyanide. The most common methods used nowadays are the treatment with peroxodisulfuric acid, ozonation, H₂O₂ and other reactants which are expensive and present disadvantages. Several methods have been developed to treat this contaminant such as heterogeneous catalysts. Layered double hydroxides (LDHs) have received much attention due to their wide applications like a catalysis support. Therefore, in this study, Mg-Al/ LDH was synthetized by coprecipitation method and then platinum was impregned on it, in order to enhance its catalytic activity. Two methods of impregnation were used, the first one, called incipient wet impregnation and the second one was developed by continuous agitation of LDH in contact with chloroplatinic acid solution for 24 h. The support impregnated was analyzed by X-ray diffraction, FTIR and SEM. Finally, the oxidation of cyanide ion was performed by preparing synthetic solutions of sodium cyanide (NaCN) with an initial concentration of 500 mg/L at pH 10,5 and air flow of 180 NL/h. After 8 hours of treatment, an 80% of oxidation of ion cyanide was achieved.

Keywords: catalysis, cyanide, LDHs, mining

Procedia PDF Downloads 123

Authors: Bartosz Olszanski, Zbigniew Nosal, Jacek Rokicki

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An experimental study of cold-jet (nitrogen) reaction control jet system has been carried out to investigate the flow control efficiency for low to moderate jet pressure ratios (total jet pressure p0jet over free stream static pressure in the wind tunnel p∞) and different angles of attack for infinite Mach number equal to 2. An investigation of jet influence was conducted on a flat plate geometry placed in the test section of intermittent supersonic wind tunnel of Department of Aerodynamics, WUT. Various convergent jet nozzle geometries to obtain different jet momentum ratios were tested on the same test model geometry. Surface static pressure measurements, Schlieren flow visualizations (using continuous and photoflash light source), load cell measurements gave insight into the supersonic crossflow interaction for different jet pressure and jet momentum ratios and their influence on the efficiency of side jet control as described by the amplification factor (actual to theoretical net force generated by the control nozzle). Moreover, the quasi-steady numerical simulations of flow through the same wind tunnel geometry (convergent-divergent nozzle plus test section) were performed using ANSYS Fluent basing on Reynolds-Averaged Navier-Stokes (RANS) solver incorporated with k-ω Shear Stress Transport (SST) turbulence model to assess the possible spurious influence of test section walls over the jet exit near field area of interest. The strong bow shock, barrel shock, and Mach disk as well as lambda separation region in front of nozzle were observed as images taken by high-speed camera examine the interaction of the jet and the free stream. In addition, the development of large-scale vortex structures (counter-rotating vortex pair) was detected. The history of complex static pressure pattern on the plate was recorded and compared to the force measurement data as well as numerical simulation data. The analysis of the obtained results, especially in the wake of the jet showed important features of the interaction mechanisms between the lateral jet and the flow field.

Keywords: flow visualization techniques, pressure measurements, reaction control jet, supersonic cross flow

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Authors: DEVASHISH KHULBE, MANU PATHAK

Abstract:

The rise in popularity of major social media platforms have enabled people to share photos and textual information about their daily life. One of the popular topics about which information is shared is food. Since a lot of media about food are attributed to particular locations and restaurants, information like spatio-temporal popularity of various cuisines can be analyzed. Tracking the popularity of food types and retail locations across space and time can also be useful for business owners and restaurant investors. In this work, we present an approach using off-the shelf machine learning techniques to identify trends and popularity of cuisine types in an area using geo-tagged data from social media, Google images and Yelp. After adjusting for time, we use the Kernel Density Estimation to get hot spots across the location and model the dependencies among food cuisines popularity using Bayesian Networks. We consider the Manhattan borough of New York City as the location for our analyses but the approach can be used for any area with social media data and information about retail businesses.

Keywords: Web Mining, Geographic Information Systems, Business popularity, Spatial Data Analyses

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Authors: Adesola O. Orimoloye, Edward Gobina

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Membrane separation technology is still considered as an emerging technology in the mining sector and does not yet have the widespread acceptance that it has in other industrial sectors. Underground Coal Gasification (UCG), wherein coal is converted to gas in-situ, is a safer alternative to mining method that retains all pollutants underground making the process environmentally friendly. In-situ combustion of coal for power generation allows access to more of the physical global coal resource than would be included in current economically recoverable reserve estimates. Where mining is no longer taking place, for economic or geological reasons, controlled gasification permits exploitation of the deposit (again a reaction of coal to form a synthesis gas) of coal seams in situ. The oxygen supply stage is one of the most expensive parts of any gasification project but the use of membranes is a potentially attractive approach for producing oxygen-enriched air. In this study, a variety of cost-effective membrane materials that gives an optimal amount of oxygen concentrations in the range of interest was designed and tested at diverse operating conditions. Oxygen-enriched atmosphere improves the combustion temperature but a decline is observed if oxygen concentration exceeds optimum. Experimental result also reveals the preparatory method, apparatus and performance of the fabricated membrane.

Keywords: membranes, oxygen-enrichment, gasification, coal

Procedia PDF Downloads 301

Authors: Emanuel Koseos

Abstract:

Data-Driven Decision Making (DDDM) refers to making decisions that are based on historical data in order to inform practice, develop strategies and implement policies that benefit organizational settings. In educational technology, DDDM facilitates the implementation of differential educational learning approaches such as Educational Data Mining (EDM) and Competency-Based Education (CBE), which commonly target university classrooms. There is a current need for DDDM models applied to middle and secondary schools from a concern for assessing the needs, progress and performance of students and educators with respect to regional standards, policies and evolution of curriculums. To address these concerns, we propose a DDDM reference model developed using educational key process initiatives as inputs to a machine learning framework implemented with statistical software (SAS, R) to provide a best-practices, complex-free and automated approach for educators at their regional level. We assessed the efficiency of the model over a six-year period using data from 45 schools and grades K-12 in the Langley, BC, Canada regional school district. We concluded that the model has wider appeal, such as business learning systems.

Keywords: competency-based learning, data-driven decision making, machine learning, secondary schools

Procedia PDF Downloads 152

Authors: Sandhya Baskaran, Hari Kumar Nagabushanam

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Sarcasm sentiment recognition is an area of natural language processing that is being probed into in the recent times. Even with the advancements in NLP, typical translations of words, sentences in its context fail to provide the exact information on a sentiment or emotion of a user. For example, if something bad happens, the statement ‘That's just what I need, great! Terrific!’ is expressed in a sarcastic tone which could be misread as a positive sign by any text-based analyzer. In this paper, we are presenting a unique real time ‘word with its tone’ spotting technique which would provide the sentiment analysis for a tone or pitch of a voice in combination with the words being expressed. This hybrid approach increases the probability for identification of special sentiment like sarcasm much closer to the real world than by mining text or speech individually. The system uses a tone analyzer such as YIN-FFT which extracts pitch segment-wise that would be used in parallel with a speech recognition system. The clustered data is classified for sentiments and sarcasm score for each of it determined. Our Simulations demonstrates the improvement in f-measure of around 12% compared to existing detection techniques with increased precision and recall.

Keywords: sarcasm recognition, tone-word spotting, natural language processing, pitch analyzer

Procedia PDF Downloads 273