Search results for: surface mining

Authors: Zawawi Daud

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Agro waste can be defined as waste from agricultural plant. Oil palm leaf and corn stalk can be categorized as ago waste material. At first, the comparison between oil palm leaf and corn stalk by mechanical properties from soda pulping process. After that, focusing on surface characterization by Scanning Electron Microscopy (SEM). Both material have a potential due to mechanical properties (tensile, tear, burst and fold) and surface characterization but corn stalk shows more in strength and compactness due to fiber characterization compared to oil palm leaf. This study promoting the green technology in develop a friendly product and suitable to be used as an alternative pulp in paper making industry.

Keywords: fiber, oil palm leaf, corn stalk, green technology

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Authors: Abderrahmane Hemmani, Hamid Khachab, Dennai Benmoussa, Hassane Benslimane, Abderrachid Helmaoui

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Back surface field GaAs with n -p-p+ structures are found to have better characteristics than the conventional solar cells. A theory, based on the transport of both minority carriers under the charge neutrality condition, has been developed in the present paper which explains behavior of the back surface field solar cells. That is reported with an efficiency of 25,05% (Jsc=33.5mA/cm2, Vco=0.87v and fill factor 86% under AM1.5 global conditions). We present the effect of technological parameters of the p+ layer on the conversion efficiency on the solar cell. Good agreement is achieved between our results and the simulation results given the variation of the equivalent recombination velocity to p+ layer as a function of BSF thickness and BSF doping.

Keywords: back surface field, GaAs, solar cell, technological parameters

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Authors: Gurinder Singh Brar, Sarbjeet Singh, Harry Garg

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Wire Electric Discharge Machining (WEDM) is thermal machining process capable of machining very hard electrically conductive material irrespective of their hardness. WEDM is being widely used to machine micro-scale parts with the high dimensional accuracy and surface finish. The objective of this paper is to optimize the process parameters of wire EDM to fabricate the microchannels and to calculate the surface finish and material removal rate of microchannels fabricated using wire EDM. The material used is aluminum 6061 alloy. The experiments were performed using CNC wire cut electric discharge machine. The effect of various parameters of WEDM like pulse on time (TON) with the levels (100, 150, 200), pulse off time (TOFF) with the levels (25, 35, 45) and current (IP) with the levels (105, 110, 115) were investigated to study the effect on output parameter i.e. Surface Roughness and Material Removal Rate (MRR). Each experiment was conducted under different conditions of a pulse on time, pulse off time and peak current. For material removal rate, TON and Ip were the most significant process parameter. MRR increases with the increase in TON and Ip and decreases with the increase in TOFF. For surface roughness, TON and Ip have the maximum effect and TOFF was found out to be less effective.

Keywords: microchannels, Wire Electric Discharge Machining (WEDM), Metal Removal Rate (MRR), surface finish

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Authors: Ezra Yehuwalashet, Alireza Malehmir

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Blötberget mining area in central Sweden, part of the Bergslagen mineral district, is well known for its various type of mineralization particularly iron-oxide deposits since the 1600. To shed lights on the knowledge of the host rock structures, depth extent and tonnage of the mineral deposits and support deep mineral exploration potential in the study area, new ground gravity and existing aeromagnetic data (from the Geological Survey of Sweden) were used for interpretations and modelling. A major boundary separating a gravity low from a gravity high in the southern part of the study area is noticeable and likely representing a fault boundary separating two different lithological units. Gravity data and modeling offers a possible new target area in the southeast of the known mineralization while suggesting an excess high-density region down to 800 m depth.

Keywords: gravity, magnetics, ore deposit, geophysics

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Authors: Xiuxia Sun, Yan Jin, Zilong Liu, Shiming Wei

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As a critical mineral component of shale, illite is essential in oil exploration and development due to its surface hydration characteristics and action mechanism. This paper, starting from the perspective of the molecular structure of organic matter, uses molecular dynamics simulation technology to deeply explore the interaction mechanism between organic molecules and the illite surface. In the study, we thoroughly considered the forces such as van der Waals force, electrostatic force, and steric hindrance and constructed an illite crystal model covering C8-C18 modifiers. Subsequently, we systematically analyzed surfactants' adsorption behavior and hydration characteristics with different alkyl chain numbers, lengths, and concentrations on the illite surface. The simulation results show that surfactant molecules with shorter alkyl chains present a lateral monolayer or inclined double-layer arrangement on the illite surface, and these two arrangements may coexist under different concentration conditions. In addition, with the increase in the number of alkyl chains, the interlayer spacing of illite increases significantly. In contrast, the change in alkyl chain length has a limited effect on surface properties. It is worth noting that the change in functional group structure has a particularly significant effect on the wettability of the illite surface, and its influence even exceeds the change in the alkyl chain structure. This discovery gives us a new perspective on understanding and regulating the wetting properties. The results obtained are consistent with the XRD analysis and wettability experimental data in this paper, further confirming the reliability of the research conclusions. This study deepened our understanding of illite's hydration characteristics and mechanism. We provided new ideas and directions for the molecular design and application development of oilfield chemicals.

Keywords: illite, surfactant, hydration, wettability, adsorption

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Authors: Ahmed Mohammed Alsalama

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Recommendation systems are widely used in e-commerce applications. The engine of a current recommendation system recommends items to a particular user based on user preferences and previous high ratings. Various recommendation schemes such as collaborative filtering and content-based approaches are used to build a recommendation system. Most of the current recommendation systems were developed to fit a certain domain such as books, articles, and movies. We propose a hybrid framework recommendation system to be applied on two-dimensional spaces (User x Item) with a large number of Users and a small number of Items. Moreover, our proposed framework makes use of both favorite and non-favorite items of a particular user. The proposed framework is built upon the integration of association rules mining and the content-based approach. The results of experiments show that our proposed framework can provide accurate recommendations to users.

Keywords: data mining, association rules, recommendation systems, hybrid systems

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Authors: Kewei Fan, Sihong Liu, Yi Pik Cheng

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This paper aims to analyse the failure behaviour of the retaining wall constructed with soil bags that are formed by filling river sand into woven bags (geosynthetics). Model tests were conducted to obtain the failure mode of the wall, and shear tests on two-layers and five-layers of soil bags were designed to investigate the mechanical characteristics of the interface of soil bags. The test results show that the slip surface in the soil bags-constructed retaining wall is ladder-like due to the inter-layer insertion of soil bags, and the wall above the ladder-like surface undergoes a rigid body translation. The insertion strengthens the shear strength of two-layer staggered-stacked soil bags. Meanwhile, it affects the shape of the slip surface of the five-layer staggered-stacked soil bags. Finally, the interlayer resisting friction of soil bags is found to be related to the shape of the slip surface.

Keywords: geosynthetics, retaining wall, soil bag, failure mode, interface, shear strength

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Authors: Maria De Albuquerque Bercot, Caio Gustavo Mesquita Angelo, Daniela Maria Moreira Siqueira, Augusto Assucena De Vasconcellos, Rodrigo Studart Correa

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Mining is an important socioeconomic activity in Brazil although it negatively impacts the environment. Mineral operations cause irreversible changes in topography, removal of vegetation and topsoil, habitat destruction, displacement of fauna, loss of biodiversity, soil erosion, siltation of watercourses and have potential to enhance climate change. Due to the impacts and its pollution potential, mining activity in Brazil is legally subjected to environmental licensing. Unlicensed mining operations or operations that not abide to the terms of an obtained license are taken as environmental crimes in the country. This work reports a case analyzed in the Forensic Institute of the Brazilian Federal District Civil Police. The case consisted of detecting illegal aspects of sand exploitation from a licensed mine in Federal District, nearby Brasilia city. The fieldwork covered an area of roughly 6 ha, which was surveyed with an unmanned aerial vehicle (UAV) (PHANTOM 3 ADVANCED). The overflight with UAV took about 20 min, with maximum flight height of 100 m. 592 UAV georeferenced images were obtained and processed in a photogrammetric software (AGISOFT PHOTOSCAN 1.1.4), which generated a mosaic of geo-referenced images and a 3D model in less than six working hours. The 3D model was analyzed in a forensic software for accurate modeling and volumetric analysis. (MAPTEK I-SITE FORENSIC 2.2). To ensure the 3D model was a true representation of the mine site, coordinates of ten control points and reference measures were taken during fieldwork and compared to respective spatial data in the model. Finally, these spatial data were used for measuring mining area, excavation depth and volume of exploited sand. Results showed that mine holder had not complied with some terms and conditions stated in the granted license, such as sand exploration beyond authorized extension, depth and volume. Easiness, the accuracy and expedition of procedures used in this case highlight the employment of UAV imagery and computational photogrammetry as efficient tools for outdoor forensic exams, especially on environmental issues.

Keywords: computational photogrammetry, environmental monitoring, mining, UAV

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Authors: F. R. Sultanov Ch. Daulbayev, B. Bakbolat, Z. A. Mansurov, A. A. Zhurintaeva, R. I. Gadilshina, A. B. Dugali

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Both hydrophilic-oleophobic and hydrophobic-oleophilic membranes were obtained by coating of the substrate of membranes, presented by stainless steel meshes with various dimensions of their openings, with a composition that forms the special type of their surface wettability via spray-coating method. The surface morphology of resulting membranes was studied using SEM, the type of their wettability was identified by measuring the contact angle between the surface of membrane and a drop of studied liquid (water or organic liquid) and efficiency of continuous separation of water and organic liquid was studied on self-assembled setup.

Keywords: membrane, stainless steel mesh, oleophobicity, hydrophobicity, separation, water, organic liquids

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Authors: Nikhil Jain, Bin Yu

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We explore the potential of using ultra-thin hexagonal boron nitride (h-BN) as both supporting substrate and gate dielectric for graphene-channel field effect transistors (GFETs). Different from commonly used oxide-based dielectric materials which are typically amorphous, very rough in surface, and rich with surface traps, h-BN is layered insulator free of dangling bonds and surface states, featuring atomically smooth surface. In a graphene-channel-last device structure with local buried metal gate electrode (TiN), thin h-BN multilayer is employed as both supporting “substrate” and gate dielectric for graphene active channel. We observed superior carrier mobility and electrical conduction, significantly improved from that in GFETs with SiO2 as substrate/gate insulator. In addition, we report excellent dielectric behavior of layered h-BN, including ultra-low leakage current and high critical electric field for breakdown.

Keywords: graphene, field-effect transistors, hexagonal boron nitride, dielectric strength, tunneling

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Authors: Lebea Nthunya, Arne Verliefde, Bhekie Mamba, Sabelo Mhlanga

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A study aimed at developing membrane distillation (MD) processes that can be used for brackish/saline water purification will be presented. MD is a membrane-based technology that presents a possibility to counteract challenges associated with pressure driven membranes at high separation efficiencies. Membrane distillation membranes (MDM) are affected by wettability and fouling. Wetting inside the pores of the membrane is elevated by the hydrophilic characteristic of the membrane, while fouling is mostly induced by the hydrophobic-hydrophobic interaction of pollutants and the surface of the hydrophobic membranes, hence block the pores of the membranes. These properties are not desirable. As such, a carefully designed polyvinylidene fluoride (PVDF) MDM composed of a super-hydrophobic modified backbone and a super-hydrophilic thin layer has been developed to concurrently overcome these challenges. The membranes were characterized using contact angle measurements to confirm their hydrophobicity/hydrophilicity. SEM and SAXS were used to study the morphology and pore distribution on the surface of the membrane. The contact angles of the active surface ≤ 30º and that of the backbone ≥ 140º has thus revealed that the active surface was highly hydrophilic while the backbone was highly hydrophobic. The SEM and the SAXS results have also confirmed that the membranes are highly porous. These materials demonstrated a potential to remove salts from water at high efficiencies.

Keywords: membrane distillation, modification, energy efficiency, desalination

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Authors: M. Brik, S. Harmand, I. Zaaroura

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This report, an experimental investigation, concerns the sessile daughter drop remaining during the coalescence of water drops in a liquid-liquid (LL) system. The two drops are initially vertically aligned where the sessile drop is deposited on a chemically treated super-hydrophobic surface of a cube fill of silicone oil. In order to analyze the coalescence dynamics, a series of experiments have been performed using a generation droplets system (KRUSS) that measures contact angles as well coupled with a high-speed camera (Keyence VW-9000E) to record the process at a frame rate of 15000s-1. It’s depicted that in such configuration, the head drop volume has a primordial impact on the dynamics of the coalescence process, especially at the last stage. It’s found that for a sessile drop deposited on a super-hydrophobic surface, where the contact angle is about θ ≈ 145°, the coalescence process is remarked to be complete without any recoiling of the coalesced drop or a generation of a sessile daughter drop at the super-hydrophobic surface when the head drop volume is small enough (Vₐᵦ< Vₛ up to Vₐᵦ = 3Vₛ). On the other side, the coalescence process starts to be followed by jumping off the resulted drop as well as a remaining of a small sessile daughter drop on the bottom surface of the cube from a head drop volume Vₐᵦ of about 4 times than that of the sessile drop Vₛ.

Keywords: drops coalescence, dispersed multiphase flow, drops dynamics, liquid-liquid system

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Authors: B. Bouktif, M. Gaidi, M. Benrabha

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Metal-nano particle-assisted chemical etching is an extraordinary developed wet etching method of producing uniform semiconductor nanostructure (nanowires) from the patterned metallic film on the crystalline silicon surface. The metal films facilitate the etching in HF and H2O2 solution and produce silicon nanowires (SiNWs). Creation of different SiNWs morphologies by changing the etching time and its effects on optical and optoelectronic properties was investigated. Combination effect of formed SiNWs and stain etching treatment in acid (HF/HNO3/H2O) solution on the surface morphology of Si wafers as well as on the optical and optoelectronic properties are presented in this paper.

Keywords: semiconductor nanostructure, chemical etching, optoelectronic property, silicon surface

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Authors: Gaurav Verma

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Organoclay loaded (0-5 weight %) polyester-urethane (PU) coatings were prepared with a branched hydroxyl-bearing polyester and an aliphatic poly-isocyanate. TEM micrographs show partial exfoliation and intercalation of clay platelets in organoclay-polyester dispersions. AFM surface images reveals that the PU hard domains tend to regularise and also self-organise into spherical shapes of sizes 50 nm (0 wt %), 60 nm (2 wt %) and 190 nm (4 wt %) respectively. IR analysis shows that PU chains have increasing tendency to interact with exfoliated clay platelets through hydrogen bonding. This interaction strengthens inter-chain linkages in PU matrix and hence improves anti-ageing properties. 1000 hours of accelerated weathering was evaluated by ATR spectroscopy, while yellowing and overall discoloration was quantified by the Δb* and ΔE* values of the CIELab colour scale. Post-weathering surface properties also showed improvement as the loss of thickness and reduction in gloss in neat PU was 25% and 42%; while it was just 3.5% and 14% respectively for the 2 wt% nanocomposite coating. This work highlights the importance of modifying surface and bulk properties of PU coatings at nanoscale, which led to improved performance in accelerated weathering conditions.

Keywords: coatings, AFM, ageing, spectroscopy

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Authors: Francisco Javier Montes Ruiz-Cabello, Guillermo Guerrero-Vacas, Sara Bermudez-Romero, Miguel Cabrerizo Vilchez, Miguel Angel Rodriguez-Valverde

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Galvanized steel is one of the widespread metallic materials used in industry. It consists on a iron-based alloy (steel) coated with a layer of zinc with variable thickness. The zinc is aimed to prevent the inner steel from corrosion and staining. Its production is cheaper than the stainless steel and this is the reason why it is employed in the construction of materials with large dimensions in aeronautics, urban/ industrial edification or ski-resorts. In all these applications, turning the natural hydrophilicity of the metal surface into superhydrophobicity is particularly interesting and would open a wide variety of additional functionalities. However, producing a superhydrophobic surface on galvanized steel may be a very difficult task. Superhydrophobic surfaces are characterized by a specific surface texture which is reached either by coating the surface with a material that incorporates such texture, or by conducting several roughening methods. Since galvanized steel is already a coated material, the incorporation of a second coating may be undesired. On the other hand, the methods that are recurrently used to incorporate the surface texture leading to superhydrophobicity in metals are aggressive and may damage their surface. In this work, we used a novel strategy which goal is to produce superhydrophobic galvanized steel by a two-step non-aggressive process. The first process is aimed to create a hierarchical structure by incorporating zinc nanoparticles sintered on the surface at a temperature slightly lower than the zinc’s melting point. The second one is a hydrophobization by a thick fluoropolymer layer deposition. The wettability of the samples is characterized in terms of tilting plate and bouncing drop experiments, while the roughness is analyzed by confocal microscopy. The durability of the produced surfaces was also explored.

Keywords: galvanaized steel, superhydrophobic surfaces, sintering nanoparticles, zinc nanopowder

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Authors: Eman AbuKhousa, Marwan Z. Bataineh

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The 21^st century higher education and globalization challenge new faculty members to build effective professional networks and partnership with industry in order to accelerate their growth and success. This creates the need for community of practice (CoP)-oriented development approaches that focus on cognitive apprenticeship while considering individual predisposition and future career needs. This work adopts data mining, clustering analysis, and social networking technologies to present the CoP-Network as a virtual space that connects together similar career-aspiration individuals who are socially influenced to join and engage in a process for domain-related knowledge and practice acquisitions. The CoP-Network model can be integrated into higher education to extend traditional graduate and professional development programs.

Keywords: clustering analysis, community of practice, data mining, higher education, new faculty challenges, social network, social influence, professional development

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Authors: Azyuni Aziz, Syed A. Malik, Shahrul Kadri Ayop, Fatin Hana Naning

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Currently, organic-inorganic hybrid thin films have attracted researchers to explore them, where these thin films can give a lot of benefits. Hybrid thin films are thin films that consist of inorganic and organic materials. Inorganic and organic materials give high efficiency and low manufacturing cost in some applications such as solar cells application, furthermore, organic materials are environment-friendly. In this study, poly (3-hexylthiophene) was choosing as organic material which combined with inorganic nanoparticles, Cadmium Sulfide (CdS) quantum dots. Samples were prepared using new technique, Angle Lifting Deposition (ALD) at different weight percentage. All prepared samples were then characterized by Field Emission Scanning Electron Microscopy (FESEM) with Energy-dispersive X-ray spectroscopy (EDX) and Atomic Force Microscopy (AFM) to study surface of samples and determine their surface roughness. Results show that these inorganic nanoparticles have affected the surface of samples and surface roughness of samples increased due to increasing of weight percentage of CdS in the thin films samples.

Keywords: AFM, CdS, FESEM-EDX, hybrid thin films, P3HT

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Authors: Kiatnarong Supapanmanee, Ekkarin Phongphinittana, Pongsak Nimdum

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Natural fibers are readily available raw materials that are widely used as composite materials. The most common problem facing many researchers with composites made from this fiber is the adhesion between the natural fiber contact surface and the matrix material. Part of the problem is due to the hydrophilic properties of natural fibers and the hydrophobic properties of the matrix material. Based on the aforementioned problems, this research selected bamboo fiber, which is a strong natural fiber in the research study. The first step was to study the effect of the mechanical properties of the pure bamboo strip by testing the tensile strength of different measurement lengths. The bamboo strip was modified surface with sodium hydroxide (NaOH) at 6wt% concentrations for different soaking periods. After surface modification, the physical and mechanical properties of the pure bamboo strip fibers were studied. The modified and unmodified bamboo strips were molded into a composite material using epoxy as a matrix to compare the mechanical properties and adhesion between the fiber surface and the material with tensile and bending tests. In addition, the results of these tests were compared with the finite element method (FEM). The results showed that the length of the bamboo strip affects the strength of the fibers, with shorter fibers causing higher tensile stress. Effects of surface modification of bamboo strip with NaOH, this chemical eliminates lignin and hemicellulose, resulting in the smaller dimension of the bamboo strip and increased density. From the pretreatment results above, it was found that the treated bamboo strip and composite material had better Ultimate tensile stress and Young's modulus. Moreover, that results in better adhesion between bamboo fiber and matrix material.

Keywords: bamboo fiber, bamboo strip, composite material, bamboo composite, pure bamboo, surface modification, mechanical properties of bamboo, bamboo finite element method

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Authors: Tovondahiniriko Fanjirindratovo, Olga Ramiarinjanahary, Paulisimone Rasoavonjy

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The sunshine duration, which is the sum of all the moments when the solar beam radiation is up to a minimal value, is an important parameter for climatology, tourism, agriculture and solar energy. Its measure is usually given by a pyrheliometer installed on a two-axis solar tracker. Due to the high cost of this device and the availability of global radiation on a horizontal surface, on the other hand, several studies have been done to make a correlation between global radiation and sunshine duration. Most of these studies are fitted for the northern hemisphere using a pyrheliometric database. The aim of the present work is to list and assess all the existing methods and apply them to Reunion Island, a tropical region in the southern hemisphere. Using a database of ten years, global, diffuse and beam radiation for a horizontal surface are employed in order to evaluate the uncertainty of existing algorithms for a tropical region. The methodology is based on indirect comparison because the solar beam radiation is not measured but calculated by the beam radiation on a horizontal surface and the sun elevation angle.

Keywords: Carpentras method, data fitting, global radiation, sunshine duration, Slob and Monna algorithm, step algorithm

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Authors: Yahya Almurtadha, Mukhtar Ghaleb, Ahmed M. Shamsan Saleh

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The world witnessed a fierce attack from the Covid-19 virus, which affected public life socially, economically, healthily and psychologically. The world's governments tried to confront the pandemic by imposing a number of precautionary measures such as general closure, curfews and social distancing. Scientists have also made strenuous efforts to develop an effective vaccine to train the immune system to develop antibodies to combat the virus, thus reducing its symptoms and limiting its spread. Artificial intelligence, along with researchers and medical authorities, has accelerated the vaccine development process through big data processing and simulation. On the other hand, one of the most important negatives of the impact of Covid 19 was the state of anxiety and fear due to the blowout of rumors through social media, which prompted governments to try to reassure the public with the available means. This study aims to proposed using Sentiment Analysis (AKA Opinion Mining) and deep learning as efficient artificial intelligence techniques to work on retrieving the tweets of the public from Twitter and then analyze it automatically to extract their opinions, expression and feelings, negatively or positively, about the symptoms they may feel after vaccination. Sentiment analysis is characterized by its ability to access what the public post in social media within a record time and at a lower cost than traditional means such as questionnaires and interviews, not to mention the accuracy of the information as it comes from what the public expresses voluntarily.

Keywords: deep learning, opinion mining, natural language processing, sentiment analysis

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Authors: Lintang Putra Sadewa, Ilham Prasetya Budhi

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Slope monitoring program has now become a mandatory campaign for any open pit mines around the world to operate safely. Utilizing various slope monitoring instruments and strategies, miners are now able to deliver precise decisions in mitigating the risk of slope failures which can be catastrophic. Currently, the most sophisticated slope monitoring technology available is the Slope Stability Radar (SSR), whichcan measure wall deformation in submillimeter accuracy. One of its eminent features is that SSRcan provide a timely warning by automatically raise an alarm when a predetermined rate-of-movement threshold is reached. However, establishing proper alarm thresholds is arguably one of the onerous challenges faced in any slope monitoring program. The difficulty mainly lies in the number of considerations that must be taken when generating a threshold becausean alarm must be effectivethat it should limit the occurrences of false alarms while alsobeing able to capture any real wall deformations. In this sense, experience shows that a site-specific alarm thresholdtendsto produce more reliable results because it considers site distinctive variables. This study will attempt to determinealarming thresholds for safety-critical monitoring based on an empirical model of slope deformation behaviour that is defined statistically fromdeformation data captured by the Slope Stability Radar (SSR). The study area comprises of upright-dipping highwall setting in a coal mining area with intense mining activities, andthe deformation data used for the study were recorded by the SSR throughout the year 2022. The model is site-specific in nature thus, valuable information extracted from the model (e.g., time-to-failure, onset-of-acceleration, and velocity) will be applicable in setting up site-specific alarm thresholds and will give a clear understanding of how deformation trends evolve over the area.

Keywords: safety-critical monitoring, alarming strategy, slope deformation behaviour model, coal mining

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Authors: Neveen AlQasas, Daniel Johnson

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Membranes for water treatment are an established technology that attracts great attention due to its simplicity and cost effectiveness. However, membranes in operation suffer from the adverse effect of membrane fouling. Bio-fouling is a phenomenon that occurs at the water-membrane interface, and is a dynamic process that is initiated by the adsorption of dissolved organic material, including biomacromolecules, on the membrane surface. After initiation, attachment of microorganisms occurs, followed by biofilm growth. The biofilm blocks the pores of the membrane and consequently results in reducing the water flux. Moreover, the presence of a fouling layer can have a substantial impact on the membrane separation properties. Understanding the mechanism of the initiation phase of biofouling is a key point in eliminating the biofouling on membrane surfaces. The adhesion and attachment of different fouling materials is affected by the surface properties of the membrane materials. Therefore, surface properties of different polymeric materials had been studied in terms of their surface energies and Hansen solubility parameters (HSP). The difference between the combined HSP parameters (HSP distance) allows prediction of the affinity of two materials to each other. The possibilities of measuring the HSP of different polymer films via surface measurements, such as contact angle has been thoroughly investigated. Knowing the HSP of a membrane material and the HSP of a specific foulant, facilitate the estimation of the HSP distance between the two, and therefore the strength of attachment to the surface. Contact angle measurements using fourteen different solvents on five different polymeric films were carried out using the sessile drop method. Solvents were ranked as good or bad solvents using different ranking method and ranking was used to calculate the HSP of each polymeric film. Results clearly indicate the absence of a direct relation between contact angle values of each film and the HSP distance between each polymer film and the solvents used. Therefore, estimating HSP via contact angle alone is not sufficient. However, it was found if the surface tensions and viscosities of the used solvents are taken in to the account in the analysis of the contact angle values, a prediction of the HSP from contact angle measurements is possible. This was carried out via training of a neural network model. The trained neural network model has three inputs, contact angle value, surface tension and viscosity of solvent used. The model is able to predict the HSP distance between the used solvent and the tested polymer (material). The HSP distance prediction is further used to estimate the total and individual HSP parameters of each tested material. The results showed an accuracy of about 90% for all the five studied films

Keywords: surface characterization, hansen solubility parameter estimation, contact angle measurements, artificial neural network model, surface measurements

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Authors: HebatAllah Tarek, Zeyad El-Sayad, Ali F. Bakr

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Surface coating can permit the bulk materials to remain unchanged, whereas the surface functionality is engineered to afford a more required characteristic. Nano-Ceramic coatings are considered ideal coatings on materials that can significantly improve the surface properties, including anti-fouling, self-cleaning, corrosion resistance, wear resistance, anti-scratch, waterproof, anti-acid rain and anti-asphalt. Furthermore, various techniques have been utilized to fabricate a range of different ceramic coatings with more desirable properties on Nano-ceramics, which make the materials usually used in in-service environments and worth mentioning that the practical part of this study will be applied in one of the most important architectural applications due to the contamination-free conditions provided by it in the manufacturing industry. Without cleanrooms, products will become contaminated and either malfunction or infect people with bacteria. Cleanrooms are used for the manufacture of items used in computers, cars, airplanes, spacecraft, televisions, disc players and many other electronic and mechanical devices, as well as the manufacture of medicines, medical devices, and foods. The aim of this study will be to examine the Nano-ceramics on porcelain and glass panels. The investigation will be included fabrications, methods, surface properties and applications in clean rooms. The unfamiliarity in this study is using Nano-ceramics in clean rooms instead of using them on metallic materials.

Keywords: nano-ceramic coating, clean rooms, porcelain, surface properties

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Authors: Siyang Wang, Yujin Hu, Xuelin Wang, Wenqian Zhang

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Austenitic stainless steels are widely used in nuclear industry to manufacture critical components owing to their excellent corrosion resistance at high temperatures. Almost all the components used in nuclear power plants are produced by surface finishing (surface cold work) such as milling, grinding and so on. The change of surface states induced by machining has great influence on the corrosion behavior. In the present study, long time oxidation behavior of machined 316 austenitic stainless steel exposed to simulated pressure water reactor environment was investigated considering different surface states. Four surface finishes were produced by electro-polishing (P), grinding (G), and two milling (M and M1) processes respectively. Before oxidation, the surface Vickers micro-hardness, surface roughness of each type of sample was measured. Corrosion behavior of four types of sample was studied by using oxidation weight gain method for six oxidation periods. The oxidation time of each period was 120h, 216h, 336h, 504h, 672h and 1344h, respectively. SEM was used to observe the surface morphology of oxide film in several period. The results showed that oxide film on austenitic stainless steel has a duplex-layer structure. The inner oxide film is continuous and compact, while the outer layer is composed of oxide particles. The oxide particle consisted of large particles (nearly micron size) and small particles (dozens of nanometers to a few hundred nanometers). The formation of oxide particle could be significantly affected by the machined surface states. The large particle on cold worked samples (grinding and milling) appeared earlier than electro-polished one, and the milled sample has the largest particle size followed by ground one and electro-polished one. For machined samples, the large particles were almost distributed along the direction of machining marks. Severe exfoliation was observed on one milled surface (M) which had the most heavily cold worked layer, while rare local exfoliation occurred on the ground sample (G) and the other milled sample (M1). The electro-polished sample (P) entirely did not exfoliate.

Keywords: austenitic stainless steel, oxidation, machining, SEM

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Authors: Sudipto Shanker Dasgupta

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One of the largest mining companies wanted to look at health analytics for their driverless trucks. These trucks were the key to their supply chain logistics. The automated trucks had multi-level sub-assemblies which would send out sensor information. The use case that was worked on was to capture the sensor signal from the truck subcomponents and analyze the health of the trucks from repair and replacement purview. Open source software was used to stream the data into a clustered Hadoop setup in Amazon Web Services cloud and Apache Spark SQL was used to analyze the data. All of this was achieved through a 10 node amazon 32 core, 64 GB RAM setup real-time analytics was achieved on ‘300 million records’. To check the scalability of the system, the cluster was increased to 100 node setup. This talk will highlight how Open Source software was used to achieve the above use case and the insights on the high data throughput on a cloud set up.

Keywords: streaming analytics, data science, big data, Hadoop, high throughput, sensor data

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Authors: Peter Thissen

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In this work, we report about the influence of the chemical potential of water on the carbonation reaction of wollastonite (CaSiO3) as model surface of cement and concrete. Total energy calculations based on density functional theory (DFT) combined with kinetic barrier predictions based on nudge elastic band (NEB) method show that the exposure of the water-free wollastonite surface to CO2 results in a barrier-less carbonation. CO2 reacts with the surface oxygen and forms carbonate (CO32-) complexes together with a major reconstruction of the surface. The reaction comes to a standstill after one carbonate monolayer has been formed. In case one water monolayer is covering the wollastonite surface, the carbonation is no more barrier-less, yet ending in a localized monolayer. Covered with multilayers of water, the thermodynamic ground state of the wollastonite completely changes due to a metal-proton exchange reaction (MPER, also called early stage hydration) and Ca2+ ions are partially removed from solid phase into the H2O/wollastonite interface. Mobile Ca2+ react again with CO2 and form carbonate complexes, ending in a delocalized layer. By means of high resolution time-of-flight secondary-ion mass-spectroscopy images (ToF-SIMS), we confirm that hydration can lead to a partially delocalization of Ca2+ ions on wollastonite surfaces. Finally, we evaluate the impact of our model surface results by means of Low Energy Ion Scattering (LEIS) spectroscopy combined with careful discussion about the competing reactions of carbonation vs. hydration.

Keywords: Calcium-silicate, carbonation, hydration, metal-proton exchange reaction

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Authors: Yiea Funk Te, Daniel Mueller, Irena Pletikosa Cvijikj

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Small and medium enterprises (SMEs) play an important role in the economy of many countries. When the overall world economy is considered, SMEs represent 95% of all businesses in the world, accounting for 66% of the total employment. Existing studies show that the current business environment is characterized as highly turbulent and strongly influenced by modern information and communication technologies, thus forcing SMEs to experience more severe challenges in maintaining their existence and expanding their business. To support SMEs at improving their competitiveness, researchers recently turned their focus on applying data mining techniques to build risk and growth prediction models. However, data used to assess risk and growth indicators is primarily obtained via questionnaires, which is very laborious and time-consuming, or is provided by financial institutes, thus highly sensitive to privacy issues. Recently, web mining (WM) has emerged as a new approach towards obtaining valuable insights in the business world. WM enables automatic and large scale collection and analysis of potentially valuable data from various online platforms, including companies’ websites. While WM methods have been frequently studied to anticipate growth of sales volume for e-commerce platforms, their application for assessment of SME risk and growth indicators is still scarce. Considering that a vast proportion of SMEs own a website, WM bears a great potential in revealing valuable information hidden in SME websites, which can further be used to understand SME risk and growth indicators, as well as to enhance current SME risk and growth prediction models. This study aims at developing an automated system to collect business-relevant data from the Web and predict future growth trends of SMEs by means of WM and data mining techniques. The envisioned system should serve as an 'early recognition system' for future growth opportunities. In an initial step, we examine how structured and semi-structured Web data in governmental or SME websites can be used to explain the success of SMEs. WM methods are applied to extract Web data in a form of additional input features for the growth prediction model. The data on SMEs provided by a large Swiss insurance company is used as ground truth data (i.e. growth-labeled data) to train the growth prediction model. Different machine learning classification algorithms such as the Support Vector Machine, Random Forest and Artificial Neural Network are applied and compared, with the goal to optimize the prediction performance. The results are compared to those from previous studies, in order to assess the contribution of growth indicators retrieved from the Web for increasing the predictive power of the model.

Keywords: data mining, SME growth, success factors, web mining

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Authors: A. T. Muruviwa

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To-date, the discourse on corporate social responsibility (CSR) has primarily centred on the actions and inactions of corporations; hence, the dominant focus on CSR has been on impacts and outcomes. The obscuring effect of this approach has, arguably, resulted in the emergence of what may be termed a ‘Northern’ agenda on CSR theory and practice, in contrast to an emergency ‘Southern’ discourse, which appears to highlight the crucial issues of poverty reduction, infrastructure development and the broader questions of social provisioning and community empowerment. Some scholars have explicitly called for a CSR research agenda that focuses on the 'reciprocal duties' of the stakeholders in the CSR process rather than fixate on the actions and inactions of business. It is against the backdrop of these contestations that this study assesses the reciprocal relationships amongst CSR stakeholders in a Zimbabwean platinum mining town, with a view to demonstrating how such relationships – and the expectations and obligations embedded in them – impact on the success or failure of CSR initiatives. The existence of mutual relations between the corporation and its stakeholders signifies the successes of CSR processes and hence the outcomes. The company is Zimplats Mining Company; the community is Mhondoro-Ngezi, and the stakeholders are clearly identified in the study. The study utilised a triangulated design, with data collected using a mini survey, focus groups, in-depth interview and observation. The key findings are that the CSR process in the study community is dominated by the mining company. Despite the existence of a CSR framework that recognises government, local leaders and community members as legitimate stakeholders, there is little evidence of concrete contributions made by these stakeholders towards the realisation of CSR objectives. As a result, the community development process – in so far as CSR is concerned – fails to address the developmental concerns of the various stakeholders. On the basis of these findings, the study concludes that there is a crisis of reciprocity in the CSR process in Mhondoro-Ngezi, and that a situation where the conceptualisation of local development needs and the deployment of specific development tools seems to be driven by one stakeholder almost to the exclusion of all others, can only present contradictory development outcomes. The significance of this study is that it allows for the development of a more nuanced and robust CSR discourse. Rather than focusing on the corporate and stakeholder perspectives and outcomes of CSR initiatives, this study examines the CSR- development nexus by interrogating the idea of reciprocal responsibility as a sin qua non to CSR success. This analytical strategy and focus allow the researcher to gain a clear understanding of how stakeholder relationships and duties influence CSR processes and also the overall outcome. At a more practical level, the findings of the study should help to shape the policy on corporate community relationships with a view to enhancing the role of mining in development.

Keywords: community development, processes, reciprocity, stakeholders

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Authors: Dong Jiang

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Turnout is the essential equipment on the railway, which also belongs to one of the strongest demanded infrastructural facilities of railway on account of the more seriously frog rail failures. In cooperation with Germany Company (DB Systemtechnik AG), our research team focuses on the quantitative analysis about the frog rails to predict their lifetimes. Moreover, the suggestions for the timely and effective maintenances are made to improve the economy of the frog rails. The lifetime of the frog rail depends strongly on the internal damage of the running surface until the breakages occur. On the basis of Hertzian theory of the contact mechanics, the dynamic loads of the running surface are calculated in form of the contact pressures on the running surface and the equivalent tensile stress inside the running surface. According to material mechanics, the strength of the frog rail is determined quantitatively in form of the Stress-cycle (S-N) curve. Under the interaction between the dynamic loads and the strength, the internal damage of the running surface is calculated by means of the linear damage hypothesis of the Miner’s rule. The emergence of the first Breakage on the running surface is to be defined as the failure criterion that the damage degree equals 1.0. From the microscopic perspective, the running surface of the frog rail is divided into numerous segments for the detailed analysis. The internal damage of the segment grows slowly in the beginning and disproportionately quickly in the end until the emergence of the breakage. From the macroscopic perspective, the internal damage of the running surface develops simply always linear along the lifetime. With this linear growth of the internal damages, the lifetime of the frog rail could be predicted simply through the immediate introduction of the slope of the linearity. However, the superficial abrasion plays an essential role in the results of the internal damages from the both perspectives. The influences of the superficial abrasion on the lifetime are described in form of the abrasion rate. It has two contradictory effects. On the one hand, the insufficient abrasion rate causes the concentration of the damage accumulation on the same position below the running surface to accelerate the rail failure. On the other hand, the excessive abrasion rate advances the disappearance of the head hardened surface of the frog rail to result in the untimely breakage on the surface. Thus, the relationship between the abrasion rate and the lifetime is subdivided into an initial phase of the increased lifetime and a subsequent phase of the more rapid decreasing lifetime with the continuous growth of the abrasion rate. Through the compensation of these two effects, the critical abrasion rate is discussed to reach the optimal lifetime.

Keywords: breakage, critical abrasion rate, frog rail, internal damage, optimal lifetime

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Authors: Julian Wise

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Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

Procedia PDF Downloads 94