Search results for: rough surface

Authors: Nauman A. Siddiqui

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High performance requirement of aircrafts and marines industry demands to cater major industrial problems like wetting, high-speed efficiency, and corrosion resistance. These problems can be resolved by producing the hydrophobic surfaces on the metal substrate. By anodization process, the surface of AA 7075 has been modified and achieved a rough surface with a porous aluminum oxide (Al2O3) structure at nano-level. This surface modification process reduces the surface contact energy and increases the liquid contact angle which ultimately enhances the anti-icing properties. Later the Silane and Polyurethane (PU) coatings on the anodized surface have produced a contact angle of 130°. The results showed a good water repellency and self-cleaning properties. Using SEM analysis, micrographs revealed the round nano-porous oxide structure on the substrate. Therefore this technique can help in increasing the speed efficiency by reducing the friction with the outer interaction and can also be declared as a green technique since it is user-friendly.

Keywords: AA 7075, hydrophobicity, silanes, polyurethane, anodization

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Authors: Raja V., Chokkalingam B.

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For rough cutting, in many industries and educational institutions using carbon steels or HSS single point cutting tools in center lathe machine. In power hacksaw blades, only the cutter teeth region used to parting off the given material. The portions other than the teeth can be used as a single point cutting tool for rough turning and facing on soft materials. The hardness and Tensile strength of this used Power hacksaw blade is almost same as conventional cutting tools. In this paper, the effect of power hacksaw blades over conventional tool has been compared. Thickness of the blade (1.6 mm) is very small compared to its length and width. Hence, a special tool holding device is designed to hold the tool.

Keywords: hardness, high speed steels, power hacksaw blade, tensile strength

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Authors: Waranya Pongpaiboon, Warangkana Srichamnong, Supat Chaiyakul

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Enzymatic modification of rice flour can produce highly functional derivatives use in food industries. This study aimed to evaluate the physical properties and resistant starch content of rice flour residues hydrolyzed by α-amylase. Rice flour hydrolyzed by α-amylase (60 and 300 u/g) for 1, 24 and 48 hours were investigated. Increasing enzyme concentration and hydrolysis time resulted in decreased rice flour residue’s lightness (L*) but increased redness (a*) and yellowness (b*) of rice flour residues. The resistant starch content and peak viscosity increased when hydrolysis time increased. Pasting temperature, trough viscosity, breakdown, final viscosity, setback and peak time of the hydrolyzed flours were not significantly different (p>0.05). The morphology of native flour was smooth without observable pores and polygonal with sharp angles and edges. However, after hydrolysis, granules with a slightly rough and porous surface were observed and a rough and porous surface was increased with increasing hydrolyzed time. The X-ray diffraction patterns of native flour showed A-type configuration, which hydrolyzed flour showed almost 0% crystallinity indicated that both amorphous and crystalline structures of starch were simultaneously hydrolyzed by α-amylase.

Keywords: α-Amylase, enzymatic hydrolysis, pasting properties, resistant starch

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Authors: S. Gao, S. Srirattayawong

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In this study, a computational fluid dynamics (CFD) model has been developed for studying the effect of surface roughness profile on the EHL problem. The cylinders contact geometry, meshing and calculation of the conservation of mass and momentum equations are carried out by using the commercial software packages ICEMCFD and ANSYS Fluent. The user defined functions (UDFs) for density, viscosity and elastic deformation of the cylinders as the functions of pressure and temperature have been defined for the CFD model. Three different surface roughness profiles are created and incorporated into the CFD model. It is found that the developed CFD model can predict the characteristics of fluid flow and heat transfer in the EHL problem, including the leading parameters such as the pressure distribution, minimal film thickness, viscosity, and density changes. The obtained results show that the pressure profile at the center of the contact area directly relates to the roughness amplitude. The rough surface with kurtosis value over 3 influences the fluctuated shape of pressure distribution higher than other cases.

Keywords: CFD, EHL, kurtosis, surface roughness

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Authors: Dong Nyoung Heo, Il Keun Kwon

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Three-dimensional (3D) technology is a promising method for bone tissue engineering. In order to enhance bone tissue regeneration, it is important to have ideal 3D constructs with biomimetic mechanical strength, structure interconnectivity, roughened surface, and the presence of chemical functionality. In this respect, a 3D printing system combined with cold atmospheric plasma (CAP) was developed to fabricate a 3D construct that has a rough surface with polar functional chemical groups. The CAP-etching process leads to oxidation of chemical groups existing on the polycaprolactone (PCL) surface without conformational change. The surface morphology, chemical composition, mean roughness of the CAP-treated PCL surfaces were evaluated. 3D printed constructs composed of CAP-treated PCL showed an effective increment in the hydrophilicity and roughness of the PCL surface. Also, an in vitro study revealed that CAP-treated 3D PCL constructs had higher cellular behaviors such as cell adhesion, cell proliferation, and osteogenic differentiation. Therefore, a 3D printing system with CAP can be a highly useful fabrication method for bone tissue regeneration.

Keywords: bone tissue engineering, cold atmospheric plasma, PCL, 3D printing

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Authors: Azadeh Malekan, Shahin Rouhani

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Superlubricity is a phenomenon where two surfaces in contact show negligible friction;this may be because the asperities of the two surfaces do not interlock. Two rough surfaces, when pressed against each other, can get into a formation where the summits of asperities of one surface lock into the valleys of the other surface. The amount of interlock depends on the geometry of the two surfaces. We suggest the friction force may then be proportional to the amount of interlock; this explains Superlubricity as the situation where there is little interlock. Then the friction force will be directly proportional to the normal force as it is related to the work necessary to lift the upper surface in order to clear the interlock. To investigate this model, we simulate the contact of two surfaces. In order to validate our model, we first investigate Amontons‘ law. Assuming that asperities retain deformations in the time scale while the top asperity moves across the lattice spacing Amonton’s law is observed. Structural superlubricity is examined by the hypothesis that surfaces are very rigid and there is no deformation in asperities. This may happen at small normal forces. When two identical surfaces come into contact, rotating the top surface we observe a peak in friction force near the angle of orientation where the two surfaces can interlock.

Keywords: friction, amonton`s law, superlubricity, contact model

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Authors: Jamal Choudhry, Roland Larsson, Andreas Almqvist

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A multi-scale flash temperature model has been developed and validated against existing work. The core strength of the proposed model is that it can be adapted to predict flash contact temperatures occurring in various types of sliding systems. In this paper, it is used to investigate how different surface roughness parameters affect the flash temperatures. The results show that for decreasing Hurst exponents as well as increasing values of the high-frequency cut-off, the maximum flash temperature increases. It was also shown that the effect of surface roughness does not influence the average interface temperature. The model predictions were validated against data from an experiment conducted in a pin-on-disc machine. This also showed the importance of including a wear model when simulating flash temperature development in a sliding system.

Keywords: multiscale, pin-on-disc, finite element method, flash temperature, surface roughness

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Authors: Suraj Amrutkar, R. Gowri, Asma Khan, Nazam Khan, Vikas Mahajan, Manpreet Kour And Bharti Deshmukh

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Herbal additives are rich in vitamin C, A and other biological active compounds and may act as surrogate source to subdue heat stress in chicken. Among various herbal additives such as rough lemon (Citrus Jambhiri Lush) juice, amla (Emblica officinalis) juice and aloe vera (Aloe barbadensis miller) gel are easily available during summer (stress period) and also cost less as comparison to synthetic feed additives in market. In order to analyze the performance by supplementation of rough lemon juice, amla juice and aloe vera gel in broiler under heat stress conditions. Study was carried out with a random distribution of day old straight run chicks (240 No.) in to four treatment group (n=60) was done. All the groups were given basal diet (Maize-Soya based; T0) was same for all the groups with supplementation of rough lemon juice (T1), amla juice (T2) and aloe vera (T3) @ 2% in drinking water. Experiment trial lasted for 42 days during heat stress period (June-July) with minimum THI (78.2) and Maximum THI (88.02). Feed and water were offered ad-libitum throughout the trial. Results revealed significantly higher (P<0.05) body weight in T3 and T2, followed by T1 and least in T0 at 42 days of age. The overall mean of Feed conversion ratio of various treatment T0, T1, T2 andT3 were 2.16, 1.98, 1.89 and 1.82, respectively. The mortality percentage in various treatment, T0, T1, T2 and T3, were 6.67, 3.33, 0.0 and 1.67, respectively. pH value, PCV (%), Sodium (mmol/L) and Potassium (mmol/L) was higher in T3 than rest of the groups. HL ratio is significantly lower (P<0.05) in T3, T2 followed by T1 than T0 at 42 days of age. It may be inferred that amongst these phyto-additives, aloe vera leads in alleviating heat stress in broiler in an economical way, followed by amla and rough lemon.

Keywords: rough lemon, amla, aloe vera, heat stress, broiler

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Authors: Bi Wa, Su-Yeon Kwon, Ik-Joong Kang

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Surface-enhanced Raman Scattering (SERS) as the principle for enhancing Raman scattering by molecules adsorbed on rough metal surfaces or by nanostructures is used to detect the concentration change of γ-Aminobutyric Acid (GABA). GABA is the mainly inhibitory neurotransmitter in the mammalian central nervous system in the human body. It plays such significant role in reducing neuronal excitability throughout the nervous system. In this case, the Mercaptopropionic Acid (MPA) is used to modified chitosan –gold nanoshell, which enhances the absorption between GABA and Chitosan-gold nanoshell. The sulfur end of the MPA is linked to gold which is the surface of the chitosan nanoparticles via the very strong S–Au bond, while a functional group (carboxyl group) attached to GABA. The controlling of particles’ size and the surface morphology are also the important factors during the whole experiment. The particle around 100nm is using to link to MPA, and the range of GABA from 1mM to 30mM was detected by the Raman Scattering to obtain the calibrate curve. In this study, DLS, SEM, FT-IR, UV, SERS were used to analyze the products to obtain the conclusion.

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

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Authors: Kunwar Mrityunjai Sharma, Trilok Nath Singh

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The Navier-Stokes equation is used to study nonlinear fluid flow in rough 2D fractures. The major goal is to investigate the influence of inertial flow owing to fracture wall roughness on nonlinear flow behavior. Roughness profiles are developed using Barton's Joint Roughness Coefficient (JRC) and used as fracture walls to assess wall roughness. Four JRC profiles (5, 11, 15, and 19) are employed in the study, where a higher number indicates higher roughness. A parametric study has been performed using varying pressure gradients, and the corresponding Forchheimer number is calculated to observe the nonlinear behavior. The results indicate that the fracture roughness has a significant effect on the onset of nonlinearity. Additionally, the validity of the cubic law is evaluated and observed that it overestimates the flow in rough fractures and should be used with utmost care.

Keywords: fracture flow, nonlinear flow, cubic law, Navier-stokes equation

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Authors: Michinori Nakata, Hiroshi Sakai

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A rough set, which consists of lower and upper approximations, is formulated in information tables containing possibilistic information. First, lower and upper approximations on the basis of possible world semantics in the same way as Lipski did in the field of incomplete databases are shown in order to clarify fundamentals of rough sets under possibilistic information. Possibility and necessity measures are used, as is done in possibilistic databases. As a result, each object has certain and possible membership degrees to lower and upper approximations, which degrees are the lower and upper bounds. Therefore, the degree that the object belongs to lower and upper approximations is expressed by an interval value. And the complementary property linked with the lower and upper approximations holds, as is valid under complete information. Second, the approach based on indiscernibility relations, which is proposed by Dubois and Prade, are extended in three cases. The first case is that objects used to approximate a set of objects are characterized by possibilistic information. The second case is that objects used to approximate a set of objects with possibilistic information are characterized by complete information. The third case is that objects that are characterized by possibilistic information approximate a set of objects with possibilistic information. The extended approach create the same results as the approach based on possible world semantics. This justifies our extension.

Keywords: rough sets, possibilistic information, possible world semantics, indiscernibility relations, lower approximations, upper approximations

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Authors: R. Sri Karthi Krishna, A. Saravana Kumar, Kesava Brahmaji, V. S. Vinoj

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The lunar surface may contain rough and non-uniform terrain with dips and peaks. Soft-landing is a method of landing the lander on the lunar surface without any damage to the vehicle. This project focuses on finding a safe landing site for the vehicle by developing a method for the lateral velocity determination of the lunar lander. This is done by processing the real time images obtained by means of an on-board vision sensor. The hazard avoidance phase of the soft-landing starts when the vehicle is about 200 m above the lunar surface. Here, the lander has a very low velocity of about 10 cm/s:vertical and 5 m/s:horizontal. On the detection of a hazard the lander is navigated by controlling the vertical and lateral velocity. In order to find an appropriate landing site and to accordingly navigate, the lander image processing is performed continuously. The images are taken continuously until the landing site is determined, and the lander safely lands on the lunar surface. By integrating this vision-based navigation with the INS a better accuracy for the soft-landing of the lunar lander can be obtained.

Keywords: vision aided INS, image processing, lateral velocity estimation, materials engineering

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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: Rahul Madathiparambil Visalakshan, Alex Cavallaro, John Hayball, Krasimir Vasilev

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The role of biomaterial surface nanotopograhy on fibrinogen adsorption and unfolding, and the subsequent immune response were studied. Inconsistent topography and varying chemical functionalities along with a lack of reproducibility pose a challenge in determining the specific effects of nanotopography or chemistry on proteins and cells. It is important to have a well-defined nanotopography with a homogeneous chemistry to study the real effect of nanotopography on biological systems. Therefore, we developed a technique that can produce well-defined and highly reproducible topography to identify the role of specific roughness, size, height and density with the presence of homogeneous chemical functionality. Using plasma polymerisation of oxazoline monomers and immobilized gold nanoparticles we created surfaces with an equal number density of nanoparticles of different sizes. This surface was used to study the role of surface nanotopography and the interplay of surface chemistry on proteins and immune cells. The effect of nanotopography on fibrinogen adsorption was investigated using Quartz Cristal Microbalance with Dissipation and micro BCA. The mass of fibrinogen adsorbed on the surface increased with increasing size of nano-topography. Protein structural changes up on adsorption to the nano rough surface was studied using circular dichroism spectroscopy. Fibrinogen unfolding varied depending on the specific nanotopography of the surfaces. It was revealed that the in vitro immune response to the nanotopography surfaces changed due to this protein unfolding.

Keywords: biomaterial inflammation, protein and cell responses, protein unfolding, surface nanotopography

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Authors: Soumendu Monia, Vaibhav Jain, Hrishikesh Jugade, Manashi Adhikary, Goutam Mukhopadhyay

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'Rolled in scale' (RIS) and 'Rolled in Scum' (RISc) are two superficial surface defects on cold rolled and annealed steel sheets which affect the aesthetics of surface and thereby that of the end-product. Both the defects are believed to be originating from distinctly different sources having different mechanisms of formation. However, due to their similar physical appearance, RIS and RISc are generally confused with each other and hence attaining the exact root cause for elimination of the defect becomes difficult. RIS appears irregular in shape, sometimes scattered, and always oriented in rolling direction. RISc is generally oval shaped, having identifiable pointed edges and mostly oriented in rolling direction. Visually, RIS appears to be greyish in colour whereas RISc is whitish in colour. Both the defects have quite random occurrence and do not leave any imprints on the reverse-side of the sheet. In the current study, an attempt has been made to differentiate these two similar looking surface defects using various metallographic and characterization techniques. Systematic experiments have been carried out to identify possible mechanisms of formation of these defects. Detailed characterization revealed basic differences between RIS and RISc with respect to their surface morphology. To summarize, RIS was observed as a residue of an otherwise under-pickled scale patch on surface, after it has been subjected to cold rolling and annealing in a batch/continuous furnace. Whereas RISc was found to be a localized rubbing of the surface, at the time of cold rolling itself, resulting in a rough surface texture.

Keywords: annealing, rolled in scale, rolled in scum, skin panel

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Authors: Sungpyo Kim, Changseok Oh, Ga-Young Lee, Hyun-Man Kim

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Intercellular junction of keratinocytes is crucial for epithelia to build an epithelial barrier. Junctional epithelium (JE) seals the interfaces between tooth and gingival tissue. Keratinocytes of JE attach to surfaces roughened by abrasion or erosion with aging. Thus behavior of oral keratinocytes on the rough substrates may help understand the epithelial seal of JE of which major intercellular junction is E-cadherin junction (ECJ). The present study investigated the influence of various substrate roughnesses on the development of ECJ between normal human gingival epithelial keratinocytes, HOK-16B cells. HOK-16B cells were slow in the development of ECJ on the rough substrates compared to on the smooth substrates. Furthermore, oral keratinocytes on the substrates of higher roughnesses were delayed in the development of E-cadherin junction than on the substrates of lower roughnesses. Delayed development of E-cadherin junction on the rough substrates was ascribed to the impaired spreading of cells and its higher JNK activity. Cells on the smooth substrates rapidly spread wide cytoplasmic extensions around cells. However, cells on the rough substrates slowly extended narrow cytoplasmic extensions of which number was limited due to the substrate irregularity. As these cytoplasmic extensions formed ECJ when met with the extensions of neighboring cells, thus, the present study demonstrated that a limited chance of contacts between cytoplasmic extensions due to the limited number of cytoplasmic extensions and slow development of cytoplasmic extensions brought about a delayed development of ECJ in oral keratinocytes on the rougher substrates. Sealing between cells was not complete because only part of cell membrane contributes to the formation of intercellular junction between cells on the substrates of higher roughnesses. Interestingly, inhibition of JNK activity promoted the development of ECJ on the rough substrates, of which mechanism remains to be studied further.

Keywords: substrate roughness, E-cadherin junction, oral keratinocyte, cell spreading, JNK

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Authors: Javad Rahimipour Anaraki, Saeed Samet, Mahdi Eftekhari, Chang Wook Ahn

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Feature selection and attribute reduction are crucial problems, and widely used techniques in the field of machine learning, data mining and pattern recognition to overcome the well-known phenomenon of the Curse of Dimensionality. This paper presents a feature selection method that efficiently carries out attribute reduction, thereby selecting the most informative features of a dataset. It consists of two components: 1) a measure for feature subset evaluation, and 2) a search strategy. For the evaluation measure, we have employed the fuzzy-rough dependency degree (FRFDD) of the lower approximation-based fuzzy-rough feature selection (L-FRFS) due to its effectiveness in feature selection. As for the search strategy, a modified version of a binary shuffled frog leaping algorithm is proposed (B-SFLA). The proposed feature selection method is obtained by hybridizing the B-SFLA with the FRDD. Nine classifiers have been employed to compare the proposed approach with several existing methods over twenty two datasets, including nine high dimensional and large ones, from the UCI repository. The experimental results demonstrate that the B-SFLA approach significantly outperforms other metaheuristic methods in terms of the number of selected features and the classification accuracy.

Keywords: binary shuffled frog leaping algorithm, feature selection, fuzzy-rough set, minimal reduct

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Authors: Md Abdullah Al Faruque, Ram Balachandar

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Sudden change of bed condition is frequent in open channel flow. Change of bed condition affects the turbulence characteristics in both streamwise and wall-normal direction. Understanding the turbulence intensity in open channel flow is of vital importance to the modeling of sediment transport and resuspension, bed formation, entrainment, and the exchange of energy and momentum. A comprehensive study was carried out to understand the extent of the effect of Reynolds number and bed roughness on different turbulence characteristics in an open channel flow. Four different bed conditions (impervious smooth bed, impervious continuous rough bed, pervious rough sand bed, and impervious distributed roughness) and two different Reynolds numbers were adopted for this cause. The effect of bed roughness on different turbulence characteristics is seen to be prevalent for most of the flow depth. Effect of Reynolds number on different turbulence characteristics is also evident for flow over different bed, but the extent varies on bed condition. Although the same sand grain is used to create the different rough bed conditions, the difference in turbulence characteristics is an indication that specific geometry of the roughness has an influence on turbulence characteristics. Roughness increases the contribution of the extreme turbulent events which produces very large instantaneous Reynolds shear stress and can potentially influence the sediment transport, resuspension of pollutant from bed and alter the nutrient composition, which eventually affect the sustainability of benthic organisms.

Keywords: open channel flow, Reynolds Number, roughness, turbulence

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Authors: Priya Varshney, Soumya S. Mohapatra

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Fabrication of anti-corrosion and self-cleaning superhydrophobic coatings for metallic surfaces which are regenerable and durable in the aggressive conditions has shown tremendous interest in materials science. In this work, the superhydrophobic coatings on metallic surfaces (aluminum, steel, copper) were prepared by two-step and one-step chemical etching process. In two-step process, roughness on surface was created by chemical etching and then passivation of roughened surface with low surface energy materials whereas, in one-step process, roughness on surface by chemical etching and passivation of surface with low surface energy materials were done in a single step. Beside this, the effect of etchant concentration and etching time on wettability and morphology was also studied. Thermal, mechanical, ultra-violet stability of these coatings were also tested. Along with this, regeneration of coatings and self-cleaning, corrosion resistance and water repelling characteristics were also studied. The surface morphology shows the presence of a rough microstuctures on the treated surfaces and the contact angle measurements confirms the superhydrophobic nature. It is experimentally observed that the surface roughness and contact angle increases with increase in etching time as well as with concentration of etchant. Superhydrophobic surfaces show the excellent self-cleaning behaviour. Coatings are found to be stable and maintain their superhydrophobicity in acidic and alkaline solutions. Water jet impact, floatation on water surface, and low temperature condensation tests prove the water-repellent nature of the coatings. These coatings are found to be thermal, mechanical and ultra-violet stable. These durable superhydrophobic metallic surfaces have potential industrial applications.

Keywords: superhydrophobic, water-repellent, anti-corrosion, self-cleaning

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Authors: Taher El-Bitar, Maha El-Meligy, Eman El-Shenawy, Almosilhy Almosilhy, Nader Dawood

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The steel contains 0.3% C and 0.004% B, beside Mn, Cr, Mo, and Ni. The alloy was processed by using 20-ton capacity electric arc furnace (EAF), and then refined by ladle furnace (LF). Liquid steel was cast as rectangular ingots. Dilatation test showed the critical transformation temperatures Ac₁, Ac₃, M_s and M_f as 716, 835, 356, and 218 °C. The ingots were austenitized and soaked and then rough rolled to thin slabs with 80 mm thickness. The thin slabs were then reheated and soaked for finish rolling to 6.0 mm thickness plates. During the rough rolling, the roll force increases as a result of rolling at temperatures less than recrystallization temperature. However, during finish rolling, the steel reflects initially continuous static recrystallization after which it shows strain hardening due to fall of temperature. It was concluded that, the steel plates were successfully heat treated by quenching-tempering at 250 ºC for 20 min.

Keywords: armor steel, austenitizing, critical transformation temperatures (CTTs), dilatation curve, martensite, quenching, rough and finish rolling processes, soaking, tempering, thermo-mechanical processing

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Authors: Arindam Chaudhuri

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Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

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Authors: Suzan Arslanturk, Mohammad-Reza Siadat, Theophilus Ogunyemi, Ananias Diokno

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Missing data is a common challenge in statistical analyses of most clinical survey datasets. A variety of methods have been developed to enable analysis of survey data to deal with missing values. Imputation is the most commonly used among the above methods. However, in order to minimize the bias introduced due to imputation, one must choose the right imputation technique and apply it to the correct type of missing data. In this paper, we have identified different types of missing values: missing data due to skip pattern (SPMD), undetermined missing data (UMD), and genuine missing data (GMD) and applied rough set imputation on only the GMD portion of the missing data. We have used rough set imputation to evaluate the effect of such imputation on prediction by generating several simulation datasets based on an existing epidemiological dataset (MESA). To measure how well each dataset lends itself to the prediction model (logistic regression), we have used p-values from the Wald test. To evaluate the accuracy of the prediction, we have considered the width of 95% confidence interval for the probability of incontinence. Both imputed and non-imputed simulation datasets were fit to the prediction model, and they both turned out to be significant (p-value < 0.05). However, the Wald score shows a better fit for the imputed compared to non-imputed datasets (28.7 vs. 23.4). The average confidence interval width was decreased by 10.4% when the imputed dataset was used, meaning higher precision. The results show that using the rough set method for missing data imputation on GMD data improve the predictive capability of the logistic regression. Further studies are required to generalize this conclusion to other clinical survey datasets.

Keywords: rough set, imputation, clinical survey data simulation, genuine missing data, predictive index

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Authors: Zhengkun Yi

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Surface texture discrimination using artificial tactile sensors has attracted increasing attentions in the past decade as it can endow technical and robot systems with a key missing ability. However, as a major component of texture, roughness has rarely been explored. This paper presents an approach for tactile surface roughness discrimination, which includes two parts: (1) design and fabrication of a bioinspired artificial fingertip, and (2) tactile signal processing for tactile surface roughness discrimination. The bioinspired fingertip is comprised of two polydimethylsiloxane (PDMS) layers, a polymethyl methacrylate (PMMA) bar, and two perpendicular polyvinylidene difluoride (PVDF) film sensors. This artificial fingertip mimics human fingertips in three aspects: (1) Elastic properties of epidermis and dermis in human skin are replicated by the two PDMS layers with different stiffness, (2) The PMMA bar serves the role analogous to that of a bone, and (3) PVDF film sensors emulate Meissner’s corpuscles in terms of both location and response to the vibratory stimuli. Various extracted features and classification algorithms including support vector machines (SVM) and k-nearest neighbors (kNN) are examined for tactile surface roughness discrimination. Eight standard rough surfaces with roughness values (Ra) of 50 μm, 25 μm, 12.5 μm, 6.3 μm 3.2 μm, 1.6 μm, 0.8 μm, and 0.4 μm are explored. The highest classification accuracy of (82.6 ± 10.8) % can be achieved using solely one PVDF film sensor with kNN (k = 9) classifier and the standard deviation feature.

Keywords: bioinspired fingertip, classifier, feature extraction, roughness discrimination

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Authors: Mafarja Majdi, Salwani Abdullah, Najmeh S. Jaddi

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One of the global combinatorial optimization problems in machine learning is feature selection. It concerned with removing the irrelevant, noisy, and redundant data, along with keeping the original meaning of the original data. Attribute reduction in rough set theory is an important feature selection method. Since attribute reduction is an NP-hard problem, it is necessary to investigate fast and effective approximate algorithms. In this paper, we proposed two feature selection mechanisms based on memetic algorithms (MAs) which combine the genetic algorithm with a fuzzy record to record travel algorithm and a fuzzy controlled great deluge algorithm to identify a good balance between local search and genetic search. In order to verify the proposed approaches, numerical experiments are carried out on thirteen datasets. The results show that the MAs approaches are efficient in solving attribute reduction problems when compared with other meta-heuristic approaches.

Keywords: rough set theory, attribute reduction, fuzzy logic, memetic algorithms, record to record algorithm, great deluge algorithm

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Authors: Usiobaifo Agharese Rosemary, Osaseri Roseline Oghogho

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Diabetes is a complex group of disease with a variety of causes; it is a disorder of the body metabolism in the digestion of carbohydrates food. The application of machine learning in the field of medical diagnosis has been the focus of many researchers and the use of recognition and classification model as a decision support tools has help the medical expert in diagnosis of diseases. Considering the large volume of medical data which require special techniques, experience, and high diagnostic skill in the diagnosis of diseases, the application of an artificial intelligent system to assist medical personnel in order to enhance their efficiency and accuracy in diagnosis will be an invaluable tool. In this study will propose a diabetes diagnosis model using rough set and K-nearest Neighbor classifier algorithm. The system consists of two modules: the feature extraction module and predictor module, rough data set is used to preprocess the attributes while K-nearest neighbor classifier is used to classify the given data. The dataset used for this model was taken for University of Benin Teaching Hospital (UBTH) database. Half of the data was used in the training while the other half was used in testing the system. The proposed model was able to achieve over 80% accuracy.

Keywords: classifier algorithm, diabetes, diagnostic model, machine learning

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Authors: Balwinder Singh

Abstract:

In the current competitive environment, casting industry has several challenges such as production of intricate castings, near net shape castings, decrease lead-time from product design to production, improved casting quality and to control costs. The raw materials used to make ceramic shell play an important role in determining the overall final ceramic shell characteristics. In this work, primary slurries were formulated using various combinations of zircon flour, fused silica and aluminosilicate powders as filler, colloidal silica as binder along with wetting and antifoaming agents (Catalyst). Taguchi’s parameter design strategy has been applied to investigate the effect of primary slurry parameters on the viscosity of the slurry and primary coating of shell. The result reveals that primary coating with low viscosity slurry has produced a rough surface of the shell due to stucco penetration.

Keywords: ceramic shell, primary slurry, filler, slurry viscosity, surface roughness

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Authors: Khalid Hussein, Waleed Abdalati, Pakorn Petchprayoon, Khaula Alkaabi

Abstract:

In this study, we integrated ASTER thermal data with an area-based spatial insolation model to identify and delineate geothermally active areas in Yellowstone National Park (YNP). Two pairs of L1B ASTER day- and nighttime scenes were used to calculate land surface temperature. We employed the Emissivity Normalization Algorithm which separates temperature from emissivity to calculate surface temperature. We calculated the incoming solar radiation for the area covered by each of the four ASTER scenes using an insolation model and used this information to compute temperature due to solar radiation. We then identified the statistical thermal anomalies using land surface temperature and the residuals calculated from modeled temperatures and ASTER-derived surface temperatures. Areas that had temperatures or temperature residuals greater than 2σ and between 1σ and 2σ were considered ASTER-modeled thermal anomalies. The areas identified as thermal anomalies were in strong agreement with the thermal areas obtained from the YNP GIS database. Also the YNP hot springs and geysers were located within areas identified as anomalous thermal areas. The consistency between our results and known geothermally active areas indicate that thermal remote sensing data, integrated with a spatial-based insolation model, provides an effective means for identifying and locating areas of geothermal activities over large areas and rough terrain.

Keywords: thermal remote sensing, insolation model, land surface temperature, geothermal anomalies

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Authors: Gayatri Swarnakar

Abstract:

Paramphistomiasis and fascioliasis diseases have been prevalent due to presence of trematode parasites in the rumen and liver of domestic buffalo (Bubalus bubalis) in Udaipur, India. The trematode parasites such as Paramphistomum cervi, Gastrothylax crumenifer, Cotylophoron cotylophorum, Orthocoelium scoliocoelium, Fasciola hepatica and Fasciola gigantica were collected from infected rumen and liver of the freshly slaughtered buffaloes (Bubalus bubalis) at local zoo abattoir in Udaipur. Live trematodes were washed in normal saline, fixed in 0.2M cacodylate fixative, post fixed in osmium tetraoxide, dehydrated, dried, coated with gold sputter and observed under scanning electronic microscope (SEM). The surface tegument of Paramphistomum cervi was spineless with transverse folds, discontinuous with ridges and grooves. Two types of sensory papillae such as knob like and button shaped were also observed. The oral opening of Cotylophoron cotylophorum was surrounded by wrinkled and ridged tegument which formed concentric elevated rings. Tegument of Cotylophoron cotylophorum in acetabulum region was observed to be rough and bee-comb like structure. Genital sucker of this worm was surrounded by a tyre- shaped elevation of the tegument. Orthocoelium scoliocoelium showed circular and concentric rings of tegumental folds around the oral sucker. Genital pore had knob like papillae with radial tegumental folds. Surface topography of Fasciola gigantica and Fasciola hepatica were found to be rough due to occurrence of different types of spines, three types of sensory papillae, transverse folds and grooves. Oral and ventral suckers were spineless and covered with thick rims of transverse folds. Genital pore showed small scattered spines. Present research work would provide knowledge for ultrastructural characteristics of trematode parasites for chemotherapeutic measures and help us to evolve suitable strategy for the eradication of trematode parasites from the domestic buffalo (Bubalus bubalis).

Keywords: Domestic buffalo, tegument, trematode parasites, ultrastructure

Procedia PDF Downloads 280

Authors: S. Oluwagbemiga Alayande, E. Olugbenga Dare, Titus A. M. Msagati, A. Kehinde Akinlabi , P. O. Aiyedun

Abstract:

This paper presents a cheap route procedure for the preparation of a potential oil membrane with superhydrophobic /superoleophillic properties for selective removal of crude oil from water. In these study, expanded polystyrene (EPS) was electrospun to produce beaded fibers in which zeolite was introduced to the polymer matrix in order to impart rough surface to non-beaded fiber. Films of the EPS and EPS/Zeolite solutions were also made for comparative study. The electrospun fibers EPS, EPS/Zeolite and resultant films were characterized using SEM, BET, FTIR and optical contact angle. The fibers exhibited superhydrophic and superoleophillic wetting properties with water and crude oil. The selective removal of crude oil presents new opportunity for the re-use of EPS as adsorbent in petroleum/petrochemical industry.

Keywords: expanded polystyrene, superhydrophobic, superoleophillic, oil-membrane

Procedia PDF Downloads 441

Authors: Ahmed A. D. Sarhan, S. R. Besharaty, Javad Akbaria, M. Hamdi

Abstract:

The capability of CNC gantry milling machines in manufacturing long components has caused the expanded use of such machines. On the other hand, the machines’ gantry rigidity can reduce under severe loads or vibration during operation. Indeed, the quality of machining is dependent on the machine’s dynamic behavior throughout the operating process. For this reason, this type of machines has always been used prudently and are non efficient. Therefore, they can usually be employed for rough machining and may not produce adequate surface finishing. In this paper, a CNC gantry milling machine with the potential to produce good surface finish has been designed and analyzed. The lowest natural frequency of this machine is 202 Hz at all motion amplitudes with a full range of suitable frequency responses. Meanwhile, the maximum deformation under dead loads for the gantry machine is 0.565µm, indicating that this machine tool is capable of producing higher product quality.

Keywords: frequency response, finite element, gantry machine, gantry design, static and dynamic analysis

Procedia PDF Downloads 327