Search results for: Deep and surface approaches

Authors: K. Jaroensutasinee

Abstract:

The general global behavior of particle S a non-linear (Q - xy)2 potential cannot be revealed a Poincare surface of section method (PSS) because inost trajectories take practically infinitely long time to integrate numerically before they come back to the surface. In this study as an alternative to PSS, a multiple scale perturbation is applied to analyze global adiabatic, non-adiabatic and chaotic behavior of particles in this potential. It was found that the results can be summarized as a form of a Fermi-like map. Additionally, this method gives a variation of global stochasticity criteria with Q.

Keywords: Multiple Scak Perturbation The Poincare Surface or Section, Fermi Map

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Authors: Zhong Ma, Zhuping Wang, Congxin Liu, Xiangzeng Liu

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Satellite imagery classification is a challenging problem with many practical applications. In this paper, we designed a deep convolution neural network (DCNN) to classify the satellite imagery. The contributions of this paper are twofold — First, to cope with the large-scale variance in the satellite image, we introduced the inception module, which has multiple filters with different size at the same level, as the building block to build our DCNN model. Second, we proposed a genetic algorithm based method to efficiently search the best hyper-parameters of the DCNN in a large search space. The proposed method is evaluated on the benchmark database. The results of the proposed hyper-parameters search method show it will guide the search towards better regions of the parameter space. Based on the found hyper-parameters, we built our DCNN models, and evaluated its performance on satellite imagery classification, the results show the classification accuracy of proposed models outperform the state of the art method.

Keywords: Satellite imagery classification, deep convolution network, genetic algorithm, hyper-parameter optimization.

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Authors: Tharini N. de Silva, Xiao Zhibo, Zhao Rui, Mao Kezhi

Abstract:

Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.

Keywords: Causal relation identification, convolutional neural networks, natural Language Processing, Machine Learning.

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Authors: A. Kawamura, K. Ishida, K. Okada, T. Sato

Abstract:

Simultaneous measurements of the curves for wear versus distance, wear rate versus distance, and coefficient of friction versus distance were performed in situ to distinguish the transition from severe running-in wear to mild wear. The effects of the initial surface roughness on the severe running-in wear volume were investigated. Disk-on-plate friction and wear tests were carried out with SUS304 austenitic stainless steel in contact with itself under repeated dry sliding conditions at room temperature. The wear volume was dependent on the initial surface roughness. The wear volume when the initial surfaces on the plate and disk had dissimilar roughness was lower than that when these surfaces had similar roughness. For the dissimilar roughness, the wear volume decreased with decreasing initial surface roughness and reached a minimum; it stayed nearly constant as the roughness was less than the mean size of the oxide particles.

Keywords: Austenitic stainless steel, initial surface roughness, running-in, severe wear.

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Authors: M. Farahnakian, M.R. Razfar, S. Elhami-Joosheghan

Abstract:

This paper presents an approach for the determination of the optimal cutting parameters (spindle speed, feed rate, depth of cut and engagement) leading to minimum surface roughness in face milling of high silicon stainless steel by coupling neural network (NN) and Electromagnetism-like Algorithm (EM). In this regard, the advantages of statistical experimental design technique, experimental measurements, artificial neural network, and Electromagnetism-like optimization method are exploited in an integrated manner. To this end, numerous experiments on this stainless steel were conducted to obtain surface roughness values. A predictive model for surface roughness is created by using a back propogation neural network, then the optimization problem was solved by using EM optimization. Additional experiments were performed to validate optimum surface roughness value predicted by EM algorithm. It is clearly seen that a good agreement is observed between the predicted values by EM coupled with feed forward neural network and experimental measurements. The obtained results show that the EM algorithm coupled with back propogation neural network is an efficient and accurate method in approaching the global minimum of surface roughness in face milling.

Keywords: cutting parameters, face milling, surface roughness, artificial neural network, Electromagnetism-like algorithm,

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Authors: S. Dey, P. Sibanda, S. Gupta, A. Chakraborty

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The occurrence of high nocturnal surface ozone over a tropical urban area (23̊ 32′16.99″ N and 87̊ 17′ 38.95″ E) is analyzed in this paper. Five incidences of nocturnal ozone maxima are recorded during the observational span of two years (June, 2013 to May, 2015). The maximum and minimum values of the surface ozone during these five occasions are 337.630 μg/m³ and 13.034 μg/m³ respectively. HYSPLIT backward trajectory analyses and wind rose diagrams support the horizontal transport of ozone from distant polluted places. Planetary boundary layer characteristics, concentration of precursor (NO₂) and meteorology are found to play important role in the horizontal and vertical transport of surface ozone during nighttime.

Keywords: Nocturnal ozone, planetary boundary layer, horizontal transport, meteorology, urban area.

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Authors: Watcharee Rattanasakulthong, Pichai Sirisangsawang, Supree Pinitsoontorn

Abstract:

Sputtered CoxCu100-x films with the different compositions of x = 57.7, 45.8, 25.5, 13.8, 8.8, 7.5 and 1.8 were deposited on Cr under-layer by RF-sputtering. SEM result reveals that the averaged thickness of Co-Cu film and Cr under-layer are 92 nm and 22nm, respectively. All Co-Cu films are composed of Co (FCC) and Cu (FCC) phases in (111) directions on BCC-Cr (110) under-layers. Magnetic properties, surface roughness and morphology of Co-Cu films are dependent on the film composition. The maximum and minimum surface roughness of 3.24 and 1.16nm are observed on the Co7.5Cu92.5 and Co45.8Cu54.2films, respectively. It can be described that the variance of surface roughness of the film because of the difference of the agglomeration rate of Co and Cu atoms on Cr under-layer. The Co57.5Cu42.3, Co45.8Cu54.2 and Co25.5Cu74.5 films shows the ferromagnetic phase whereas the rest of the film exhibits the paramagnetic phase at room temperature. The saturation magnetization, remnant magnetization and coercive field of Co-Cu films on Cr under-layer are slightly increased with increasing the Co composition. It can be concluded that the required magnetic properties and surface roughness of the Co-Cu film can be adapted by the adjustment of the film composition.

Keywords: Co-Cu films, Under-layers, Sputtering, Surface roughness, Magnetic properties, Atomic force microscopy (AFM).

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Authors: Hesham Muhammad Ibrahim

Abstract:

This paper introduces and proves new concept of salt dissolving in water as very tiny solid sodium chloride particles of nanovolumes, from this point of view salt water can be desalinated by collision with special surface characterized by smoothness upon nano level, high rigidity, high hardness under appropriate conditions of water launching in the form of thin laminar flow under suitable speed and angle of incidence to get desalinated water.

Keywords: Desalination by collision, nano coating, water desalination, water repellent surface.

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Authors: I. Markovska, F. Yovkova, G. Minov, D. Rusev, L. Lyubchev

Abstract:

The present research focus on the processing of mullite-based ceramics from oil refinery industrial wastes and byproducts of agricultural industry and on the investigating of silane modified surface of ceramics. Two waste products were used as initial material – waste aluminum oxide and waste rice husk. The burning - out additives used were waste rise husk. It is known that  the oxide ceramics surface is hydrophilic due to the presence of – OH groups in it. The nature of ceramic surface regarding permeation of water and hydrocarbons can be changed by further treatment with silanes. The samples were studied mainly by X-ray analysis, FT-IR absorbance measurements and microscopic analysis. The X-ray analyses showed the phase composition depends on the firing temperature and on the purity of the starting alumina. Two kind of silanes were used for the transformation of surface from hydrophilic to hydrophobic – trimethoxymethylsilane (TMMS) and trimethylclorsilane (TMCS).

Keywords: Porous mullite ceramics, waste materials, trimethoxymethylsilane, trimethylclorsilane.

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Authors: M. Aruna, V. Dhanalaksmi

Abstract:

Inconel 718, a nickel based super-alloy is an extensively used alloy, accounting for about 50% by weight of materials used in an aerospace engine, mainly in the gas turbine compartment. This is owing to their outstanding strength and oxidation resistance at elevated temperatures in excess of 5500 C. Machining is a requisite operation in the aircraft industries for the manufacture of the components especially for gas turbines. This paper is concerned with optimization of the surface roughness when turning Inconel 718 with cermet inserts. Optimization of turning operation is very useful to reduce cost and time for machining. The approach is based on Response Surface Method (RSM). In this work, second-order quadratic models are developed for surface roughness, considering the cutting speed, feed rate and depth of cut as the cutting parameters, using central composite design. The developed models are used to determine the optimum machining parameters. These optimized machining parameters are validated experimentally, and it is observed that the response values are in reasonable agreement with the predicted values.

Keywords: Inconel 718, Optimization, Response Surface Methodology (RSM), Surface roughness

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Authors: K.-H. Yang

Abstract:

In the past, there was a lot of excellent research studies conducted on topics related to supplier selection. Because the considered factors of supplier selection are complicated and difficult to be quantified, most researchers deal supplier selection issues by qualitative approaches. Compared to qualitative approaches, quantitative approaches are less applicable in the real world. This study tried to apply the quantitative approach to study a supplier selection problem with considering operation cost and delivery reliability. By those factors, this study applies Normalized Normal Constraint Method to solve the dual objectives mixed integer program of the supplier selection problem.

Keywords: Bi-objectives MIP, normalized normal constraint method, supplier selection, quantitative approach.

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Authors: S. Shahrooi, I. H. Metselaar, Z. Huda

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When considering the development of constitutive equations describing the behavior of materials under cyclic plastic strains, different kinds of formulations can be adopted. The primary intention of this study is to develop computer programming of plasticity models to accurately predict the life of engineering components. For this purpose, the energy or cyclic strain is computed in multi-surface plasticity models in non-proportional loading and to present their procedures and codes results.

Keywords: Strain energy, cyclic plasticity model, multi-surface model, codes result.

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Authors: H. Baseri, G. Alinejad

Abstract:

The objective of this study is to design an adaptive neuro-fuzzy inference system (ANFIS) for estimation of surface roughness in grinding process. The Used data have been generated from experimental observations when the wheel has been dressed using a rotary diamond disc dresser. The input parameters of model are dressing speed ratio, dressing depth and dresser cross-feed rate and output parameter is surface roughness. In the experimental procedure the grinding conditions are constant and only the dressing conditions are varied. The comparison of the predicted values and the experimental data indicates that the ANFIS model has a better performance with respect to back-propagation neural network (BPNN) model which has been presented by the authors in previous work for estimation of the surface roughness.

Keywords: Grinding, ANFIS, Neural network, Disc dressing.

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Authors: Ali Gholami, Ebrahim Panahpour, Amir Hossein Davami

Abstract:

In this research, a part of Aghche basin in Isfahan province with an area about 2000 hectars, was chosen to be obtain curve number coefficient runoff and W indicator in second Cook method By using aerial photos 1968 and 1995, the satellite data of the IRS in 2008. Then the process of land use changes in the period of study and its effect on the changes of curve number (CN), W indicator and surface runoff coefficient (C) of the basin was investigated. These results showed that on the track of these land use changes the weight averages curve number (CN), surface runoff coefficient (C) and W indicator of the basin were increased to 0.92, 0.02 and 0.78 unit in the first period of study and 1.18, 0.03, 0.99 Unit in the second period of study respectively.

Keywords: Aghche Watershed, Curve Numbers (CV), Land UseChanges, Surface Runoff Coefficient(C) Map, W indicator

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Authors: Ko-Shao Chen, Yun Tsao, Chia-Hsuan Tsen, Chien-Chung Chen, Shu-Chuan Liao

Abstract:

Electrospun microtube array membranes (MTAMs) made of PLLA (poly-L-lactic acid) have wide potential applications in tissue engineering. However, their surface hydrophobicity and poor biocompatability have limited their further usage. In this study, the surface of PLLA MTAMs were made hydrophilic by introducing extra functional groups, such as peroxide, via an acetic acid plasma (AAP). UV-graft polymerization of acrylic acid (G-AAc) was then used to produce carboxyl group on MTAMs surface, which bonded covalently with chitosan through EDC / NHS crosslinking agents. To evaluate the effects of the surface modification on PLLA MTAMs, water contact angle (WCA) measurement and cell compatibility tests were carried out. We found that AAP treated electrospun PLLA MTAMs grafted with AAc and, finally, with chitosan immobilized via crosslinking agent, exhibited improved hydrophilic and cell compatibility.

Keywords: Plasma, EDC/NHS, UV grafting, chitosan, microtube array membrane.

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Authors: S. A. Kondratyev, O. I. Ibragimova

Abstract:

The authors discuss the collecting abilities of desorbable species (DS) of saturated fatty acids. The DS species of the reagent are understood as species capable of moving from the surface of the mineral particle to the bubble at the moment of the rupture of the interlayer of liquid separating these objects of interaction. DS species of carboxylic acids (molecules and ionic-molecular complexes) have the ability to spread over the surface of the bubble. The rate of their spreading at pH 7 and 10 over the water surface is determined. The collectibility criterion of saturated fatty acids is proposed. The values of forces exerted by the spreading DS species of reagents on liquid in the interlayer and the liquid flow rate from the interlayer are determined.

Keywords: Criterion of action of physically adsorbed reagent, flotation, saturated fatty acids, surface pressure.

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Authors: Jinrui Ren, Li Wu

Abstract:

Anthropogenic activities and changes of underlying surface affect the temporal and spatial distribution of surface temperature in Kunming. Taking Kunming city as the research area, the surface temperature in 2000, 2010 and 2020 as the research object, using ENVI 5.3 and ArcGIS 10.8 as auxiliary tools, and based on the spatial autocorrelation method, this paper devoted to exploring the interactions among the changes of surface temperature, urban heat island effect and land use type, so as to provide theoretical basis and scientific basis for mitigating climate change. The results showed that: (1) The heat island effect was obvious in Kunming City, the high temperature area increased from 604 km2 in 2000 to 1269 km2 in 2020, and the sub-high temperature area reached 1099 km2 in 2020; (2) In terms of space, the spatial distribution of LST was significantly different with the change of underlying surface. The high temperature zone extended in three directions: south, north and east. The overall spatial distribution pattern of LST was high in the east and low in the west. (3) The inter-annual fluctuation of land surface temperature (LST) was large, and the growth rate was faster, from 2000 to 2010. The lowest temperature in 2000 was 13.45 ℃, which raised to 19.71 ℃ in 2010, and the temperature difference in 10 years was 6.26 ℃. (4) The land use/land cover type has a strong effect on the change of LST: the man-made land made a great contribution to the increase of LST, followed by grassland and farmland, while forest and water have a significant cooling effect on LST. To sum up, the variation of surface temperature in Kunming is the result of the interactions of human activities and climate change.

Keywords: Surface temperature, urban heat island effect, land use cover type, spatiotemporal variation.

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Authors: Chungkuk Jin, Moo-Hyun Kim, HeonYong Kang

Abstract:

A surface riding (SR) wave energy converter (WEC) is designed and its feasibility and performance are numerically simulated by the author-developed floater-mooring-magnet-electromagnetics fully-coupled dynamic analysis computer program. The biggest advantage of the SR-WEC is that the performance is equally effective even in low sea states and its structural robustness is greatly improved by simply riding along the wave surface compared to other existing WECs. By the numerical simulations and actuator testing, it is clearly demonstrated that the concept works and through the optimization process, its efficiency can be improved.

Keywords: Computer simulation, electromagnetics fully-coupled dynamics, floater-mooring-magnet, optimization, performance evaluation, surface riding, wave energy converter.

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Authors: Fidel Lòpez Saca, Carlos Avilés-Cruz, Miguel Magos-Rivera, José Antonio Lara-Chávez

Abstract:

Automated object recognition and identification systems are widely used throughout the world, particularly in assembly lines, where they perform quality control and automatic part selection tasks. This article presents the design and implementation of an object recognition system in an assembly line. The proposed shapes-color recognition system is based on deep learning theory in a specially designed convolutional network architecture. The used methodology involve stages such as: image capturing, color filtering, location of object mass centers, horizontal and vertical object boundaries, and object clipping. Once the objects are cut out, they are sent to a convolutional neural network, which automatically identifies the type of figure. The identification system works in real-time. The implementation was done on a Raspberry Pi 3 system and on a Jetson-Nano device. The proposal is used in an assembly course of bachelor’s degree in industrial engineering. The results presented include studying the efficiency of the recognition and processing time.

Keywords: Deep-learning, image classification, image identification, industrial engineering.

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Authors: Hsuan-Ming S Hu, Jolanta A Watson, Bronwen W Cribb, Gregory S Watson

Abstract:

Biomimicry has many potential benefits as many technologies found in nature are superior to their man-made counterparts. As technological device components approach the micro and nanoscale, surface properties such as surface adhesion and friction may need to be taken into account. Lowering surface adhesion by manipulating chemistry alone might no longer be sufficient for such components and thus physical manipulation may be required. Adhesion reduction is only one of the many surface functions displayed by micro/nano-structured cuticles of insects. Here, we present a mini review of our understanding of insect cuticle structures and the relationship between the structure dimensions and the corresponding functional mechanisms. It may be possible to introduce additional properties to material surfaces (indeed multi-functional properties) based on the design of natural surfaces.

Keywords: Biomimicry, micro/nanostructures, self-cleaning surfaces, superhydrophobicity

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Authors: H.Seidi, M.Jalali Azizpour, S.A.Zahedi

Abstract:

Today, Hydroforming technology provides an attractive alternative to conventional matched die forming, especially for cost-sensitive, lower volume production, and for parts with irregular contours. In this study the critical fluid pressures which lead to rupture in the workpiece has been investigated by theoretical and finite element methods. The axisymmetric analysis was developed to investigate the tearing phenomenon in cylindrical Hydroforming Deep Drawing (HDD). By use of obtained equations the effect of anisotropy, drawing ratio, sheet thickness and strain hardening exponent on tearing diagram were investigated.

Keywords: Hydroforming deep drawing, Pressure path, Axisymmetric analysis, Finite element simulation.

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Authors: Seyed Abolhasan Naeini, Saeideh Mohammadi

Abstract:

Site response has a profound effect on earthquake damages. Seismic interaction of urban tunnels with surface structures could also affect seismic site response. Here, we use FLAC 2D to investigate the interaction of a single tunnel and twin tunnels-surface structures on the site response. Soil stratification and properties are selected based on Line. No 7 of the Tehran subway. The effect of surface structure is considered in two ways: Equivalent surcharge and geometrical modeling of the structure. Comparison of the results shows that consideration of the structure geometry is vital in dynamic analysis and leads to the changes in the magnitude of displacements, accelerations and response spectrum. Therefore it is necessary for the surface structures to be wholly modeled and not just considered as a surcharge in dynamic analysis. The use of twin tunnel also leads to the reduction of dynamic residual settlement.

Keywords: Superstructure, tunnel, site response, surcharge, interaction.

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Authors: Jie Liu, Xudong Luo, Pingping Lin, Yifan Fan

Abstract:

Facebook, Twitter, Weibo, and other social media and significant e-commerce sites generate a massive amount of online texts, which can be used to analyse people’s opinions or sentiments for better decision-making. So, sentiment analysis, especially the fine-grained sentiment analysis, is a very active research topic. In this paper, we survey various methods for fine-grained sentiment analysis, including traditional sentiment lexicon-based methods, ma-chine learning-based methods, and deep learning-based methods in aspect/target/attribute-based sentiment analysis tasks. Besides, we discuss their advantages and problems worthy of careful studies in the future.

Keywords: sentiment analysis, fine-grained, machine learning, deep learning

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Authors: J. Hassan

Abstract:

Water 2H NMR signal on the surface of nano-silica material, MCM-41, consists of two overlapping resonances. The 2H water spectrum shows a superposition of a Lorentzian line shape and the familiar NMR powder pattern line shape, indicating the existence of two spin components. Chemical exchange occurs between these two groups. Decomposition of the two signals is a crucial starting point for study the exchange process. In this article we have determined these spin component populations along with other important parameters for the 2H water NMR signal over a temperature range between 223 K and 343 K.

Keywords: Nano-Silica, surface water, NMR

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Authors: Victor E. Gromov, Evgenii A. Budovskikh, Ludmila P. Bashchenko, Yurii F. Ivanov, Anna V. Ionina, Nina A. Soskova, Guoyi Tang

Abstract:

The peculiarities of the nanoscale structure-phase states formed after electroexplosive carburizing and subsequent electron-beam treatment of technically pure titanium surface in different regimes are established by methods of transmission electron diffraction microscopy and physical mechanisms are discussed. Electroexplosive carburizing leads to surface layer formation (40 m thickness) with increased (in 3.5 times) microhardness. It consists of β-titanium, graphite (monocrystals 100-150 nm, polycrystals 5-10 nm, amorphous particles 3-5nm), TiC (5-10 nm), β-Ti02 (2-20nm). After electron-beam treatment additionally increasing the microhardness the surface layer consists of TiC.

Keywords: nanoscale, phase, structure, titanium

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Authors: Z. Mazrouei-Sebdani, A. Khoddami, H. Hadadzadeh, M. Zarrebini

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In this research, waterglass based aerogel powder was prepared by sol–gel process and ambient pressure drying. Inspired by limited dust releasing, aerogel powder was introduced to the PET electrospinning solution in an attempt to create required bulk and surface structure for the nanofibers to improve their hydrophobic and insulation properties. The samples evaluation was carried out by measuring density, porosity, contact angle, heat transfer, FTIR, BET, and SEM. According to the results, porous silica aerogel powder was fabricated with mean pore diameter of 24 nm and contact angle of 145.9º. The results indicated the usefulness of the aerogel powder confined into nanofibers to control surface roughness for manipulating superhydrophobic nanowebs with water contact angle of 147º. It can be due to a multi-scale surface roughness which was created by nanowebs structure itself and nanofibers surface irregularity in presence of the aerogels while a layer of fluorocarbon created low surface energy. The wettability of a solid substrate is an important property that is controlled by both the chemical composition and geometry of the surface. Also, a decreasing trend in the heat transfer was observed from 22% for the nanofibers without any aerogel powder to 8% for the nanofibers with 4% aerogel powder. The development of thermal insulating materials has become increasingly more important than ever in view of the fossil energy depletion and global warming that call for more demanding energysaving practices.

Keywords: Superhydrophobicity, Insulation, Sol-gel, Surface energy, Roughness.

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Authors: M. A. Fodha, H. Benfradj, A. Ghazel

Abstract:

This paper is a survey of recent works that proposes a baseband processor architecture for software defined radio. A classification of different approaches is proposed. The performance of each architecture is also discussed in order to clarify the suitable approaches that meet software-defined radio constraints.

Keywords: Multi-core architectures, reconfigurable architecture, software defined radio.

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Authors: A. Mahdy, Sameh E. Ahmed

Abstract:

Detailed numerical calculations are illustrated in our investigation for unsteady natural convection heat and mass transfer of non-Newtonian Casson fluid along a vertical wavy surface. The surface of the plate is kept at a constant temperature and uniform concentration. To transform the complex wavy surface to a flat plate, a simple coordinate transformation is employed. The resulting partial differential equations are solved using the fully implicit finite difference method with SUR procedure. Flow and heat transfer characteristics are investigated for a wide range of values of the Casson parameter, the dimensionless time parameter, the buoyancy ratio and the amplitude-wavelength parameter. It is found that, the variations of the Casson parameter have significant effects on the fluid motion, heat and mass transfer. Also, the maximum and minimum values of the local Nusselt and Sherwood numbers increase by increase either the Casson parameter or the buoyancy ratio.

Keywords: Casson fluid, wavy surface, mass transfer, transient analysis.

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Authors: M. Si Abdallah, B. Zeghmati

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A numerical analysis used to simulate the effects of wavy surfaces and thermal radiation on natural convection heat transfer boundary layer flow over an inclined wavy plate has been investigated. A simple coordinate transformation is employed to transform the complex wavy surface into a flat plate. The boundary layer equations and the boundary conditions are discretized by the finite difference scheme and solved numerically using the Gauss-Seidel algorithm with relaxation coefficient. Effects of the wavy geometry, the inclination angle of the wavy plate and the thermal radiation on the velocity profiles, temperature profiles and the local Nusselt number are presented and discussed in detail.

Keywords: Free convection, wavy surface, inclined surface, thermal radiation.

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Authors: Konstantinos Perifanos, Eirini Florou, Dionysis Goutsos

Abstract:

This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state-of-the-art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of training tuples, the related sentences and their labels. The outcome is a state-of-the-art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.

Keywords: Metaphor detection, deep learning, representation learning, embeddings.

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