Search results for: differential images

Authors: S. Sieniutycz

Abstract:

This paper unifies power optimization approaches in various energy converters, such as: thermal, solar, chemical, and electrochemical engines, in particular fuel cells. Thermodynamics leads to converter-s efficiency and limiting power. Efficiency equations serve to solve problems of upgrading and downgrading of resources. While optimization of steady systems applies the differential calculus and Lagrange multipliers, dynamic optimization involves variational calculus and dynamic programming. In reacting systems chemical affinity constitutes a prevailing component of an overall efficiency, thus the power is analyzed in terms of an active part of chemical affinity. The main novelty of the present paper in the energy yield context consists in showing that the generalized heat flux Q (involving the traditional heat flux q plus the product of temperature and the sum products of partial entropies and fluxes of species) plays in complex cases (solar, chemical and electrochemical) the same role as the traditional heat q in pure heat engines. The presented methodology is also applied to power limits in fuel cells as to systems which are electrochemical flow engines propelled by chemical reactions. The performance of fuel cells is determined by magnitudes and directions of participating streams and mechanism of electric current generation. Voltage lowering below the reversible voltage is a proper measure of cells imperfection. The voltage losses, called polarization, include the contributions of three main sources: activation, ohmic and concentration. Examples show power maxima in fuel cells and prove the relevance of the extension of the thermal machine theory to chemical and electrochemical systems. The main novelty of the present paper in the FC context consists in introducing an effective or reduced Gibbs free energy change between products p and reactants s which take into account the decrease of voltage and power caused by the incomplete conversion of the overall reaction.

Keywords: Power yield, entropy production, chemical engines, fuel cells, exergy.

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Authors: Mohammed A. Alolfe, Abou-Bakr M. Youssef, Yasser M. Kadah

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The proper design of RF pulses in magnetic resonance imaging (MRI) has a direct impact on the quality of acquired images, and is needed for many applications. Several techniques have been proposed to obtain the RF pulse envelope given the desired slice profile. Unfortunately, these techniques do not take into account the limitations of practical implementation such as limited amplitude resolution. Moreover, implementing constraints for special RF pulses on most techniques is not possible. In this work, we propose to develop an approach for designing optimal RF pulses under theoretically any constraints. The new technique will pose the RF pulse design problem as a combinatorial optimization problem and uses efficient techniques from this area such as genetic algorithms (GA) to solve this problem. In particular, an objective function will be proposed as the norm of the difference between the desired profile and the one obtained from solving the Bloch equations for the current RF pulse design values. The proposed approach will be verified using analytical solution based RF simulations and compared to previous methods such as Shinnar-Le Roux (SLR) method, and analysis, selected, and tested the options and parameters that control the Genetic Algorithm (GA) can significantly affect its performance to get the best improved results and compared to previous works in this field. The results show a significant improvement over conventional design techniques, select the best options and parameters for GA to get most improvement over the previous works, and suggest the practicality of using of the new technique for most important applications as slice selection for large flip angles, in the area of unconventional spatial encoding, and another clinical use.

Keywords: Selective excitation, magnetic resonance imaging, combinatorial optimization, pulse design.

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Authors: Akbar Cahyadhi Pratama Putra, Tantri Utami Widhaningtyas, M. Randy Aswin

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Indonesia, as an archipelagic nation, has a very long coastline with significant potential for marine resources, including mangrove ecosystems. The Lapindo mudflow disaster in Sidoarjo, East Java, resulted in mudflow being discharged into the sea through the Brantas and Porong rivers. The mud material transported by the river flow is feared to be dangerous because it contains harmful substances such as heavy metals. This study aims to map the mangrove ecosystem in terms of its density and assess the impact of the Lapindo mud disaster on the mangrove ecosystem, along with efforts to sustain its continuity. The mapping of the coastal mangrove conditions in Sidoarjo was carried out using remote sensing products, specifically Landsat 7 ETM+ images, taken during dry months in 2002, 2006, 2009, and 2014. The density of mangroves was determined using NDVI, which utilizes band 3 (the red channel) and band 4 (the near IR channel). Image processing to generate NDVI was performed using ENVI 5.1 software. The NDVI results were used to assess mangrove density on a scale from 0 to 1. The growth of mangrove ecosystems, both in terms of area and density, showed a significant increase from year to year. The development of mangrove ecosystems was influenced by the deposition of Lapindo mud in the estuaries of the Porong and Brantas rivers, where the silt provided a suitable medium for the growth of the mangrove ecosystem, leading to an increase in its density. The rise in density was supported by public awareness to mitigate heavy metal contamination, allowing for mangrove breeding near the affected areas.

Keywords: Archipelagic nation, Mangrove, Lapindo mudflow disaster, NDVI.

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Authors: Cheng Zeng, George Michailidis, Hitoshi Iyatomi, Leo L Duan

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The conditional density characterizes the distribution of a response variable y given other predictor x, and plays a key role in many statistical tasks, including classification and outlier detection. Although there has been abundant work on the problem of Conditional Density Estimation (CDE) for a low-dimensional response in the presence of a high-dimensional predictor, little work has been done for a high-dimensional response such as images. The promising performance of normalizing flow (NF) neural networks in unconditional density estimation acts a motivating starting point. In this work, we extend NF neural networks when external x is present. Specifically, they use the NF to parameterize a one-to-one transform between a high-dimensional y and a latent z that comprises two components [zP , zN]. The zP component is a low-dimensional subvector obtained from the posterior distribution of an elementary predictive model for x, such as logistic/linear regression. The zN component is a high-dimensional independent Gaussian vector, which explains the variations in y not or less related to x. Unlike existing CDE methods, the proposed approach, coined Augmented Posterior CDE (AP-CDE), only requires a simple modification on the common normalizing flow framework, while significantly improving the interpretation of the latent component, since zP represents a supervised dimension reduction. In image analytics applications, AP-CDE shows good separation of x-related variations due to factors such as lighting condition and subject id, from the other random variations. Further, the experiments show that an unconditional NF neural network, based on an unsupervised model of z, such as Gaussian mixture, fails to generate interpretable results.

Keywords: Conditional density estimation, image generation, normalizing flow, supervised dimension reduction.

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Authors: M. A. Talha, M. Osman Gani, M. Ferdows

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This paper focuses on the study of two dimensional magnetohydrodynamic (MHD) steady incompressible viscous Williamson nanofluid with exponential internal heat generation containing gyrotactic microorganism over a stretching sheet. The governing equations and auxiliary conditions are reduced to a set of non-linear coupled differential equations with the appropriate boundary conditions using similarity transformation. The transformed equations are solved numerically through spectral relaxation method. The influences of various parameters such as Williamson parameter γ, power constant λ, Prandtl number P_r, magnetic field parameter M, Peclet number P_e, Lewis number Le, Bioconvection Lewis number Lb, Brownian motion parameter Nb, thermophoresis parameter Nt, and bioconvection constant σ are studied to obtain the momentum, heat, mass and microorganism distributions. Moment, heat, mass and gyrotactic microorganism profiles are explored through graphs and tables. We computed the heat transfer rate, mass flux rate and the density number of the motile microorganism near the surface. Our numerical results are in better agreement in comparison with existing calculations. The Residual error of our obtained solutions is determined in order to see the convergence rate against iteration. Faster convergence is achieved when internal heat generation is absent. The effect of magnetic parameter M decreases the momentum boundary layer thickness but increases the thermal boundary layer thickness. It is apparent that bioconvection Lewis number and bioconvection parameter has a pronounced effect on microorganism boundary. Increasing brownian motion parameter and Lewis number decreases the thermal boundary layer. Furthermore, magnetic field parameter and thermophoresis parameter has an induced effect on concentration profiles.

Keywords: Convection flow, internal heat generation, similarity, spectral method, numerical analysis, Williamson nanofluid.

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Authors: M. M. Hasan, A. S. M. A. Haseeb, R. Saidur, H. H. Masjuki

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In this investigation, anatase TiO2 thin films were grown by radio frequency magnetron sputtering on glass substrates at a high sputtering pressure and room temperature. The anatase films were then annealed at 300-600 °C in air for a period of 1 hour. To examine the structure and morphology of the films, X-ray diffraction (XRD) and atomic force microscopy (AFM) methods were used respectively. From X-ray diffraction patterns of the TiO2 films, it was found that the as-deposited film showed some differences compared with the annealed films and the intensities of the peaks of the crystalline phase increased with the increase of annealing temperature. From AFM images, the distinct variations in the morphology of the thin films were also observed. The optical constants were characterized using the transmission spectra of the films obtained by UV-VIS-IR spectrophotometer. Besides, optical thickness of the film deposited at room temperature was calculated and cross-checked by taking a cross-sectional image through SEM. The optical band gaps were evaluated through Tauc model. It was observed that TiO2 films produced at room temperatures exhibited high visible transmittance and transmittance decreased slightly with the increase of annealing temperatures. The films were found to be crystalline having anatase phase. The refractive index of the films was found from 2.31-2.35 in the visible range. The extinction coefficient was nearly zero in the visible range and was found to increase with annealing temperature. The allowed indirect optical band gap of the films was estimated to be in the range from 3.39 to 3.42 eV which showed a small variation. The allowed direct band gap was found to increase from 3.67 to 3.72 eV. The porosity was also found to decrease at a higher annealing temperature making the film compact and dense.

Keywords: Titanium dioxide, RF reactive sputtering, Structuralproperties, Surface morphology, Optical properties.

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Authors: Paola Lecca, Lorenzo Dematte

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Reactiondiffusion systems are mathematical models that describe how the concentration of one or more substances distributed in space changes under the influence of local chemical reactions in which the substances are converted into each other, and diffusion which causes the substances to spread out in space. The classical representation of a reaction-diffusion system is given by semi-linear parabolic partial differential equations, whose general form is ÔêétX(x, t) = DΔX(x, t), where X(x, t) is the state vector, D is the matrix of the diffusion coefficients and Δ is the Laplace operator. If the solute move in an homogeneous system in thermal equilibrium, the diffusion coefficients are constants that do not depend on the local concentration of solvent and of solutes and on local temperature of the medium. In this paper a new stochastic reaction-diffusion model in which the diffusion coefficients are function of the local concentration, viscosity and frictional forces of solvent and solute is presented. Such a model provides a more realistic description of the molecular kinetics in non-homogenoeus and highly structured media as the intra- and inter-cellular spaces. The movement of a molecule A from a region i to a region j of the space is described as a first order reaction Ai k- → Aj , where the rate constant k depends on the diffusion coefficient. Representing the diffusional motion as a chemical reaction allows to assimilate a reaction-diffusion system to a pure reaction system and to simulate it with Gillespie-inspired stochastic simulation algorithms. The stochastic time evolution of the system is given by the occurrence of diffusion events and chemical reaction events. At each time step an event (reaction or diffusion) is selected from a probability distribution of waiting times determined by the specific speed of reaction and diffusion events. Redi is the software tool, developed to implement the model of reaction-diffusion kinetics and dynamics. It is a free software, that can be downloaded from http://www.cosbi.eu. To demonstrate the validity of the new reaction-diffusion model, the simulation results of the chaperone-assisted protein folding in cytoplasm obtained with Redi are reported. This case study is redrawing the attention of the scientific community due to current interests on protein aggregation as a potential cause for neurodegenerative diseases.

Keywords: Reaction-diffusion systems, Fick's law, stochastic simulation algorithm.

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Authors: M. R. Homaeinezhad, E. Tavakkoli, M. Habibi, S. A. Atyabi, A. Ghaffari

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This paper describes a new supervised fusion (hybrid) electrocardiogram (ECG) classification solution consisting of a new QRS complex geometrical feature extraction as well as a new version of the learning vector quantization (LVQ) classification algorithm aimed for overcoming the stability-plasticity dilemma. Toward this objective, after detection and delineation of the major events of ECG signal via an appropriate algorithm, each QRS region and also its corresponding discrete wavelet transform (DWT) are supposed as virtual images and each of them is divided into eight polar sectors. Then, the curve length of each excerpted segment is calculated and is used as the element of the feature space. To increase the robustness of the proposed classification algorithm versus noise, artifacts and arrhythmic outliers, a fusion structure consisting of five different classifiers namely as Support Vector Machine (SVM), Modified Learning Vector Quantization (MLVQ) and three Multi Layer Perceptron-Back Propagation (MLP–BP) neural networks with different topologies were designed and implemented. The new proposed algorithm was applied to all 48 MIT–BIH Arrhythmia Database records (within–record analysis) and the discrimination power of the classifier in isolation of different beat types of each record was assessed and as the result, the average accuracy value Acc=98.51% was obtained. Also, the proposed method was applied to 6 number of arrhythmias (Normal, LBBB, RBBB, PVC, APB, PB) belonging to 20 different records of the aforementioned database (between– record analysis) and the average value of Acc=95.6% was achieved. To evaluate performance quality of the new proposed hybrid learning machine, the obtained results were compared with similar peer– reviewed studies in this area.

Keywords: Feature Extraction, Curve Length Method, SupportVector Machine, Learning Vector Quantization, Multi Layer Perceptron, Fusion (Hybrid) Classification, Arrhythmia Classification, Supervised Learning Machine.

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Authors: Sang Wook Park, Jun Su Park, Byung Kwan Oh, Yousok Kim, Hyo Seon Park

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This study suggests the estimation method of stress distribution for the beam structures based on TLS (Terrestrial Laser Scanning). The main components of method are the creation of the lattices of raw data from TLS to satisfy the suitable condition and application of CSSI (Cubic Smoothing Spline Interpolation) for estimating stress distribution. Estimation of stress distribution for the structural member or the whole structure is one of the important factors for safety evaluation of the structure. Existing sensors which include ESG (Electric strain gauge) and LVDT (Linear Variable Differential Transformer) can be categorized as contact type sensor which should be installed on the structural members and also there are various limitations such as the need of separate space where the network cables are installed and the difficulty of access for sensor installation in real buildings. To overcome these problems inherent in the contact type sensors, TLS system of LiDAR (light detection and ranging), which can measure the displacement of a target in a long range without the influence of surrounding environment and also get the whole shape of the structure, has been applied to the field of structural health monitoring. The important characteristic of TLS measuring is a formation of point clouds which has many points including the local coordinate. Point clouds are not linear distribution but dispersed shape. Thus, to analyze point clouds, the interpolation is needed vitally. Through formation of averaged lattices and CSSI for the raw data, the method which can estimate the displacement of simple beam was developed. Also, the developed method can be extended to calculate the strain and finally applicable to estimate a stress distribution of a structural member. To verify the validity of the method, the loading test on a simple beam was conducted and TLS measured it. Through a comparison of the estimated stress and reference stress, the validity of the method is confirmed.

Keywords: Structural health monitoring, terrestrial laser scanning, estimation of stress distribution, coordinate transformation, cubic smoothing spline interpolation.

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Authors: Eric Sitorus, Septian Prahastudhi, Turgod Nainggolan, Erwin Riyanto

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Mining by block or panel caving is a mining method that takes advantage of fractures within an ore body, coupled with gravity, to extract material from a predetermined column of ore. The caving column is weakened from beneath through the use of undercutting, after which the ore breaks up and is extracted from below in a continuous cycle. The nature of this method induces cyclical stresses on the pillars of excavations as stress is built up and released over time, which has a detrimental effect on both the installed ground support and the rock mass itself. Ground support capacity, especially on the production where excavation void ratio is highest, is subjected to heavy loading. Strain above threshold of the elongation of support capacity can yield resulting in damage to excavations. Geotechnical engineers must evaluate not only the remnant capacity of ground support systems but also investigate depth of rock mass yield within pillars, backs and floors. Ground Penetrating Radar (GPR) is a geophysical method that has the ability to evaluate rock mass damage using electromagnetic waves. This paper illustrates a case study from the Grasberg mining complex where non-invasive information on the depth of damage and condition of the remaining rock mass was required. GPR with 100 MHz antenna resolution was used to obtain images of the subsurface to determine rehabilitation requirements prior to recommencing production activities. The GPR surveys were used to calibrate the reflection coefficient response of varying rock mass conditions to known Rock Quality Designation (RQD) parameters observed at the mine. The calibrated GPR survey allowed site engineers to map subsurface conditions and plan rehabilitation accordingly.

Keywords: Block caving, ground penetrating radar, reflectivity, RQD.

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Authors: Melis Inalpulat, Levent Genc

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In the present study, an attempt was made to state the Land Use Land Cover (LULC) transformation over three decades around the urban regions of Balıkesir, Bursa, and Çanakkale provincial centers (PCs) in Turkey. Landsat imageries acquired in 1984, 1999 and 2014 were used to determine the LULC change. Images were classified using the supervised classification technique and five main LULC classes were considered including forest (F), agricultural land (A), residential area (urban) - bare soil (R-B), water surface (W), and other (O). Change detection analyses were conducted for 1984-1999 and 1999-2014, and the results were evaluated. Conversions of LULC types to R-B class were investigated. In addition, population changes (1985-2014) were assessed depending on census data, the relations between population and the urban areas were stated, and future populations and urban area needs were forecasted for 2030. The results of LULC analysis indicated that urban areas, which are covered under R-B class, were expanded in all PCs. During 1984-1999 R-B class within Balıkesir, Bursa and Çanakkale PCs were found to have increased by 7.1%, 8.4%, and 2.9%, respectively. The trend continued in the 1999-2014 term and the increment percentages reached to 15.7%, 15.5%, and 10.2% at the end of 30-year period (1984-2014). Furthermore, since A class in all provinces was found to be the principal contributor for the R-B class, urban sprawl lead to the loss of agricultural lands. Moreover, the areas of R-B classes were highly correlated with population within all PCs (R²>0.992). Depending on this situation, both future populations and R-B class areas were forecasted. The estimated values of increase in the R-B class areas for Balıkesir, Bursa, and Çanakkale PCs were 1,586 ha, 7,999 ha and 854 ha, respectively. Due to this fact, the forecasted values for 2,030 are 7,838 ha, 27,866, and 2,486 ha for Balıkesir, Bursa, and Çanakkale, and thus, 7.7%, 8.2%, and 9.7% more R-B class areas are expected to locate in PCs in respect to the same order.

Keywords: Landsat, LULC change, population, urban sprawl.

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Authors: Kunchit Pirapake

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Application of Geo-Informatic technology in land tenure and land use on the economic crop area, to create sustainable land, access to the area, and produce sustainable food for the demand of its people in the community. The research objectives are to 1) apply Geo-Informatic Technology on land ownership and agricultural land use (cash crops) in the research area, 2) create GIS database on land ownership and land use, 3) create database of an online Geoinformation system on land tenure and land use. The results of this study reveal that, first; the study area is on high slope, mountains and valleys. The land is mainly in the forest zone which was included in the Forest Act 1941 and National Conserved Forest 1964. Residents gained the rights to exploit the land passed down from their ancestors. The practice was recognized by communities. The land was suitable for cultivating a wide variety of economic crops that was the main income of the family. At present the local residents keep expanding the land to grow cash crops. Second; creating a database of the geographic information system consisted of the area range, announcement from the Interior Ministry, interpretation of satellite images, transportation routes, waterways, plots of land with a title deed available at the provincial land office. Most pieces of land without a title deed are located in the forest and national reserve areas. Data were created from a field study and a land zone determined by a GPS. Last; an online Geo-Informatic System can show the information of land tenure and land use of each economic crop. Satellite data with high resolution which could be updated and checked on the online Geo-Informatic System simultaneously.

Keywords: Geo-Informatic Technology, Land Tenure, Online Geo-Informatic System, Land Use of cash crops.

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Authors: Qing Liu, Jean-Fabien Capsal, Claude Richard

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In this current contribution, authors are dedicated to investigate influence of the crystal lamellae orientation on electromechanical behaviors of relaxor ferroelectric Poly (vinylidene fluoride –trifluoroethylene -chlorotrifluoroethylene) (P(VDF-TrFE-CTFE)) films by control of polymer microstructure, aiming to picture the full map of structure-property relationship. In order to define their crystal orientation films, terpolymer films were fabricated by solution-casting, stretching and hot-pressing process. Differential scanning calorimetry, impedance analyzer, and tensile strength techniques were employed to characterize crystallographic parameters, dielectric permittivity, and elastic Young’s modulus respectively. In addition, large electrical induced out-of-plane electrostrictive strain was obtained by cantilever beam mode. Consequently, as-casted pristine films exhibited surprisingly high electrostrictive strain 0.1774% due to considerably small value of elastic Young’s modulus although relatively low dielectric permittivity. Such reasons contributed to large mechanical elastic energy density. Instead, due to 2 folds increase of elastic Young’s modulus and less than 50% augmentation of dielectric constant, fullycrystallized film showed weak electrostrictive behavior and mechanical energy density as well. And subjected to mechanical stretching process, Film C exhibited stronger dielectric constant and out-performed electrostrictive strain over Film B because edge-on crystal lamellae orientation induced by uniaxially mechanical stretch. Hot-press films were compared in term of cooling rate. Rather large electrostrictive strain of 0.2788% for hot-pressed Film D in quenching process was observed although its dielectric permittivity equivalent to that of pristine as-casted Film A, showing highest mechanical elastic energy density value of 359.5 J/m3. In hot-press cooling process, dielectric permittivity of Film E saw values at 48.8 concomitant with ca.100% increase of Young’s modulus. Films with intermediate mechanical energy density were obtained.

Keywords: Crystal orientation, electrostrictive strain, mechanical energy density, permittivity, relaxor ferroelectric.

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Authors: A. Atli, K. Candelier, J. Alteyrac

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Environmental and sustainability concerns push the industries to manufacture alternative materials having less environmental impact. The Wood Plastic Composites (WPCs) produced by blending the biopolymers and natural fillers permit not only to tailor the desired properties of materials but also are the solution to meet the environmental and sustainability requirements. This work presents the elaboration and characterization of the fully green WPCs prepared by blending a biopolymer, BIOPLAST® GS 2189 and spruce sawdust used as filler with different amounts. Since both components are bio-based, the resulting material is entirely environmentally friendly. The mechanical, thermal, structural properties of these WPCs were characterized by different analytical methods like tensile, flexural and impact tests, Thermogravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC) and X-ray Diffraction (XRD). Their water absorption properties and resistance to the termite and fungal attacks were determined in relation with different wood filler content. The tensile and flexural moduli of WPCs increased with increasing amount of wood fillers into the biopolymer, but WPCs became more brittle compared to the neat polymer. Incorporation of spruce sawdust modified the thermal properties of polymer: The degradation, cold crystallization, and melting temperatures shifted to higher temperatures when spruce sawdust was added into polymer. The termite, fungal and water absorption resistance of WPCs decreased with increasing wood amount in WPCs, but remained in durability class 1 (durable) concerning fungal resistance and quoted 1 (attempted attack) in visual rating regarding to the termites resistance except that the WPC with the highest wood content (30 wt%) rated 2 (slight attack) indicating a long term durability. All the results showed the possibility to elaborate the easy injectable composite materials with adjustable properties by incorporation of BIOPLAST® GS 2189 and spruce sawdust. Therefore, lightweight WPCs allow both to recycle wood industry byproducts and to produce a full ecologic material.

Keywords: Biodegradability, durability, mechanical properties, melt flow index, spectrophotometry, structural properties, thermal properties, wood-plastic composites.

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Authors: Hamidullah Binol, Abdullah Bal

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Nowadays, food safety is a great public concern; therefore, robust and effective techniques are required for detecting the safety situation of goods. Hyperspectral Imaging (HSI) is an attractive material for researchers to inspect food quality and safety estimation such as meat quality assessment, automated poultry carcass inspection, quality evaluation of fish, bruise detection of apples, quality analysis and grading of citrus fruits, bruise detection of strawberry, visualization of sugar distribution of melons, measuring ripening of tomatoes, defect detection of pickling cucumber, and classification of wheat kernels. HSI can be used to concurrently collect large amounts of spatial and spectral data on the objects being observed. This technique yields with exceptional detection skills, which otherwise cannot be achieved with either imaging or spectroscopy alone. This paper presents a nonlinear technique based on kernel Fukunaga-Koontz transform (KFKT) for detection of fat content in ground meat using HSI. The KFKT which is the nonlinear version of FKT is one of the most effective techniques for solving problems involving two-pattern nature. The conventional FKT method has been improved with kernel machines for increasing the nonlinear discrimination ability and capturing higher order of statistics of data. The proposed approach in this paper aims to segment the fat content of the ground meat by regarding the fat as target class which is tried to be separated from the remaining classes (as clutter). We have applied the KFKT on visible and nearinfrared (VNIR) hyperspectral images of ground meat to determine fat percentage. The experimental studies indicate that the proposed technique produces high detection performance for fat ratio in ground meat.

Keywords: Food (Ground meat) inspection, Fukunaga-Koontz transform, hyperspectral imaging, kernel methods.

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Authors: Yongquan Zhao, Bo Huang

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Spatial, Temporal, and Spectral Resolution (STSR) are three key characteristics of Earth observation satellite sensors; however, any single satellite sensor cannot provide Earth observations with high STSR simultaneously because of the hardware technology limitations of satellite sensors. On the other hand, a conflicting circumstance is that the demand for high STSR has been growing with the remote sensing application development. Although image fusion technology provides a feasible means to overcome the limitations of the current Earth observation data, the current fusion technologies cannot enhance all STSR simultaneously and provide high enough resolution improvement level. This study proposes a Hybrid Spatial-Temporal-Spectral image Fusion Model (HSTSFM) to generate synthetic satellite data with high STSR simultaneously, which blends the high spatial resolution from the panchromatic image of Landsat-8 Operational Land Imager (OLI), the high temporal resolution from the multi-spectral image of Moderate Resolution Imaging Spectroradiometer (MODIS), and the high spectral resolution from the hyper-spectral image of Hyperion to produce high STSR images. The proposed HSTSFM contains three fusion modules: (1) spatial-spectral image fusion; (2) spatial-temporal image fusion; (3) temporal-spectral image fusion. A set of test data with both phenological and land cover type changes in Beijing suburb area, China is adopted to demonstrate the performance of the proposed method. The experimental results indicate that HSTSFM can produce fused image that has good spatial and spectral fidelity to the reference image, which means it has the potential to generate synthetic data to support the studies that require high STSR satellite imagery.

Keywords: Hybrid spatial-temporal-spectral fusion, high resolution synthetic imagery, least square regression, sparse representation, spectral transformation.

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Authors: Jožef Ritonja

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The biochemical industry is one of the most important modern industries. Biochemical reactors are crucial devices of the biochemical industry. The essential bioprocess carried out in bioreactors is the fermentation process. A thorough insight into the fermentation process and the knowledge how to control it are essential for effective use of bioreactors to produce high quality and quantitatively enough products. The development of the control system starts with the determination of a mathematical model that describes the steady state and dynamic properties of the controlled plant satisfactorily, and is suitable for the development of the control system. The paper analyses the fermentation process in bioreactors thoroughly, using existing mathematical models. Most existing mathematical models do not allow the design of a control system for controlling the fermentation process in batch bioreactors. Due to this, a mathematical model was developed and presented that allows the development of a control system for batch bioreactors. Based on the developed mathematical model, a control system was designed to ensure optimal response of the biochemical quantities in the fermentation process. Due to the time-varying and non-linear nature of the controlled plant, the conventional control system with a proportional-integral-differential controller with constant parameters does not provide the desired transient response. The improved adaptive control system was proposed to improve the dynamics of the fermentation. The use of the adaptive control is suggested because the parameters’ variations of the fermentation process are very slow. The developed control system was tested to produce dairy products in the laboratory bioreactor. A carbon dioxide concentration was chosen as the controlled variable. The carbon dioxide concentration correlates well with the other, for the quality of the fermentation process in significant quantities. The level of the carbon dioxide concentration gives important information about the fermentation process. The obtained results showed that the designed control system provides minimum error between reference and actual values of carbon dioxide concentration during a transient response and in a steady state. The recommended control system makes reference signal tracking much more efficient than the currently used conventional control systems which are based on linear control theory. The proposed control system represents a very effective solution for the improvement of the milk fermentation process.

Keywords: Bioprocess engineering, biochemical reactor, fermentation process, modeling, adaptive control.

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Authors: Naoto Suzuki

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A decline in visual sensitivity at arbitrary points on the retina can be measured using a precise perimetry apparatus along with a fundus camera. However, the retinal layer associated with this decline cannot be identified accurately with current medical technology. To investigate cryptogenic diseases, such as macular dystrophy, acute zonal occult outer retinopathy (AZOOR), and multiple evanescent white dot syndrome (MEWDS), we evaluated an electroretinogram (ERG) function that allows moving the center of the multifocal hexagonal stimulus array to a chosen position. Macular dystrophy is a generalized term used for a variety of functional disorders of the macula lutea, and the ERG shows a diminution of the b-wave in these disorders. AZOOR causes an acute functional disorder to an outer layer of the retina, and the ERG shows a-wave and b-wave amplitude reduction as well as delayed 30 Hz flicker responses. MEWDS causes acute visual loss and the ERG shows a decrease in a-wave amplitude. We combined an electroretinographic optical system and a perimetric optical system into an experimental apparatus that has the same optical system as that of a fundus camera. We also deployed an EO-50231 Edmund infrared camera, a 45-degree cold mirror, a lens with a 25-mm focal length, a halogen lamp, and an 8-inch monitor. Then, we also employed a differential amplifier with gain 10, a 50 Hz notch filter, a high-pass filter with a 21.2 Hz cut-off frequency, and two non-inverting amplifiers with gains 1001 and 11. In addition, we used a USB-6216 National Instruments I/O device, a NE-113A Nihon Kohden plate electrode, a SCB-68A shielded connector block, and LabVIEW 2017 software for data retrieval. The software was used to generate the multifocal hexagonal stimulus array on the computer monitor with C++Builder 10.2 and to move the center of the array toward the left and right and up and down. Cone and bright flash ERG results were observed using the moving ERG function. The a-wave, b-wave, c-wave, and the photopic negative response were identified with cone ERG. The moving ERG function allowed the identification of the retinal layer causing visual alterations.

Keywords: Moving ERG, multifocal ERG, precise perimetry, retinal layers, visual sensitivity

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Authors: Moses C. Siame, Kazutoshi Haga, Atsushi Shibayama

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This study investigates the removal of silica, alumina and phosphorus as impurities from Sanje iron ore using wet high-intensity magnetic separation (WHIMS). Sanje iron ore contains low-grade hematite ore found in Nampundwe area of Zambia from which iron is to be used as the feed in the steelmaking process. The chemical composition analysis using X-ray Florence spectrometer showed that Sanje low-grade ore contains 48.90 mass% of hematite (Fe₂O₃) with 34.18 mass% as an iron grade. The ore also contains silica (SiO₂) and alumina (Al₂O₃) of 31.10 mass% and 7.65 mass% respectively. The mineralogical analysis using X-ray diffraction spectrometer showed hematite and silica as the major mineral components of the ore while magnetite and alumina exist as minor mineral components. Mineral particle distribution analysis was done using scanning electron microscope with an X-ray energy dispersion spectrometry (SEM-EDS) and images showed that the average mineral size distribution of alumina-silicate gangue particles is in order of 100 μm and exists as iron-bearing interlocked particles. Magnetic separation was done using series L model 4 Magnetic Separator. The effect of various magnetic separation parameters such as magnetic flux density, particle size, and pulp density of the feed was studied during magnetic separation experiments. The ore with average particle size of 25 µm and pulp density of 2.5% was concentrated using pulp flow of 7 L/min. The results showed that 10 T was optimal magnetic flux density which enhanced the recovery of 93.08% of iron with 53.22 mass% grade. The gangue mineral particles containing 12 mass% silica and 3.94 mass% alumna remained in the concentrate, therefore the concentrate was further treated in the second stage WHIMS using the same parameters from the first stage. The second stage process recovered 83.41% of iron with 67.07 mass% grade. Silica was reduced to 2.14 mass% and alumina to 1.30 mass%. Accordingly, phosphorus was also reduced to 0.02 mass%. Therefore, the two stage magnetic separation process was established using these results.

Keywords: Sanje iron ore, magnetic separation, silica, alumina, recovery.

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Authors: Ilona Copik

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The aim of this study is to analyze the representation of memories of the forced displacement of Poles and Germans from the eastern territories in 1945 as depicted by Polish and German feature films between the years 1945-1960. The aftermath of World War II and the Allied agreements concluded at Yalta and Potsdam (1945) resulted in changes in national borders in Central and Eastern Europe and the large-scale transfer of civilians. The westward migration became a symbol of the new post-war division of Europe, new spheres of influence separated by the Iron Curtain. For years it was a controversial topic in both Poland and Germany due to the geopolitical alignment (the socialist East and capitalist West of Europe), as well as the unfinished debate between the victims and perpetrators of the war. The research premise is to take a comparative view of the conflicted cultures of Polish and German memory, to reflect on the possibility of an international dialogue about the past recorded in film images, and to discover the potential of film as a narrative warning against totalitarian inclinations. Until now, films made between 1945 and 1960 in Poland and the German occupation zones have been analyzed mainly in the context of artistic strategies subordinated to ideology and historical politics. In this study, the intention is to take a critical approach leading to the recognition of how films work as collective memory media, how they reveal the mechanisms of memory/ forgetting, and what settlement topoi and migration myths they contain. The main hypothesis is that feature films about forced displacement, in addition to the politics of history - separate in each country - reveal comparable transnational individual experiences: the chaos of migration, the trauma of losing one's home, the conflicts accompanying the familiar/foreign, the difficulty of cultural adaptation, the problem of lost identity, etc.

Keywords: Forced displacement, Polish and German cinema, war victims, World War II.

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Authors: Gabi Nehme

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The relationship between different types of Molybdenum disulfide greases under extreme pressure loading and different speed situations have been studied using Design of Experiment (DOE) under 1200rpm steady state rotational speed and cyclic frequencies between 2400 and 1200rpm using a Plint machine software to set up the different rotational speed situations.  Research described here is aimed at providing good friction and wear performance while optimizing cyclic frequencies and MoS2 concentration due to the recent concern about grease behavior in extreme pressure applications. Extreme load of 785 Newton was used in conjunction with different cyclic frequencies (2400rpm -3.75min, 1200rpm -7.5min, 2400rpm -3.75min, 1200rpm -7.5min), to examine lithium based grease with and without MoS2 for equal number of revolutions, and a total run of 36000 revolutions; then compared to 1200rpm steady speed for the same total number of revolutions. 4 Ball wear tester was utilized to run large number of experiments randomly selected by the DOE software. The grease was combined with fine grade MoS2 or technical grade then heated to 750C and the wear scar width was collected at the end of each test. DOE model validation results verify that the data were very significant and can be applied to a wide range of extreme pressure applications. Based on simulation results and Scanning Electron images (SEM), it has been found that wear was largely dependent on the cyclic frequency condition. It is believed that technical grade MoS2 greases under faster cyclic speeds perform better and provides antiwear film that can resist extreme pressure loadings. Figures showed reduced wear scars width and improved frictional values.

 

Keywords: MoS2 grease, wear, friction, extreme load, cyclic frequencies, aircraft grade bearing.

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Authors: Mohamed K. Shahin, Ahmed M. Badawi, Mohamed E. M. Rasmy

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Prior research evidenced that unimodal biometric systems have several tradeoffs like noisy data, intra-class variations, restricted degrees of freedom, non-universality, spoof attacks, and unacceptable error rates. In order for the biometric system to be more secure and to provide high performance accuracy, more than one form of biometrics are required. Hence, the need arise for multimodal biometrics using combinations of different biometric modalities. This paper introduces a multimodal biometric system (MMBS) based on fusion of whole dorsal hand geometry and fingerprints that acquires right and left (Rt/Lt) near-infra-red (NIR) dorsal hand geometry (HG) shape and (Rt/Lt) index and ring fingerprints (FP). Database of 100 volunteers were acquired using the designed prototype. The acquired images were found to have good quality for all features and patterns extraction to all modalities. HG features based on the hand shape anatomical landmarks were extracted. Robust and fast algorithms for FP minutia points feature extraction and matching were used. Feature vectors that belong to similar biometric traits were fused using feature fusion methodologies. Scores obtained from different biometric trait matchers were fused using the Min-Max transformation-based score fusion technique. Final normalized scores were merged using the sum of scores method to obtain a single decision about the personal identity based on multiple independent sources. High individuality of the fused traits and user acceptability of the designed system along with its experimental high performance biometric measures showed that this MMBS can be considered for med-high security levels biometric identification purposes.

Keywords: Unimodal, Multi-Modal, Biometric System, NIR Imaging, Dorsal Hand Geometry, Fingerprint, Whole Hands, Feature Extraction, Feature Fusion, Score Fusion

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Authors: Feyzan Tuzkaya, Nihan S. Soylu, Çağlar Solak, Hilal Peker, Mehmet Peker, Kemal Özeralp, Ceren Mete, Ezgi Mehmetoğlu, Mehmet Karasu, Cihan Elçi, Ece Akca, Melek Göregenli

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Perception, evaluation and representation of the environment have been the subject of many disciplines including psychology, geography and architecture. In environmental and social psychology literature there are several evidences which suggest that cognitive representations about a place consisted of not only geographic items but also social and cultural. Mental representations of residence area or a country are influenced and determined by social-demographics, the physical and social context. Thus, all mental representations of a given place are also social representations. Cognitive maps are the main and common instruments that are used to identify spatial images and the difference between physical and subjective environments. The aim of the current study is investigating the mental and social representations of Turkey in university students’ minds. Data was collected from 249 university students from different departments (i.e. psychology, geography, history, tourism departments) of Ege University. Participants were requested to reflect Turkey in their mind onto the paper drawing sketch maps. According to the results, cognitive maps showed geographic aspects of Turkey as well as the context of symbolic, cultural and political reality of Turkey. That is to say, these maps had many symbolic and verbal items related to critics on social and cultural problems, ongoing ethnic and political conflicts, and actual political agenda of Turkey. Additionally, one of main differentiations in these representations appeared in terms of the East and West side of the Turkey, and the representations of the East and West was varied correspondingly participants’ cultural background, their ethnic values, and where they have born. The results of the study were discussed in environmental and social psychological perspective considering cultural and social values of Turkey and current political circumstances of the country.

Keywords: Cognitive maps, East and West, politics, social representations, Turkey.

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Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

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Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, unmanned aerial vehicle, UAV, random, Kriging.

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Authors: Umberto Di Staso, Marco Soave, Alessio Giori, Federico Prandi, Raffaele De Amicis

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The increasing availability of information about earth surface elevation (Digital Elevation Models DEM) generated from different sources (remote sensing, Aerial Images, Lidar) poses the question about how to integrate and make available to the most than possible audience this huge amount of data. In order to exploit the potential of 3D elevation representation the quality of data management plays a fundamental role. Due to the high acquisition costs and the huge amount of generated data, highresolution terrain surveys tend to be small or medium sized and available on limited portion of earth. Here comes the need to merge large-scale height maps that typically are made available for free at worldwide level, with very specific high resolute datasets. One the other hand, the third dimension increases the user experience and the data representation quality, unlocking new possibilities in data analysis for civil protection, real estate, urban planning, environment monitoring, etc. The open-source 3D virtual globes, which are trending topics in Geovisual Analytics, aim at improving the visualization of geographical data provided by standard web services or with proprietary formats. Typically, 3D Virtual globes like do not offer an open-source tool that allows the generation of a terrain elevation data structure starting from heterogeneous-resolution terrain datasets. This paper describes a technological solution aimed to set up a so-called “Terrain Builder”. This tool is able to merge heterogeneous-resolution datasets, and to provide a multi-resolution worldwide terrain services fully compatible with CesiumJS and therefore accessible via web using traditional browser without any additional plug-in.

Keywords: Terrain builder, WebGL, virtual globe, CesiumJS, tiled map service, TMS, height-map, regular grid, Geovisual analytics, DTM.

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Authors: Ali K. M. Al-Nasrawi, Uday A. Al-Hamdany, Sarah M. Hamylton, Brian G. Jones, Yasir M. Alyazichi

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Surface elevation dynamics have always responded to disturbance regimes. Creating Digital Elevation Models (DEMs) to detect surface dynamics has led to the development of several methods, devices and data clouds. DEMs can provide accurate and quick results with cost efficiency, in comparison to the inherited geomatics survey techniques. Nowadays, remote sensing datasets have become a primary source to create DEMs, including LiDAR point clouds with GIS analytic tools. However, these data need to be tested for error detection and correction. This paper evaluates various DEMs from different data sources over time for Apple Orchard Island, a coastal site in southeastern Australia, in order to detect surface dynamics. Subsequently, 30 chosen locations were examined in the field to test the error of the DEMs surface detection using high resolution global positioning systems (GPSs). Results show significant surface elevation changes on Apple Orchard Island. Accretion occurred on most of the island while surface elevation loss due to erosion is limited to the northern and southern parts. Concurrently, the projected differential correction and validation method aimed to identify errors in the dataset. The resultant DEMs demonstrated a small error ratio (≤ 3%) from the gathered datasets when compared with the fieldwork survey using RTK-GPS. As modern modelling approaches need to become more effective and accurate, applying several tools to create different DEMs on a multi-temporal scale would allow easy predictions in time-cost-frames with more comprehensive coverage and greater accuracy. With a DEM technique for the eco-geomorphic context, such insights about the ecosystem dynamic detection, at such a coastal intertidal system, would be valuable to assess the accuracy of the predicted eco-geomorphic risk for the conservation management sustainability. Demonstrating this framework to evaluate the historical and current anthropogenic and environmental stressors on coastal surface elevation dynamism could be profitably applied worldwide.

Keywords: DEMs, eco-geomorphic-dynamic processes, geospatial information science. Remote sensing, surface elevation changes.

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Authors: Tanvi P. Medshinge, Prasad Vaidya, Monisha E. Royan

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In India, cooling loads in residential sector is a major contributor to its total energy consumption. Due to the increasing cooling need, the market penetration of air-conditioners is further expected to rise. Natural Ventilation (NV), however, possesses great potential to save significant energy consumption especially for residential buildings in moderate climates. As multifamily residential apartment buildings are designed by repetitive use of prototype designs, deriving individual NV based design prototype solutions for a combination of different wind incidence angles and orientations would provide significant opportunity to address the rise in cooling loads by residential sector. This paper presents the results of NV performance of a selected prototype apartment design with a cluster of four units in Pune, India, and an attempt to improve the NV performance through design modifications. The water table apparatus, a physical modelling tool, is used to study the flow patterns and simulate wind-induced NV performance. Quantification of NV performance is done by post processing images captured from video recordings in terms of percentage of area with good and poor access to ventilation. NV performance of the existing design for eight wind incidence angles showed that of the cluster of four units, the windward units showed good access to ventilation for all rooms, and the leeward units had lower access to ventilation with the bedrooms in the leeward units having the least access. The results showed improved performance in all the units for all wind incidence angles to more than 80% good access to ventilation. Some units showed an additional improvement to more than 90% good access to ventilation. This process of design and performance evaluation improved some individual units from 0% to 100% for good access to ventilation. The results demonstrate the ease of use and the power of the water table apparatus for performance-based design to simulate wind induced NV.  

Keywords: Prototype design, water table apparatus, NV, wind incidence angles, simulations, fluid dynamics.

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Authors: Hira Lal Gope, Hidekazu Fukai

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The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.

Keywords: Convolutional neural networks, coffee bean, peaberry, sorting, support vector machine.

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Authors: Mustafa M. Donma, Orkide Donma

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Metabolic syndrome (MetS) is a severe health problem caused by morbid obesity, the severest form of obesity. The components of MetS are rather stable in adults. However, the diagnosis of MetS in morbid obese (MO) children still constitutes a matter of discussion. The aim of this study was to develop a formula, which facilitated the diagnosis of MetS in MO children and was capable of discriminating MO children with and without MetS findings. The study population comprised MO children. Age and sex-dependent body mass index (BMI) percentiles of the children were above 99. Increased blood pressure, elevated fasting blood glucose (FBG), elevated triglycerides (TRG) and/or decreased high density lipoprotein cholesterol (HDL-C) in addition to central obesity were listed as MetS components for each child. Two groups were constituted. In the first group, there were 42 MO children without MetS components. Second group was composed of 44 MO children with at least two MetS components. Anthropometric measurements including weight, height, waist and hip circumferences were performed during physical examination. BMI and homeostatic model assessment of insulin resistance (HOMA-IR) values were calculated. Informed consent forms were obtained from the parents of the children. Institutional Non-Interventional Clinical Studies Ethics Committee approved the study design. Routine biochemical analyses including FBG, insulin (INS), TRG, HDL-C were performed. The performance and the clinical utility of Diagnostic Obesity Notation Model Assessment Metabolic Syndrome Index (DONMA MetS index) [(INS/FBG)/(HDL-C/TRG)*100] was tested. Appropriate statistical tests were applied to the study data. p value smaller than 0.05 was defined as significant. MetS index values were 41.6 ± 5.1 in MO group and 104.4 ± 12.8 in MetS group. Corresponding values for HDL-C values were 54.5 ± 13.2 mg/dl and 44.2 ± 11.5 mg/dl. There was a statistically significant difference between the groups (p < 0.001). Upon evaluation of the correlations between MetS index and HDL-C values, a much stronger negative correlation was found in MetS group (r = -0.515; p = 0.001) in comparison with the correlation detected in MO group (r = -0.371; p = 0.016). From these findings, it was concluded that the statistical significance degree of the difference between MO and MetS groups was highly acceptable for this recently introduced MetS index. This was due to the involvement of all of the biochemically defined MetS components into the index. This is particularly important because each of these four parameters used in the formula is a cardiac risk factor. Aside from discriminating MO children with and without MetS findings, MetS index introduced in this study is important from the cardiovascular risk point of view in MetS group of children.

Keywords: Fasting blood glucose, high density lipoprotein cholesterol, insulin, metabolic syndrome, morbid obesity, triglycerides.

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Authors: Davide D’Aria, Paolo Falcone, Luigi Maggi, Aldo Cero, Giovanni Amoroso

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The paper presents a methodology for real-time structural health monitoring and geophysical applications. The key elements of the system are a high performance MIMO RADAR sensor, an optical camera and a dedicated set of software algorithms encompassing interferometry, tomography and photogrammetry. The MIMO Radar sensor proposed in this work, provides an extremely high sensitivity to displacements making the system able to react to tiny deformations (up to tens of microns) with a time scale which spans from milliseconds to hours. The MIMO feature of the system makes the system capable of providing a set of two-dimensional images of the observed scene, each mapped on the azimuth-range directions with noticeably resolution in both the dimensions and with an outstanding repetition rate. The back-scattered energy, which is distributed in the 3D space, is projected on a 2D plane, where each pixel has as coordinates the Line-Of-Sight distance and the cross-range azimuthal angle. At the same time, the high performing processing unit allows to sense the observed scene with remarkable refresh periods (up to milliseconds), thus opening the way for combined static and dynamic structural health monitoring. Thanks to the smart TX/RX antenna array layout, the MIMO data can be processed through a tomographic approach to reconstruct the three-dimensional map of the observed scene. This 3D point cloud is then accurately mapped on a 2D digital optical image through photogrammetric techniques, allowing for easy and straightforward interpretations of the measurements. Once the three-dimensional image is reconstructed, a 'repeat-pass' interferometric approach is exploited to provide the user of the system with high frequency three-dimensional motion/vibration estimation of each point of the reconstructed image. At this stage, the methodology leverages consolidated atmospheric correction algorithms to provide reliable displacement and vibration measurements.

Keywords: Interferometry, MIMO RADAR, SAR, tomography.

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