Search results for: statistical texture

Authors: Neha Bhardwaj

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In this paper, we consider positive linear operators and study the Voronovskaya type result of the operator then obtain an error estimate in terms of the higher order modulus of continuity of the function being approximated and its A-statistical convergence. Also, we compute the corresponding rate of A-statistical convergence for the linear positive operators.

Keywords: Poisson distribution, Voronovskaya, modulus of continuity, a-statistical convergence

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Authors: Yuko Matayoshi, Takashi Sakai, Yin-Gjum Jin, Jun-ichi Koyama

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To elucidate the material characteristics of single crystals of pure aluminum and copper, the respective relations between crystallographic orientations and micro structures were examined, along with bending and mechanical properties. The texture distribution was also analysed. Bending tests were performed in a SEM apparatus while its behaviors were observed. Some analytical results related to crystal direction maps, inverse pole figures, and textures were obtained from electron back scatter diffraction (EBSD) analyses.

Keywords: pure aluminum, pure copper, single crystal, bending, SEM-EBSD analysis, texture, microstructure

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Authors: Mohamed Alimoussa, Alice Porebski, Nicolas Vandenbroucke, Rachid Oulad Haj Thami, Sana El Fkihi

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Color and texture are highly discriminant visual cues that provide an essential information in many types of images. Color texture representation and classification is therefore one of the most challenging problems in computer vision and image processing applications. Color textures can be represented in different color spaces by using multiple image descriptors which generate a high dimensional set of texture features. In order to reduce the dimensionality of the feature set, feature selection techniques can be used. The goal of feature selection is to find a relevant subset from an original feature space that can improve the accuracy and efficiency of a classification algorithm. Traditionally, feature selection is focused on removing irrelevant features, neglecting the possible redundancy between relevant ones. This is why some feature selection approaches prefer to use feature clustering analysis to aid and guide the search. These techniques can be divided into two categories. i) Feature clustering-based ranking algorithm uses feature clustering as an analysis that comes before feature ranking. Indeed, after dividing the feature set into groups, these approaches perform a feature ranking in order to select the most discriminant feature of each group. ii) Feature clustering-based subset search algorithms can use feature clustering following one of three strategies; as an initial step that comes before the search, binded and combined with the search or as the search alternative and replacement. In this paper, we propose a new feature clustering-based sequential selection approach for the purpose of color texture representation and classification. Our approach is a three step algorithm. First, irrelevant features are removed from the feature set thanks to a class-correlation measure. Then, introducing a new automatic feature clustering algorithm, the feature set is divided into several feature clusters. Finally, a sequential search algorithm, based on a filter model and a separability measure, builds a relevant and non redundant feature subset: at each step, a feature is selected and features of the same cluster are removed and thus not considered thereafter. This allows to significantly speed up the selection process since large number of redundant features are eliminated at each step. The proposed algorithm uses the clustering algorithm binded and combined with the search. Experiments using a combination of two well known texture descriptors, namely Haralick features extracted from Reduced Size Chromatic Co-occurence Matrices (RSCCMs) and features extracted from Local Binary patterns (LBP) image histograms, on five color texture data sets, Outex, NewBarktex, Parquet, Stex and USPtex demonstrate the efficiency of our method compared to seven of the state of the art methods in terms of accuracy and computation time.

Keywords: feature selection, color texture classification, feature clustering, color LBP, chromatic cooccurrence matrix

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Authors: Lukanda Kalobo

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In South Africa, the High School Mathematics Curriculum provides teachers with specific aims and skills to be developed which involves the understanding about the measures of central tendency. The exploration begins with the definitions of statistical literacy, measurement of central tendency and a discussion on why statistical literacy is essential today. It furthermore discusses the statistical literacy basics involved in understanding the concepts of measures of central tendency. The statistical literacy test on the measures of central tendency, was used to collect data which was administered to 78 first year students direct from high schools. The results indicated that students seemed to have forgotten about the statistical literacy in understanding the concepts of measure of central tendency after completing their high school study. The authors present inferences regarding the alignment between statistical literacy and the understanding of the concepts about the measures of central tendency, leading to the conclusion that there is a need to provide in-service and pre-service training.

Keywords: conceptual understanding, mean, median, mode, statistical literacy

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Authors: Saroj Bijarnia, Preety Singh

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We propose a simple and effective biometrics system based on face verification across aging using a new variant of texture feature, Pyramid Binary Pattern. This employs Local Binary Pattern along with its hierarchical information. Dimension reduction of generated texture feature vector is done using Principal Component Analysis. Support Vector Machine is used for classification. Our proposed method achieves an accuracy of 92:24% and can be used in an automated age-invariant face verification system.

Keywords: biometrics, age invariant, verification, support vector machine

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Authors: Esra Yaldız, Dicle Aydın

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Sustainability is a term that provides deciding about the future considering environment and investigates the harmony and balance between protection and usage of the resource. The main objective of sustainability is creating residential areas is nature compatible or providing continuance thereby adapting existing residential area to nature. In this context, historical and traditional areas must have utilized according to sustainability. Traditional housing texture are identified as a traditional architectural product has been designed based on this term. General characteristics of traditional housing within the context of sustainable architecture are their specific dynamics and components and their harmonisation of environment and nature. Owing to the fact that traditional housing texture harmonizes natural conditions of the region, topography, climate and their context, construction materials are provided from environment and traditional techniques and their forms are used and due to construction materials has natural insulation traditional housing create healthy and comfortable living environment, traditional housing is rather significant in terms of sustainable architecture. The basis of this study comprise the routers in traditional housing design in accordance with the principles of sustainability. These are, accommodating topography, climate, and geography, accessibility, structuring at the scale of human, utilization of green zones, unique to the region used construction materials, the form of construction, building envelope and space organization of dwelling. In this context, the purpose of this study is that vernacular architecture approaches of traditional housing textures which are in Central Anatolia Region Located in Anatolia are utilized with regard to sustainability.

Keywords: Anatolia, sustainability, traditional housing texture, vernacular architecture

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Authors: S. Sushma, S. Balasubramanian, K. C. Latha, R. Sridhar

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Structural texture measures are used to address the aspect of breast cancer risk assessment in screening mammograms. The current study investigates whether texture properties characterized by local Fractal Dimension (FD) and lacunarity contribute to assess breast cancer risk. Fractal Dimension represents the complexity while the lacunarity characterize the gap of a fractal dimension. In this paper, we present our result confirming that the lacunarity value resulted in algorithm using mammogram images states that level of lacunarity will be low when the Fractal Dimension value will be high.

Keywords: breast cancer, fractal dimension, image analysis, lacunarity, mammogram

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Authors: Roopchand Tandon, Zaheer Khan Yusufzai, R. Manna, R. K. Mandal

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Present work describes microstructures, mechanical properties, and texture characteristics of the friction stir processed AA7075T7352 aluminum alloy. Phases were analyzed with the help of x-ray diffractometre (XRD), transmission electron microscope (TEM) along with the differential scanning calorimeter (DSC). Depth-wise microstructures and dislocation characteristics from the nugget-zone of the friction stir processed specimens were studied using the bright field (BF) and weak beam dark-field (WBDF) TEM micrographs, and variation in the microstructures as well as dislocation characteristics were the noteworthy features found. XRD analysis display changes in the chemistry as well as size of the phases in the nugget and heat affected zones (Nugget and HAZ). Whereas the base metal (BM) microstructures remain un-affected. High density dislocations were noticed in the nugget regions of the processed specimen, along with the formation of dislocation contours and tangles. .The ɳ’ and ɳ phases, along with the GP-Zones were completely dissolved and trapped by the dislocations. Such an observations got corroborated to the improved mechanical as well as stress corrosion cracking (SCC) performances. Bulk texture and residual stress measurements were done by the Panalytical Empyrean MRD system with Co- kα radiation. Nugget zone (NZ) display compressive residual stress as compared to thermo-mechanically(TM) and heat affected zones (HAZ). Typical f.c.c. deformation texture components (e.g. Copper, Brass, and Goss) were seen. Such a phenomenon is attributed to the enhanced hardening as well as other mechanical performance of the alloy. Mechanical characterizations were done using the tensile test and Anton Paar Instrumented Micro Hardness tester. Enhancement in the yield strength value is reported from the 89MPa to the 170MPa; on the other hand, highest hardness value was reported in the nugget-zone of the processed specimens.

Keywords: aluminum alloy, mechanical characterization, texture characterstics, friction stir processing

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Authors: M. Veeresham

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The microstructure, texture, phase stability, and tensile properties of annealed Ta_0.5Nb_0.5Hf_0.5ZrTi_1.5 alloy have been investigated in the present research. The alloy was severely hybrid-rolled up to 93.5% thickness reduction, subsequently rolled samples subjected to an annealing treatment at 800 °C and 1000 °C temperatures for 1 h. Consequently, the rolled condition and both annealed temperatures have a body-centered cubic (BCC) structure. Furthermore, quantitative texture measurements (orientation distribution function (ODF) analysis) and microstructural examinations (analytical electron backscatter diffraction (EBSD) maps) permitted to establish a good relationship between annealing texture and microstructure and universal testing machine (UTM) utilized for obtaining the mechanical properties. Impressive room temperature tensile properties combination with the tensile strength (1380 MPa) and (24.7%) elongation is achieved for the 800 °C heat-treated condition. The evolution of the coarse microstructure featured in the case of 1000 °C annealed temperature ascribed to the influence of high thermal energy.

Keywords: refractory high entropy alloys, hybrid-rolling, recrystallization, microstructure, tensile properties

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Authors: Tahra Elobeid, Emmerich Berghofer

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The aim of this study is to find innovative approaches for the production of iron rich foods using natural iron sources. The vehicle used for fortification was sorghum whereas the iron fortificant was white bean. Fortified sorghum cookies were produced from five different mixtures; iron content, iron bioavailability, cookie texture and acceptability were measured. Cookies were prepared from the three fortified flours; 90% sorghum + 10% white bean (S9WB1), 75% sorghum + 25% white bean (S3WB1), 50% sorghum + 50% white bean (S1WB1) and 100% sorghum and 100% white bean. The functional properties gave good results in all the formulations. Statistical analysis of the iron content in the five different cookies showed that there was significant difference at the 95% confidence level (ANOVA). The iron content in all the recipes including the 100% sorghum improved, the increase ranging from 112% in 100% sorghum cookies to 476% in 100% white bean cookies. This shows that the increase in the amount of white bean used for fortification leads to the improvement of the iron content of cookies. The bioavailability of iron ranged from 21.3% in 100% sorghum to 28.6% in 100% white bean cookies. In the 100% sorghum cookies the iron bioavailability increased with reference to raw sorghum due to the addition of eggs. Bioavailability of iron in raw sorghum is 16.2%, therefore the percentage increase ranged from 5.1% to 28.6%. The cookies prepared from 10% white bean (S9WB1) scored the lowest 3.7 in terms of acceptability. They were the least preferred due to their somewhat soft texture. The 30% white bean cookies (S3WB1) gave results comparable to the 50% (S1WB1) and 100% white bean cookies. Cookies prepared with high percentage of white bean (50% and 100% white bean) gave the best results. Therefore cookie formulations from sorghum and white bean are successful in improving the iron status of anaemic individuals.

Keywords: sorghum, white bean, iron content, bioavailable iron, cookies

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Authors: Insaf Bellamine, Hamid Tairi

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Detecting moving objects in sequences is an essential step for video analysis. This paper mainly contributes to the Color Space-Time Interest Points (CSTIP) extraction and detection. We propose a new method for detection of moving objects. Two main steps compose the proposed method. First, we suggest to apply the algorithm of the detection of Color Space-Time Interest Points (CSTIP) on both components of the Color Structure-Texture Image Decomposition which is based on a Partial Differential Equation (PDE): a color geometric structure component and a color texture component. A descriptor is associated to each of these points. In a second stage, we address the problem of grouping the points (CSTIP) into clusters. Experiments and comparison to other motion detection methods on challenging sequences show the performance of the proposed method and its utility for video analysis. Experimental results are obtained from very different types of videos, namely sport videos and animation movies.

Keywords: Color Space-Time Interest Points (CSTIP), Color Structure-Texture Image Decomposition, Motion Detection, clustering

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Authors: L. S. Godlevsky, N. V. Kresyun, V. P. Martsenyuk, K. S. Shakun, T. V. Tatarchuk, K. O. Prybolovets, L. F. Kalinichenko, M. Karpinski, T. Gancarczyk

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Structures of eye bottom were extracted using multiscale texture gradient method and color characteristics of macular zone and vessels were verified in CIELAB scale. The difference of average values of L*, a* and b* coordinates of CIE (International Commision of Illumination) scale in patients with diabetes and healthy volunteers was compared. The average value of L* in diabetic patients exceeded such one in the group of practically healthy persons by 2.71 times (P < 0.05), while the value of a* index was reduced by 3.8 times when compared with control one (P < 0.05). b* index exceeded such one in the control group by 12.4 times (P < 0.05). The integrated index on color difference (ΔE) exceeded control value by 2.87 times (P < 0.05). More pronounced differences with ΔE were followed by a shorter period of MA appearance with a correlation level at -0.56 (P < 0.05). The specificity of diagnostics raised by 2.17 times (P < 0.05) and negative prognostic index exceeded such one determined with the expert method by 2.26 times (P < 0.05).

Keywords: diabetic retinopathy, multiscale texture gradient, color spectrum analysis, medical diagnostics

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Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza

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The aim of the present work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. Based on feature selection in different phases, in this research, we design a neural network system that has optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each ROI, 6 distinct set of texture features are extracted such as first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. We show that with the injection of liquid and the analysis of more phases the high relevant features in each region changed. Our results show that for detecting HCC tumor phase3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between these two classes according to our method, relates to first order histogram parameters with the accuracy of 85% in phase 1, 95% phase 2, and 95% in phase 3.

Keywords: multi-phasic liver images, texture analysis, neural network, hidden layer

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Authors: Abbas S. Alwan, Waleed K. Hussan

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In this paper, a general verification of possible heat treatment of steel has been done with the view of conditions of real abrasive wear of rotivater with soil texture. This technique is found promising to improve the quality of agriculture components working with the soil in dry condition. Abrasive wear resistance is very important in many applications and in most cases it is directly correlated with the hardness of materials surface. Responded of heat treatments were carried out in various media (Still air, Cottonseed oil, and Brine water 10 %) and follow by low-temperature tempering (250°C) was applied on steel type (AISI 1030). After heat treatment was applied wear with soil texture by using tillage process to determine the (actual wear rate) of the specimens depending on weight loss method. It was found; the wear resistance Increases with increase hardness with varying quenching media as follows; 30 HRC, 45 HRC, 52 HRC, and 60 HRC for nontreated (as received) cooling media as still air, cottonseed oil, and Brine water 10 %, respectively. Martensitic structure with retained austenite can be obtained depending on the quenching medium. Wear was presented on the worn surfaces of the steels which were used in this work.

Keywords: microstructures, hardness, abrasive wear, heat treatment, soil texture

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Authors: Sidra Naeem, Ayesha Naeem, Sahar Rahim, Nadia Nawaz Qadri

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Citrus greening is a bacterial disease that causes considerable damage to citrus fruits worldwide. Efficient method for this disease detection must be carried out to minimize the production loss. This paper presents a pattern recognition system that comprises three stages for the detection of citrus greening from Orange leaves: segmentation, feature extraction and classification. Image segmentation is accomplished by adaptive thresholding. The feature extraction stage comprises of three visual descriptors i.e. shape, color and texture. From shape feature we have used asymmetry index, from color feature we have used histogram of Cb component from YCbCr domain and from texture feature we have used local binary pattern. Classification was done using support vector machines and k nearest neighbors. The best performances of the system is Accuracy = 88.02% and AUROC = 90.1% was achieved by automatic segmented images. Our experiments validate that: (1). Segmentation is an imperative preprocessing step for computer assisted diagnosis of citrus greening, and (2). The combination of shape, color and texture features form a complementary set towards the identification of citrus greening disease.

Keywords: citrus greening, pattern recognition, feature extraction, classification

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Authors: Liliana Zura-Brravo, Antonio Vega-Galvez, Roberto Lemus-Mondaca, Jessica Lopez

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Murta (Ugni molinae T.) is an endemic fruit of Southern Chile, possesses qualities exceptional as its high antioxidants content, that make it increasingly more appreciated for marketing. Dehydration has the potential providing safe food products through the decreased activity water while maintaining their functional properties. The objective of this study was to evaluate the effect of different drying methods on the antioxidant capacity (AC), total flavonoid content (TFC), rehydration indexes and texture the dried murta berry. Five drying technologies were used: convective drying, vacuum drying, sun-air drying, infrared drying and freezing-drying. The antioxidant capacity was measured by the ORAC method, CFT was determined by spectrophotometry, rehydration capacity (CR) and water retention (WHC) by gravimetry, texture profile (TPA) by a texture analyzer TA-XT2 and microstructure by SEM. The results showed that the lyophilized murta had smaller losses AC and TFC with values of 2886.27 routine mg rutin/ 100 g dm and 23359.99 μmol ET/100 g dm, respectively. According to the rehydration indexes, these were affected by the drying methods, where the maximum value of WHC was 92.60 g retained water/100 g sample for the vacuum drying, and the lowest value of CR was 1.43 g water absorbed/g dm for the sun-air drying. Furthermore, the microstructure and TPA showed that lyophilized samples had characteristics similar to the fresh sample. Therefore, it is possible to mention that lyophilization achieved greater extent preserving the characteristics of the murta samples, showing that this method can be used in the food industry and encourage the consumption of dried fruit and thus give it greater added value.

Keywords: antioxidant, drying method, flavonoid, murta berry, texture

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Authors: Supatchalee Sirichokworrakit, Pannin Intasen, Chansuda Angkawut

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Hom Nin rice (Oryza Sativa L.) was processed into flour and used to substitute wheat flour in donuts. The donuts were prepared with 0, 20, 40, 60, and 80% Hom Nin rice flour (HNF). The donuts were subjected to proximate, texture, color and sensory evaluations. The results of the study revealed that the ash, moisture, crude fiber contents increased while crude fat and protein contents decreased as the level of HNF increased. The hardness and chewiness of donut increased as the HNF increased but the cohesiveness, springiness, and specific volume decreased. Color of donut (L*, a*, and b* values) decreased with the addition of HNF. Overall acceptability for the 20-40% HNF additions did not differ significantly from the score of the 100% wheat flour.

Keywords: Hom Nin rice, donut, texture evaluation, sensory evaluation

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Authors: M. Hanif Irsyada, Rifaldy, Arif Lutfi Namury, Syahreza S. Angkasa, Khalid Rizky, Ricky Aryanto, M. Alfiyan Bagus, Excobar Arman, Fahri Septianto, Firman Najib Wibisana

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Galunggung Mountain is an active volcano in Indonesia, precisely on the island of Java. This area is included in the Sunda Sunda arc formed by the tendency of the Australian oceanic plate to Eurasian continental plate. This research was conducted to determine the characteristics and document the mineralogical composition of the Galunggung eruption of the second phase 1982-1983. In fragment samples, petrographic analysis is carried out under a qualitative and quantitative polarizing microscope. This sample was obtained from the second phase eruption in the Cibanjanj formation. Based on the analysis results obtained filter texture characteristics, olivine parallel growth, lamellar structure, glass inclusion, plagioclase zonation and obtained special texture in the gabbroic cummulate. The mineral composition consists of phenocryst plagioclase (41vol%), pyroxene (26vol%), olivin (4vol%) and mineral opaque (29vol%). Microlite minerals consist of plagioclase (31.95vol%), pyroxene (12.09vol%), opaque minerals (55.96vol%). This research is expected to be developed by further researchers to be able to explain in more detail related to Galunggung mountain with 3 phases of eruption that are so intense. Also, it is expected to explain the structural characteristics and mineralogical composition that can be used to determine the origin of all the results of the Galunggung eruption 1982-1983.

Keywords: Galunggung eruption, mineralogical composition, texture characterization, gabbroic cumulate

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Authors: Anne C. Richer-De-Forges, Dominique Arrouays, Songchao Chen, Mercedes Roman Dobarco

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Most of the digital soil mapping (DSM) products rely on machine learning (ML) prediction models and/or the use or pedotransfer functions (PTF) in which calibration data come from soil analyses performed in labs. However, many other observations (often qualitative, nominal, or ordinal) could be used as proxies of lab measurements or as input data for ML of PTF predictions. DSM and ML are briefly described with some examples taken from the literature. Then, we explore the potential of an ordinal qualitative variable, i.e., the hand-feel soil texture (HFST) estimating the mineral particle distribution (PSD): % of clay (0-2µm), silt (2-50µm) and sand (50-2000µm) in 15 classes. The PSD can also be measured by lab measurements (LAST) to determine the exact proportion of these particle-sizes. However, due to cost constraints, HFST are much more numerous and spatially dense than LAST. Soil texture (ST) is a very important soil parameter to map as it is controlling many of the soil properties and functions. Therefore, comes an essential question: is it possible to use HFST as a proxy of LAST for calibration and/or validation of DSM predictions of ST? To answer this question, the first step is to compare HFST with LAST on a representative set where both information are available. This comparison was made on ca 17,400 samples representative of a French region (34,000 km2). The accuracy of HFST was assessed, and each HFST class was characterized by a probability distribution function (PDF) of its LAST values. This enables to randomly replace HFST observations by LAST values while respecting the PDF previously calculated and results in a very large increase of observations available for the calibration or validation of PTF and ML predictions. Some preliminary results are shown. First, the comparison between HFST classes and LAST analyses showed that accuracies could be considered very good when compared to other studies. The causes of some inconsistencies were explored and most of them were well explained by other soil characteristics. Then we show some examples applying these relationships and the increase of data to several issues related to DSM. The first issue is: do the PDF functions that were established enable to use HSFT class observations to improve the LAST soil texture prediction? For this objective, we replaced all HFST for topsoil by values from the PDF 100 time replicates). Results were promising for the PTF we tested (a PTF predicting soil water holding capacity). For the question related to the ML prediction of LAST soil texture on the region, we did the same kind of replacement, but we implemented a 10-fold cross-validation using points where we had LAST values. We obtained only preliminary results but they were rather promising. Then we show another example illustrating the potential of using HFST as validation data. As in numerous countries, the HFST observations are very numerous; these promising results pave the way to an important improvement of DSM products in all the countries of the world.

Keywords: digital soil mapping, improvement of digital soil mapping predictions, potential of using hand-feel soil texture, soil texture prediction

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Authors: Nazim Uddin, Yohiko Nakaura, Kazutaka Yamamoto

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Compote (fruit in syrup) of pineapple (Ananas comosus L. Merrill) is expected to have a high market potential as one of convenient ready-to-eat (RTE) foods worldwide. High hydrostatic pressure (HHP) in combination with low temperature (LT) was applied to the processing of pineapple compote as well as medium HHP (MHHP) in combination with medium-high temperature (MHT) since both processes can enhance liquid impregnation and inactivate microbes. MHHP+MHT (55 or 65 °C) process, as well as the HHP+LT process, has successfully inactivated the microbes in the compote to a non-detectable level. Although the compotes processed by MHHP+MHT or HHP+LT have lost the fresh texture as in a similar manner as those processed solely by heat, it was indicated that the texture degradations by heat were suppressed under MHHP. Degassing process reduced the hardness, while calcium (Ca) contributed to be retained hardness in MHT and MHHP+MHT processes. Electrical impedance measurement supported the damage due to degassing and heat. The color, Brix, and appearance were not affected by the processing methods significantly. MHHP+MHT and HHP+LT processes may be applicable to produce high-quality, safe RTE pineapple compotes. Further studies on the optimization of packaging and storage condition will be indispensable for commercialization.

Keywords: compote of pineapple, RTE, medium high hydrostatic pressure, postharvest loss, texture

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Authors: Dalia Feiziene, Virginijus Feiza, Agne Putramentaite, Jonas Volungevicius, Kristina Amaleviciute, Sarunas Antanaitis

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The investigations on soil conservation are one of the most important topics in modern agronomy. Soil management practices have great influence on soil physico-chemical quality and GHG emission. Research objective: To reveal the sensitivity and vitality of soils with different texture to long-term antropogenisation on Cambisol in Central Lithuania and to compare them with not antropogenised soil resources. Methods: Two long-term field experiments (loam on loam; sandy loam on loam) with different management intensity were estimated. Disturbed and undisturbed soil samples were collected from 5-10, 15-20 and 30-35 cm depths. Soil available P and K contents were determined by ammonium lactate extraction, total N by the dry combustion method, SOC content by Tyurin titrimetric (classical) method, texture by pipette method. In undisturbed core samples soil pore volume distribution, plant available water (PAW) content were determined. A closed chamber method was applied to quantify soil respiration (SR). Results: Long-term resources management changed soil quality. In soil with loam texture, within 0-10, 10-20 and 30-35 cm soil layers, significantly higher PAW, SOC and mesoporosity (MsP) were under no-tillage (NT) than under conventional tillage (CT). However, total porosity (TP) under NT was significantly higher only in 0-10 cm layer. MsP acted as dominant factor for N, P and K accumulation in adequate layers. P content in all soil layers was higher under NT than in CT. N and K contents were significantly higher than under CT only in 0-10 cm layer. In soil with sandy loam texture, significant increase in SOC, PAW, MsP, N, P and K under NT was only in 0-10 cm layer. TP under NT was significantly lower in all layers. PAW acted as strong dominant factor for N, P, K accumulation. The higher PAW the higher NPK contents were determined. NT did not secure chemical quality within deeper layers than CT. Long-term application of mineral fertilisers significantly increased SOC and soil NPK contents primarily in top-soil. Enlarged fertilization determined the significantly higher leaching of nutrients to deeper soil layers (CT) and increased hazards of top-soil pollution. Straw returning significantly increased SOC and NPK accumulation in top-soil. The SR on sandy loam was significantly higher than on loam. At dry weather conditions, on loam SR was higher in NT than in CT, on sandy loam SR was higher in CT than in NT. NPK fertilizers promoted significantly higher SR in both dry and wet year, but suppressed SR on sandy loam during usual year. Not antropogenised soil had similar SOC and NPK distribution within 0-35 cm layer and depended on genesis of soil profile horizons.

Keywords: fertilizers, long-term experiments, soil texture, soil tillage, straw

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Authors: A. Nguyen, K. Nguyen, J. Jackson, E. Manlapig

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With the recent advancement in core imaging systems, a large volume of high resolution drill core images can now be collected rapidly. This paper presents a method for rapid prediction of ore-specific breakage parameters from high resolution mineral classified core images. The aim is to allow for a rapid assessment of the variability in ore hardness within a mineral deposit with reduced amount of physical breakage tests. This method sees its application primarily in project evaluation phase, where proper evaluation of the variability in ore hardness of the orebody normally requires prolong and costly metallurgical test work program. Applying this image-based texture analysis method on mineral classified core images, the ores are classified according to their textural characteristics. A small number of physical tests are performed to produce a dataset used for developing the relationship between texture classes and measured ore hardness. The paper also presents a case study in which this method has been applied on core samples from a copper porphyry deposit to predict the ore-specific breakage A*b parameter, obtained from JKRBT tests.

Keywords: geometallurgy, hyperspectral drill core imaging, process simulation, texture analysis

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Authors: Leila Ben Haj Said, Sihem Bellagha, Karim Allaf

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The present study deals with the dehydrofreezing assisted by instant controlled pressure drop (DIC) treatment of apple fruits. Samples previously dehydrated until different water contents (200, 100, and 30% dry basis (db)) and DIC treated were frozen at two different freezing velocities (V+ and V-), depending on the thermal resistance established between the freezing airflow and the sample surface. The effects of sample water content (W) and freezing velocity (V) on freezing curves and characteristics, exudate water (EW) and texture variation were examined. Lower sample water content implied higher freezing rates, lower initial freezing points (IFP), lower practical freezing time (PFT), and lower specific freezing time (SFT). EW (expressed in g exudate water/100 g water in the product) of 200% and 100% db apple samples was approximately 3%, at low freezing velocity (V-). Whereas, it was lower than 0.5% for apple samples with 30% db water content. Moreover, the impact of freezing velocity on EW was significant and very important only for high water content samples. For samples whose water content was lower than 100% db, firmness (maximum puncture force) was as higher as the water content was lower, without any insignificant impact of freezing velocity.

Keywords: dehydrofreezing, instant controlled pressure drop DIC, freezing time, texture

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Authors: Vladimir S. Timofeev

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In this article the problem of distributional moments estimation is considered. The new approach of moments estimation based on usage of the characteristic function is proposed. By statistical simulation technique, author shows that new approach has some robust properties. For calculation of the derivatives of characteristic function there is used numerical differentiation. Obtained results confirmed that author’s idea has a certain working efficiency and it can be recommended for any statistical applications.

Keywords: characteristic function, distributional moments, robustness, outlier, statistical estimation problem, statistical simulation

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Authors: Wipharat Saimo, Benjawan Thumthanaruk, Panida Banjongsinsiri, Nowwapan Noojuy

Abstract:

Thai northern style sausage (sai-ou) is originally cuisine made of chili paste, pork, and lard. It always serves with curry paste, vegetable, and rice. The meat and lard ingredients used can be substituted by Shiitake mushroom (Lentinus edodes) and King oyster (Pleurotus eryngii) mushroom (50:50 w/w) which is suitable for all people, especially vegetarians. However, the texture of mushroom type sai-ou had no homogenous texture due to no adhesiveness property of mushroom. Therefore, this research aimed to study the ratio of hydrocolloids (konjac flour (0-100%), konjac gel (0-100%) and Citri-fi®100 FG (0-2%)) on the physicochemical properties mushroom type sai-ou. The mixture design was applied by using Minitab 16 software. Nine formula were designed for the test. The values of moisture content and water activity of nine formula were ranged from 66.25-72.17% and 0.96-0.97. The pH values were 5.44-5.89. The optimal ratio of konjac flour, konjac gel and Citri-fi®100 FG (74.75:24.75:0.5 (w/w)) yielded the highest texture profiles (hardness, springiness, cohesiveness, gumminess and chewiness) as well as color parameters (L*, a* and b*). Sensory results showed had higher acceptability scores in term of overall liking with the level of ‘like moderately’ (5.9 on 7 pointed scale). The mushroom type sai-ou sausage could be an alternative food for health-conscious consumers.

Keywords: Citri-fi® 100 FG, konjac flour, konjac gel, Thai northern style sausages

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Authors: Iman A. Saad, Loay E. George

Abstract:

Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.

Keywords: iris recognition, contrast stretching, gradient features, texture features, Euclidean metric

Procedia PDF Downloads 333

Authors: Petar Sarajcev, Josip Vasilj, Damir Jakus

Abstract:

This paper presents a novel statistical description of the counterpoise effective length due to lightning surges, where the (impulse) effective length had been obtained by means of regressive formulas applied to the transient simulation results. The effective length is described in terms of a statistical distribution function, from which median, mean, variance, and other parameters of interest could be readily obtained. The influence of lightning current amplitude, lightning front duration, and soil resistivity on the effective length has been accounted for, assuming statistical nature of these parameters. A method for determining the optimal counterpoise length, in terms of the statistical impulse effective length, is also presented. It is based on estimating the number of dangerous events associated with lightning strikes. Proposed statistical description and the associated method provide valuable information which could aid the design engineer in optimising physical lengths of counterpoises in different grounding arrangements and soil resistivity situations.

Keywords: counterpoise, grounding conductor, effective length, lightning, Monte Carlo method, statistical distribution

Procedia PDF Downloads 425

Authors: C. C. Okafor

Abstract:

The effect of different varieties of plantain (Horn, false horn and French) and fibre types (soy bean residue, cassava sievette and rice bran) on functional and organoleptic properties of plantain-based flour was assessed. Horn, false horn french were processed by washing, peeling with knife, slicing into 3mm thickness and steam blanched at 80℃ for 5minutes, oven dried at 65℃ for 48 hours and milled into flours with attrition mill, sieved with 60 mesh sieve, separately. Fibre sources were processed, milled and fractionated into 60, 40 & 20 mesh sizes. Both flours were blended as 80:20, 70:30 and 60:40. Results obtained indicated that water absorption capacity is highest (2.68) in French plantain variety irrespective of the fibre type used. And in all variety tested the swelling capacity is highest (2.93) when the plantain flour is blended with soy residue (SR) and lowest (1.25) when blended with rice brain (RB). The results show that there is significant variety and fibre type interaction effect at (P < : 0.05). Again the results showed that texture mold ability and overall acceptability were best (7.00) when soy residue was used where as addition of rice bran into plantain flour resulted in fufu with poor texture. This trend was observed in all the verities of plantain tested and in all of the particle size of flour. Using cassava serviette also yield fufu similar to that produced with soy residue in all the parameter tested (mold ability, texture and overall acceptability. Generally, plantain flours from french and false horn yielded better quality fufu in terms of texture mold ability, overall acceptability, irrespective of the fibre type used.

Keywords: functional, organoleptic, particle size, sieve mesh, variety

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Authors: Annalakshmi G., Sakthivel Murugan S.

Abstract:

This paper presents a local directional encoded derivative binary pattern (LDEDBP) feature extraction method that can be applied for the classification of submarine coral reef images. The classification of coral reef images using texture features is difficult due to the dissimilarities in class samples. In coral reef image classification, texture features are extracted using the proposed method called local directional encoded derivative binary pattern (LDEDBP). The proposed approach extracts the complete structural arrangement of the local region using local binary batten (LBP) and also extracts the edge information using local directional pattern (LDP) from the edge response available in a particular region, thereby achieving extra discriminative feature value. Typically the LDP extracts the edge details in all eight directions. The process of integrating edge responses along with the local binary pattern achieves a more robust texture descriptor than the other descriptors used in texture feature extraction methods. Finally, the proposed technique is applied to an extreme learning machine (ELM) method with a meta-heuristic algorithm known as weighted distance grey wolf optimizer (GWO) to optimize the input weight and biases of single-hidden-layer feed-forward neural networks (SLFN). In the empirical results, ELM-WDGWO demonstrated their better performance in terms of accuracy on all coral datasets, namely RSMAS, EILAT, EILAT2, and MLC, compared with other state-of-the-art algorithms. The proposed method achieves the highest overall classification accuracy of 94% compared to the other state of art methods.

Keywords: feature extraction, local directional pattern, ELM classifier, GWO optimization

Procedia PDF Downloads 163

Authors: A. Özyer, N. G. Turan, Y. Ardalı

Abstract:

The environmental fate of organic contaminants in soils is influenced significantly by the pH, texture of soil, water content and also presence of organic matter. In this study, biodegradation of endosulfan isomers was studied in two different soils (Soil A and Soil B) that have contrasting properties in terms of their texture, pH, organic content, etc. Two Nocardia sp., which were isolated from soil, were used for degradation of endosulfan. Soils were contaminated with commercial endosulfan. Six sets were maintained from two different soils, contaminated with different endosulfan concentrations for degradation experiments. Inoculated and uninoculated mineral media with Nocardia isolates were added to the soils and mixed. Soils were incubated at a certain temperature (30 °C) during ten weeks. Residue endosulfan and its metabolites’ concentrations were determined weekly during the incubation period. The changes of the soil microorganisms were investigated weekly.

Keywords: endosulfan, biodegradation, Nocardia sp. soil, organochlorine pesticide

Procedia PDF Downloads 380