Search results for: texture identification

Authors: Ahmad Zaini, F. Muhammad Reza Hadafi, Surya Sumpeno, Muhtadin, Mochamad Hariadi

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The lack of information about museum’s collection reduces the number of visits of museum. Museum’s revitalization is an urgent activity to increase the number of visits. The research's roadmap is building a web-based application that visualizes museum in the virtual form including museum's statue reconstruction in the form of 3D. This paper describes implementation of three-dimensional model reconstruction method based on light-strip pattern on the museum statue using 3D scanner. Noise removal, alignment, meshing and refinement model's processes is implemented to get a better 3D object reconstruction. Model’s texture derives from surface texture mapping between object's images with reconstructed 3D model. Accuracy test of dimension of the model is measured by calculating relative error of virtual model dimension compared against the original object. The result is realistic three-dimensional model textured with relative error around 4.3% to 5.8%.

Keywords: 3D reconstruction, light pattern structure, texture mapping, museum

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Authors: Go Woon Kwak, Siyoung Jun, Soyun Maeng, Haeyoung Lee

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Entry is an education platform used in South Korea, created to help students learn to program, in which they can learn to code while playing. Using the online version of the entry, teachers can easily assign programming homework to the student and the students can make programs simply by linking programming blocks. However, the programs may be made by others, so that the authors of the programs should be identified. In this paper, as the first step toward author identification of entry programs, we present an artificial neural network based classification approach to identify genders of authors of a program written in an entry. A neural network has been trained from labeled training data that we have collected. Our result in progress, although preliminary, shows that the proposed approach could be feasible to be applied to the online version of entry for gender identification of authors. As future work, we will first use a machine learning technique for age identification of entry programs, which would be the second step toward the author identification.

Keywords: artificial intelligence, author identification, deep neural network, gender identification, machine learning

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Authors: L. Kiefer, C. Richter, G. Reinhart

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The uprising complexity in production systems due to an increasing amount of variants up to customer innovated products leads to requirements that hierarchical control systems are not able to fulfil. Therefore, factory planners can install autonomous manufacturing systems. The fundamental requirement for an autonomous control is the identification of objects within production systems. In this approach an attribute-based identification is focused for avoiding dose-dependent identification costs. Instead of using an identification mark (ID) like a radio frequency identification (RFID)-Tag, an object type is directly identified by its attributes. To facilitate that it’s recommended to include the identification and the corresponding sensors within handling processes, which connect all manufacturing processes and therefore ensure a high identification rate and reduce blind spots. The presented methodology reduces the individual effort to integrate identification processes in handling systems. First, suitable object attributes and sensor systems for object identification in a production environment are defined. By categorising these sensor systems as well as handling systems, it is possible to match them universal within a compatibility matrix. Based on that compatibility further requirements like identification time are analysed, which decide whether the combination of handling and sensor system is well suited for parallel handling and identification within an autonomous control. By analysing a list of more than thousand possible attributes, first investigations have shown, that five main characteristics (weight, form, colour, amount, and position of subattributes as drillings) are sufficient for an integrable identification. This knowledge limits the variety of identification systems and leads to a manageable complexity within the selection process. Besides the procedure, several tools, as an example a sensor pool are presented. These tools include the generated specific expert knowledge and simplify the selection. The primary tool is a pool of preconfigured identification processes depending on the chosen combination of sensor and handling device. By following the defined procedure and using the created tools, even laypeople out of other scientific fields can choose an appropriate combination of handling devices and sensors which enable parallel handling and identification.

Keywords: agent systems, autonomous control, handling systems, identification

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Authors: Sebastian Oportus, Fabrizio Alvarez

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3D digitalization of heritage objects is widely used nowadays. However, the most advanced 3D scanners in the market that capture topology and texture at the same time, and are specifically made for this purpose, don’t deliver the accuracy that is needed for scientific research. In the last three years, we have developed a method that combines the use of Metrologic grade laser scans, that allows us to work with a high accuracy topology up to 15 times more precise and combine this mesh with a texture obtained from high definition photogrammetry with up to 100 times more pixel concentrations. The result is an accurate digitalization that promotes heritage preservation, scientific study, high detail reproduction, and digital restoration, among others. In Chile, we have already performed 478 digitalizations of high-value heritage pieces and compared the results with up to five different digitalization methods; the results obtained show a considerable better dimensional accuracy and texture resolution. We know the importance of high precision and resolution for academics and museology; that’s why our proposal is to set a worldwide standard using this open source methodology.

Keywords: 3D digitalization, digital heritage, heritage preservation, digital restauration, heritage reproduction

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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: Brouri Adil, Giri Fouad

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The problem of identifying Wiener-Hammerstein systems is addressed in the presence of two linear subsystems of structure totally unknown. Presently, the nonlinear element is allowed to be noninvertible. The system identification problem is dealt by developing a two-stage frequency identification method such a set of points of the nonlinearity are estimated first. Then, the frequency gains of the two linear subsystems are determined at a number of frequencies. The method involves Fourier series decomposition and only requires periodic excitation signals. All involved estimators are shown to be consistent.

Keywords: Wiener-Hammerstein systems, Fourier series expansions, frequency identification, automation science

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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: 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: Mohammad Javad Mollakazemi, Farhad Asadi, Aref Ghafouri

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In this paper, we considered and applied parametric modeling for some experimental data of dynamical system. In this study, we investigated the different distribution of output measurement from some dynamical systems. Also, with variance processing in experimental data we obtained the region of nonlinearity in experimental data and then identification of output section is applied in different situation and data distribution. Finally, the effect of the spanning the measurement such as variance to identification and limitation of this approach is explained.

Keywords: Gaussian process, nonlinearity distribution, particle filter, system identification

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Authors: E. Karacabey, Ş. G. Özçelik, M. S. Turan, C. Baltacıoğlu, E. Küçüköner

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Changes in textural properties of any food material during processing is significant for further consumer’s evaluation and directly affects their decisions. Thus any food material should be considered in terms of textural properties after any process. In the present study zucchini slices were partially predried to control and reduce the product’s final oil content. A conventional oven was used for partially dehydration of zucchini slices. Following frying was carried in an industrial fryer having temperature controller. This study was based on the effect of this predrying process on textural properties of fried zucchini slices. Texture profile analysis was performed. Hardness, elasticity, chewiness, cohesiveness were studied texture parameters of fried zucchini slices. Temperature and weight loss were monitored parameters of predrying process, whereas, in frying, oil temperature and process time were controlled. Optimization of two successive processes was done by response surface methodology being one of the common used statistical process optimization tools. Models developed for each texture parameters displayed high success to predict their values as a function of studied processes’ conditions. Process optimization was performed according to target values for each property determined for directly fried zucchini slices taking the highest score from sensory evaluation. Results indicated that textural properties of predried and then fried zucchini slices could be controlled by well-established equations. This is thought to be significant for fried stuff related food industry, where controlling of sensorial properties are crucial to lead consumer’s perception and texture related ones are leaders. This project (113R015) has been supported by TUBITAK.

Keywords: optimization, response surface methodology, texture profile analysis, conventional oven, modelling

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Authors: Carmen Silvia Gabriel, Maria de Fátima Paiva Brito, Mariane de Paula Candido, Vanessa Barato Oliveira

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Patient identification is a necessary practice to ensure patient safety in any healthcare environment, including emergency care units, test laboratories, home care and clinics. The present study aimed to provide evidence that can effectively contribute to practices concerning patient identification. Its objective was to investigate patient identification in basic healthcare units through patient safety standards. To do so, a descriptive and non-experimental research outline study was carried out to inquire how patient identification takes place in a particular situation. All technical manager nurses from the chosen healthcare facilities were included in the sample for the study. Data was collected in September of 2014 after approval from the Committee of Ethics. All researched institutions fit the same profile: they’re public facilities for general care with observation beds. None of them has a wristband identification protocol or policy. Only one institution mentioned using some kind of visual identification; namely, body tags separated by colors according to the type of care, but it still does not apply the recommended tags by the Brazilian Ministry of Health. This study allowed the authors to acknowledge how important the commitment from the whole healthcare team in the patient identification process is and also acknowledge how necessary it is to implement institutional policies that may aid the healthcare units in this area to promote a quality and safe patient care.

Keywords: patient safety, identification, nursing, emergency care units

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Authors: Ashwini Kumar, Vinod Nayak, Shankar M. Bakkannavar

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The identification of humans is important in forensic investigations not only in living but also in dead, especially in cases of mass disorders. The procedure followed in dead known as post-mortem identification is a challenging task for the forensic pathologist. However, it is mandatory in terms of the law to fulfill the social norms. Many times, due to mutilation of body parts, the normal methods of identification using skeletal remains cannot be used in the process of identification. In such cases, the intact components of the skeletal remains or bony parts play an important role in identification. In these situations, digital forensics can come to our rescue. The authors hereby made a study for determination of sex based on nasal index by using (Big Bore 16 Slice) Multidetector Computed Tomography 2D Scans. The results are represented as a poster.

Keywords: sex determination, multidetector computed tomography, nasal index, digital forensic

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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: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof

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Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.

Keywords: classification, feature extraction, fuzzy, inspection system, image analysis, macroscopic images

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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: M. Khairudin

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This paper investigates the system identification and design quantitative feedback theory (QFT) for the robust control of a lathe spindle. The dynamic of the lathe spindle is uncertain and time variation due to the deepness variation on cutting process. System identification was used to obtain the dynamics model of the lathe spindle. In this work, real time system identification is used to construct a linear model of the system from the nonlinear system. These linear models and its uncertainty bound can then be used for controller synthesis. The real time nonlinear system identification process to obtain a set of linear models of the lathe spindle that represents the operating ranges of the dynamic system. With a selected input signal, the data of output and response is acquired and nonlinear system identification is performed using Matlab to obtain a linear model of the system. Practical design steps are presented in which the QFT-based conditions are formulated to obtain a compensator and pre-filter to control the lathe spindle. The performances of the proposed controller are evaluated in terms of velocity responses of the the lathe machine spindle in corporating deepness on cutting process.

Keywords: lathe spindle, QFT, robust control, system identification

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Authors: Margarita Grushanina

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After several prominent central banks including European Central Bank (ECB), Federal Reserve System (Fed), Bank of Japan and Bank of England employed unconventional monetary policies in the aftermath of the financial crisis of 2008-2009 the problem of identification of the effects from such policies became of great interest. One of the main difficulties in identification of shocks from unconventional monetary policy measures in structural VAR analysis is that they often are anticipated, which leads to a non-fundamental MA representation of the VAR model. Moreover, the unconventional monetary policy actions may indirectly transmit to markets information about the future stance of the interest rate, which raises a question of the plausibility of the assumption of orthogonality between shocks from unconventional and conventional policy measures. This paper offers a method of identification that takes into account the abovementioned issues. The author uses factor-augmented VARs to increase the information set and identification through heteroskedasticity of error terms and rank restrictions on the errors’ second moments’ matrix to deal with the cross-correlation of the structural shocks.

Keywords: factor-augmented VARs, identification through heteroskedasticity, monetary policy, structural VARs

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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: K. Sekulová, M. Šimon

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The article demonstrates on a case study how it is possible to identify MSD risk. It is based on a dissertation risk identification model of occupational diseases formation in relation to the work activity that determines what risk can endanger workers who are exposed to the specific risk factors. It is evaluated based on statistical calculations. These risk factors are main cause of upper-extremities musculoskeletal disorders.

Keywords: case study, upper-extremity musculoskeletal disorders, ergonomics, risk identification

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Authors: Liang Zhao, Chong-quan Zhong

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In order to improve the control performance of vector inverter, an improved parameter identification solution for induction motor is proposed in this paper. Dc or AC voltage is applied to the induction motor using the SVPWM through the inverter. Then stator resistance, stator leakage inductance, rotor resistance, rotor leakage inductance and mutual inductance are obtained according to the signal response. The discrete Fourier transform (DFT) is used to deal with the noise and harmonic. The impact on parameter identification caused by delays in the inverter switch tube, tube voltage drop and dead-time is avoided by effective compensation measures. Finally, the parameter identification experiment is conducted based on the vector inverter which using TMS320F2808 DSP as the core processor and results show that the strategy is verified.

Keywords: vector inverter, parameter identification, SVPWM; DFT, dead-time compensation

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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

Abstract:

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

Procedia PDF Downloads 188

Authors: Asadullah I. Qazi, Mansoor Ahsan, Zahir Ashraf, Uzair Ahmad

Abstract:

System identification of an Unmanned Aerial Vehicle (UAV), to acquire its mathematical model, is a significant step in the process of aircraft flight automation. The need for reliable mathematical model is an established requirement for autopilot design, flight simulator development, aircraft performance appraisal, analysis of aircraft modifications, preflight testing of prototype aircraft and investigation of fatigue life and stress distribution etc.  This research is aimed at system identification of a fixed wing UAV by means of specifically designed flight experiment. The purposely designed flight maneuvers were performed on the UAV and aircraft states were recorded during these flights. Acquired data were preprocessed for noise filtering and bias removal followed by parameter estimation of longitudinal dynamics transfer functions using MATLAB system identification toolbox. Black box identification based transfer function models, in response to elevator and throttle inputs, were estimated using least square error   technique. The identification results show a high confidence level and goodness of fit between the estimated model and actual aircraft response.

Keywords: fixed wing UAV, system identification, black box modeling, longitudinal dynamics, least square error

Procedia PDF Downloads 292