Search results for: eigenvalues of matrices

Authors: Lily Ingsrisawang, Tasanee Nacharoen

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Introduction: The problems of unbalanced data sets generally appear in real world applications. Due to unequal class distribution, many research papers found that the performance of existing classifier tends to be biased towards the majority class. The k -nearest neighbors’ nonparametric discriminant analysis is one method that was proposed for classifying unbalanced classes with good performance. Hence, the methods of discriminant analysis are of interest to us in investigating misclassification error rates for class-imbalanced data of three diabetes risk groups. Objective: The purpose of this study was to compare the classification performance between parametric discriminant analysis and nonparametric discriminant analysis in a three-class classification application of class-imbalanced data of diabetes risk groups. Methods: Data from a healthy project for 599 staffs in a government hospital in Bangkok were obtained for the classification problem. The staffs were diagnosed into one of three diabetes risk groups: non-risk (90%), risk (5%), and diabetic (5%). The original data along with the variables; diabetes risk group, age, gender, cholesterol, and BMI was analyzed and bootstrapped up to 50 and 100 samples, 599 observations per sample, for additional estimation of misclassification error rate. Each data set was explored for the departure of multivariate normality and the equality of covariance matrices of the three risk groups. Both the original data and the bootstrap samples show non-normality and unequal covariance matrices. The parametric linear discriminant function, quadratic discriminant function, and the nonparametric k-nearest neighbors’ discriminant function were performed over 50 and 100 bootstrap samples and applied to the original data. In finding the optimal classification rule, the choices of prior probabilities were set up for both equal proportions (0.33: 0.33: 0.33) and unequal proportions with three choices of (0.90:0.05:0.05), (0.80: 0.10: 0.10) or (0.70, 0.15, 0.15). Results: The results from 50 and 100 bootstrap samples indicated that the k-nearest neighbors approach when k = 3 or k = 4 and the prior probabilities of {non-risk:risk:diabetic} as {0.90:0.05:0.05} or {0.80:0.10:0.10} gave the smallest error rate of misclassification. Conclusion: The k-nearest neighbors approach would be suggested for classifying a three-class-imbalanced data of diabetes risk groups.

Keywords: error rate, bootstrap, diabetes risk groups, k-nearest neighbors

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Authors: Mohammad Esmaeilpour

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One of the important open problems in the field of medical image processing is detection and quantification of small changes. In this poster, we try to investigate that, how the algebraic decomposition techniques can be used for semiautomatically detecting and quantifying subtle changes in Magnetic Resonance (MR) neuroimaging volumes. We mostly focus on the low-rank values of the matrices achieved from decomposing MR image pairs during a period of time. Besides, a skillful neuroradiologist will help the algorithm to distinguish between noises and small changes.

Keywords: magnetic resonance neuroimaging, subtle change detection and quantification, algebraic decomposition, basis functions

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Authors: H. Assaedi, F. U. A. Shaikh, I. M. Low

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This paper presents the effects of mixing procedures on mechanical properties of flyash-based geopolymer matrices containing nanosilica (NS) at 0.5%, 1.0%, 2.0%, and 3.0% by wt.. Comparison is made with conventional mechanical dry-mixing of NS with flyash and wet-mixing of NS in alkaline solutions. Physical and mechanical properties are investigated using X-Ray Diffraction (XRD) and Scanning Electron Microscope (SEM). Results show that generally the addition of NS particles enhanced the microstructure and improved flexural and compressive strengths of geopolymer nanocomposites. However, samples prepared using dry-mixing approach demonstrate better physical and mechanical properties than wet-mixing of NS.

Keywords: geopolymer, nano-silica, dry mixing, wet mixing, physical properties, mechanical properties

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Authors: Humayun R. H. Kabir

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An analytical solution before used for static and free-vibration response has been extended for thermal buckling response on cylindrical panel with anti-symmetric laminations. The partial differential equations that govern kinematic behavior of shells produce five coupled differential equations. The basic displacement and rotational unknowns are similar to first order shear deformation theory---three displacement in spatial space, and two rotations about in-plane axes. No drilling degree of freedom is considered. Boundary conditions are considered as complete hinge in all edges so that the panel respond on thermal inductions. Two sets of double Fourier series are considered in the analytical solution process. The sets are selected that satisfy mixed type of natural boundary conditions. Numerical results are presented for the first 10 eigenvalues, and first 10 mode shapes for Ux, Uy, and Uz components. The numerical results are compared with a finite element based solution.

Keywords: higher order shear deformation, composite, thermal buckling, angle-ply laminations

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Authors: O. P. Popoola, O. A. Alawode, M. O. Olayiwola, A. M. Oladele

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This research work is based on using discriminant analysis to forecast crime rate in Nigeria between 1996 and 2008. The work is interested in how gender (male and female) relates to offences committed against the government, against other properties, disturbance in public places, murder/robbery offences and other offences. The data used was collected from the National Bureau of Statistics (NBS). SPSS, the statistical package was used to analyse the data. Time plot was plotted on all the 29 offences gotten from the raw data. Eigenvalues and Multivariate tests, Wilks’ Lambda, standardized canonical discriminant function coefficients and the predicted classifications were estimated. The research shows that the distribution of the scores from each function is standardized to have a mean O and a standard deviation of 1. The magnitudes of the coefficients indicate how strongly the discriminating variable affects the score. In the predicted group membership, 172 cases that were predicted to commit crime against Government group, 66 were correctly predicted and 106 were incorrectly predicted. After going through the predicted classifications, we found out that most groups numbers that were correctly predicted were less than those that were incorrectly predicted.

Keywords: discriminant analysis, DA, multivariate analysis of variance, MANOVA, canonical correlation, and Wilks’ Lambda

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Authors: Liqin Zhi, Lin Xu, Wenxia Wei, Yaqi Cai

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Recently, replacing some of the methyl groups in polydimethylsiloxanes with other functional groups has been extensively explored to obtain modified polymethylsiloxanes with special properties that enable new industrial applications. Fluorinated polysiloxanes, one type of these modified polysiloxanes, are based on a siloxane backbone with fluorinated groups attached to the side chains of polysiloxanes. As a commercially significant material, poly[methyl(trifluoropropyl)siloxane] (PMTFPS) has sufficient fluorine content to be useful as a fuel-and oil-resistant elastomer, which combines both the chemical and solvent resistance of fluorocarbons and the wide temperature range applicability of organosilicones. PMTFPS products can be used in many applications in which resistance to fuel, oils and hydrocarbon solvents is required, including use as lubricants in bearings, sealants, and elastomers for aerospace and automotive fuel systems. Fluorinated methylsiloxanes, a type of modified methylsiloxane, include tris(trifluoropropyl)trimethylcyclotrisiloxane (D3F) and tetrakis(trifluoropropyl)tetramethylcyclotetrasiloxane (D4F), both of which contain trifluoropropyl groups in the side chains of cyclic methylsiloxanes. D3F, as an important monomer in the manufacture of PMTFPS, is often present as an impurity in PMTFPS. In addition, the synthesis of PMTFPS from D3F could form other fluorinated methylsiloxanes with low molecular weights (such as D4F). The yearly demand and production volumes of D3F increased rapidly all over world. Fluorinated methylsiloxanes might be released into the environment via different pathways during the production and application of PMTFPS. However, there is a lack of data concerning the emission, environmental occurrence and potential environmental impacts of fluorinated methylsiloxanes. Here, we report fluorinated methylsiloxanes (D3F and D4F) in surface water and sediment samples collected near a fluorinated methylsiloxane manufacturing plant in Weihai, China. The concentrations of D3F and D4F in surface water ranged from 3.29 to 291 ng/L and from 7.02 to 168 ng/L, respectively. The concentrations of D3F and D4F in sediment ranged from 11.8 to 5478 ng/g and from 17.2 to 6277 ng/g, respectively. In simulation experiment, the half-lives of D3F and D4F at different pH values (5.2, 6.4, 7.2, 8.3 and 9.2) varied from 80.6 to 154 h and from 267 to 533 h respectively. CF₃(CH₂)₂MeSi(OH)₂ was identified as one of the main hydrolysis products of fluorinated methylsiloxanes. It was also detected in the river samples at concentrations of 72.1-182.9 ng/L. In addition, the slow rearrangement of D3F (spiked concentration = 500 ng/L) to D4F (concentration = 11.0-22.7 ng/L) was also found during 336h hydrolysis experiment.

Keywords: fluorinated methylsiloxanes, environmental matrices, hydrolysis, sediment

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Authors: Yessica Nataliani, Miin-Shen Yang

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Cell formation (CF) is an important step in group technology. It is used in designing cellular manufacturing systems using similarities between parts in relation to machines so that it can identify part families and machine groups. There are many CF methods in the literature, but there is less spectral clustering used in CF. In this paper, we propose a spectral clustering algorithm for machine-part CF. Some experimental examples are used to illustrate its efficiency. Overall, the spectral clustering algorithm can be used in CF with a wide variety of machine/part matrices.

Keywords: group technology, cell formation, spectral clustering, grouping efficiency

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Authors: Juan M. Rodriguez-Diaz

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The precision of parameter estimators in the Gaussian linear model is traditionally accounted by the variance-covariance matrix of the asymptotic distribution. However, this measure can underestimate the true variance, specially for small samples. Traditionally, optimal design theory pays attention to this variance through its relationship with the model's information matrix. For this reason it seems convenient, at least in some cases, adapt the optimality criteria in order to get the best designs for the actual variance structure, otherwise the loss in efficiency of the designs obtained with the traditional approach may be very important.

Keywords: correlated observations, information matrix, optimality criteria, variance-covariance matrix

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Authors: Arcady Ponosov., Ramazan Kadiev

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The work studies the global moment stability of solutions of systems of nonlinear differential Itô equations with delays. A modified regularization method (W-method) for the analysis of various types of stability of such systems, based on the choice of the auxiliaryequations and applications of the theory of positive invertible matrices, is proposed and justified. Development of this method for deterministic functional differential equations is due to N.V. Azbelev and his students. Sufficient conditions for the moment stability of solutions in terms of the coefficients for sufficiently general as well as specific classes of Itô equations are given.

Keywords: asymptotic stability, delay equations, operator methods, stochastic noise

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Authors: Gulay Oncu Ince, Sibel Karakaya

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Food is a worldwide concern. Among the factors that have influences on human health, food, nutrition and life style have been regarded as the most important factors since they can be intervened. While some parts of the world has been faced with food shortages and hence, chronic metabolic diseases, the other part of the world have been emerged from over consumption of food. Both situations can result in shorter life expectancy and represent a major global health problem. Hunger, satiety and appetite sensation form a balance ensures the operation of feeding behavior between food intake and energy consumption. Satiety is one of the approaches that is effective in ensuring weight control and avoid eating more in the postprandial period. By manipulating the microstructure of food macro and micronutrient bioavailability may be increased or reduced. For the food industry appearance, texture, taste structural properties as well as the gastrointestinal tract behavior of the food after the consumption is becoming increasingly important. Also, this behavior has been the subject of several researches in recent years by the scientific community. Numerous studies have been published about changing the food matrix in order to increase expected impacts. In this study, yogurts were enriched with caseinomacropeptide (CMP), whey protein (WP), CMP and sodium alginate (SA), and WP + SA in order to produce goat yogurts having different food matrices. SDS Page profiles of the samples after in vitro digestion and viscosities of the stomach digesta at different share rates were determined. Energy values were 62.11kcal/100 g, 70.27 kcal/100 g, 70.61 kcal/100 g, 71.20 kcal/100 g and 71.67 kcal/100 g for control, CMP added WP added, WP + SA added, and CMP + SA added yogurts respectively. The results of viscosity analysis showed that control yogurt had the lowest viscosity value and this was followed by CMP added, WP added, CMP + SA added and WP + SA added yogurts, respectively. Protein contents of the stomach and duedonal digests of the samples after subjected to two different in vitro digestion methods were changed between 5.34-5.91 mg protein / g sample and 16.93-19.75 mg protein /g of sample, respectively. Viscosity measurements of the stomach digests showed that CMP + SA added yogurt displayed the highest viscosity value in both in vitro digestion methods. There were differences between the protein profiles of the stomach and duedonal digests obtained by two different in vitro digestion methods (p<0.05).

Keywords: caseinomacropeptide, protein profile, whey protein, yogurt

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Authors: Epameinondas Xanthakis, Erik Kaunisto, Alain Le-Bail, Lilia Ahrné

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Fruits and vegetables are characterized as perishable food matrices due to their short shelf life as several deterioration mechanisms are being involved. Prior to the common preservation methods like freezing or canning, fruits and vegetables are being blanched in order to inactivate deteriorative enzymes. Both conventional blanching pretreatments and conventional freezing methods hide drawbacks behind their beneficial impacts on the preservation of those matrices. Conventional blanching methods may require longer processing times, leaching of minerals and nutrients due to the contact with the warm water which in turn leads to effluent production with large BOD. An important issue of freezing technologies is the size of the formed ice crystals which is also critical for the final quality of the frozen food as it can cause irreversible damage to the cellular structure and subsequently to degrade the texture and the colour of the product. Herein, the developed microwave blanching methodology and the results regarding quality aspects and enzyme inactivation will be presented. Moreover, heat transfer phenomena, mass balance, temperature distribution, and enzyme inactivation (such as Pectin Methyl Esterase and Ascorbic Acid Oxidase) of our microwave blanching approach will be evaluated based on measurements and computer modelling. The present work is part of the COLDμWAVE project which aims to the development of an innovative environmentally sustainable process for blanching and freezing of fruits and vegetables with improved textural and nutritional quality. In this context, COLDµWAVE will develop tailored equipment for MW blanching of vegetables that has very high energy efficiency and no water consumption. Furthermore, the next steps of this project regarding the development of innovative pathways in MW assisted freezing to improve the quality of frozen vegetables, by exploring in depth previous results acquired by the authors, will be presented. The application of MW assisted freezing process on fruits and vegetables it is expected to lead to improved quality characteristics compared to the conventional freezing. Acknowledgments: COLDμWAVE has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grand agreement No 660067.

Keywords: blanching, freezing, fruits, microwave blanching, microwave

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Authors: Mehrnaz Alibeikloo, Hadi Khabbaz, Behzad Fatahi

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The spectral random field method is one of the widely used methods to obtain more reliable and accurate results in geotechnical problems involving material variability. Karhunen-Loeve (K-L) expansion method was applied to perform random field discretization of cross-correlated creep parameters. Karhunen-Loeve expansion method is based on eigenfunctions and eigenvalues of covariance function adopting Kernel integral solution. In this paper, the accuracy of Karhunen-Loeve expansion was investigated to predict long-term settlement of soft soils adopting elastic visco-plastic creep model. For this purpose, a parametric study was carried to evaluate the effect of K-L expansion terms and spatial correlation length on the reliability of results. The results indicate that small values of spatial correlation length require more K-L expansion terms. Moreover, by increasing spatial correlation length, the coefficient of variation (COV) of creep settlement increases, confirming more conservative and safer prediction.

Keywords: Karhunen-Loeve expansion, long-term settlement, reliability analysis, spatial correlation length

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Authors: Essam Al Daoud

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This study solves a phylogeny problem by using modified wild dog pack optimization. The least squares error is considered as a cost function that needs to be minimized. Therefore, in each iteration, new distance matrices based on the constructed trees are calculated and used to select the alpha dog. To test the suggested algorithm, ten homologous genes are selected and collected from National Center for Biotechnology Information (NCBI) databanks (i.e., 16S, 18S, 28S, Cox 1, ITS1, ITS2, ETS, ATPB, Hsp90, and STN). The data are divided into three categories: 50 taxa, 100 taxa and 500 taxa. The empirical results show that the proposed algorithm is more reliable and accurate than other implemented methods.

Keywords: least square, neighbor joining, phylogenetic tree, wild dog pack

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Authors: Okpala Charles Chikwendu, Ezeanyim Okechukwu Chiedu, Onukwuli Somto Kenneth

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The demand for lightweight and fuel-efficient automobiles has led to the use of fiber-reinforced polymer composites in place of traditional metal parts. Coir, a natural fiber, offers qualities such as low cost, good tensile strength, and biodegradability, making it a potential filler material for automotive components. However, poor interfacial adhesion between coir and polymeric matrices has been a challenge. To address poor interfacial adhesion with polymeric matrices due to their moisture content and method of preparation, the extracted coir was chemically treated using NaOH. To develop a side view mirror encasement by investigating the mechanical effect of fiber percentage composition, fiber length and percentage composition of Epoxy in a coir fiber reinforced composite, polyester was adopted as the resin for the mold, while that of the product is Epoxy. Coir served as the filler material for the product. Specimens with varied compositions of fiber loading (15, 30 and 45) %, length (10, 15, 20, 30 and 45) mm, and (55, 70, 85) % weight of epoxy resin were fabricated using hand lay-up technique, while those specimens were later subjected to mechanical tests (Tensile, Flexural and Impact test). The results of the mechanical test showed that the optimal solution for the input factors is coir at 45%, epoxy at 54.543%, and 45mm coir length, which was used for the development of a vehicle’s side view mirror encasement. The optimal solutions for the response parameters are 49.333 Mpa for tensile strength, flexural for 57.118 Mpa, impact strength for 34.787 KJ/M2, young modulus for 4.788 GPa, stress for 4.534 KN, and 20.483 mm for strain. The models that were developed using Design Expert software revealed that the input factors can achieve the response parameters in the system with 94% desirability. The study showed that coir is quite durable for filler material in an epoxy composite for automobile applications and that fiber loading and length have a significant effect on the mechanical behavior of coir fiber-reinforced epoxy composites. The coir's low density, considerable tensile strength, and bio-degradability contribute to its eco-friendliness and potential for reducing the environmental hazards of synthetic automotive components.

Keywords: coir, composite, coir fiber, coconut husk, polymer, automobile, mechanical test

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Authors: Elizabeth Latham

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Billions of people worldwide profess some feeling of psychological or spiritual connection with the divine. The majority of them attribute this personal connection to the God of the Christian Bible. The objective of this research was to discover what could be known about the exact social nature of these relationships and to see if they mimic the interactions recounted in the bible; if a worldwide majority believes that the Christian Bible is a true account of God’s interactions with mankind, it is reasonable to assume that the interactions between God and the aforementioned people would be similar to the ones in the bible. This analysis required the employment of an unusual method of biblical analysis: Game Theory. Because the research focused on documented social interaction between God and man in scripture, it was important to go beyond text-analysis methods. We used stories from the New Revised Standard Version of the bible to set up “games” using economics-style matrices featuring each player’s motivations and possible courses of action, modeled after interactions in the Old and New Testaments between the Judeo-Christian God and some mortal person. We examined all relevant interactions for the objectives held by each party and their strategies for obtaining them. These findings were then compared to similar “games” created based on interviews with people subscribing to different levels of Christianity who ranged from barely-practicing to clergymen. The range was broad so as to look for a correlation between scriptural knowledge and game-similarity to the bible. Each interview described a personal experience someone believed they had with God and matrices were developed to describe each one as social interaction: a “game” to be analyzed quantitively. The data showed that in most cases, the social features of God-man interactions in the modern lives of people were like those present in the “games” between God and man in the bible. This similarity was referred to in the study as “biblical faith” and it alone was a fascinating finding with many implications. The even more notable finding, however, was that the amount of game-similarity present did not correlate with the amount of scriptural knowledge. Each participant was also surveyed on family background, political stances, general education, scriptural knowledge, and those who had biblical faith were not necessarily the ones that knew the bible best. Instead, there was a high degree of correlation between biblical faith and family religious observance. It seems that to have a biblical psychological relationship with God, it is more important to have a religious family than to have studied scripture, a surprising insight with massive implications on the practice and preservation of religion.

Keywords: bible, Christianity, game theory, social psychology

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Authors: Hossein Pourbashash

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Recent experimental studies have shown that HIV can be transmitted directly from cell to cell when structures called virological synapses form during interactions between T cells. In this article, we describe a new within-host model of HIV infection that incorporates two mechanisms: infection by free virions and the direct cell-to-cell transmission. We conduct the local and global stability analysis of the model. We show that if the basic reproduction number R0 1, the virus is cleared and the disease dies out; if R0 > 1, the virus persists in the host. We also prove that the unique positive equilibrium attracts all positive solutions under additional assumptions on the parameters.

Keywords: HIV virus model, cell-to-cell transmission, global stability, Lyapunov function, second compound matrices

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Authors: Pu Ying-Chih, Yang Yin-Ju, Hang Jian-Yi, Jang Guang-Way

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Organic-Inorganic hybrid materials consisting of graded distributions of inorganic nano particles in organic polymer matrices were successfully prepared by the sol-gel process. Optical and surface properties of the resulting nano composites can be manipulated by changing their compositions and nano particle distribution gradients. Applications of gradient nano composite materials include sealants for LED packaging and screen lenses for smartphones. Optical transparency, prism coupler, TEM, SEM, Energy Dispersive X-ray Spectrometer (EDX), Izod impact strength, conductivity, pencil hardness, and thermogravimetric characterizations of the nano composites were performed and the results will be presented.

Keywords: Gradient, Hybrid, Nanocomposite, Organic-Inorganic

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Authors: Garry A. Einicke, Langford B. White

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This paper describes an optimum filter and smoother for recovering a Markov process message from noisy measurements. The developments follow from an equivalence between a state space model and a hidden Markov chain. The ensuing filter and smoother employ transition probability matrices and approximate probability distribution vectors. The properties of the optimum solutions are retained, namely, the estimates are unbiased and minimize the variance of the output estimation error, provided that the assumed parameter set are correct. Methods for estimating unknown parameters from noisy measurements are discussed. Signal recovery examples are described in which performance benefits are demonstrated at an increased calculation cost.

Keywords: optimal filtering, smoothing, Markov chains

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Authors: Stephanie Cornish

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The use of synthetic dermal templates, also known as dermal matrices, such as PolyNovo® Biodegradable Temporising Matrix (BTM), has been well established in the reconstruction of acute wounds with a full thickness defect of the skin. Its use has become common place in the treatment of full thickness burns and is not unfamiliar in the realm of necrotising fasciitis, free flap donor site reconstruction, and the management of acute traumatic wounds. However, the use of dermal templates for more chronic wounds is rare. The authors present the successful use of BTM in the reconstruction of a chronic scalp wound following the excision of a malignancy and multiple previous failed attempts at repair, thus demonstrating the potential for an increased scope of use.

Keywords: dermal template, BTM, chronic, scalp wound, reconstruction

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Authors: Nancy Ibrahim Abdalla, Abdelaziz Karamalla Gaiballa

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Rangelands in semi-arid areas provide a good source for feeding huge numbers of animals and serving environmental, economic and social importance; therefore, these areas are considered economically very important for the pastoral sector in Sudan. This paper investigates the means of differentiating between different rangelands sites according to soil types using principal component analysis to assist in monitoring and assessment purposes. Three rangeland sites were identified in the study area as flat sandy sites, sand dune site, and hard clay site. Principal component analysis (PCA) was used to reduce the number of factors needed to distinguish between rangeland sites and produce a new set of data including the most useful spectral information to run satellite image processing. It was performed using selected types of data (two vegetation indices, topographic data and vegetation surface reflectance within the three bands of MODIS data). Analysis with PCA indicated that there is a relatively high correspondence between vegetation and soil of the total variance in the data set. The results showed that the use of the principal component analysis (PCA) with the selected variables showed a high difference, reflected in the variance and eigenvalues and it can be used for differentiation between different range sites.

Keywords: principal component analysis, PCA, rangeland sites, semi-arid areas, soil types

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Authors: Malihe Aliasgari, Yousef Nejatbakhsh

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The era of Big Data and the immensity of real-life datasets compels computation tasks to be performed in a distributed fashion, where the data is dispersed among many servers that operate in parallel. However, massive parallelization leads to computational bottlenecks due to faulty servers and stragglers. Stragglers refer to a few slow or delay-prone processors that can bottleneck the entire computation because one has to wait for all the parallel nodes to finish. The problem of straggling processors, has been well studied in the context of distributed computing. Recently, it has been pointed out that, for the important case of linear functions, it is possible to improve over repetition strategies in terms of the tradeoff between performance and latency by carrying out linear precoding of the data prior to processing. The key idea is that, by employing suitable linear codes operating over fractions of the original data, a function may be completed as soon as enough number of processors, depending on the minimum distance of the code, have completed their operations. The problem of matrix-matrix multiplication in the presence of practically big sized of data sets faced with computational and memory related difficulties, which makes such operations are carried out using distributed computing platforms. In this work, we study the problem of distributed matrix-matrix multiplication W = XY under storage constraints, i.e., when each server is allowed to store a fixed fraction of each of the matrices X and Y, which is a fundamental building of many science and engineering fields such as machine learning, image and signal processing, wireless communication, optimization. Non-secure and secure matrix multiplication are studied. We want to study the setup, in which the identity of the matrix of interest should be kept private from the workers and then obtain the recovery threshold of the colluding model, that is, the number of workers that need to complete their task before the master server can recover the product W. The problem of secure and private distributed matrix multiplication W = XY which the matrix X is confidential, while matrix Y is selected in a private manner from a library of public matrices. We present the best currently known trade-off between communication load and recovery threshold. On the other words, we design an achievable PSGPD scheme for any arbitrary privacy level by trivially concatenating a robust PIR scheme for arbitrary colluding workers and private databases and the proposed SGPD code that provides a smaller computational complexity at the workers.

Keywords: coded distributed computation, private information retrieval, secret sharing, stragglers

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Authors: Arka Roy, Chandra Prakash Dubey

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Inverse problem generally used for recovering hidden information from outside available data. Vertical component of gravity field we will be going to use for underneath density structure calculation. Ill-posing nature is main obstacle for any inverse problem. Linear regularization using Tikhonov formulation are used for appropriate choice of SVD and GSVD components. For real time data handle, signal to noise ratios should have to be less for reliable solution. In our study, 2D and 3D synthetic model with rectangular grid are used for gravity field calculation and its corresponding inversion for density reconstruction. Fine grid also we have considered to hold any irregular structure. Keeping in mind of algebraic ambiguity factor number of observation point should be more than that of number of data point. Picard plot is represented here for choosing appropriate or main controlling Eigenvalues for a regularized solution. Another important study is depth resolution plot (DRP). DRP are generally used for studying how the inversion is influenced by regularizing or discretizing. Our further study involves real time gravity data inversion of Vredeforte Dome South Africa. We apply our method to this data. The results include density structure is in good agreement with known formation in that region, which puts an additional support of our method.

Keywords: depth resolution plot, gravity inversion, Picard plot, SVD, Tikhonov formulation

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Authors: Mina Boroujerdi, Javad Tavakoli

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Hydrogels are extensively studied as matrices for the controlled release of drugs. To evaluate the mobility of embedded molecules, these drug delivery systems are usually characterized by release studies. In this contribution, an electronic device for swelling pressure measurement during drug release from hydrogel network was developed. Also, poly acrylic acid micro particles were prepared for prolonged and sustained controlled acetaminophen release. Effect of swelling pressure on drug release from micro particles studied under different environment pH in order to predict release profile in gastro-intestine medium. Swelling ratio and swelling pressure were measured in different pH.

Keywords: swelling pressure, drug delivery, hydrogel, polyelectrolyte

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Authors: Victor Sotero, Cindy Castro, Ena Velazco, Ursula Monteiro, Dora Garcia

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The aim of this study is to carry out the evaluation of the artificial pollination of the female flowers of E. oleifera with pollen of E. guineensis, to obtain the hybrid Palma OXG, which presents two characteristics of interest, such as high resistance to the disease of spear rot and high concentration of oleic acid. The works were carried out with matrices from the experimental fields and INIA in the Province of Colonel Portillo in the Ucayali Region-Peru. From the pollination of five species of E. oleifera, fruits were obtained in two of them, called O7 and O68, with a percentage of 23.6% and 18.6% of fertile fruits. When germination was carried out in a controlled environment of temperature, air, and humidity, only the O17 species were germinated with a yield of 68.7%.

Keywords: Elaeis oleífera, Elaeis guineensis, palm OXG, pollination

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Authors: Ghazi Bouaziz, Abderrahim Derouiche, Damien Brulin, Hélène Pigot, Eric Campo

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Automatic ADL classification is a crucial part of ambient assisted living technologies. It allows to monitor the daily life of the elderly and to detect any changes in their behavior that could be related to health problem. But detection of ADLs is a challenge, especially because each person has his/her own rhythm for performing them. Therefore, we used a correlation matrix to extract custom rules that enable to detect ADLs, including eating activity. Data collected from 3 different individuals between 35 and 105 days allows the extraction of personalized eating patterns. The comparison of the results of the process of eating activity extracted from the correlation matrices with the declarative data collected during the survey shows an accuracy of 90%.

Keywords: elderly monitoring, ADL identification, matrix correlation, meal-taking activity

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Authors: Egor Stadnichuk

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Relativistic runaway electron avalanches (RREA) are a widely accepted source of thunderstorm gamma-radiation. In regions with huge electric field strength, RREA can multiply via relativistic feedback. The relativistic feedback is caused both by positron production and by runaway electron bremsstrahlung gamma-rays reversal. In complex multilayer thunderstorm electric field structures, an additional reactor feedback mechanism appears due to gamma-ray exchange between separate strong electric field regions with different electric field directions. The study of this reactor mechanism in conjunction with the relativistic feedback with Monte Carlo simulations or by direct solution of the kinetic Boltzmann equation requires a significant amount of computational time. In this work, a theoretical approach to study feedback mechanisms in RREA physics is developed. It is based on the matrix of feedback operators construction. With the feedback matrix, the problem of the dynamics of avalanches in complex electric structures is reduced to the problem of finding eigenvectors and eigenvalues. A method of matrix elements calculation is proposed. The proposed concept was used to study the dynamics of RREAs in multilayer thunderclouds.

Keywords: terrestrial Gamma-ray flashes, thunderstorm ground enhancement, relativistic runaway electron avalanches, gamma-rays, high-energy atmospheric physics, TGF, TGE, thunderstorm, relativistic feedback, reactor feedback, reactor model

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Authors: Dolly Selikane, Thandi Gumede

Abstract:

Among the commonly studied organic fillers for polycaprolactone (PCL), cellulose is the most promising. It is available in various particle sizes and sources, providing numerous options for finding a suitable match for PCL matrices. In this study, cellulose was extracted from the leaves of E. autumnalis to create a PCL/nanocellulose composite through melt blending. The prepared nanocellulose was blended with PCL at a weight ratio of 97/3, and the resulting composite was characterized by its thermal and mechanical properties. The results showed that the addition of nanocellulose to PCL improved its mechanical properties, with a maximum increase of 29% in tensile strength and 31% in Young's modulus. The SEM analysis confirmed the successful blending of PCL and nanocellulose. The findings of this study suggest that the nanocellulose from Eucomis autumnalis plant has the potential to improve the mechanical properties of PCL and could be used in biomedical and packaging applications.

Keywords: polycaprolactone, medicinal plants, Eucomis autumnalis, nanocellulose, composite

Procedia PDF Downloads 78

Authors: Haiyang Su, Kun Qian

Abstract:

We developed a novel plasmonic matrix assisted laser desorption/ionization mass spectrometry (MALDI MS) approach to detect small nutrients and toxin in complex biological emulsion samples. We used silver nanoshells (SiO₂@Ag) with optimized structures as matrices and achieved direct analysis of ~6 nL of human breast milk without any enrichment or separation. We performed identification and quantitation of small nutrients and toxins with limit-of-detection down to 0.4 pmol (for melamine) and reaction time shortened to minutes, superior to the conventional biochemical methods currently in use. Our approach contributed to the near-future application of MALDI MS in a broad field and personalized design of plasmonic materials for real case bio-analysis.

Keywords: plasmonic materials, laser desorption/ionization, mass spectrometry, small nutrients, toxins

Procedia PDF Downloads 176

Authors: Ling Zhang, Feng Liu

Abstract:

A matrix is called a ray pattern matrix if its entries are either 0 or a ray in complex plane which originates from 0. A ray pattern A of order n is called spectrally arbitrary if the complex matrices in the ray pattern class of A give rise to all possible nth degree complex polynomial. Otherwise, it is said to be spectrally non-arbitrary ray pattern. We call that a spectrally arbitrary ray pattern A of order n is minimally spectrally arbitrary if any nonzero entry of A is replaced, then A is not spectrally arbitrary. In this paper, we find that is not spectrally arbitrary when n equals to 4 for any θ which is greater than or equal to 0 and less than or equal to n. In this article, we give several ray patterns A(θ) of order n that are not spectrally arbitrary for some θ which is greater than or equal to 0 and less than or equal to n. by using the nilpotent-Jacobi method. One example is given in our paper.

Keywords: spectrally arbitrary, nilpotent matrix , ray patterns, sign patterns

Procedia PDF Downloads 149

Authors: Behnaz Moradijamei, Michael Higgins

Abstract:

Identifying community structure is a critical task in analyzing social media data sets often modeled by networks. Statistical models such as the stochastic block model have proven to explain the structure of communities in real-world network data. In this work, we develop a goodness-of-fit test to examine community structure's existence by using a distinguishing property in networks: cyclic structures are more prevalent within communities than across them. To better understand how communities are shaped by the cyclic structure of the network rather than just the number of edges, we introduce a novel method for deciding on the existence of communities. We utilize these structures by using renewal non-backtracking random walk (RNBRW) to the existing goodness-of-fit test. RNBRW is an important variant of random walk in which the walk is prohibited from returning back to a node in exactly two steps and terminates and restarts once it completes a cycle. We investigate the use of RNBRW to improve the performance of existing goodness-of-fit tests for community detection algorithms based on the spectral properties of the adjacency matrix. Our proposed test on community structure is based on the probability distribution of eigenvalues of the normalized retracing probability matrix derived by RNBRW. We attempt to make the best use of asymptotic results on such a distribution when there is no community structure, i.e., asymptotic distribution under the null hypothesis. Moreover, we provide a theoretical foundation for our statistic by obtaining the true mean and a tight lower bound for RNBRW edge weights variance.

Keywords: hypothesis testing, RNBRW, network inference, community structure

Procedia PDF Downloads 115