Search results for: linear temperature sensor
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4850

Search results for: linear temperature sensor

3980 The Effect of Impinging WC-12Co Particles Temperature on Thickness of HVOF Thermally Sprayed Coatings

Authors: M. Jalali Azizpour, H. Mohammadi Majd

Abstract:

In this paper, the effect of WC-12Co particle temperature in HVOF thermal spraying process on the coating thickness has been studied. The statistical results show that the spray distance and oxygen-to-fuel ratio are effective factors on particle characterization and thickness of HVOF thermal spraying coatings. Spray Watch diagnostic system, scanning electron microscopy (SEM), X-ray diffraction and thickness measuring system were used for this purpose.

Keywords: HVOF, Temperature, Thickness, Velocity, WC- 12Co.

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3979 The Removal of Cu (II) Ions from Aqueous Solutions on Synthetic Zeolite NaA

Authors: Dimitar Georgiev, Bogdan Bogdanov, Yancho Hristov, Irena Markovska

Abstract:

In this study the adsorption of Cu (II) ions from aqueous solutions on synthetic zeolite NaA was evaluated. The effect of solution temperature and the determination of the kinetic parameters of adsorption of Cu(II) from aqueous solution on zeolite NaA is important in understanding the adsorption mechanism. Variables of the system include adsorption time, temperature (293- 328K), initial solution concentration and pH for the system. The sorption kinetics of the copper ions were found to be strongly dependent on pH (the optimum pH 3-5), solute ion concentration and temperature (293 – 328 K). It was found, the pseudo-second-order model was the best choice among all the kinetic models to describe the adsorption behavior of Cu(II) onto ziolite NaA, suggesting that the adsorption mechanism might be a chemisorptions process The activation energy of adsorption (Ea) was determined as Cu(II) 13.5 kJ mol-1. The low value of Ea shows that Cu(II) adsorption process by zeolite NaA may be an activated chemical adsorption. The thermodynamic parameters (ΔG0, ΔH0, and ΔS0) were also determined from the temperature dependence. The results show that the process of adsorption Cu(II) is spontaneous and endothermic process and rise in temperature favors the adsorption.

Keywords: Zeolite NaA, adsorption, adsorption capacity, kinetic sorption

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3978 Development of an Autonomous Friction Gripper for Industrial Robots

Authors: Majid Tolouei-Rad, Peter Kalivitis

Abstract:

Industrial robots become useless without end-effectors that for many instances are in the form of friction grippers. Commonly friction grippers apply frictional forces to different objects on the basis of programmers- experiences. This puts a limitation on the effectiveness of gripping force that may result in damaging the object. This paper describes various stages of design and development of a low cost sensor-based robotic gripper that would facilitate the task of applying right gripping forces to different objects. The gripper is also equipped with range sensors in order to avoid collisions of the gripper with objects. It is a fully functional automated pick and place gripper which can be used in many industrial applications. Yet it can also be altered or further developed in order to suit a larger number of industrial activities. The current design of gripper could lead to designing completely automated robot grippers able to improve the efficiency and productivity of industrial robots.

Keywords: Control system, end-effector, robot, sensor

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3977 Behaviour of Lightweight Expanded Clay Aggregate Concrete Exposed to High Temperatures

Authors: Lenka Bodnárová, Rudolf Hela, Michala Hubertová, Iveta Nováková

Abstract:

This paper is concerning the issues of behaviour of lightweight expanded clay aggregates concrete exposed to high temperature. Lightweight aggregates from expanded clay are produced by firing of row material up to temperature 1050°C. Lightweight aggregates have suitable properties in terms of volume stability, when exposed to temperatures up to 1050°C, which could indicate their suitability for construction applications with higher risk of fire. The test samples were exposed to heat by using the standard temperature-time curve ISO 834. Negative changes in resulting mechanical properties, such as compressive strength, tensile strength, and flexural strength were evaluated. Also visual evaluation of the specimen was performed. On specimen exposed to excessive heat, an explosive spalling could be observed, due to evaporation of considerable amount of unbounded water from the inner structure of the concrete.

Keywords: Expanded clay aggregate, explosive spalling, high temperature, lightweight concrete, temperature-time curve ISO 834.

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3976 Thermal Fatigue Behavior of Austenitic Stainless Steels

Authors: Jung-Ho Moon, Tae Kwon Ha

Abstract:

Continually increasing working temperature and growing need for greater efficiency and reliability of automotive exhaust require systematic investigation into the thermal fatigue properties especially of high temperature stainless steels. In this study, thermal fatigue properties of 300 series austenitic stainless steels have been evaluated in the temperature ranges of 200-800oC and 200-900oC. Systematic methods for control of temperatures within the predetermined range and measurement of load applied to specimens as a function of temperature during thermal cycles have been established. Thermal fatigue tests were conducted under fully constrained condition, where both ends of specimens were completely fixed. Load relaxation behavior at the temperatures of thermal cycle was closely related with the thermal fatigue property.

Keywords: Austenitic stainless steel, automotive exhaust, thermal fatigue, microstructure, load relaxation.

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3975 Probabilistic Bayesian Framework for Infrared Face Recognition

Authors: Moulay A. Akhloufi, Abdelhakim Bendada

Abstract:

Face recognition in the infrared spectrum has attracted a lot of interest in recent years. Many of the techniques used in infrared are based on their visible counterpart, especially linear techniques like PCA and LDA. In this work, we introduce a probabilistic Bayesian framework for face recognition in the infrared spectrum. In the infrared spectrum, variations can occur between face images of the same individual due to pose, metabolic, time changes, etc. Bayesian approaches permit to reduce intrapersonal variation, thus making them very interesting for infrared face recognition. This framework is compared with classical linear techniques. Non linear techniques we developed recently for infrared face recognition are also presented and compared to the Bayesian face recognition framework. A new approach for infrared face extraction based on SVM is introduced. Experimental results show that the Bayesian technique is promising and lead to interesting results in the infrared spectrum when a sufficient number of face images is used in an intrapersonal learning process.

Keywords: Face recognition, biometrics, probabilistic imageprocessing, infrared imaging.

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3974 Low-Cost Monitoring System for Hydroponic Urban Vertical Farms

Authors: Francesco Ruscio, Paolo Paoletti, Jens Thomas, Paul Myers, Sebastiano Fichera

Abstract:

This paper presents the development of a low-cost monitoring system for a hydroponic urban vertical farm, enabling its automation and a quantitative assessment of the farm performance. Urban farming has seen increasing interest in the last decade thanks to the development of energy efficient and affordable LED lights; however, the optimal configuration of such systems (i.e. amount of nutrients, light-on time, ambient temperature etc.) is mostly based on the farmers’ experience and empirical guidelines. Moreover, even if simple, the maintenance of such systems is labor intensive as it requires water to be topped-up periodically, mixing of the nutrients etc. To unlock the full potential of urban farming, a quantitative understanding of the role that each variable plays in the growth of the plants is needed, together with a higher degree of automation. The low-cost monitoring system proposed in this paper is a step toward filling this knowledge and technological gap, as it enables collection of sensor data related to water and air temperature, water level, humidity, pressure, light intensity, pH and electric conductivity without requiring any human intervention. More sensors and actuators can also easily be added thanks to the modular design of the proposed platform. Data can be accessed remotely via a simple web interface. The proposed platform can be used both for quantitatively optimizing the setup of the farms and for automating some of the most labor-intensive maintenance activities. Moreover, such monitoring system can also potentially be used for high-level decision making, once enough data are collected.

Keywords: Automation, hydroponics, internet of things, monitoring system, urban farming.

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3973 Complex Condition Monitoring System of Aircraft Gas Turbine Engine

Authors: A. M. Pashayev, D. D. Askerov, C. Ardil, R. A. Sadiqov, P. S. Abdullayev

Abstract:

Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE workand output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.

Keywords: aviation gas turbine engine, technical condition, fuzzy logic, neural networks, fuzzy statistics

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3972 Preparation and Characterization of Organic Silver Precursors for Conductive Ink

Authors: Wendong Yang, Changhai Wang, Valeria Arrighi

Abstract:

Low ink sintering temperature is desired for flexible electronics, as it would widen the application of the ink on temperature-sensitive substrates where the selection of silver precursor is very critical. In this paper, four types of organic silver precursors, silver carbonate, silver oxalate, silver tartrate and silver itaconate, were synthesized using an ion exchange method, firstly. Various characterization methods were employed to investigate their physical phase, chemical composition, morphologies and thermal decomposition behavior. It was found that silver oxalate had the ideal thermal property and showed the lowest decomposition temperature. An ink was then formulated by complexing the as-prepared silver oxalate with ethylenediamine in organic solvents. Results show that a favorable conductive film with a uniform surface structure consisting of silver nanoparticles and few voids could be produced from the ink at a sintering temperature of 150 °C.

Keywords: Conductive ink, electrical property, film, organic silver.

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3971 Using Tabu Search to Analyze the Mauritian Economic Sectors

Authors: J. Cheeneebash, V. Beeharry, A. Gopaul

Abstract:

The aim of this paper is to express the input-output matrix as a linear ordering problem which is classified as an NP-hard problem. We then use a Tabu search algorithm to find the best permutation among sectors in the input-output matrix that will give an optimal solution. This optimal permutation can be useful in designing policies and strategies for economists and government in their goal of maximizing the gross domestic product.

Keywords: Input-Output matrix, linear ordering problem, Tabusearch.

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3970 A New Derivative-Free Quasi-Secant Algorithm For Solving Non-Linear Equations

Authors: F. Soleymani, M. Sharifi

Abstract:

Most of the nonlinear equation solvers do not converge always or they use the derivatives of the function to approximate the root of such equations. Here, we give a derivative-free algorithm that guarantees the convergence. The proposed two-step method, which is to some extent like the secant method, is accompanied with some numerical examples. The illustrative instances manifest that the rate of convergence in proposed algorithm is more than the quadratically iterative schemes.

Keywords: Non-linear equation, iterative methods, derivative-free, convergence.

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3969 Development for the Evaluation Index of an Anesthesia Depth using the Bispectrum Analysis

Authors: Soo-young Ye, Jun-mo Park, Jae-hyung Kim, Jae-hee Jung, Ah-young Jeon, In-cheol Kim, Jung-man Son, Ki-gon Nam, Seong-wan Baik, Jung-hoon Ro, Gye-rok Jeon

Abstract:

The linear SEF (Spectral Edge Frequency) parameter and spectrum analysis method can not reflect the non-linear of EEG. This method can not contribute to acquire real time analysis and obtain a high confidence in the clinic due to low discrimination. To solve the problems, the development of a new index is carried out using the bispectrum analyzing the EEG(electroencephalogram) including the non-linear characteristic. After analyzing the bispectrum of the 2 dimension, the most significant power spectrum density peaks appeared abundantly at the specific area in awakening and anesthesia state. These points are utilized to create the new index since many peaks appeared at the specific area in the frequency coordinate. The measured range of an index was 0-100. An index is 20-50 at an anesthesia, while the index is 90-60 at the awake. New index could afford to effectively discriminate the awake and anesthesia state.

Keywords: Bispectrum, anesthesia depth, EEG, SEF.

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3968 Ageing and Partial Discharge Patterns in Oil-Impregnated Paper and Pressboard Insulation at High Temperature

Authors: R. H. Khawaja, T. R. Blackburn, M. Rehan Arif

Abstract:

The power transformer is the most expensive, indispensable and arguably the most important equipment item in a power system Insulation failure in transformers can cause long term interruption to supply and loss of revenue and the condition assessment of the insulation is thus an important maintenance procedure. Oil-impregnated transformer insulation consists of mainly organic materials including mineral oil and cellulose-base paper and pressboard. The operating life of cellulose-based insulation, as with most organic insulation, depends heavily on its operating temperature rise above ambient. This paper reports results of a laboratory-based experimental investigation of partial discharge (PD) activity at high temperature in oil-impregnated insulation. The experiments reported here are part an on-going programme aimed at investigating the way in which insulation deterioration can be monitored and quantified by use of partial discharge diagnostics. Partial discharge patterns were recorded and analysed during increasing and decreasing phases of the temperature. The effect of ageing of the insulation on the PD patterns in oil and oil-impregnated insulation are also considered.

Keywords: Ageing, high temperature, PD, oil-impregnated insulation.

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3967 CFD Modeling of High Temperature Seal Chamber

Authors: Mikhail P. Strongin, Ragupathi Soundararajan

Abstract:

The purpose of this work is fast design optimization of the seal chamber. The study includes the mass transfer between lower and upper chamber on seal chamber for hot water application pumps. The use of Fluent 12.1 commercial code made it possible to capture complex flow with heat-mass transfer, radiation, Tailor instability, and buoyancy effect. Realizable k-epsilon model was used for turbulence modeling. Radiation heat losses were taken into account. The temperature distribution at seal region is predicted with respect to heat addition. Results show the possibilities of the model simplifications by excluding the water domain in low chamber from calculations. CFD simulations permit to improve seal chamber design to meet target water temperature around the seal. This study can be used for the analysis of different seal chamber configurations.

Keywords: CFD, heat transfer, seal chamber, high temperature water

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3966 Generation of 3D Models Obtained with Low-Cost RGB and Thermal Sensors Mounted on Drones

Authors: Julio Manuel de Luis Ruiz, Javier Sedano Cibrián, Rubén Pérez Álvarez, Raúl Pereda García, Felipe Piña García

Abstract:

Nowadays it is common to resort to aerial photography to carry out the prospection and/or exploration of archaeological sites. In recent years, Unmanned Aerial Vehicles (UAVs) have been applied as the vehicles that carry the sensor. This implies certain advantages, such as the possibility of including low-cost sensors, given that these vehicles can carry the sensor at relatively low altitudes. Due to this, low-cost dual sensors have recently begun to be used. This new equipment can collaborate with classic Digital Elevation Models (DEMs) in the exploration of archaeological sites, but this entails the need for a methodological setting to optimize the acquisition, processing and exploitation of the information provided by low-cost dual sensors. This research focuses on the design of an appropriate workflow to obtain 3D models with low-cost sensors carried on UAVs, both in the RGB and thermal domains. All the foregoing has been applied to the archaeological site of Juliobriga, located in Cantabria (Spain). To this end, a flight with this type of sensors has been planned, developed and analyzed. It has been applied to the archaeological site of Juliobriga (Cantabria, Spain). A strong dependence of the thermal sensor on the GSD, and the capability of this technique to interpret underground materials. This research allows to state that the thermal nature of the site does not provide main information about the site itself, but with combination with other types of information, such as the DEM, the typology of materials, etc., can produce very positive results with respect to the exploration and knowledge of the site. 

Keywords: process optimization, RGB models, thermal models, UAV, workflow

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3965 On Algebraic Structure of Improved Gauss-Seidel Iteration

Authors: O. M. Bamigbola, A. A. Ibrahim

Abstract:

Analysis of real life problems often results in linear systems of equations for which solutions are sought. The method to employ depends, to some extent, on the properties of the coefficient matrix. It is not always feasible to solve linear systems of equations by direct methods, as such the need to use an iterative method becomes imperative. Before an iterative method can be employed to solve a linear system of equations there must be a guaranty that the process of solution will converge. This guaranty, which must be determined apriori, involve the use of some criterion expressible in terms of the entries of the coefficient matrix. It is, therefore, logical that the convergence criterion should depend implicitly on the algebraic structure of such a method. However, in deference to this view is the practice of conducting convergence analysis for Gauss- Seidel iteration on a criterion formulated based on the algebraic structure of Jacobi iteration. To remedy this anomaly, the Gauss- Seidel iteration was studied for its algebraic structure and contrary to the usual assumption, it was discovered that some property of the iteration matrix of Gauss-Seidel method is only diagonally dominant in its first row while the other rows do not satisfy diagonal dominance. With the aid of this structure we herein fashion out an improved version of Gauss-Seidel iteration with the prospect of enhancing convergence and robustness of the method. A numerical section is included to demonstrate the validity of the theoretical results obtained for the improved Gauss-Seidel method.

Keywords: Linear system of equations, Gauss-Seidel iteration, algebraic structure, convergence.

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3964 Application of the Central-Difference with Half- Sweep Gauss-Seidel Method for Solving First Order Linear Fredholm Integro-Differential Equations

Authors: E. Aruchunan, J. Sulaiman

Abstract:

The objective of this paper is to analyse the application of the Half-Sweep Gauss-Seidel (HSGS) method by using the Half-sweep approximation equation based on central difference (CD) and repeated trapezoidal (RT) formulas to solve linear fredholm integro-differential equations of first order. The formulation and implementation of the Full-Sweep Gauss-Seidel (FSGS) and Half- Sweep Gauss-Seidel (HSGS) methods are also presented. The HSGS method has been shown to rapid compared to the FSGS methods. Some numerical tests were illustrated to show that the HSGS method is superior to the FSGS method.

Keywords: Integro-differential equations, Linear fredholm equations, Finite difference, Quadrature formulas, Half-Sweep iteration.

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3963 Optimization of Soy Epoxide Hydroxylation to Properties of Prepolymer Polyurethane

Authors: Flora Elvistia Firdaus

Abstract:

The epoxidation of soybean oil at temperature of 600C was provided the best result in terms of attaching the –OH functionality. Temperatures below and above 600C it is likely the attaching reaction did not proceed sufficiently fast. The considerable yield below 40%, implies the oil is not completely converted, it is not possible by conventional methods, because the epoxide decomposes at the temperature required. The objective of this work was the development of catalyst toward the conversion of epoxide and polyol with reaction temperature at 50,60, and 700C. The effect of different type of catalyst were studied, the effect of alcohols with different molecular configuration was determined which leads to selective addition of alcohols to the epoxide oils.

Keywords: optimization, epoxide, soybean, catalyst

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3962 Optimal Production Planning in Aromatic Coconuts Supply Chain Based On Mixed-Integer Linear Programming

Authors: Chaimongkol Limpianchob

Abstract:

This work addresses the problem of production planning that arises in the production of aromatic coconuts from Samudsakhorn province in Thailand. The planning involves the forwarding of aromatic coconuts from the harvest areas to the factory, which is classified into two groups; self-owned areas and contracted areas, the decisions of aromatic coconuts flow in the plant, and addressing a question of which warehouse will be in use. The problem is formulated as a mixed-integer linear programming model within supply chain management framework. The objective function seeks to minimize the total cost including the harvesting, labor and inventory costs. Constraints on the system include the production activities in the company and demand requirements. Numerical results are presented to demonstrate the feasibility of coconuts supply chain model compared with base case.

Keywords: Aromatic coconut, supply chain management, production planning, mixed-integer linear programming.

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3961 Liquid Chromatography Microfluidics for Detection and Quantification of Urine Albumin Using Linear Regression Method

Authors: Patricia B. Cruz, Catrina Jean G. Valenzuela, Analyn N. Yumang

Abstract:

Nearly a hundred per million of the Filipino population is diagnosed with Chronic Kidney Disease (CKD). The early stage of CKD has no symptoms and can only be discovered once the patient undergoes urinalysis. Over the years, different methods were discovered and used for the quantification of the urinary albumin such as the immunochemical assays where most of these methods require large machinery that has a high cost in maintenance and resources, and a dipstick test which is yet to be proven and is still debated as a reliable method in detecting early stages of microalbuminuria. This research study involves the use of the liquid chromatography concept in microfluidic instruments with biosensor as a means of separation and detection respectively, and linear regression to quantify human urinary albumin. The researchers’ main objective was to create a miniature system that quantifies and detect patients’ urinary albumin while reducing the amount of volume used per five test samples. For this study, 30 urine samples of unknown albumin concentrations were tested using VITROS Analyzer and the microfluidic system for comparison. Based on the data shared by both methods, the actual vs. predicted regression were able to create a positive linear relationship with an R2 of 0.9995 and a linear equation of y = 1.09x + 0.07, indicating that the predicted values and actual values are approximately equal. Furthermore, the microfluidic instrument uses 75% less in total volume – sample and reagents combined, compared to the VITROS Analyzer per five test samples.

Keywords: Chronic kidney disease, microfluidics, linear regression, VITROS analyzer, urinary albumin.

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3960 Some Results on Preconditioned Modified Accelerated Overrelaxation Method

Authors: Guangbin Wang, Deyu Sun, Fuping Tan

Abstract:

In this paper, we present new preconditioned modified accelerated overrelaxation (MAOR) method for solving linear systems. We compare the spectral radii of the iteration matrices of the preconditioned and the original methods. The comparison results show that the preconditioned MAOR method converges faster than the MAOR method whenever the MAOR method is convergent. Finally, we give one numerical example to confirm our theoretical results.

Keywords: preconditioned, MAOR method, linear system, convergence, comparison.

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3959 Prediction of Bath Temperature Using Neural Networks

Authors: H. Meradi, S. Bouhouche, M. Lahreche

Abstract:

In this work, we consider an application of neural networks in LD converter. Application of this approach assumes a reliable prediction of steel temperature and reduces a reblow ratio in steel work. It has been applied a conventional model to charge calculation, the obtained results by this technique are not always good, this is due to the process complexity. Difficulties are mainly generated by the noisy measurement and the process non linearities. Artificial Neural Networks (ANNs) have become a powerful tool for these complex applications. It is used a backpropagation algorithm to learn the neural nets. (ANNs) is used to predict the steel bath temperature in oxygen converter process for the end condition. This model has 11 inputs process variables and one output. The model was tested in steel work, the obtained results by neural approach are better than the conventional model.

Keywords: LD converter, bath temperature, neural networks.

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3958 Spatial Time Series Models for Rice and Cassava Yields Based On Bayesian Linear Mixed Models

Authors: Panudet Saengseedam, Nanthachai Kantanantha

Abstract:

This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.

Keywords: Bayesian method, Linear mixed model, Multivariate conditional autoregressive model, Spatial time series.

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3957 Tree-on-DAG for Data Aggregation in Sensor Networks

Authors: Prakash G L, Thejaswini M, S H Manjula, K R Venugopal, L M Patnaik

Abstract:

Computing and maintaining network structures for efficient data aggregation incurs high overhead for dynamic events where the set of nodes sensing an event changes with time. Moreover, structured approaches are sensitive to the waiting time that is used by nodes to wait for packets from their children before forwarding the packet to the sink. An optimal routing and data aggregation scheme for wireless sensor networks is proposed in this paper. We propose Tree on DAG (ToD), a semistructured approach that uses Dynamic Forwarding on an implicitly constructed structure composed of multiple shortest path trees to support network scalability. The key principle behind ToD is that adjacent nodes in a graph will have low stretch in one of these trees in ToD, thus resulting in early aggregation of packets. Based on simulations on a 2,000-node Mica2- based network, we conclude that efficient aggregation in large-scale networks can be achieved by our semistructured approach.

Keywords: Aggregation, Packet Merging, Query Processing.

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3956 Ion- Acoustic Solitary Waves in a Self- Gravitating Dusty Plasma Having Two-Temperature Electrons

Authors: S.N.Paul, G.Pakira, B.Paul, B.Ghosh

Abstract:

Nonlinear propagation of ion-acoustic waves in a selfgravitating dusty plasma consisting of warm positive ions, isothermal two-temperature electrons and negatively charged dust particles having charge fluctuations is studied using the reductive perturbation method. It is shown that the nonlinear propagation of ion-acoustic waves in such plasma can be described by an uncoupled third order partial differential equation which is a modified form of the usual Korteweg-deVries (KdV) equation. From this nonlinear equation, a new type of solution for the ion-acoustic wave is obtained. The effects of two-temperature electrons, gravity and dust charge fluctuations on the ion-acoustic solitary waves are discussed with possible applications.

Keywords: Charge fluctuations, gravitating dusty plasma, Ionacoustic solitary wave, Two-temperature electrons

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3955 An Iterative Algorithm for KLDA Classifier

Authors: D.N. Zheng, J.X. Wang, Y.N. Zhao, Z.H. Yang

Abstract:

The Linear discriminant analysis (LDA) can be generalized into a nonlinear form - kernel LDA (KLDA) expediently by using the kernel functions. But KLDA is often referred to a general eigenvalue problem in singular case. To avoid this complication, this paper proposes an iterative algorithm for the two-class KLDA. The proposed KLDA is used as a nonlinear discriminant classifier, and the experiments show that it has a comparable performance with SVM.

Keywords: Linear discriminant analysis (LDA), kernel LDA (KLDA), conjugate gradient algorithm, nonlinear discriminant classifier.

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3954 Material Characterization and Numerical Simulation of a Rubber Bumper

Authors: Tamás Mankovits, Dávid Huri, Imre Kállai, Imre Kocsis, Tamás Szabó

Abstract:

Non-linear FEM calculations are indispensable when important technical information like operating performance of a rubber component is desired. Rubber bumpers built into air-spring structures may undergo large deformations under load, which in itself shows non-linear behavior. The changing contact range between the parts and the incompressibility of the rubber increases this non-linear behavior further. The material characterization of an elastomeric component is also a demanding engineering task. In this paper a comprehensive investigation is introduced including laboratory measurements, mesh density analysis and complex finite element simulations to obtain the load-displacement curve of the chosen rubber bumper. Contact and friction effects are also taken into consideration. The aim of this research is to elaborate a FEM model which is accurate and competitive for a future shape optimization task.

Keywords: Rubber bumper, finite element analysis, compression test, Mooney-Rivlin material model.

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3953 Investigation of Fire Damaged Reinforced Concrete Walls with Axial Force

Authors: Hyun Ah Yoon, Ji Yeon Kang, Hee Sun Kim, Yeong Soo Shin

Abstract:

Reinforced concrete (RC) shear wall system of residential buildings is popular in South Korea. RC walls are subjected to axial forces in common and the effect of axial forces on the strength loss of the fire damaged walls has not been investigated. This paper aims at investigating temperature distribution on fire damaged concrete walls having different axial loads. In the experiments, a variable of specimens is axial force ratio. RC walls are fabricated with 150mm of wall thicknesses, 750mm of lengths and 1,300mm of heights having concrete strength of 24MPa. After curing, specimens are heated on one surface with ISO-834 standard time-temperature curve for 2 hours and temperature distributions during the test are measured using thermocouples inside the walls. The experimental results show that the temperature of the RC walls exposed to fire increases as axial force ratio increases. To verify the experiments, finite element (FE) models are generated for coupled temperature-structure analyses. The analytical results of thermal behaviors are in good agreement with the experimental results. The predicted displacement of the walls decreases when the axial force increases. 

Keywords: Axial force ratio, coupled analysis, fire, reinforced concrete wall, temperature distribution.

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3952 Yield Onset of Thermo-Mechanical Loading of FGM Thick Walled Cylindrical Pressure Vessels

Authors: S. Ansari Sadrabadi, G. H. Rahimi

Abstract:

In this paper, thick walled Cylindrical tanks or tubes made of functionally graded material under internal pressure and temperature gradient are studied. Material parameters have been considered as power functions. They play important role in the elastoplastic behavior of these materials. To clarify their role, different materials with different parameters have been used under temperature gradient. Finally, their effect and loading effect have been determined in first yield point. Also, the important role of temperature gradient was also shown. At the end the study has been results obtained from changes in the elastic modulus and yield stress. Also special attention is also given to the effects of this internal pressure and temperature gradient in the creation of tensile and compressive stresses.

Keywords: FGM, Cylindrical pressure tubes, Small deformation theory, Yield onset, Thermal loading.

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3951 Overview of CARDIOSENSOR Project on the Development of a Nanosensor for Assessing the Risk of Cardiovascular Disease

Authors: A.C. Duarte, C.I.L. Justino, K. Duarte, A.C. Freitas, R. Pereira, P. Chaves, P. Bettencourt, S. Cardoso, T.A.P. Rocha-Santos

Abstract:

This paper aims at overviewing the topics of a research project (CARDIOSENSOR) on the field of health sciences (biomaterials and biomedical engineering). The project has focused on the development of a nanosensor for the assessment of the risk of cardiovascular diseases by the monitoring of C-reactive protein (CRP), which has been currently considered as the best validated inflammatory biomarker associated to cardiovascular diseases. The project involves tasks such as: 1) the development of sensor devices based on field effect transistors (FET): assembly, optimization and validation; 2) application of sensors to the detection of CRP in standard solutions and comparison with enzyme-linked immunosorbent assay (ELISA); and 3) application of sensors to real samples such as blood and saliva and evaluation of their ability to predict the risk of cardiovascular disease.

Keywords: Carbon nanotubes field effect transistors, cardiovascular diseases, C-reactive protein, sensor.

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