Applying Element Free Galerkin Method on Beam and Plate

This paper develops a meshless approach, called Element Free Galerkin (EFG) method, which is based on the weak form Moving Least Squares (MLS) of the partial differential governing equations and employs the interpolation to construct the meshless shape functions. The variation weak form is used in the EFG where the trial and test functions are approximated bye the MLS approximation. Since the shape functions constructed by this discretization have the weight function property based on the randomly distributed points, the essential boundary conditions can be implemented easily. The local weak form of the partial differential governing equations is obtained by the weighted residual method within the simple local quadrature domain. The spline function with high continuity is used as the weight function. The presently developed EFG method is a truly meshless method, as it does not require the mesh, either for the construction of the shape functions, or for the integration of the local weak form. Several numerical examples of two-dimensional static structural analysis are presented to illustrate the performance of the present EFG method. They show that the EFG method is highly efficient for the implementation and highly accurate for the computation. The present method is used to analyze the static deflection of beams and plate hole

Kalman Filter Design in Structural Identification with Unknown Excitation

This article is about first step of structural health monitoring by identifying structural system in the presence of unknown input. In the structural system identification, identification of structural parameters such as stiffness and damping are considered. In this study, the Kalman filter (KF) design for structural systems with unknown excitation is expressed. External excitations, such as earthquakes, wind or any other forces are not measured or not available. The purpose of this filter is its strengths to estimate the state variables of the system in the presence of unknown input. Also least squares estimation (LSE) method with unknown input is studied. Estimates of parameters have been adopted. Finally, using two examples advantages and drawbacks of both methods are studied.

Massively-Parallel Bit-Serial Neural Networks for Fast Epilepsy Diagnosis: A Feasibility Study

There are about 1% of the world population suffering from the hidden disability known as epilepsy and major developing countries are not fully equipped to counter this problem. In order to reduce the inconvenience and danger of epilepsy, different methods have been researched by using a artificial neural network (ANN) classification to distinguish epileptic waveforms from normal brain waveforms. This paper outlines the aim of achieving massive ANN parallelization through a dedicated hardware using bit-serial processing. The design of this bit-serial Neural Processing Element (NPE) is presented which implements the functionality of a complete neuron using variable accuracy. The proposed design has been tested taking into consideration non-idealities of a hardware ANN. The NPE consists of a bit-serial multiplier which uses only 16 logic elements on an Altera Cyclone IV FPGA and a bit-serial ALU as well as a look-up table. Arrays of NPEs can be driven by a single controller which executes the neural processing algorithm. In conclusion, the proposed compact NPE design allows the construction of complex hardware ANNs that can be implemented in a portable equipment that suits the needs of a single epileptic patient in his or her daily activities to predict the occurrences of impending tonic conic seizures.

A Method for Modeling Flexible Manipulators: Transfer Matrix Method with Finite Segments

This paper presents a computationally efficient method for the modeling of robot manipulators with flexible links and joints. This approach combines the Discrete Time Transfer Matrix Method with the Finite Segment Method, in which the flexible links are discretized by a number of rigid segments connected by torsion springs; and the flexibility of joints are modeled by torsion springs. The proposed method avoids the global dynamics and has the advantage of modeling non-uniform manipulators. Experiments and simulations of a single-link flexible manipulator are conducted for verifying the proposed methodologies. The simulations of a three-link robot arm with links and joints flexibility are also performed.

From Research to Teaching: Integrating Social Robotics in Engineering Degrees

When industrial robotics subject is taught in a degree in robotics, social and humanoid robotics concepts are rarely mentioned because this field of robotics is not used in industry. In this paper, an educational project related with industrial robotics is presented which includes social and humanoid robotics. The main motivations to realize this research are: i) humanoid robotics will be appearing soon in industry, the experience, based on research projects, indicates their deployment sooner than expected; ii) its educational interest, technology is shared with industrial robotics; iii) it is very attractive, students are interested in this part of the subject and thus they are interested in the whole subject. As a pedagogical methodology, the use of the problem-based learning is considered. Those concepts are introduced in a seminar during the last part of the subject and developed as a set of practices in the laboratory.

Optimization of Process Parameters in Wire Electrical Discharge Machining of Inconel X-750 for Dimensional Deviation Using Taguchi Technique

The effective optimization of machining process parameters affects dramatically the cost and production time of machined components as well as the quality of the final products. This paper presents the optimization aspects of a Wire Electrical Discharge Machining operation using Inconel X-750 as work material. The objective considered in this study is minimization of the dimensional deviation. Six input process parameters of WEDM namely spark gap voltage, pulse-on time, pulse-off time, wire feed rate, peak current and wire tension, were chosen as variables to study the process performance. Taguchi's design of experiments methodology has been used for planning and designing the experiments. The analysis of variance was carried out for raw data as well as for signal to noise ratio. Four input parameters and one two-factor interaction have been found to be statistically significant for their effects on the response of interest. The confirmation experiments were also performed for validating the predicted results.

Despiking of Turbulent Flow Data in Gravel Bed Stream

The present experimental study insights the decontamination of instantaneous velocity fluctuations captured by Acoustic Doppler Velocimeter (ADV) in gravel-bed streams to ascertain near-bed turbulence for low Reynolds number. The interference between incidental and reflected pulses produce spikes in the ADV data especially in the near-bed flow zone and therefore filtering the data are very essential. Nortek’s Vectrino four-receiver ADV probe was used to capture the instantaneous three-dimensional velocity fluctuations over a non-cohesive bed. A spike removal algorithm based on the acceleration threshold method was applied to note the bed roughness and its influence on velocity fluctuations and velocity power spectra in the carrier fluid. The velocity power spectra of despiked signals with a best combination of velocity threshold (VT) and acceleration threshold (AT) are proposed which ascertained velocity power spectra a satisfactory fit with the Kolmogorov “–5/3 scaling-law” in the inertial sub-range. Also, velocity distributions below the roughness crest level fairly follows a third-degree polynomial series.

NiO-CeO2 Nano-Catalyst for the Removal of Priority Organic Pollutants from Wastewater through Catalytic Wet Air Oxidation at Mild Conditions

Catalytic wet air oxidation (CWAO) is normally carried out at elevated temperature and pressure. This work investigates the potential of NiO-CeO2 nano-catalyst in CWAO of paper industry wastewater under milder operating conditions of 90 °C and 1 atm. The NiO-CeO2 nano-catalysts were synthesized by a simple co-precipitation method and characterized by X-ray diffraction (XRD), before and after use, in order to study any crystallographic change during experiment. The extent of metal-leaching from the catalyst was determined using the inductively coupled plasma optical emission spectrometry (ICP-OES). The catalytic activity of nano-catalysts was studied in terms of total organic carbon (TOC), adsorbable organic halides (AOX) and chlorophenolics (CHPs) removal. Interestingly, mixed oxide catalysts exhibited higher activity than the corresponding single-metal oxides. The maximum removal efficiency was achieved with Ce40Ni60 catalyst. The results indicate that the CWAO process is efficient in removing the priority organic pollutants from wastewater, as it exhibited up to 59% TOC, 55% AOX, and 54 % CHPs removal.

Analysis of Residual Stresses and Angular Distortion in Stiffened Cylindrical Shell Fillet Welds Using Finite Element Method

In this paper, a two-dimensional method is developed to simulate the fillet welds in a stiffened cylindrical shell, using finite element method. The stiffener material is aluminum 2519. The thermo-elasto-plastic analysis is used to analyze the thermo-mechanical behavior. Due to the high heat flux rate of the welding process, two uncouple thermal and mechanical analysis are carried out instead of performing a single couple thermo-mechanical simulation. In order to investigate the effects of the welding procedures, two different welding techniques are examined. The resulted residual stresses and distortions due to different welding procedures are obtained. Furthermore, this study employed the technique of element birth and death to simulate the weld filler variation with time in fillet welds. The obtained results are in good agreement with the published experimental and three-dimensional numerical simulation results. Therefore, the proposed 2D modeling technique can effectively give the corresponding results of 3D models. Furthermore, by inspection of the obtained residual hoop and transverse stresses and angular distortions, proper welding procedure is suggested.

A Hybrid Gene Selection Technique Using Improved Mutual Information and Fisher Score for Cancer Classification Using Microarrays

Feature Selection is significant in order to perform constructive classification in the area of cancer diagnosis. However, a large number of features compared to the number of samples makes the task of classification computationally very hard and prone to errors in microarray gene expression datasets. In this paper, we present an innovative method for selecting highly informative gene subsets of gene expression data that effectively classifies the cancer data into tumorous and non-tumorous. The hybrid gene selection technique comprises of combined Mutual Information and Fisher score to select informative genes. The gene selection is validated by classification using Support Vector Machine (SVM) which is a supervised learning algorithm capable of solving complex classification problems. The results obtained from improved Mutual Information and F-Score with SVM as a classifier has produced efficient results.

Dependence of Densification, Hardness and Wear Behaviors of Ti6Al4V Powders on Sintering Temperature

The sintering step in powder metallurgy (P/M) processes is very sensitive as it determines to a large extent the properties of the final component produced. Spark plasma sintering over the past decade has been extensively used in consolidating a wide range of materials including metallic alloy powders. This novel, non-conventional sintering method has proven to be advantageous offering full densification of materials, high heating rates, low sintering temperatures, and short sintering cycles over conventional sintering methods. Ti6Al4V has been adjudged the most widely used α+β alloy due to its impressive mechanical performance in service environments, especially in the aerospace and automobile industries being a light metal alloy with the capacity for fuel efficiency needed in these industries. The P/M route has been a promising method for the fabrication of parts made from Ti6Al4V alloy due to its cost and material loss reductions and the ability to produce near net and intricate shapes. However, the use of this alloy has been largely limited owing to its relatively poor hardness and wear properties. The effect of sintering temperature on the densification, hardness, and wear behaviors of spark plasma sintered Ti6Al4V powders was investigated in this present study. Sintering of the alloy powders was performed in the 650–850°C temperature range at a constant heating rate, applied pressure and holding time of 100°C/min, 50 MPa and 5 min, respectively. Density measurements were carried out according to Archimedes’ principle and microhardness tests were performed on sectioned as-polished surfaces at a load of 100gf and dwell time of 15 s. Dry sliding wear tests were performed at varied sliding loads of 5, 15, 25 and 35 N using the ball-on-disc tribometer configuration with WC as the counterface material. Microstructural characterization of the sintered samples and wear tracks were carried out using SEM and EDX techniques. The density and hardness characteristics of sintered samples increased with increasing sintering temperature. Near full densification (99.6% of the theoretical density) and Vickers’ micro-indentation hardness of 360 HV were attained at 850°C. The coefficient of friction (COF) and wear depth improved significantly with increased sintering temperature under all the loading conditions examined, except at 25 N indicating better mechanical properties at high sintering temperatures. Worn surface analyses showed the wear mechanism was a synergy of adhesive and abrasive wears, although the former was prevalent.

Automatic Detection of Defects in Ornamental Limestone Using Wavelets

A methodology based on wavelets is proposed for the automatic location and delimitation of defects in limestone plates. Natural defects include dark colored spots, crystal zones trapped in the stone, areas of abnormal contrast colors, cracks or fracture lines, and fossil patterns. Although some of these may or may not be considered as defects according to the intended use of the plate, the goal is to pair each stone with a map of defects that can be overlaid on a computer display. These layers of defects constitute a database that will allow the preliminary selection of matching tiles of a particular variety, with specific dimensions, for a requirement of N square meters, to be done on a desktop computer rather than by a two-hour search in the storage park, with human operators manipulating stone plates as large as 3 m x 2 m, weighing about one ton. Accident risks and work times are reduced, with a consequent increase in productivity. The base for the algorithm is wavelet decomposition executed in two instances of the original image, to detect both hypotheses – dark and clear defects. The existence and/or size of these defects are the gauge to classify the quality grade of the stone products. The tuning of parameters that are possible in the framework of the wavelets corresponds to different levels of accuracy in the drawing of the contours and selection of the defects size, which allows for the use of the map of defects to cut a selected stone into tiles with minimum waste, according the dimension of defects allowed.

Current Developments in Flat-Plate Vacuum Solar Thermal Collectors

Vacuum flat plate solar thermal collectors offer several advantages over other collectors namely the excellent optical and thermal characteristics they exhibit due to a combination of their wide surface area and high vacuum thermal insulation. These characteristics can offer a variety of applications for industrial process heat as well as for building integration as they are much thinner than conventional collectors making installation possible in limited spaces. However, many technical challenges which need to be addressed to enable wide scale adoption of the technology still remain. This paper will discuss the challenges, expectations and requirements for the flat-plate vacuum solar collector development. In addition, it will provide an overview of work undertaken in Ulster University, Loughborough University, and the University of Warwick on flat-plate vacuum solar thermal collectors. Finally, this paper will present a detailed experimental investigation on the development of a vacuum panel with a novel sealing method which will be used to accommodate a novel slim hydroformed solar absorber.

Mental Health Surveys on Community and Organizational Levels: Challenges, Issues, Conclusions and Possibilities

In addition to the fact that mental health bears great significance to a particular individual, it can also be regarded as an organizational, community and societal resource. Within the Szeged Health Promotion Research Group, we conducted mental health surveys on two levels: The inhabitants of a medium-sized Hungarian town and students of a Hungarian university with a relatively big headcount were requested to participate in surveys whose goals were to define local government priorities and organization-level health promotion programmes, respectively. To facilitate professional decision-making, we defined three, pragmatically relevant, groups of the target population: the mentally healthy, the vulnerable and the endangered. In order to determine which group a person actually belongs to, we designed a simple and quick measurement tool, which could even be utilised as a smoothing method, the Mental State Questionnaire validity of the above three categories was verified by analysis of variance against psychological quality of life variables. We demonstrate the pragmatic significance of our method via the analyses of the scores of our two mental health surveys. On town level, during our representative survey in Hódmezővásárhely (N=1839), we found that 38.7% of the participants was mentally healthy, 35.3% was vulnerable, while 16.3% was considered as endangered. We were able to identify groups that were in a dramatic state in terms of mental health. For example, such a group consisted of men aged 45 to 64 with only primary education qualification and the ratios of the mentally healthy, vulnerable and endangered were 4.5, 45.5 and 50%, respectively. It was also astonishing to see to what a little extent qualification prevailed as a protective factor in the case of women. Based on our data, the female group aged 18 to 44 with primary education—of whom 20.3% was mentally healthy, 42.4% vulnerable and 37.3% was endangered—as well as the female group aged 45 to 64 with university or college degree—of whom 25% was mentally healthy, 51.3 vulnerable and 23.8% endangered—are to be handled as priority intervention target groups in a similarly difficult position. On organizational level, our survey involving the students of the University of Szeged, N=1565, provided data to prepare a strategy of mental health promotion for a university with a headcount exceeding 20,000. When developing an organizational strategy, it was important to gather information to estimate the proportions of target groups in which mental health promotion methods; for example, life management skills development, detection, psychological consultancy, psychotherapy, would be applied. Our scores show that 46.8% of the student participants were mentally healthy, 42.1% were vulnerable and 11.1% were endangered. These data convey relevant information as to the allocation of organizational resources within a university with a considerable headcount. In conclusion, The Mental State Questionnaire, as a valid smoothing method, is adequate to describe a community in a plain and informative way in the terms of mental health. The application of the method can promote the preparation, design and implementation of mental health promotion interventions. 

Selection of Designs in Ordinal Regression Models under Linear Predictor Misspecification

The purpose of this article is to find a method of comparing designs for ordinal regression models using quantile dispersion graphs in the presence of linear predictor misspecification. The true relationship between response variable and the corresponding control variables are usually unknown. Experimenter assumes certain form of the linear predictor of the ordinal regression models. The assumed form of the linear predictor may not be correct always. Thus, the maximum likelihood estimates (MLE) of the unknown parameters of the model may be biased due to misspecification of the linear predictor. In this article, the uncertainty in the linear predictor is represented by an unknown function. An algorithm is provided to estimate the unknown function at the design points where observations are available. The unknown function is estimated at all points in the design region using multivariate parametric kriging. The comparison of the designs are based on a scalar valued function of the mean squared error of prediction (MSEP) matrix, which incorporates both variance and bias of the prediction caused by the misspecification in the linear predictor. The designs are compared using quantile dispersion graphs approach. The graphs also visually depict the robustness of the designs on the changes in the parameter values. Numerical examples are presented to illustrate the proposed methodology.

Analysis of the Evolution of Social and Economic Indicators of the Mercosur´s Members: 1980-2012

The objective of this study is to analyze the evolution of some social and economic indicators of Mercosur´s economies from 1980 to 2012, based on the statistics of the Latin American Integration Association (LAIA). The objective is to observe if after the accession of these economies to Mercosur (the first accessions occurred in 1994) these indicators showed better performance, in order to demonstrate if economic integration contributed to improved trade, macroeconomic performance, and level of social and economic development of member countries. To this end, the methodologies used will be a literature review and descriptive statistics. The theoretical framework that guides the work are the theories of Integration: Classical Liberal, Marxist and structural-proactive. The results reveal that most social and economic indicators showed better performance in those economies that joined Mercosur after 1994. This work is the result of an investigation already completed.

Comparison between Deterministic and Probabilistic Stability Analysis, Featuring Consequent Risk Assessment

Slope stability analyses are largely carried out by deterministic methods and evaluated through a single security factor. Although it is known that the geotechnical parameters can present great dispersal, such analyses are considered fixed and known. The probabilistic methods, in turn, incorporate the variability of input key parameters (random variables), resulting in a range of values of safety factors, thus enabling the determination of the probability of failure, which is an essential parameter in the calculation of the risk (probability multiplied by the consequence of the event). Among the probabilistic methods, there are three frequently used methods in geotechnical society: FOSM (First-Order, Second-Moment), Rosenblueth (Point Estimates) and Monte Carlo. This paper presents a comparison between the results from deterministic and probabilistic analyses (FOSM method, Monte Carlo and Rosenblueth) applied to a hypothetical slope. The end was held to evaluate the behavior of the slope and consequent risk analysis, which is used to calculate the risk and analyze their mitigation and control solutions. It can be observed that the results obtained by the three probabilistic methods were quite close. It should be noticed that the calculation of the risk makes it possible to list the priority to the implementation of mitigation measures. Therefore, it is recommended to do a good assessment of the geological-geotechnical model incorporating the uncertainty in viability, design, construction, operation and closure by means of risk management. 

Employing QR Code as an Effective Educational Tool for Quick Access to Sources of Kindergarten Concepts

This study discusses a simple solution for the problem of shortage in learning resources for kindergarten teachers. Occasionally, kindergarten teachers cannot access proper resources by usual search methods as libraries or search engines. Furthermore, these methods require a long time and efforts for preparing. The study is expected to facilitate accessing learning resources. Moreover, it suggests a potential direction for using QR code inside the classroom. The present work proposes that QR code can be used for digitizing kindergarten curriculums and accessing various learning resources. It investigates using QR code for saving information related to the concepts which kindergarten teachers use in the current educational situation. The researchers have established a guide for kindergarten teachers based on the Egyptian official curriculum. The guide provides different learning resources for each scientific and mathematical concept in the curriculum, and each learning resource is represented as a QR code image that contains its URL. Therefore, kindergarten teachers can use smartphone applications for reading QR codes and displaying the related learning resources for students immediately. The guide has been provided to a group of 108 teachers for using inside their classrooms. The results showed that the teachers approved the guide, and gave a good response.

Numerical Analysis and Influence of the Parameters on Slope Stability

A designing of a structure requires its realization on rough or sloping ground. Besides the problem of the stability of the landslide, the behavior of the foundations that are bearing the structure is influenced by the destabilizing effect of the ground’s slope. This article focuses on the analysis of the slope stability exposed to loading by introducing the different factors influencing the slope’s behavior on the one hand, and on the influence of this slope on the foundation’s behavior on the other hand. This study is about the elastoplastic modelization using FLAC 2D. This software is based on the finite difference method, which is one of the older methods of numeric resolution of differential equations system with initial and boundary conditions. It was developed for the geotechnical simulation calculation. The aim of this simulation is to demonstrate the notable effect of shear modulus « G », cohesion « C », inclination angle (edge) « β », and distance between the foundation and the head of the slope on the stability of the slope as well as the stability of the foundation. In our simulation, the slope is constituted by homogenous ground. The foundation is considered as rigid/hard; therefore, the loading is made by the application of the vertical strengths on the nodes which represent the contact between the foundation and the ground. 

Disaggregating and Forecasting the Total Energy Consumption of a Building: A Case Study of a High Cooling Demand Facility

Energy disaggregation has been focused by many energy companies since energy efficiency can be achieved when the breakdown of energy consumption is known. Companies have been investing in technologies to come up with software and/or hardware solutions that can provide this type of information to the consumer. On the other hand, not all people can afford to have these technologies. Therefore, in this paper, we present a methodology for breaking down the aggregate consumption and identifying the highdemanding end-uses profiles. These energy profiles will be used to build the forecast model for optimal control purpose. A facility with high cooling load is used as an illustrative case study to demonstrate the results of proposed methodology. We apply a high level energy disaggregation through a pattern recognition approach in order to extract the consumption profile of its rooftop packaged units (RTUs) and present a forecast model for the energy consumption.