On the EM Algorithm and Bootstrap Approach Combination for Improving Satellite Image Fusion

This paper discusses EM algorithm and Bootstrap approach combination applied for the improvement of the satellite image fusion process. This novel satellite image fusion method based on estimation theory EM algorithm and reinforced by Bootstrap approach was successfully implemented and tested. The sensor images are firstly split by a Bayesian segmentation method to determine a joint region map for the fused image. Then, we use the EM algorithm in conjunction with the Bootstrap approach to develop the bootstrap EM fusion algorithm, hence producing the fused targeted image. We proposed in this research to estimate the statistical parameters from some iterative equations of the EM algorithm relying on a reference of representative Bootstrap samples of images. Sizes of those samples are determined from a new criterion called 'hybrid criterion'. Consequently, the obtained results of our work show that using the Bootstrap EM (BEM) in image fusion improve performances of estimated parameters which involve amelioration of the fused image quality; and reduce the computing time during the fusion process.

Evolutionary Techniques Based Combined Artificial Neural Networks for Peak Load Forecasting

This paper presents a new approach using Combined Artificial Neural Network (CANN) module for daily peak load forecasting. Five different computational techniques –Constrained method, Unconstrained method, Evolutionary Programming (EP), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) – have been used to identify the CANN module for peak load forecasting. In this paper, a set of neural networks has been trained with different architecture and training parameters. The networks are trained and tested for the actual load data of Chennai city (India). A set of better trained conventional ANNs are selected to develop a CANN module using different algorithms instead of using one best conventional ANN. Obtained results using CANN module confirm its validity.

Implementation and Analysis of Elliptic Curve Cryptosystems over Polynomial basis and ONB

Polynomial bases and normal bases are both used for elliptic curve cryptosystems, but field arithmetic operations such as multiplication, inversion and doubling for each basis are implemented by different methods. In general, it is said that normal bases, especially optimal normal bases (ONB) which are special cases on normal bases, are efficient for the implementation in hardware in comparison with polynomial bases. However there seems to be more examined by implementing and analyzing these systems under similar condition. In this paper, we designed field arithmetic operators for each basis over GF(2233), which field has a polynomial basis recommended by SEC2 and a type-II ONB both, and analyzed these implementation results. And, in addition, we predicted the efficiency of two elliptic curve cryptosystems using these field arithmetic operators.

The Index of Sustainable Functionality: An Application for Measuring Sustainability

The index of sustainable functionality (ISF) is an adaptive, multi-criteria technique that is used to measure sustainability; it is a concept that can be transposed to many regions throughout the world. An ISF application of the Southern Regional Organisation of Councils (SouthROC) in South East Queensland (SEQ) – the fastest growing region in Australia – indicated over a 25 year period an increase of over 10% level of functionality from 58.0% to 68.3%. The ISF of SouthROC utilised methodologies that derived from an expert panel based approach. The overall results attained an intermediate level of functionality which amounted to related concerns of economic progress and lack of social awareness. Within the region, a solid basis for future testing by way of measured changes and developed trends can be established. In this regard as management tool, the ISF record offers support for regional sustainability practice and decision making alike. This research adaptively analyses sustainability – a concept that is lacking throughout much of the academic literature and any reciprocal experimentation. This lack of knowledge base has been the emphasis of where future sustainability research can grow from and prove useful in rapidly growing regions. It is the intentions of this research to help further develop the notions of index-based quantitative sustainability.

Influence of Silica Fume on High Strength Lightweight Concrete

The main objective of this paper is to determine the isolated effect of silica fume on tensile, compressive and flexure strengths on high strength lightweight concrete. Many experiments were carried out by replacing cement with different percentages of silica fume at different constant water-binder ratio keeping other mix design variables constant. The silica fume was replaced by 0%, 5%, 10%, 15%, 20% and 25% for a water-binder ratios ranging from 0.26 to 0.42. For all mixes, split tensile, compressive and flexure strengths were determined at 28 days. The results showed that the tensile, compressive and flexure strengths increased with silica fume incorporation but the optimum replacement percentage is not constant because it depends on the water–cementitious material (w/cm) ratio of the mix. Based on the results, a relationship between split tensile, compressive and flexure strengths of silica fume concrete was developed using statistical methods.

Combined Sewer Overflow forecasting with Feed-forward Back-propagation Artificial Neural Network

A feed-forward, back-propagation Artificial Neural Network (ANN) model has been used to forecast the occurrences of wastewater overflows in a combined sewerage reticulation system. This approach was tested to evaluate its applicability as a method alternative to the common practice of developing a complete conceptual, mathematical hydrological-hydraulic model for the sewerage system to enable such forecasts. The ANN approach obviates the need for a-priori understanding and representation of the underlying hydrological hydraulic phenomena in mathematical terms but enables learning the characteristics of a sewer overflow from the historical data. The performance of the standard feed-forward, back-propagation of error algorithm was enhanced by a modified data normalizing technique that enabled the ANN model to extrapolate into the territory that was unseen by the training data. The algorithm and the data normalizing method are presented along with the ANN model output results that indicate a good accuracy in the forecasted sewer overflow rates. However, it was revealed that the accurate forecasting of the overflow rates are heavily dependent on the availability of a real-time flow monitoring at the overflow structure to provide antecedent flow rate data. The ability of the ANN to forecast the overflow rates without the antecedent flow rates (as is the case with traditional conceptual reticulation models) was found to be quite poor.

A Study on the Application of TRIZ to CAD/CAM System

This study created new graphical icons and operating functions in a CAD/CAM software system by analyzing icons in some of the popular systems, such as AutoCAD, AlphaCAM, Mastercam and the 1st edition of LiteCAM. These software systems all focused on geometric design and editing, thus how to transmit messages intuitively from icon itself to users is an important function of graphical icons. The primary purpose of this study is to design innovative icons and commands for new software. This study employed the TRIZ method, an innovative design method, to generate new concepts systematically. Through literature review, it then investigated and analyzed the relationship between TRIZ and idea development. Contradiction Matrix and 40 Principles were used to develop an assisting tool suitable for icon design in software development. We first gathered icon samples from the selected CAD/CAM systems. Then grouped these icons by meaningful functions, and compared useful and harmful properties. Finally, we developed new icons for new software systems in order to avoid intellectual property problem.

Arriving at an Optimum Value of Tolerance Factor for Compressing Medical Images

Medical imaging uses the advantage of digital technology in imaging and teleradiology. In teleradiology systems large amount of data is acquired, stored and transmitted. A major technology that may help to solve the problems associated with the massive data storage and data transfer capacity is data compression and decompression. There are many methods of image compression available. They are classified as lossless and lossy compression methods. In lossy compression method the decompressed image contains some distortion. Fractal image compression (FIC) is a lossy compression method. In fractal image compression an image is coded as a set of contractive transformations in a complete metric space. The set of contractive transformations is guaranteed to produce an approximation to the original image. In this paper FIC is achieved by PIFS using quadtree partitioning. PIFS is applied on different images like , Ultrasound, CT Scan, Angiogram, X-ray, Mammograms. In each modality approximately twenty images are considered and the average values of compression ratio and PSNR values are arrived. In this method of fractal encoding, the parameter, tolerance factor Tmax, is varied from 1 to 10, keeping the other standard parameters constant. For all modalities of images the compression ratio and Peak Signal to Noise Ratio (PSNR) are computed and studied. The quality of the decompressed image is arrived by PSNR values. From the results it is observed that the compression ratio increases with the tolerance factor and mammogram has the highest compression ratio. The quality of the image is not degraded upto an optimum value of tolerance factor, Tmax, equal to 8, because of the properties of fractal compression.

CFD Simulation and Validation of Flap Type Wave-Maker

A general purpose viscous flow solver Ansys CFX was used to solve the unsteady three-dimensional (3D) Reynolds Averaged Navier-Stokes Equation (RANSE) for simulating a 3D numerical viscous wave tank. A flap-type wave generator was incorporated in the computational domain to generate the desired incident waves. Authors have made effort to study the physical behaviors of Flap type wave maker with governing parameters. Dependency of the water fill depth, Time period of oscillations and amplitude of oscillations of flap were studied. Effort has been made to establish relations between parameters. A validation study was also carried out against CFD methodology with wave maker theory. It has been observed that CFD results are in good agreement with theoretical results. Beaches of different slopes were introduced to damp the wave, so that it should not cause any reflection from boundary. As a conclusion this methodology can simulate the experimental wave-maker for regular wave generation for different wave length and amplitudes.

Systematic Functional Analysis Methods for Design Retrieval and Documentation

Apart from geometry, functionality is one of the most significant hallmarks of a product. The functionality of a product can be considered as the fundamental justification for a product existence. Therefore a functional analysis including a complete and reliable descriptor has a high potential to improve product development process in various fields especially in knowledge-based design. One of the important applications of the functional analysis and indexing is in retrieval and design reuse concept. More than 75% of design activity for a new product development contains reusing earlier and existing design know-how. Thus, analysis and categorization of product functions concluded by functional indexing, influences directly in design optimization. This paper elucidates and evaluates major classes for functional analysis by discussing their major methods. Moreover it is finalized by presenting a noble hybrid approach for functional analysis.

Identification, Prediction and Detection of the Process Fault in a Cement Rotary Kiln by Locally Linear Neuro-Fuzzy Technique

In this paper, we use nonlinear system identification method to predict and detect process fault of a cement rotary kiln. After selecting proper inputs and output, an input-output model is identified for the plant. To identify the various operation points in the kiln, Locally Linear Neuro-Fuzzy (LLNF) model is used. This model is trained by LOLIMOT algorithm which is an incremental treestructure algorithm. Then, by using this method, we obtained 3 distinct models for the normal and faulty situations in the kiln. One of the models is for normal condition of the kiln with 15 minutes prediction horizon. The other two models are for the two faulty situations in the kiln with 7 minutes prediction horizon are presented. At the end, we detect these faults in validation data. The data collected from White Saveh Cement Company is used for in this study.

Photovoltaic Array Sizing for PV-Electrolyzer

Hydrogen that used as fuel in fuel cell vehicles can be produced from renewable sources such as wind, solar, and hydro technologies. PV-electrolyzer is one of the promising methods to produce hydrogen with zero pollution emission. Hydrogen production from a PV-electrolyzer system depends on the efficiency of the electrolyzer and photovoltaic array, and sun irradiance at that site. In this study, the amount of hydrogen is obtained using mathematical equations for difference driving distance and sun peak hours. The results show that the minimum of 99 PV modules are used to generate 1.75 kgH2 per day for two vehicles.

Spatial Variability of Some Soil Properties in Mountain Rangelands of Northern Iran

In this paper spatial variability of some chemical and physical soil properties were investigated in mountain rangelands of Nesho, Mazandaran province, Iran. 110 soil samples from 0-30 cm depth were taken with systematic method on grid 30×30 m2 in regions with different vegetation cover and transported to laboratory. Then soil chemical and physical parameters including Acidity (pH), Electrical conductivity, Caco3, Bulk density, Particle density, total phosphorus, total Nitrogen, available potassium, Organic matter, Saturation moisture, Soil texture (percentage of sand, silt and clay), Sodium, Calcium, magnesium were measured in laboratory. Data normalization was performed then was done statistical analysis for description of soil properties and geostatistical analysis for indication spatial correlation between these properties and were perpetrated maps of spatial distribution of soil properties using Kriging method. Results indicated that in the study area Saturation moisture and percentage of Sand had highest and lowest spatial correlation respectively.

A Review of Methods for 2D/3D Registration

2D/3D registration is a special case of medical image registration which is of particular interest to surgeons. Applications of 2D/3D registration are [1] radiotherapy planning and treatment verification, spinal surgery, hip replacement, neurointerventions and aortic stenting. The purpose of this paper is to provide a literature review of the main methods for image registration for the 2D/3D case. At the end of the paper an algorithm is proposed for 2D/3D registration based on the Chebyssev polynomials iteration loop.

Actionable Rules: Issues and New Directions

Knowledge Discovery in Databases (KDD) is the process of extracting previously unknown, hidden and interesting patterns from a huge amount of data stored in databases. Data mining is a stage of the KDD process that aims at selecting and applying a particular data mining algorithm to extract an interesting and useful knowledge. It is highly expected that data mining methods will find interesting patterns according to some measures, from databases. It is of vital importance to define good measures of interestingness that would allow the system to discover only the useful patterns. Measures of interestingness are divided into objective and subjective measures. Objective measures are those that depend only on the structure of a pattern and which can be quantified by using statistical methods. While, subjective measures depend only on the subjectivity and understandability of the user who examine the patterns. These subjective measures are further divided into actionable, unexpected and novel. The key issues that faces data mining community is how to make actions on the basis of discovered knowledge. For a pattern to be actionable, the user subjectivity is captured by providing his/her background knowledge about domain. Here, we consider the actionability of the discovered knowledge as a measure of interestingness and raise important issues which need to be addressed to discover actionable knowledge.

Effects of Natural Frequency and Rotational Speed on Dynamic Stress in Spur Gear

Natural frequencies and dynamic response of a spur gear sector are investigated using a two dimensional finite element model that offers significant advantages for dynamic gear analyses. The gear teeth are analyzed for different operating speeds. A primary feature of this modeling is determination of mesh forces using a detailed contact analysis for each time step as the gears roll through the mesh. Transient mode super position method has been used to find horizontal and vertical components of displacement and dynamic stress. The finite element analysis software ANSYS has been used on the proposed model to find the natural frequencies by Block Lanczos technique and displacements and dynamic stresses by transient mode super position method. A comparison of theoretical (natural frequency and static stress) results with the finite element analysis results has also been done. The effect of rotational speed of the gears on the dynamic response of gear tooth has been studied and design limits have been discussed.

Heat Transfer in a Parallel-Plate Enclosure with Graded-Index Coatings on its Walls

A numerical study on the heat transfer in the thermal barrier coatings and the substrates of a parallel-plate enclosure is carried out. Some of the thermal barrier coatings, such as ceramics, are semitransparent and are of interest for high-temperature applications where radiation effects are significant. The radiative transfer equations and the energy equations are solved by using the discrete ordinates method and the finite difference method. Illustrative results are presented for temperature distributions in the coatings and the opaque walls under various heating conditions. The results show that the temperature distribution is more uniform in the interior portion of each coating away from its boundary for the case with a larger average of varying refractive index and a positive gradient of refractive index enhances radiative transfer to the substrates.

Fabrication and Characterization of CdS Nanoparticles Annealed by using Different Radiations

The systematic manipulations of shapes and sizes of inorganic compounds greatly benefit the various application fields including optics, magnetic, electronics, catalysis and medicine. However shape control has been much more difficult to achieve. Hence exploration of novel method for the preparation of differently shaped nanoparticles is challenging research area. II-VI group of semiconductor cadmium sulphide (CdS) nanostructure with different morphologies (such as, acicular like, mesoporous, spherical shapes) and of crystallite sizes vary from 11 to 16 nm were successfully synthesized by chemical aqueous precipitation of Cd2+ ions with homogeneously released S2- ions from decomposition of cadmium sulphate (CdSO4) and thioacetamide (CH3CSNH2) by annealing at different radiations (microwave, ultrasonic and sunlight) with matter and systematic research has been done for various factors affecting the controlled growth rate of CdS nanoparticles. The obtained nanomaterials have been characterized by X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), Thermogravometric (DSC-TGA) analysis and Scanning Electron Microscopy (SEM). The result indicates that on increasing the reaction time particle size increases but on increasing the molar ratios grain size decreases.

A Fixed Band Hysteresis Current Controller for Voltage Source AC Chopper

Most high-performance ac drives utilize a current controller. The controller switches a voltage source inverter (VSI) such that the motor current follows a set of reference current waveforms. Fixed-band hysteresis (FBH) current control has been widely used for the PWM inverter. We want to apply the same controller for the PWM AC chopper. The aims of the controller is to optimize the harmonic content at both input and output sides, while maintaining acceptable losses in the ac chopper and to control in wide range the fundamental output voltage. Fixed band controller has been simulated and analyzed for a single-phase AC chopper and are easily extended to three-phase systems. Simulation confirmed the advantages and the excellent performance of the modulation method applied for the AC chopper.

Investigation of Titanium Oxide Layer in Thermal-Electrochemical Anodizing of Ti6Al4V Alloy

In this paper the combination of thermal oxidation and electrochemical anodizing processes is used to produce titanium oxide layers. The response of titanium alloy Ti6Al4V to oxidation processes at various temperatures and electrochemical anodizing in various voltages are investigated. Scanning electron microscopy (SEM); X-Ray Diffraction (XRD) and porosity determination have been used to characterize the oxide layer thickness, surface morphology, oxide layer-substrate adhesion and porosity. In the first experiment, samples modified by thermal oxidation process then followed by electrochemical anodizing. Second experiment consists of surfaces modified by electrochemical anodizing process and then followed by thermal oxidation. The first method shows better properties than other one. In second experiment, Surfaces modified were achieved by thicker and more adherent thick oxide layers on titanium surface. The existence of an electrochemical anodized oxide layer did not improve the adhesion of thermal oxide layer. The high temperature, thermal formation of an oxide layer leads to a coarse oxide grain morphology and a complete oxidative particle. In addition, in high temperature oxidation porosity content is increased. The oxide layer of thermal oxidation and electrochemical anodizing processes; on Ti–6Al–4V substrate was covered with different colored oxide layers.