Order Statistics-based “Anti-Bayesian“ Parametric Classification for Asymmetric Distributions in the Exponential Family

Although the field of parametric Pattern Recognition (PR) has been thoroughly studied for over five decades, the use of the Order Statistics (OS) of the distributions to achieve this has not been reported. The pioneering work on using OS for classification was presented in [1] for the Uniform distribution, where it was shown that optimal PR can be achieved in a counter-intuitive manner, diametrically opposed to the Bayesian paradigm, i.e., by comparing the testing sample to a few samples distant from the mean. This must be contrasted with the Bayesian paradigm in which, if we are allowed to compare the testing sample with only a single point in the feature space from each class, the optimal strategy would be to achieve this based on the (Mahalanobis) distance from the corresponding central points, for example, the means. In [2], we showed that the results could be extended for a few symmetric distributions within the exponential family. In this paper, we attempt to extend these results significantly by considering asymmetric distributions within the exponential family, for some of which even the closed form expressions of the cumulative distribution functions are not available. These distributions include the Rayleigh, Gamma and certain Beta distributions. As in [1] and [2], the new scheme, referred to as Classification by Moments of Order Statistics (CMOS), attains an accuracy very close to the optimal Bayes’ bound, as has been shown both theoretically and by rigorous experimental testing.

Data Embedding Based on Better Use of Bits in Image Pixels

In this study, a novel approach of image embedding is introduced. The proposed method consists of three main steps. First, the edge of the image is detected using Sobel mask filters. Second, the least significant bit LSB of each pixel is used. Finally, a gray level connectivity is applied using a fuzzy approach and the ASCII code is used for information hiding. The prior bit of the LSB represents the edged image after gray level connectivity, and the remaining six bits represent the original image with very little difference in contrast. The proposed method embeds three images in one image and includes, as a special case of data embedding, information hiding, identifying and authenticating text embedded within the digital images. Image embedding method is considered to be one of the good compression methods, in terms of reserving memory space. Moreover, information hiding within digital image can be used for security information transfer. The creation and extraction of three embedded images, and hiding text information is discussed and illustrated, in the following sections.

Optimization of a Three-Term Backpropagation Algorithm Used for Neural Network Learning

The back-propagation algorithm calculates the weight changes of an artificial neural network, and a two-term algorithm with a dynamically optimal learning rate and a momentum factor is commonly used. Recently the addition of an extra term, called a proportional factor (PF), to the two-term BP algorithm was proposed. The third term increases the speed of the BP algorithm. However, the PF term also reduces the convergence of the BP algorithm, and optimization approaches for evaluating the learning parameters are required to facilitate the application of the three terms BP algorithm. This paper considers the optimization of the new back-propagation algorithm by using derivative information. A family of approaches exploiting the derivatives with respect to the learning rate, momentum factor and proportional factor is presented. These autonomously compute the derivatives in the weight space, by using information gathered from the forward and backward procedures. The three-term BP algorithm and the optimization approaches are evaluated using the benchmark XOR problem.

A Technique for Reachability Graph Generation for the Petri Net Models of Parallel Processes

Reachability graph (RG) generation suffers from the problem of exponential space and time complexity. To alleviate the more critical problem of time complexity, this paper presents the new approach for RG generation for the Petri net (PN) models of parallel processes. Independent RGs for each parallel process in the PN structure are generated in parallel and cross-product of these RGs turns into the exhaustive state space from which the RG of given parallel system is determined. The complexity analysis of the presented algorithm illuminates significant decrease in the time complexity cost of RG generation. The proposed technique is applicable to parallel programs having multiple threads with the synchronization problem.

The Impact of Occupational Stress on Quality of Work Life among the Staff of e-Workspace

With the advent of new technologies, factors related to mental health in e-workspaces are taken into consideration more than ever. Studies have revealed that one of the factors affecting the productivity of employees in an organization is occupational stress. Another influential factor is quality of work life which is important in the improvement of work environment conditions and organizational efficiency. In order to uncover the quality of work life level and to investigate the impact of occupational stress on quality of work life among information technology employees in Iran, a cross-sectional study design was applied and data were gathered using a questionnaire validated by a group of experts. The results of the study showed that information technology staffs have average level of both occupational stress and quality of work life. Furthermore, it was found that occupational stress has a negative impact on quality of work life. In addition, the same results were observed for role ambiguity, role conflict, role under-load, work-pace, work repetitiveness and tension toward quality of work life. No significant relation was found between role overload and quality of work life. Finally, directions for future research are proposed and discussed.

Investigating the Effectiveness of Self-Shading Strategy on Overall Thermal Transfer Value and Window Size in High Rise Buildings

So much energy is used in high rise buildings to fulfill the basic needs of users such as lighting and thermal comfort. Malaysia has hot and humid climate, buildings especially high rise buildings receive unnecessary solar radiation that cause more solar heat gain. Energy use specially electricity consumption in high rise buildings has increased. There have been growing concerns about energy consumption and its effect on environment. Building, energy and the environment are important issues that the designers should consider to them. Self protected form is one of possible ways against the impact of solar radiation in high rise buildings. The Energy performance of building envelopes was investigated in term of the Overall Thermal Transfer Value (OTTV ).In this paper, the amount of OTTV reduction was calculated through OTTV Equations to clear the effectiveness of self shading strategy on minimizing energy consumption for cooling interior spaces in high rise buildings which has considerable envelope areas against solar radiation. Also increasing the optimum window area was investigated using self-shading strategy in designing high rise buildings. As result, the significant reduction in OTTV was shown based on WWR.In addition slight increase was demonstrated in WWR that can influence on visible comfort interior spaces.

Content-based Retrieval of Medical Images

With the advance of multimedia and diagnostic images technologies, the number of radiographic images is increasing constantly. The medical field demands sophisticated systems for search and retrieval of the produced multimedia document. This paper presents an ongoing research that focuses on the semantic content of radiographic image documents to facilitate semantic-based radiographic image indexing and a retrieval system. The proposed model would divide a radiographic image document, based on its semantic content, and would be converted into a logical structure or a semantic structure. The logical structure represents the overall organization of information. The semantic structure, which is bound to logical structure, is composed of semantic objects with interrelationships in the various spaces in the radiographic image.

Application of Remote Sensing in Development of Green Space

One of the most important parameters to develop and manage urban areas is appropriate selection of land surface to develop green spaces in these areas. In this study, in order to identify the most appropriate sites and areas cultivated for ornamental species in Jiroft, Landsat Enhanced Thematic Mapper Plus (ETM+) images due to extract the most important effective climatic and adaphic parameters for growth ornamental species were used. After geometric and atmospheric corrections applied, to enhance accuracy of multi spectral (XS) bands, the fusion of Landsat XS bands by IRS-1D panchromatic band (PAN) was performed. After field sampling to evaluate the correlation between different factors in surface soil sampling location and different bands digital number (DN) of ETM+ sensor on the same points, correlation tables formed using the best computational model and the map of physical and chemical parameters of soil was produced. Then the accuracy of them was investigated by using kappa coefficient. Finally, according to produced maps, the best areas for cultivation of recommended species were introduced.

Artificial Neural Network Application on Ti/Al Joint Using Laser Beam Welding – A Review

Today automobile and aerospace industries realise Laser Beam Welding for a clean and non contact source of heating and fusion for joining of sheets. The welding performance is mainly based on by the laser welding parameters. Some concepts related to Artificial Neural Networks and how can be applied to model weld bead geometry and mechanical properties in terms of equipment parameters are reported in order to evaluate the accuracy and compare it with traditional modeling schemes. This review reveals the output features of Titanium and Aluminium weld bead geometry and mechanical properties such as ultimate tensile strength, yield strength, elongation and reduction of the area of the weld using Artificial Neural Network.

Simulation and Workspace Analysis of a Tripod Parallel Manipulator

Industrial robots play a vital role in automation however only little effort are taken for the application of robots in machining work such as Grinding, Cutting, Milling, Drilling, Polishing etc. Robot parallel manipulators have high stiffness, rigidity and accuracy, which cannot be provided by conventional serial robot manipulators. The aim of this paper is to perform the modeling and the workspace analysis of a 3 DOF Parallel Manipulator (3 DOF PM). The 3 DOF PM was modeled and simulated using 'ADAMS'. The concept involved is based on the transformation of motion from a screw joint to a spherical joint through a connecting link. This paper work has been planned to model the Parallel Manipulator (PM) using screw joints for very accurate positioning. A workspace analysis has been done for the determination of work volume of the 3 DOF PM. The position of the spherical joints connected to the moving platform and the circumferential points of the moving platform were considered for finding the workspace. After the simulation, the position of the joints of the moving platform was noted with respect to simulation time and these points were given as input to the 'MATLAB' for getting the work envelope. Then 'AUTOCAD' is used for determining the work volume. The obtained values were compared with analytical approach by using Pappus-Guldinus Theorem. The analysis had been dealt by considering the parameters, link length and radius of the moving platform. From the results it is found that the radius of moving platform is directly proportional to the work volume for a constant link length and the link length is also directly proportional to the work volume, at a constant radius of the moving platform.

Preoperative to Intraoperative Space Registration for Management of Head Injuries

A registration framework for image-guided robotic surgery is proposed for three emergency neurosurgical procedures, namely Intracranial Pressure (ICP) Monitoring, External Ventricular Drainage (EVD) and evacuation of a Chronic Subdural Haematoma (CSDH). The registration paradigm uses CT and white light as modalities. This paper presents two simulation studies for a preliminary evaluation of the registration protocol: (1) The loci of the Target Registration Error (TRE) in the patient-s axial, coronal and sagittal views were simulated based on a Fiducial Localisation Error (FLE) of 5 mm and (2) Simulation of the actual framework using projected views from a surface rendered CT model to represent white light images of the patient. Craniofacial features were employed as the registration basis to map the CT space onto the simulated intraoperative space. Photogrammetry experiments on an artificial skull were also performed to benchmark the results obtained from the second simulation. The results of both simulations show that the proposed protocol can provide a 5mm accuracy for these neurosurgical procedures.

Despeckling of Synthetic Aperture Radar Images Using Inner Product Spaces in Undecimated Wavelet Domain

This paper introduces the effective speckle reduction of synthetic aperture radar (SAR) images using inner product spaces in undecimated wavelet domain. There are two major areas in projection onto span algorithm where improvement can be made. First is the use of undecimated wavelet transformation instead of discrete wavelet transformation. And second area is the use of smoothing filter namely directional smoothing filter which is an additional step. Proposed method does not need any noise estimation and thresholding technique. More over proposed method gives good results on both single polarimetric and fully polarimetric SAR images.

Learning of Class Membership Values by Ellipsoidal Decision Regions

A novel method of learning complex fuzzy decision regions in the n-dimensional feature space is proposed. Through the fuzzy decision regions, a given pattern's class membership value of every class is determined instead of the conventional crisp class the pattern belongs to. The n-dimensional fuzzy decision region is approximated by union of hyperellipsoids. By explicitly parameterizing these hyperellipsoids, the decision regions are determined by estimating the parameters of each hyperellipsoid.Genetic Algorithm is applied to estimate the parameters of each region component. With the global optimization ability of GA, the learned decision region can be arbitrarily complex.

On Fuzzy Weakly-Closed Sets

A new class of fuzzy closed sets, namely fuzzy weakly closed set in a fuzzy topological space is introduced and it is established that this class of fuzzy closed sets lies between fuzzy closed sets and fuzzy generalized closed sets. Alongwith the study of fundamental results of such closed sets, we define and characterize fuzzy weakly compact space and fuzzy weakly closed space.

Dynamic Decompression for Text Files

Compression algorithms reduce the redundancy in data representation to decrease the storage required for that data. Lossless compression researchers have developed highly sophisticated approaches, such as Huffman encoding, arithmetic encoding, the Lempel-Ziv (LZ) family, Dynamic Markov Compression (DMC), Prediction by Partial Matching (PPM), and Burrows-Wheeler Transform (BWT) based algorithms. Decompression is also required to retrieve the original data by lossless means. A compression scheme for text files coupled with the principle of dynamic decompression, which decompresses only the section of the compressed text file required by the user instead of decompressing the entire text file. Dynamic decompressed files offer better disk space utilization due to higher compression ratios compared to most of the currently available text file formats.

FEA Modeling of Material Removal Rate in Electrical Discharge Machining of Al6063/SiC Composites

Metal matrix composites (MMC) are generating extensive interest in diverse fields like defense, aerospace, electronics and automotive industries. In this present investigation, material removal rate (MRR) modeling has been carried out using an axisymmetric model of Al-SiC composite during electrical discharge machining (EDM). A FEA model of single spark EDM was developed to calculate the temperature distribution.Further, single spark model was extended to simulate the second discharge. For multi-discharge machining material removal was calculated by calculating the number of pulses. Validation of model has been done by comparing the experimental results obtained under the same process parameters with the analytical results. A good agreement was found between the experimental results and the theoretical value.

Numerical Study of Iterative Methods for the Solution of the Dirichlet-Neumann Map for Linear Elliptic PDEs on Regular Polygon Domains

A generalized Dirichlet to Neumann map is one of the main aspects characterizing a recently introduced method for analyzing linear elliptic PDEs, through which it became possible to couple known and unknown components of the solution on the boundary of the domain without solving on its interior. For its numerical solution, a well conditioned quadratically convergent sine-Collocation method was developed, which yielded a linear system of equations with the diagonal blocks of its associated coefficient matrix being point diagonal. This structural property, among others, initiated interest for the employment of iterative methods for its solution. In this work we present a conclusive numerical study for the behavior of classical (Jacobi and Gauss-Seidel) and Krylov subspace (GMRES and Bi-CGSTAB) iterative methods when they are applied for the solution of the Dirichlet to Neumann map associated with the Laplace-s equation on regular polygons with the same boundary conditions on all edges.

Development of Reliable Web-Based Laboratories for Developing Countries

In online context, the design and implementation of effective remote laboratories environment is highly challenging on account of hardware and software needs. This paper presents the remote laboratory software framework modified from ilab shared architecture (ISA). The ISA is a framework which enables students to remotely acccess and control experimental hardware using internet infrastructure. The need for remote laboratories came after experiencing problems imposed by traditional laboratories. Among them are: the high cost of laboratory equipment, scarcity of space, scarcity of technical personnel along with the restricted university budget creates a significant bottleneck on building required laboratory experiments. The solution to these problems is to build web-accessible laboratories. Remote laboratories allow students and educators to interact with real laboratory equipment located anywhere in the world at anytime. Recently, many universities and other educational institutions especially in third world countries rely on simulations because they do not afford the experimental equipment they require to their students. Remote laboratories enable users to get real data from real-time hand-on experiments. To implement many remote laboratories, the system architecture should be flexible, understandable and easy to implement, so that different laboratories with different hardware can be deployed easily. The modifications were made to enable developers to add more equipment in ISA framework and to attract the new developers to develop many online laboratories.

Pedestrian Areas and Sustainable Development

Transportation is one of the most fundamental challenges of urban development in contemporary world. On the other hand, sustainable urban development has received tremendous public attention in the last few years. This trend in addition to other factors such as energy cost, environmental concerns, traffic congestion and the feeling of lack of belonging have contributed to the development of pedestrian areas. The purpose of this paper is to study the role of walkable streets in sustainable development of cities. Accordingly, a documentary research through valid sources has been utilized to substantiate this study. The findings demonstrate that walking can lead to sustainable urban development from physical, social, environmental, cultural, economic and political aspects. Also, pedestrian areas –which are the main context of walking- act as focal points of development in cities and have a great effect on modifying and stimulating of their adjacent urban spaces.

Fundamental Equation of Complete Factor Synergetics of Complex Systems with Normalization of Dimension

It is by reason of the unified measure of varieties of resources and the unified processing of the disposal of varieties of resources, that these closely related three of new basic models called the resources assembled node and the disposition integrated node as well as the intelligent organizing node are put forth in this paper; the three closely related quantities of integrative analytical mechanics including the disposal intensity and disposal- weighted intensity as well as the charge of resource charge are set; and then the resources assembled space and the disposition integrated space as well as the intelligent organizing space are put forth. The system of fundamental equations and model of complete factor synergetics is preliminarily approached for the general situation in this paper, to form the analytical base of complete factor synergetics. By the essential variables constituting this system of equations we should set twenty variables respectively with relation to the essential dynamical effect, external synergetic action and internal synergetic action of the system.