Quadrilateral Decomposition by Two-Ear Property Resulting in CAD Segmentation

The objective is to split a simply connected polygon into a set of convex quadrilaterals without inserting new boundary nodes. The presented approach consists in repeatedly removing quadrilaterals from the polygon. Theoretical results pertaining to quadrangulation of simply connected polygons are derived from the usual 2-ear theorem. It produces a quadrangulation technique with O(n) number of quadrilaterals. The theoretical methodology is supplemented by practical results and CAD surface segmentation.

Data Extraction of XML Files using Searching and Indexing Techniques

XML files contain data which is in well formatted manner. By studying the format or semantics of the grammar it will be helpful for fast retrieval of the data. There are many algorithms which describes about searching the data from XML files. There are no. of approaches which uses data structure or are related to the contents of the document. In these cases user must know about the structure of the document and information retrieval techniques using NLPs is related to content of the document. Hence the result may be irrelevant or not so successful and may take more time to search.. This paper presents fast XML retrieval techniques by using new indexing technique and the concept of RXML. When indexing an XML document, the system takes into account both the document content and the document structure and assigns the value to each tag from file. To query the system, a user is not constrained about fixed format of query.

Monte Carlo Simulation of the Transport Phenomena in Degenerate Hg0.8Cd0.2Te

The present work deals with the calculation of transport properties of Hg0.8Cd0.2Te (MCT) semiconductor in degenerate case. Due to their energy-band structure, this material becomes degenerate at moderate doping densities, which are around 1015 cm-3, so that the usual Maxwell-Boltzmann approximation is inaccurate in the determination of transport parameters. This problem is faced by using Fermi-Dirac (F-D) statistics, and the non-parabolic behavior of the bands may be approximated by the Kane model. The Monte Carlo (MC) simulation is used here to determinate transport parameters: drift velocity, mean energy and drift mobility versus electric field and the doped densities. The obtained results are in good agreement with those extracted from literature.

A Bi-Objective Preventive Healthcare Facility Network Design with Incorporating Cost and Time Saving

Main goal of preventive healthcare problems are at decreasing the likelihood and severity of potentially life-threatening illnesses by protection and early detection. The levels of establishment and staffing costs along with summation of the travel and waiting time that clients spent are considered as objectives functions of the proposed nonlinear integer programming model. In this paper, we have proposed a bi-objective mathematical model for designing a network of preventive healthcare facilities so as to minimize aforementioned objectives, simultaneously. Moreover, each facility acts as M/M/1 queuing system. The number of facilities to be established, the location of each facility, and the level of technology for each facility to be chosen are provided as the main determinants of a healthcare facility network. Finally, to demonstrate performance of the proposed model, four multi-objective decision making techniques are presented to solve the model.

Variable Step-Size Affine Projection Algorithm With a Weighted and Regularized Projection Matrix

This paper presents a forgetting factor scheme for variable step-size affine projection algorithms (APA). The proposed scheme uses a forgetting processed input matrix as the projection matrix of pseudo-inverse to estimate system deviation. This method introduces temporal weights into the projection matrix, which is typically a better model of the real error's behavior than homogeneous temporal weights. The regularization overcomes the ill-conditioning introduced by both the forgetting process and the increasing size of the input matrix. This algorithm is tested by independent trials with coloured input signals and various parameter combinations. Results show that the proposed algorithm is superior in terms of convergence rate and misadjustment compared to existing algorithms. As a special case, a variable step size NLMS with forgetting factor is also presented in this paper.

Mechanical Properties of Fibre Reinforced Concrete - A Comparative Experimental Study

This paper in essence presents comparative experimental data on the mechanical performance of steel and synthetic fibre-reinforced concrete under compression, tensile split and flexure. URW1050 steel fibre and HPP45 synthetic fibre, both with the same concrete design mix, have been used to make cube specimens for a compression test, cylinders for a tensile split test and beam specimens for a flexural test. The experimental data demonstrated steel fibre reinforced concrete to be stronger in flexure at early stages, whilst both fibre reinforced concrete types displayed comparatively the same performance in compression, tensile splitting and 28-day flexural strength. In terms of post-crack controlHPP45 was preferable.

Multilevel Classifiers in Recognition of Handwritten Kannada Numerals

The recognition of handwritten numeral is an important area of research for its applications in post office, banks and other organizations. This paper presents automatic recognition of handwritten Kannada numerals based on structural features. Five different types of features, namely, profile based 10-segment string, water reservoir; vertical and horizontal strokes, end points and average boundary length from the minimal bounding box are used in the recognition of numeral. The effect of each feature and their combination in the numeral classification is analyzed using nearest neighbor classifiers. It is common to combine multiple categories of features into a single feature vector for the classification. Instead, separate classifiers can be used to classify based on each visual feature individually and the final classification can be obtained based on the combination of separate base classification results. One popular approach is to combine the classifier results into a feature vector and leaving the decision to next level classifier. This method is extended to extract a better information, possibility distribution, from the base classifiers in resolving the conflicts among the classification results. Here, we use fuzzy k Nearest Neighbor (fuzzy k-NN) as base classifier for individual feature sets, the results of which together forms the feature vector for the final k Nearest Neighbor (k-NN) classifier. Testing is done, using different features, individually and in combination, on a database containing 1600 samples of different numerals and the results are compared with the results of different existing methods.

Modeling and Simulations of Complex Low- Dimensional systems: Testing the Efficiency of Parallelization

The deterministic quantum transfer-matrix (QTM) technique and its mathematical background are presented. This important tool in computational physics can be applied to a class of the real physical low-dimensional magnetic systems described by the Heisenberg hamiltonian which includes the macroscopic molecularbased spin chains, small size magnetic clusters embedded in some supramolecules and other interesting compounds. Using QTM, the spin degrees of freedom are accurately taken into account, yielding the thermodynamical functions at finite temperatures. In order to test the application for the susceptibility calculations to run in the parallel environment, the speed-up and efficiency of parallelization are analyzed on our platform SGI Origin 3800 with p = 128 processor units. Using Message Parallel Interface (MPI) system libraries we find the efficiency of the code of 94% for p = 128 that makes our application highly scalable.

Recognition of Noisy Words Using the Time Delay Neural Networks Approach

This paper presents a recognition system for isolated words like robot commands. It’s carried out by Time Delay Neural Networks; TDNN. To teleoperate a robot for specific tasks as turn, close, etc… In industrial environment and taking into account the noise coming from the machine. The choice of TDNN is based on its generalization in terms of accuracy, in more it acts as a filter that allows the passage of certain desirable frequency characteristics of speech; the goal is to determine the parameters of this filter for making an adaptable system to the variability of speech signal and to noise especially, for this the back propagation technique was used in learning phase. The approach was applied on commands pronounced in two languages separately: The French and Arabic. The results for two test bases of 300 spoken words for each one are 87%, 97.6% in neutral environment and 77.67%, 92.67% when the white Gaussian noisy was added with a SNR of 35 dB.

The Effect of Confinement Shapes on Over-Reinforced HSC Beams

High strength concrete (HSC) provides high strength but lower ductility than normal strength concrete. This low ductility limits the benefit of using HSC in building safe structures. On the other hand, when designing reinforced concrete beams, designers have to limit the amount of tensile reinforcement to prevent the brittle failure of concrete. Therefore the full potential of the use of steel reinforcement can not be achieved. This paper presents the idea of confining concrete in the compression zone so that the HSC will be in a state of triaxial compression, which leads to improvements in strength and ductility. Five beams made of HSC were cast and tested. The cross section of the beams was 200×300 mm, with a length of 4 m and a clear span of 3.6 m subjected to four-point loading, with emphasis placed on the midspan deflection. The first beam served as a reference beam. The remaining beams had different tensile reinforcement and the confinement shapes were changed to gauge their effectiveness in improving the strength and ductility of the beams. The compressive strength of the concrete was 85 MPa and the tensile strength of the steel was 500 MPa and for the stirrups and helixes was 250 MPa. Results of testing the five beams proved that placing helixes with different diameters as a variable parameter in the compression zone of reinforced concrete beams improve their strength and ductility.

Accessible Business Process Modelling

This article concerns with the accessibility of Business process modelling tools (BPMo tools) and business process modelling languages (BPMo languages). Therefore the reader will be introduced to business process management and the authors' motivation behind this inquiry. Afterwards, the paper will reflect problems when applying inaccessible BPMo tools. To illustrate these problems the authors distinguish between two different categories of issues and provide practical examples. Finally the article will present three approaches to improve the accessibility of BPMo tools and BPMo languages.

Using Teager Energy Cepstrum and HMM distancesin Automatic Speech Recognition and Analysis of Unvoiced Speech

In this study, the use of silicon NAM (Non-Audible Murmur) microphone in automatic speech recognition is presented. NAM microphones are special acoustic sensors, which are attached behind the talker-s ear and can capture not only normal (audible) speech, but also very quietly uttered speech (non-audible murmur). As a result, NAM microphones can be applied in automatic speech recognition systems when privacy is desired in human-machine communication. Moreover, NAM microphones show robustness against noise and they might be used in special systems (speech recognition, speech conversion etc.) for sound-impaired people. Using a small amount of training data and adaptation approaches, 93.9% word accuracy was achieved for a 20k Japanese vocabulary dictation task. Non-audible murmur recognition in noisy environments is also investigated. In this study, further analysis of the NAM speech has been made using distance measures between hidden Markov model (HMM) pairs. It has been shown the reduced spectral space of NAM speech using a metric distance, however the location of the different phonemes of NAM are similar to the location of the phonemes of normal speech, and the NAM sounds are well discriminated. Promising results in using nonlinear features are also introduced, especially under noisy conditions.

Study of Temperature Changes in Fars Province

Climate change is a phenomenon has been based on the available evidence from a very long time ago and now its existence is very probable. The speed and nature of climate parameters changes at the middle of twentieth century has been different and its quickness more than the before and its trend changed to some extent comparing to the past. Climate change issue now regarded as not only one of the most common scientific topic but also a social political one, is not a new issue. Climate change is a complicated atmospheric oceanic phenomenon on a global scale and long-term. Precipitation pattern change, fast decrease of snowcovered resources and its rapid melting, increased evaporation, the occurrence of destroying floods, water shortage crisis, severe reduction at the rate of harvesting agricultural products and, so on are all the significant of climate change. To cope with this phenomenon, its consequences and events in which public instruction is the most important but it may be climate that no significant cant and effective action has been done so far. The present article is included a part of one surrey about climate change in Fars. The study area having annually mean temperature 14 and precipitation 320 mm .23 stations inside the basin with a common 37 year statistical period have been applied to the meteorology data (1974-2010). Man-kendal and change factor methods are two statistical methods, applying them, the trend of changes and the annual mean average temperature and the annual minimum mean temperature were studied by using them. Based on time series for each parameter, the annual mean average temperature and the mean of annual maximum temperature have a rising trend so that this trend is clearer to the mean of annual maximum temperature.

Fuzzy Decision Making via Multiple Attribute

In this paper, a method for decision making in fuzzy environment is presented.A new subjective and objective integrated approach is introduced that used to assign weight attributes in fuzzy multiple attribute decision making (FMADM) problems and alternatives and fmally ranked by proposed method.

Study on Carbonation Process of Several Types of Advanced Lime-Based Plasters

In this paper, study on carbonation process of several types of advanced plasters on lime basis is presented. The movement of carbonation head was measured by colorimetric method using phenolphtalein. The rate of carbonation was accessed also by gravimetric method. Samples of studied materials were placed into the climatic chamber for simulation of environment with high concentration of CO2. The particular samples were on all lateral sides and on the bottom side provided by epoxy resin in order to arrange 1-D transport of CO2 into the studied samples. The carbonation rates of particular materials pointed to the time dependence of diffusion process of CO2 for all the studied plasters. From the quantitative point of view, the carbonation of advanced modified plasters was much faster than for the reference lime plaster, what is beneficial for the practical application of the tested newly developed materials.

Introduction of Hyperaccumulator Plants with Phytoremediation Potential of a Lead- Zinc Mine in Iran

Contamination of heavy metals represents one of the most pressing threats to water and soil resources as well as human health. Phytoremediation can be potentially used to remediate metalcontaminated sites. A major step towards the development of phytoremediation of heavy metal impacted soils is the discovery of the heavy metal hyperaccumulation in plants. In this study, the several established criteria to define a hyperaccumulator plant were applied. The case study was represented by a mining area in Hamedan province in the central west part of Iran. Obtained results showed that the most of sampled species were able to grow on heavily metal-contaminated soils and also were able to accumulate extraordinarily high concentrations of some metals such as Zn, Mn, Cu, Pb and Fe. Using the most common criteria, Euphorbia macroclada and Centaurea virgata can be classified as hyperaccumulators of some measured heavy metals and, therefore, they have suitable potential for phytoremediation of contaminated soils.

Comparison of the Garden City Conceptand Green Belt Concept in Major Asian and Oceanic Cities

The purpose of this study is to review representative cases of green space development in order to compare the Garden City concept and Green Belt concept as applied and to examine its direction in major Asian and Oceanic cities. The results of previous studies and this study show that there are two major directions in such green-oriented city planning. One direction is toward Multi-Regional Development, and the other focuses on an Environmentally Symbiotic City based on the Garden City concept. In large cities and the suburbs where extremely strong pressure to urbanize makes it impossible to keep Green Belts, it is essential to strictly control land use and adopt the Garden City concept to conserve the urban environment.

Solution of Fuzzy Maximal Flow Problems Using Fuzzy Linear Programming

In this paper, the fuzzy linear programming formulation of fuzzy maximal flow problems are proposed and on the basis of the proposed formulation a method is proposed to find the fuzzy optimal solution of fuzzy maximal flow problems. In the proposed method all the parameters are represented by triangular fuzzy numbers. By using the proposed method the fuzzy optimal solution of fuzzy maximal flow problems can be easily obtained. To illustrate the proposed method a numerical example is solved and the obtained results are discussed.

A Cumulative Learning Approach to Data Mining Employing Censored Production Rules (CPRs)

Knowledge is indispensable but voluminous knowledge becomes a bottleneck for efficient processing. A great challenge for data mining activity is the generation of large number of potential rules as a result of mining process. In fact sometimes result size is comparable to the original data. Traditional data mining pruning activities such as support do not sufficiently reduce the huge rule space. Moreover, many practical applications are characterized by continual change of data and knowledge, thereby making knowledge voluminous with each change. The most predominant representation of the discovered knowledge is the standard Production Rules (PRs) in the form If P Then D. Michalski & Winston proposed Censored Production Rules (CPRs), as an extension of production rules, that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: If P Then D Unless C, where C (Censor) is an exception to the rule. Such rules are employed in situations in which the conditional statement 'If P Then D' holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence, are tight or there is simply no information available as to whether it holds or not. Thus the 'If P Then D' part of the CPR expresses important information while the Unless C part acts only as a switch changes the polarity of D to ~D. In this paper a scheme based on Dempster-Shafer Theory (DST) interpretation of a CPR is suggested for discovering CPRs from the discovered flat PRs. The discovery of CPRs from flat rules would result in considerable reduction of the already discovered rules. The proposed scheme incrementally incorporates new knowledge and also reduces the size of knowledge base considerably with each episode. Examples are given to demonstrate the behaviour of the proposed scheme. The suggested cumulative learning scheme would be useful in mining data streams.

Minimal Spanning Tree based Fuzzy Clustering

Most of fuzzy clustering algorithms have some discrepancies, e.g. they are not able to detect clusters with convex shapes, the number of the clusters should be a priori known, they suffer from numerical problems, like sensitiveness to the initialization, etc. This paper studies the synergistic combination of the hierarchical and graph theoretic minimal spanning tree based clustering algorithm with the partitional Gath-Geva fuzzy clustering algorithm. The aim of this hybridization is to increase the robustness and consistency of the clustering results and to decrease the number of the heuristically defined parameters of these algorithms to decrease the influence of the user on the clustering results. For the analysis of the resulted fuzzy clusters a new fuzzy similarity measure based tool has been presented. The calculated similarities of the clusters can be used for the hierarchical clustering of the resulted fuzzy clusters, which information is useful for cluster merging and for the visualization of the clustering results. As the examples used for the illustration of the operation of the new algorithm will show, the proposed algorithm can detect clusters from data with arbitrary shape and does not suffer from the numerical problems of the classical Gath-Geva fuzzy clustering algorithm.