SVM Based Model as an Optimal Classifier for the Classification of Sonar Signals

Research into the problem of classification of sonar signals has been taken up as a challenging task for the neural networks. This paper investigates the design of an optimal classifier using a Multi layer Perceptron Neural Network (MLP NN) and Support Vector Machines (SVM). Results obtained using sonar data sets suggest that SVM classifier perform well in comparison with well-known MLP NN classifier. An average classification accuracy of 91.974% is achieved with SVM classifier and 90.3609% with MLP NN classifier, on the test instances. The area under the Receiver Operating Characteristics (ROC) curve for the proposed SVM classifier on test data set is found as 0.981183, which is very close to unity and this clearly confirms the excellent quality of the proposed classifier. The SVM classifier employed in this paper is implemented using kernel Adatron algorithm is seen to be robust and relatively insensitive to the parameter initialization in comparison to MLP NN.

Improving Protein-Protein Interaction Prediction by Using Encoding Strategies and Random Indices

A New features are extracted and compared to improve the prediction of protein-protein interactions. The basic idea is to select and use the best set of features from the Tensor matrices that are produced by the frequency vectors of the protein sequences. Three set of features are compared, the first set is based on the indices that are the most common in the interacting proteins, the second set is based on the indices that tend to be common in the interacting and non-interacting proteins, and the third set is constructed by using random indices. Moreover, three encoding strategies are compared; that are based on the amino asides polarity, structure, and chemical properties. The experimental results indicate that the highest accuracy can be obtained by using random indices with chemical properties encoding strategy and support vector machine.

A Note on the Convergence of the Generalized AOR Iterative Method for Linear Systems

Recently, some convergent results of the generalized AOR iterative (GAOR) method for solving linear systems with strictly diagonally dominant matrices are presented in [Darvishi, M.T., Hessari, P.: On convergence of the generalized AOR method for linear systems with diagonally dominant cofficient matrices. Appl. Math. Comput. 176, 128-133 (2006)] and [Tian, G.X., Huang, T.Z., Cui, S.Y.: Convergence of generalized AOR iterative method for linear systems with strictly diagonally dominant cofficient matrices. J. Comp. Appl. Math. 213, 240-247 (2008)]. In this paper, we give the convergence of the GAOR method for linear systems with strictly doubly diagonally dominant matrix, which improves these corresponding results.

Fabrication and Characterization of Sawdust Composite Biodegradable Film

This report shows the performance of composite biodegradable film from chitosan, starch and sawdust fiber. The main objectives of this research are to fabricate and characterize composite biodegradable film in terms of morphology and physical properties. The film was prepared by casting method. Sawdust fiber was used as reinforcing agent and starch as polymer matrix in the casting solution. The morphology of the film was characterized using atomic force microscope (AFM). The result showed that the film has smooth structure. Chemical composition of the film was investigated using Fourier transform infrared (FTIR) where the result revealed present of starch in the film. The thermal properties were characterized using thermal gravimetric analyzer (TGA) and differential scanning calorimetric (DSC) where the results showed that the film has small difference in melting and degradation temperature.

The Effect of Facial Expressions on Students in Virtual Educational Environments

The scope of this research was to study the relation between the facial expressions of three lecturers in a real academic lecture theatre and the reactions of the students to those expressions. The first experiment aimed to investigate the effectiveness of a virtual lecturer-s expressions on the students- learning outcome in a virtual pedagogical environment. The second experiment studied the effectiveness of a single facial expression, i.e. the smile, on the students- performance. Both experiments involved virtual lectures, with virtual lecturers teaching real students. The results suggest that the students performed better by 86%, in the lectures where the lecturer performed facial expressions compared to the results of the lectures that did not use facial expressions. However, when simple or basic information was used, the facial expressions of the virtual lecturer had no substantial effect on the students- learning outcome. Finally, the appropriate use of smiles increased the interest of the students and consequently their performance.

A Reconfigurable Processing Element for Cholesky Decomposition and Matrix Inversion

Fixed-point simulation results are used for the performance measure of inverting matrices by Cholesky decomposition. The fixed-point Cholesky decomposition algorithm is implemented using a fixed-point reconfigurable processing element. The reconfigurable processing element provides all mathematical operations required by Cholesky decomposition. The fixed-point word length analysis is based on simulations using different condition numbers and different matrix sizes. Simulation results show that 16 bits word length gives sufficient performance for small matrices with low condition number. Larger matrices and higher condition numbers require more dynamic range for a fixedpoint implementation.

Atrial Fibrillation Analysis Based on Blind Source Separation in 12-lead ECG

Atrial Fibrillation is the most common sustained arrhythmia encountered by clinicians. Because of the invisible waveform of atrial fibrillation in atrial activation for human, it is necessary to develop an automatic diagnosis system. 12-Lead ECG now is available in hospital and is appropriate for using Independent Component Analysis to estimate the AA period. In this research, we also adopt a second-order blind identification approach to transform the sources extracted by ICA to more precise signal and then we use frequency domain algorithm to do the classification. In experiment, we gather a significant result of clinical data.

Some Characteristics of Systolic Arrays

In this paper is investigated a possible optimization of some linear algebra problems which can be solved by parallel processing using the special arrays called systolic arrays. In this paper are used some special types of transformations for the designing of these arrays. We show the characteristics of these arrays. The main focus is on discussing the advantages of these arrays in parallel computation of matrix product, with special approach to the designing of systolic array for matrix multiplication. Multiplication of large matrices requires a lot of computational time and its complexity is O(n3 ). There are developed many algorithms (both sequential and parallel) with the purpose of minimizing the time of calculations. Systolic arrays are good suited for this purpose. In this paper we show that using an appropriate transformation implicates in finding more optimal arrays for doing the calculations of this type.

Performance Analysis of Software Reliability Models using Matrix Method

This paper presents a computational methodology based on matrix operations for a computer based solution to the problem of performance analysis of software reliability models (SRMs). A set of seven comparison criteria have been formulated to rank various non-homogenous Poisson process software reliability models proposed during the past 30 years to estimate software reliability measures such as the number of remaining faults, software failure rate, and software reliability. Selection of optimal SRM for use in a particular case has been an area of interest for researchers in the field of software reliability. Tools and techniques for software reliability model selection found in the literature cannot be used with high level of confidence as they use a limited number of model selection criteria. A real data set of middle size software project from published papers has been used for demonstration of matrix method. The result of this study will be a ranking of SRMs based on the Permanent value of the criteria matrix formed for each model based on the comparison criteria. The software reliability model with highest value of the Permanent is ranked at number – 1 and so on.

Fuzzy Adjacency Matrix in Graphs

In this paper a new definition of adjacency matrix in the simple graphs is presented that is called fuzzy adjacency matrix, so that elements of it are in the form of 0 and n N n 1 , ∈ that are in the interval [0, 1], and then some charactristics of this matrix are presented with the related examples . This form matrix has complete of information of a graph.

3D Oil Reservoir Visualisation Using Octree Compression Techniques Utilising Logical Grid Co-Ordinates

Octree compression techniques have been used for several years for compressing large three dimensional data sets into homogeneous regions. This compression technique is ideally suited to datasets which have similar values in clusters. Oil engineers represent reservoirs as a three dimensional grid where hydrocarbons occur naturally in clusters. This research looks at the efficiency of storing these grids using octree compression techniques where grid cells are broken into active and inactive regions. Initial experiments yielded high compression ratios as only active leaf nodes and their ancestor, header nodes are stored as a bitstream to file on disk. Savings in computational time and memory were possible at decompression, as only active leaf nodes are sent to the graphics card eliminating the need of reconstructing the original matrix. This results in a more compact vertex table, which can be loaded into the graphics card quicker and generating shorter refresh delay times.

Analysis of Euler Angles in a Simple Two-Axis Gimbals Set

Any rotation of a 3-dimensional object can be performed by three consecutive rotations over Euler angles. Intrinsic rotations produce the same result as extrinsic rotations in transformation. Euler rotations are the movement obtained by changing one of the Euler angles while leaving the other two constant. These Euler rotations are applied in a simple two-axis gimbals set mounted on an automotives. The values of Euler angles are [π/4, π/4, π/4] radians inside the angles ranges for a given coordinate system and these actual orientations can be directly measured from these gimbals set of moving automotives but it can occur the gimbals lock in application at [π/2.24, 0, 0] radians. In order to avoid gimbals lock, the values of quaternion must be [π/4.8, π/8.2, 0, π/4.8] radians. The four-gimbals set can eliminate gimbals lock.

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.

Investigation of Anti-Inflammatory, Antipyretic and Analgesic Effect of Yemeni Sidr Honey

Traditionally, Yemini Sidr honey has been reported to cure liver problems, stomach ulcers, and respiratory disorders. In this experiment, we evaluated Yemeni Sidr honey for its ability to protect inflammations caused by acetic acid and formalin -induced writhing, carrageenan and histamine-induced paw oedema in experimental rat model. Hyperpyrexia, membrane stabilizing activity, and phytochemical screening of the honey was also examined. Yemini Sidr Honey at (100, 200 and 500 mg/kg) exhibited a concentration dependant inhibition of acetic acid induced and formalin induced writhing, paw oedema induced by carrageenan & histamine, and hyperpyrexia induced by brewer's yeast, it also inhibited membrane stabilizing activity. Phytochemical screenings of the honey reveal the presence of flavonoids, steroid, alkaloids, saponins and tannins. This study suggested that Yemeni Sidr honey possess very strong antiinflammatory, analgesic and antipyretic effects and these effects would be a result of the phytochemicals present.

Digital filters for Hot-Mix Asphalt Complex Modulus Test Data Using Genetic Algorithm Strategies

The dynamic or complex modulus test is considered to be a mechanistically based laboratory test to reliably characterize the strength and load-resistance of Hot-Mix Asphalt (HMA) mixes used in the construction of roads. The most common observation is that the data collected from these tests are often noisy and somewhat non-sinusoidal. This hampers accurate analysis of the data to obtain engineering insight. The goal of the work presented in this paper is to develop and compare automated evolutionary computational techniques to filter test noise in the collection of data for the HMA complex modulus test. The results showed that the Covariance Matrix Adaptation-Evolutionary Strategy (CMA-ES) approach is computationally efficient for filtering data obtained from the HMA complex modulus test.

Panoramic Sensor Based Blind Spot Accident Prevention System

There are many automotive accidents due to blind spots and driver inattentiveness. Blind spot is the area that is invisible to the driver's viewpoint without head rotation. Several methods are available for assisting the drivers. Simplest methods are — rear mirrors and wide-angle lenses. But, these methods have a disadvantage of the requirement for human assistance. So, the accuracy of these devices depends on driver. Another approach called an automated approach that makes use of sensors such as sonar or radar. These sensors are used to gather range information. The range information will be processed and used for detecting the collision. The disadvantage of this system is — low angular resolution and limited sensing volumes. This paper is a panoramic sensor based automotive vehicle monitoring..

Concentration of Micro Minerals in Fiber Fraction of Forages

This study was carried out to evaluate concentration of micro minerals (Zn, Fe, Mn, Cu and Se) of forages and their distribution in fiber fraction (neutral detergent fiber/NDF and acid detergent fiber/ADF) in South Sumatra during dry and rainy seasons. Seven species of commonly forages namely Axonopus compressus, Panicum maximum, Pennisetum purpuphoides, Leucaena leucocephala, Centrocema pubescens, Calopogonium mucunoides and Acacia mangium were collected at native pasture during rainy and dry seasons. The results showed that micro minerals concentration of forages and their distribution in fiber fraction varied among species and season. In general, concentration of micro minerals was slightly higher in rainy season compared to dry season either in grass or legumes forages. In grass, concentration of Fe and Mn were above the critical level, while 33.3 %, 100 % and 16.7 % of evaluated grass were deficient in Zn, Cu and Se. Data on legume forages show that 75 % of legumes were deficient in Zn and Mn, 62.5 % deficient in Cu and 50 % deficient in Se. There was no species of legume deficient in Fe. Distribution of micro minerals in NDF and ADF were also significantly affected by species and season and depends on the kinds of element measured. Generally, micro minerals were associated in fiber fractions much higher during dry season compared to rainy season. Iron (Fe) and selenium (Se) in forages were the highest elements associated in NDF and ADF, while the lowest was found in Copper (Cu).

Introductory Design Optimisation of a Machine Tool using a Virtual Machine Concept

Designing modern machine tools is a complex task. A simulation tool to aid the design work, a virtual machine, has therefore been developed in earlier work. The virtual machine considers the interaction between the mechanics of the machine (including structural flexibility) and the control system. This paper exemplifies the usefulness of the virtual machine as a tool for product development. An optimisation study is conducted aiming at improving the existing design of a machine tool regarding weight and manufacturing accuracy at maintained manufacturing speed. The problem can be categorised as constrained multidisciplinary multiobjective multivariable optimisation. Parameters of the control and geometric quantities of the machine are used as design variables. This results in a mix of continuous and discrete variables and an optimisation approach using a genetic algorithm is therefore deployed. The accuracy objective is evaluated according to international standards. The complete systems model shows nondeterministic behaviour. A strategy to handle this based on statistical analysis is suggested. The weight of the main moving parts is reduced by more than 30 per cent and the manufacturing accuracy is improvement by more than 60 per cent compared to the original design, with no reduction in manufacturing speed. It is also shown that interaction effects exist between the mechanics and the control, i.e. this improvement would most likely not been possible with a conventional sequential design approach within the same time, cost and general resource frame. This indicates the potential of the virtual machine concept for contributing to improved efficiency of both complex products and the development process for such products. Companies incorporating such advanced simulation tools in their product development could thus improve its own competitiveness as well as contribute to improved resource efficiency of society at large.

Preconditioned Jacobi Method for Fuzzy Linear Systems

A preconditioned Jacobi (PJ) method is provided for solving fuzzy linear systems whose coefficient matrices are crisp Mmatrices and the right-hand side columns are arbitrary fuzzy number vectors. The iterative algorithm is given for the preconditioned Jacobi method. The convergence is analyzed with convergence theorems. Numerical examples are given to illustrate the procedure and show the effectiveness and efficiency of the method.

Instability Analysis of Laminated Composite Beams Subjected to Parametric Axial Load

The integral form of equations of motion of composite beams subjected to varying time loads are discretized using a developed finite element model. The model consists of a straight five node twenty-two degrees of freedom beam element. The stability analysis of the beams is studied by solving the matrix form characteristic equations of the system. The principle of virtual work and the first order shear deformation theory are employed to analyze the beams with large deformation and small strains. The regions of dynamic instability of the beam are determined by solving the obtained Mathieu form of differential equations. The effects of nonconservative loads, shear stiffness, and damping parameters on stability and response of the beams are examined. Several numerical calculations are presented to compare the results with data reported by other researchers.