On Mobile Checkpointing using Index and Time Together

Checkpointing is one of the commonly used techniques to provide fault-tolerance in distributed systems so that the system can operate even if one or more components have failed. However, mobile computing systems are constrained by low bandwidth, mobility, lack of stable storage, frequent disconnections and limited battery life. Hence, checkpointing protocols having lesser number of synchronization messages and fewer checkpoints are preferred in mobile environment. There are two different approaches, although not orthogonal, to checkpoint mobile computing systems namely, time-based and index-based. Our protocol is a fusion of these two approaches, though not first of its kind. In the present exposition, an index-based checkpointing protocol has been developed, which uses time to indirectly coordinate the creation of consistent global checkpoints for mobile computing systems. The proposed algorithm is non-blocking, adaptive, and does not use any control message. Compared to other contemporary checkpointing algorithms, it is computationally more efficient because it takes lesser number of checkpoints and does not need to compute dependency relationships. A brief account of important and relevant works in both the fields, time-based and index-based, has also been included in the presentation.

Finite Element Study on Corono-Radicular Restored Premolars

Restoration of endodontically treated teeth is a common problem in dentistry, related to the fractures occurring in such teeth and to concentration of forces little information regarding variation of basic preparation guidelines in stress distribution has been available. To date, there is still no agreement in the literature about which material or technique can optimally restore endodontically treated teeth. The aim of the present study was to evaluate the influence of the core height and restoration materials on corono-radicular restored upper first premolar. The first step of the study was to achieve 3D models in order to analyze teeth, dowel and core restorations and overlying full ceramic crowns. The FEM model was obtained by importing the solid model into ANSYS finite element analysis software. An occlusal load of 100 N was conducted, and stresses occurring in the restorations, and teeth structures were calculated. Numerical simulations provide a biomechanical explanation for stress distribution in prosthetic restored teeth. Within the limitations of the present study, it was found that the core height has no important influence on the stress generated in coronoradicular restored premolars. It can be drawn that the cervical regions of the teeth and restorations were subjected to the highest stress concentrations.

Computer Proven Correctness of the Rabin Public-Key Scheme

We decribe a formal specification and verification of the Rabin public-key scheme in the formal proof system Is-abelle/HOL. The idea is to use the two views of cryptographic verification: the computational approach relying on the vocabulary of probability theory and complexity theory and the formal approach based on ideas and techniques from logic and programming languages. The analysis presented uses a given database to prove formal properties of our implemented functions with computer support. Thema in task in designing a practical formalization of correctness as well as security properties is to cope with the complexity of cryptographic proving. We reduce this complexity by exploring a light-weight formalization that enables both appropriate formal definitions as well as eficient formal proofs. This yields the first computer-proved implementation of the Rabin public-key scheme in Isabelle/HOL. Consequently, we get reliable proofs with a minimal error rate augmenting the used database. This provides a formal basis for more computer proof constructions in this area.

Arterial Stiffness Detection Depending on Neural Network Classification of the Multi- Input Parameters

Diagnostic and detection of the arterial stiffness is very important; which gives indication of the associated increased risk of cardiovascular diseases. To make a cheap and easy method for general screening technique to avoid the future cardiovascular complexes , due to the rising of the arterial stiffness ; a proposed algorithm depending on photoplethysmogram to be used. The photoplethysmograph signals would be processed in MATLAB. The signal will be filtered, baseline wandering removed, peaks and valleys detected and normalization of the signals should be achieved .The area under the catacrotic phase of the photoplethysmogram pulse curve is calculated using trapezoidal algorithm ; then will used in cooperation with other parameters such as age, height, blood pressure in neural network for arterial stiffness detection. The Neural network were implemented with sensitivity of 80%, accuracy 85% and specificity of 90% were got from the patients data. It is concluded that neural network can detect the arterial STIFFNESS depending on risk factor parameters.

Fuzzy Wavelet Packet based Feature Extraction Method for Multifunction Myoelectric Control

The myoelectric signal (MES) is one of the Biosignals utilized in helping humans to control equipments. Recent approaches in MES classification to control prosthetic devices employing pattern recognition techniques revealed two problems, first, the classification performance of the system starts degrading when the number of motion classes to be classified increases, second, in order to solve the first problem, additional complicated methods were utilized which increase the computational cost of a multifunction myoelectric control system. In an effort to solve these problems and to achieve a feasible design for real time implementation with high overall accuracy, this paper presents a new method for feature extraction in MES recognition systems. The method works by extracting features using Wavelet Packet Transform (WPT) applied on the MES from multiple channels, and then employs Fuzzy c-means (FCM) algorithm to generate a measure that judges on features suitability for classification. Finally, Principle Component Analysis (PCA) is utilized to reduce the size of the data before computing the classification accuracy with a multilayer perceptron neural network. The proposed system produces powerful classification results (99% accuracy) by using only a small portion of the original feature set.

Volterra Filtering Techniques for Removal of Gaussian and Mixed Gaussian-Impulse Noise

In this paper, we propose a new class of Volterra series based filters for image enhancement and restoration. Generally the linear filters reduce the noise and cause blurring at the edges. Some nonlinear filters based on median operator or rank operator deal with only impulse noise and fail to cancel the most common Gaussian distributed noise. A class of second order Volterra filters is proposed to optimize the trade-off between noise removal and edge preservation. In this paper, we consider both the Gaussian and mixed Gaussian-impulse noise to test the robustness of the filter. Image enhancement and restoration results using the proposed Volterra filter are found to be superior to those obtained with standard linear and nonlinear filters.

Drowsiness Warning System Using Artificial Intelligence

Nowadays, driving support systems, such as car navigation systems, are getting common, and they support drivers in several aspects. It is important for driving support systems to detect status of driver's consciousness. Particularly, detecting driver's drowsiness could prevent drivers from collisions caused by drowsy driving. In this paper, we discuss the various artificial detection methods for detecting driver's drowsiness processing technique. This system is based on facial images analysis for warning the driver of drowsiness or in attention to prevent traffic accidents.

EEG Waves Classifier using Wavelet Transform and Fourier Transform

The electroencephalograph (EEG) signal is one of the most widely signal used in the bioinformatics field due to its rich information about human tasks. In this work EEG waves classification is achieved using the Discrete Wavelet Transform DWT with Fast Fourier Transform (FFT) by adopting the normalized EEG data. The DWT is used as a classifier of the EEG wave's frequencies, while FFT is implemented to visualize the EEG waves in multi-resolution of DWT. Several real EEG data sets (real EEG data for both normal and abnormal persons) have been tested and the results improve the validity of the proposed technique.

Reduction of Linear Time-Invariant Systems Using Routh-Approximation and PSO

Order reduction of linear-time invariant systems employing two methods; one using the advantages of Routh approximation and other by an evolutionary technique is presented in this paper. In Routh approximation method the denominator of the reduced order model is obtained using Routh approximation while the numerator of the reduced order model is determined using the indirect approach of retaining the time moments and/or Markov parameters of original system. By this method the reduced order model guarantees stability if the original high order model is stable. In the second method Particle Swarm Optimization (PSO) is employed to reduce the higher order model. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical examples.

MPSO based Model Order Formulation Technique for SISO Continuous Systems

This paper proposes a new version of the Particle Swarm Optimization (PSO) namely, Modified PSO (MPSO) for model order formulation of Single Input Single Output (SISO) linear time invariant continuous systems. In the General PSO, the movement of a particle is governed by three behaviors namely inertia, cognitive and social. The cognitive behavior helps the particle to remember its previous visited best position. In Modified PSO technique split the cognitive behavior into two sections like previous visited best position and also previous visited worst position. This modification helps the particle to search the target very effectively. MPSO approach is proposed to formulate the higher order model. The method based on the minimization of error between the transient responses of original higher order model and the reduced order model pertaining to the unit step input. The results obtained are compared with the earlier techniques utilized, to validate its ease of computation. The proposed method is illustrated through numerical example from literature.

Improving Survivability in Wireless Ad Hoc Network

Topological changes in mobile ad hoc networks frequently render routing paths unusable. Such recurrent path failures have detrimental effects on quality of service. A suitable technique for eliminating this problem is to use multiple backup paths between the source and the destination in the network. This paper proposes an effective and efficient protocol for backup and disjoint path set in ad hoc wireless network. This protocol converges to a highly reliable path set very fast with no message exchange overhead. The paths selection according to this algorithm is beneficial for mobile ad hoc networks, since it produce a set of backup paths with more high reliability. Simulation experiments are conducted to evaluate the performance of our algorithm in terms of route numbers in the path set and its reliability. In order to acquire link reliability estimates, we use link expiration time (LET) between two nodes.

Syntax Sensitive and Language Independent Detection of Code Clones

This paper proposes a new technique to detect code clones from the lexical and syntactic point of view, which is based on PALEX source code representation. The PALEX code contains the recorded parsing actions and also lexical formatting information including white spaces and comments. We can record a list of parsing actions (shift, reduce, and reading a token) during a compiling process after a compiler finishes analyzing the source code. The proposed technique has advantages for syntax sensitive approach and language independency.

Understanding Charge Dynamics in Elastomers Adopting Pulsed Electro Acoustic (PEA) Technique

In the present work, Pulsed Electro Acoustic (PEA) technique was adopted to understand the space charge dynamics in elastomeric material. It is observed that the polarity of the applied DC voltage voltage and its magnitude alters the space charge dynamics in insulation structure. It is also noticed that any addition of compound to the base material/processing technique have characteristic variation in the space charge injection process. It could be concluded based on the present work that the plasticizer could inject heterocharges into the insulation medium. Also it is realized that space charge magnitude is less with the addition of plasticizer. In the PEA studies, it is observed that local electric field in the insulating material can be much more than applied electric field due to space charge formation. One of the important conclusions arrived at based on PEA technique is that one could understand the safe operating electric field of an insulation material and the charge trap sites.

Modelling Sudoku Puzzles as Block-world Problems

Sudoku is a kind of logic puzzles. Each puzzle consists of a board, which is a 9×9 cells, divided into nine 3×3 subblocks and a set of numbers from 1 to 9. The aim of this puzzle is to fill in every cell of the board with a number from 1 to 9 such that in every row, every column, and every subblock contains each number exactly one. Sudoku puzzles belong to combinatorial problem (NP complete). Sudoku puzzles can be solved by using a variety of techniques/algorithms such as genetic algorithms, heuristics, integer programming, and so on. In this paper, we propose a new approach for solving Sudoku which is by modelling them as block-world problems. In block-world problems, there are a number of boxes on the table with a particular order or arrangement. The objective of this problem is to change this arrangement into the targeted arrangement with the help of two types of robots. In this paper, we present three models for Sudoku. We modellized Sudoku as parameterized multi-agent systems. A parameterized multi-agent system is a multi-agent system which consists of several uniform/similar agents and the number of the agents in the system is stated as the parameter of this system. We use Temporal Logic of Actions (TLA) for formalizing our models.

Optimal Switching Strategies for Tracking of Currents of Voltage Source Converters

This paper proposes a new optimal feedback controller for voltage source converters VSC's, for current regulated voltage source converters, which allows compensate the harmonics of current produced by nonlinear loads and load reactive power. The aim of the present paper is to describe a novel switching signal generation technique called optimal controller which guarantees that the injected currents follow the reference currents determined by the compensation strategy, with the smallest possible tracking error and fixed switching frequency. It is compared with well-known hysteresis current controller HCC. The validity of presented method and its comparison with HCC is studied through simulation results.

Performance Analysis of a Discrete-time GeoX/G/1 Queue with Single Working Vacation

This paper treats a discrete-time batch arrival queue with single working vacation. The main purpose of this paper is to present a performance analysis of this system by using the supplementary variable technique. For this purpose, we first analyze the Markov chain underlying the queueing system and obtain its ergodicity condition. Next, we present the stationary distributions of the system length as well as some performance measures at random epochs by using the supplementary variable method. Thirdly, still based on the supplementary variable method we give the probability generating function (PGF) of the number of customers at the beginning of a busy period and give a stochastic decomposition formulae for the PGF of the stationary system length at the departure epochs. Additionally, we investigate the relation between our discretetime system and its continuous counterpart. Finally, some numerical examples show the influence of the parameters on some crucial performance characteristics of the system.

Characterization of ZrO2/PEG Composite Film as Immobilization Matrix for Glucose Oxidase

A biosensor based on glucose oxidase (GOx) immobilized onto nanoparticles zirconium oxide with polyethylene nanocomposite for glucose monitoring has been designed. The CTAB/PEG/ZrO2/GOx nanocomposite was deposited onto screen printed carbon paste (SPCE) electrode via spin coating technique. The properties of CTAB/PEG/ZrO2/GOx were study using scanning electron microscopy (SEM). The SPE modified with the CTAB/PEG/ZrO2/GOx showed electrocatalytical response to the oxidation of glucose when ferrocene carboxaldehyde was used as an artificial redox mediator, which was studied by cyclic voltammetry (CV). Several parameters such as working potential, effect of pH and effect of ZrO2/PEG layers that governed the analytical performance of the biosensor, have been studied. The biosensor was applied to detect glucose with a linear range of 0.4 to 2.0 mmol L−1 with good repetability and reproducibility.

Context-Aware Querying in Multimedia Databases – A Futuristic Approach

Efficient retrieval of multimedia objects has gained enormous focus in recent years. A number of techniques have been suggested for retrieval of textual information; however, relatively little has been suggested for efficient retrieval of multimedia objects. In this paper we have proposed a generic architecture for contextaware retrieval of multimedia objects. The proposed framework combines the well-known approaches of text-based retrieval and context-aware retrieval to formulate architecture for accurate retrieval of multimedia data.

Spatio-Temporal Video Slice Edges Analysis for Shot Transition Detection and Classification

In this work we will present a new approach for shot transition auto-detection. Our approach is based on the analysis of Spatio-Temporal Video Slice (STVS) edges extracted from videos. The proposed approach is capable to efficiently detect both abrupt shot transitions 'cuts' and gradual ones such as fade-in, fade-out and dissolve. Compared to other techniques, our method is distinguished by its high level of precision and speed. Those performances are obtained due to minimizing the problem of the boundary shot detection to a simple 2D image partitioning problem.

Performance Analysis of CATR Reflector with Super Hybrid Modulated Segmented Exponential Serrated Edges

This paper presented a theoretical and numerical investigation of the Compact Antenna Test Range (CATR) equipped with Super Hybrid Modulated Segmented Exponential Serrations (SHMSES). The investigation was based on diffraction theory and, more specifically, the Fresnel diffraction formulation. The CATR provides uniform illumination within the Fresnel region to test antenna. Application of serrated edges has been shown to be a good method to control diffraction at the edges of the reflectors. However, in order to get some insight into the positive effect of serrated edges a less rigorous analysis technique known as Physical Optics (PO) may be used. Ripple free and enhanced quiet zone width are observed for specific values of width and height modulation factors per serrations. The performance of SHMSE serrated reflector is evaluated in order to observe the effects of edge diffraction on the test zone fields.