Real-Time Image Analysis of Capsule Endoscopy for Bleeding Discrimination in Embedded System Platform

Image processing for capsule endoscopy requires large memory and it takes hours for diagnosis since operation time is normally more than 8 hours. A real-time analysis algorithm of capsule images can be clinically very useful. It can differentiate abnormal tissue from health structure and provide with correlation information among the images. Bleeding is our interest in this regard and we propose a method of detecting frames with potential bleeding in real-time. Our detection algorithm is based on statistical analysis and the shapes of bleeding spots. We tested our algorithm with 30 cases of capsule endoscopy in the digestive track. Results were excellent where a sensitivity of 99% and a specificity of 97% were achieved in detecting the image frames with bleeding spots.

MITAutomatic ECG Beat Tachycardia Detection Using Artificial Neural Network

The application of Neural Network for disease diagnosis has made great progress and is widely used by physicians. An Electrocardiogram carries vital information about heart activity and physicians use this signal for cardiac disease diagnosis which was the great motivation towards our study. In our work, tachycardia features obtained are used for the training and testing of a Neural Network. In this study we are using Fuzzy Probabilistic Neural Networks as an automatic technique for ECG signal analysis. As every real signal recorded by the equipment can have different artifacts, we needed to do some preprocessing steps before feeding it to our system. Wavelet transform is used for extracting the morphological parameters of the ECG signal. The outcome of the approach for the variety of arrhythmias shows the represented approach is superior than prior presented algorithms with an average accuracy of about %95 for more than 7 tachy arrhythmias.

Energy Recovery Soft Switching Improved Efficiency Half Bridge Inverter for Electronic Ballast Applications

An improved topology of a voltage-fed quasi-resonant soft switching LCrCdc series-parallel half bridge inverter with a constant-frequency for electronic ballast applications is proposed in this paper. This new topology introduces a low-cost solution to reduce switching losses and circuit rating to achieve high-efficiency ballast. Switching losses effect on ballast efficiency is discussed through experimental point of view. In this discussion, an improved topology in which accomplishes soft switching operation over a wide power regulation range is proposed. The proposed structure uses reverse recovery diode to provide better operation for the ballast system. A symmetrical pulse wide modulation (PWM) control scheme is implemented to regulate a wide range of out-put power. Simulation results are kindly verified with the experimental measurements obtained by ballast-lamp laboratory prototype. Different load conditions are provided in order to clarify the performance of the proposed converter.

Dynamics of a Vapour Bubble inside a Vertical Rigid Cylinder in the Absence of Buoyancy Forces

In this paper, growth and collapse of a vapour bubble generated due to a local energy input inside a rigid cylinder and in the absence of buoyancy forces is investigated using Boundary Integral Equation Method and Finite Difference Method .The fluid is treated as potential flow and Boundary Integral Equation Method is used to solve Laplace-s equation for velocity potential. Different ratios of the diameter of the rigid cylinder to the maximum radius of the bubble are considered. Results show that during the collapse phase of the bubble inside a vertical rigid cylinder, two liquid micro jets are developed on the top and bottom sides of the vapour bubble and are directed inward. It is found that by increasing the ratio of the cylinder diameter to the maximum radius of the bubble, the rate of the growth and collapse phases of the bubble increases and the life time of the bubble decreases.

Detection of Action Potentials in the Presence of Noise Using Phase-Space Techniques

Emerging Bio-engineering fields such as Brain Computer Interfaces, neuroprothesis devices and modeling and simulation of neural networks have led to increased research activity in algorithms for the detection, isolation and classification of Action Potentials (AP) from noisy data trains. Current techniques in the field of 'unsupervised no-prior knowledge' biosignal processing include energy operators, wavelet detection and adaptive thresholding. These tend to bias towards larger AP waveforms, AP may be missed due to deviations in spike shape and frequency and correlated noise spectrums can cause false detection. Also, such algorithms tend to suffer from large computational expense. A new signal detection technique based upon the ideas of phasespace diagrams and trajectories is proposed based upon the use of a delayed copy of the AP to highlight discontinuities relative to background noise. This idea has been used to create algorithms that are computationally inexpensive and address the above problems. Distinct AP have been picked out and manually classified from real physiological data recorded from a cockroach. To facilitate testing of the new technique, an Auto Regressive Moving Average (ARMA) noise model has been constructed bases upon background noise of the recordings. Along with the AP classification means this model enables generation of realistic neuronal data sets at arbitrary signal to noise ratio (SNR).

Simulating Laboratory Short Term Aging to Suit Malaysian Field Conditions

This paper characterizes the effects of artificial short term aging in the laboratory on the rheological properties of virgin 80/100 penetration grade asphalt binder. After several years in service, asphalt mixture started to deteriorate due to aging. Aging is a complex physico-chemical phenomenon that influences asphalt binder rheological properties causing a deterioration in asphalt mixture performance. To ascertain asphalt binder aging effects, the virgin, artificially aged and extracted asphalt binder were tested via the Rolling Thin film Oven (RTFO), Dynamic Shear Rheometer (DSR) and Rotational Viscometer (RV). A comparative study between laboratory and field aging conditions were also carried out. The results showed that the specimens conditioned for 85 minutes inside the RTFO was insufficient to simulate the actual short term aging caused that took place in the field under Malaysian field conditions

CAD Model of Cole Cole Representation for Analyzing Performance of Microstrip Moisture Sensing Applications

In the past decade, the development of microstrip sensor application has evolved tremendously. Although cut and trial method was adopted to develop microstrip sensing applications in the past, Computer-Aided-Design (CAD) is a more effective as it ensures less time is consumed and cost saving is achieved in developing microstrip sensing applications. Therefore microstrip sensing applications has gained popularity as an effective tool adopted in continuous sensing of moisture content particularly in products that is administered mainly by liquid content. In this research, the Cole-Cole representation of reactive relaxation is applied to assess the performance of the microstrip sensor devices. The microstrip sensor application is an effective tool suitable for sensing the moisture content of dielectric material. Analogous to dielectric relaxation consideration of Cole-Cole diagrams as applied to dielectric materials, a “reactive relaxation concept” concept is introduced to represent the frequency-dependent and moisture content characteristics of microstrip sensor devices.

Grouping-Based Job Scheduling Model In Grid Computing

Grid computing is a high performance computing environment to solve larger scale computational applications. Grid computing contains resource management, job scheduling, security problems, information management and so on. Job scheduling is a fundamental and important issue in achieving high performance in grid computing systems. However, it is a big challenge to design an efficient scheduler and its implementation. In Grid Computing, there is a need of further improvement in Job Scheduling algorithm to schedule the light-weight or small jobs into a coarse-grained or group of jobs, which will reduce the communication time, processing time and enhance resource utilization. This Grouping strategy considers the processing power, memory-size and bandwidth requirements of each job to realize the real grid system. The experimental results demonstrate that the proposed scheduling algorithm efficiently reduces the processing time of jobs in comparison to others.

Modeling the Vapor Pressure of Biodiesel Fuels

The composition, vapour pressure, and heat capacity of nine biodiesel fuels from different sources were measured. The vapour pressure of the biodiesel fuels is modeled assuming an ideal liquid phase of the fatty acid methyl esters constituting the fuel. New methodologies to calculate the vapour pressure and ideal gas and liquid heat capacities of the biodiesel fuel constituents are proposed. Two alternative optimization scenarios are evaluated: 1) vapour pressure only; 2) vapour pressure constrained with liquid heat capacity. Without physical constraints, significant errors in liquid heat capacity predictions were found whereas the constrained correlation accurately fit both vapour pressure and liquid heat capacity.

A Formal Suite of Object Relational Database Metrics

Object Relational Databases (ORDB) are complex in nature than traditional relational databases because they combine the characteristics of both object oriented concepts and relational features of conventional databases. Design of an ORDB demands efficient and quality schema considering the structural, functional and componential traits. This internal quality of the schema is assured by metrics that measure the relevant attributes. This is extended to substantiate the understandability, usability and reliability of the schema, thus assuring external quality of the schema. This work institutes a formalization of ORDB metrics; metric definition, evaluation methodology and the calibration of the metric. Three ORDB schemas were used to conduct the evaluation and the formalization of the metrics. The metrics are calibrated using content and criteria related validity based on the measurability, consistency and reliability of the metrics. Nominal and summative scales are derived based on the evaluated metric values and are standardized. Future works pertaining to ORDB metrics forms the concluding note.

Implementation and Simulation of Half-Bridge Series Resonant Inverter in Zero Voltage Switching

In switch mode power inverters, small sized inverters can be obtained by increasing the switching frequency. Switching frequency increment causes high driver losses. Also, high dt di and dt dv produced by the switching action creates high Electromagnetic Interference (EMI) and Radio Frequency Interference (RFI). In this paper, a series half bridge series resonant inverter circuit is simulated and evaluated practically to demonstrate the turn-on and turn-off conditions during zero or close to zero voltage switching. Also, the reverse recovery current effects of the body diode of the MOSFETs were investigated by operating above and below resonant frequency.

Definition of Foot Size Model using Kohonen Network

In order to define a new model of Tunisian foot sizes and for building the most comfortable shoes, Tunisian industrialists must be able to offer for their customers products able to put on and adjust the majority of the target population concerned. Moreover, the use of models of shoes, mainly from others country, causes a mismatch between the foot and comfort of the Tunisian shoes. But every foot is unique; these models become uncomfortable for the Tunisian foot. We have a set of measures produced from a 3D scan of the feet of a diverse population (women, men ...) and we try to analyze this data to define a model of foot specific to the Tunisian footwear design. In this paper we propose tow new approaches to modeling a new foot sizes model. We used, indeed, the neural networks, and specially the Kohonen network. Next, we combine neural networks with the concept of half-foot size to improve the models already found. Finally, it was necessary to compare the results obtained by applying each approach and we decide what-s the best approach that give us the most model of foot improving more comfortable shoes.

Diagnostic Investigation of Liftoff Time of Solid Propellant Rockets

In this paper parametric analytical studies have been carried out to examine the intrinsic flow physics pertaining to the liftoff time of solid propellant rockets. Idealized inert simulators of solid rockets are selected for numerical studies to examining the preignition chamber dynamics. Detailed diagnostic investigations have been carried out using an unsteady two-dimensional k-omega turbulence model. We conjectured from the numerical results that the altered variations of the igniter jet impingement angle, turbulence level, time and location of the first ignition, flame spread characteristics, the overall chamber dynamics including the boundary layer growth history are having bearing on the time for nozzle flow chocking for establishing the required thrust for the rocket liftoff. We concluded that the altered flow choking time of strap-on motors with the pre-determined identical ignition time at the lift off phase will lead to the malfunctioning of the rocket. We also concluded that, in the light of the space debris, an error in predicting the liftoff time can lead to an unfavorable launch window amounts the satellite injection errors and/or the mission failures.

Visual-Graphical Methods for Exploring Longitudinal Data

Longitudinal data typically have the characteristics of changes over time, nonlinear growth patterns, between-subjects variability, and the within errors exhibiting heteroscedasticity and dependence. The data exploration is more complicated than that of cross-sectional data. The purpose of this paper is to organize/integrate of various visual-graphical techniques to explore longitudinal data. From the application of the proposed methods, investigators can answer the research questions include characterizing or describing the growth patterns at both group and individual level, identifying the time points where important changes occur and unusual subjects, selecting suitable statistical models, and suggesting possible within-error variance.

Solving Bus Terminal Location Problem Using Genetic Algorithm

Bus networks design is an important problem in public transportation. The main step to this design, is determining the number of required terminals and their locations. This is an especial type of facility location problem, a large scale combinatorial optimization problem that requires a long time to be solved. The genetic algorithm (GA) is a search and optimization technique which works based on evolutionary principle of natural chromosomes. Specifically, the evolution of chromosomes due to the action of crossover, mutation and natural selection of chromosomes based on Darwin's survival-of-the-fittest principle, are all artificially simulated to constitute a robust search and optimization procedure. In this paper, we first state the problem as a mixed integer programming (MIP) problem. Then we design a new crossover and mutation for bus terminal location problem (BTLP). We tested the different parameters of genetic algorithm (for a sample problem) and obtained the optimal parameters for solving BTLP with numerical try and error.

A Further Improvement on the Resurrected Core-Spreading Vortex Method

In a previously developed fast vortex method, the diffusion of the vortex sheet induced at the solid wall by the no-slip boundary conditions was modeled according to the approximation solution of Koumoutsakos and converted into discrete blobs in the vicinity of the wall. This scheme had been successfully applied to a simulation of the flow induced with an impulsively initiated circular cylinder. In this work, further modifications on this vortex method are attempted, including replacing the approximation solution by the boundary-element-method solution, incorporating a new algorithm for handling the over-weak vortex blobs, and diffusing the vortex sheet circulation in a new way suitable for high-curvature solid bodies. The accuracy is thus largely improved. The predictions of lift and drag coefficients for a uniform flow past a NASA airfoil agree well with the existing literature.

An Energy Aware Dispatch Scheme WSNs

One of the key research issues in wireless sensor networks (WSNs) is how to efficiently deploy sensors to cover an area. In this paper, we present a Fishnet Based Dispatch Scheme (FiBDS) with energy aware mobility and interest based sensing angle. We propose two algorithms, one is FiBDS centralized algorithm and another is FiBDS distributed algorithm. The centralized algorithm is designed specifically for the non-time critical applications, commonly known as non real-time applications while the distributed algorithm is designed specifically for the time critical applications, commonly known as real-time applications. The proposed dispatch scheme works in a phase-selection manner. In this in each phase a specific constraint is dealt with according to the specified priority and then moved onto the next phase and at the end of each only the best suited nodes for the phase are chosen. Simulation results are presented to verify their effectiveness. 

Implementation of Sprite Animation for Multimedia Application

Animation is simply defined as the sequencing of a series of static images to generate the illusion of movement. Most people believe that actual drawings or creation of the individual images is the animation, when in actuality it is the arrangement of those static images that conveys the motion. To become an animator, it is often assumed that needed the ability to quickly design masterpiece after masterpiece. Although some semblance of artistic skill is a necessity for the job, the real key to becoming a great animator is in the comprehension of timing. This paper will use a combination of sprite animation, frame animation, and some other techniques to cause a group of multi-colored static images to slither around in the bounded area. In addition to slithering, the images will also change the color of different parts of their body, much like the real world creatures that have this amazing ability to change the colors on their bodies do. This paper was implemented by using Java 2 Standard Edition (J2SE). It is both time-consuming and expensive to create animations, regardless if they are created by hand or by using motion-capture equipment. If the animators could reuse old animations and even blend different animations together, a lot of work would be saved in the process. The main objective of this paper is to examine a method for blending several animations together in real time. This paper presents and analyses a solution using Weighted Skeleton Animation (WSA) resulting in limited CPU time and memory waste as well as saving time for the animators. The idea presented is described in detail and implemented. In this paper, text animation, vertex animation, sprite part animation and whole sprite animation were tested. In this research paper, the resolution, smoothness and movement of animated images will be carried out from the parameters, which will be obtained from the experimental research of implementing this paper.

Image Mapping with Cumulative Distribution Function for Quick Convergence of Counter Propagation Neural Networks in Image Compression

In general the images used for compression are of different types like dark image, high intensity image etc. When these images are compressed using Counter Propagation Neural Network, it takes longer time to converge. The reason for this is that the given image may contain a number of distinct gray levels with narrow difference with their neighborhood pixels. If the gray levels of the pixels in an image and their neighbors are mapped in such a way that the difference in the gray levels of the neighbor with the pixel is minimum, then compression ratio as well as the convergence of the network can be improved. To achieve this, a Cumulative Distribution Function is estimated for the image and it is used to map the image pixels. When the mapped image pixels are used the Counter Propagation Neural Network yield high compression ratio as well as it converges quickly.

A Real-Time Tracking System Developed for an Interactive Stage Performance

A real-time tracking system was built to track performers on an interactive stage. Using an ordinary, up to date, desktop workstation, the performers- silhouette was segmented from the background and parameterized by calculating the normalized central image moments. In the stage system, the silhouette moments were then sent to a parallel workstation, which used them to generate corresponding 3D virtual geometry and projected the generated graphic back onto the stage.