Study of Compaction in Hot-Mix Asphalt Using Computer Simulations

During the process of compaction in Hot-Mix Asphalt (HMA) mixtures, the distance between aggregate particles decreases as they come together and eliminate air-voids. By measuring the inter-particle distances in a cut-section of a HMA sample the degree of compaction can be estimated. For this, a calibration curve is generated by computer simulation technique when the gradation and asphalt content of the HMA mixture are known. A two-dimensional cross section of HMA specimen was simulated using the mixture design information (gradation, asphalt content and air-void content). Nearest neighbor distance methods such as Delaunay triangulation were used to study the changes in inter-particle distance and area distribution during the process of compaction in HMA. Such computer simulations would enable making several hundreds of repetitions in a short period of time without the necessity to compact and analyze laboratory specimens in order to obtain good statistics on the parameters defined. The distributions for the statistical parameters based on computer simulations showed similar trends as those of laboratory specimens.

Fuzzy Cost Support Vector Regression

In this paper, a new version of support vector regression (SVR) is presented namely Fuzzy Cost SVR (FCSVR). Individual property of the FCSVR is operation over fuzzy data whereas fuzzy cost (fuzzy margin and fuzzy penalty) are maximized. This idea admits to have uncertainty in the penalty and margin terms jointly. Robustness against noise is shown in the experimental results as a property of the proposed method and superiority relative conventional SVR.

Researches on Simulation and Validation of Airborne Enhanced Ground Proximity Warning System

In this paper, enhanced ground proximity warning simulation and validation system is designed and implemented. First, based on square grid and sub-grid structure, the global digital terrain database is designed and constructed. Terrain data searching is implemented through querying the latitude and longitude bands and separated zones of global terrain database with the current aircraft position. A combination of dynamic scheduling and hierarchical scheduling is adopted to schedule the terrain data, and the terrain data can be read and delete dynamically in the memory. Secondly, according to the scope, distance, approach speed information etc. to the dangerous terrain in front, and using security profiles calculating method, collision threat detection is executed in real-time, and provides caution and warning alarm. According to this scheme, the implementation of the enhanced ground proximity warning simulation system is realized. Simulations are carried out to verify a good real-time in terrain display and alarm trigger, and the results show simulation system is realized correctly, reasonably and stable.

Performance Evaluation of ROI Extraction Models from Stationary Images

In this paper three basic approaches and different methods under each of them for extracting region of interest (ROI) from stationary images are explored. The results obtained for each of the proposed methods are shown, and it is demonstrated where each method outperforms the other. Two main problems in ROI extraction: the channel selection problem and the saliency reversal problem are discussed and how best these two are addressed by various methods is also seen. The basic approaches are 1) Saliency based approach 2) Wavelet based approach 3) Clustering based approach. The saliency approach performs well on images containing objects of high saturation and brightness. The wavelet based approach performs well on natural scene images that contain regions of distinct textures. The mean shift clustering approach partitions the image into regions according to the density distribution of pixel intensities. The experimental results of various methodologies show that each technique performs at different acceptable levels for various types of images.

Optimizing the Design of Radial/Axial PMSM and SRM used for Powered Wheel-Chairs

the paper presents the optimization results for several electrical machines dedicated for powered electric wheel-chairs. The optimization, using the Hook-Jeeves algorithm, was employed based on a design approach which takes into consideration the road conditions. Also, through numerical simulations (based on finite element method), the analytical approach was validated. The optimization approach gave satisfactory results and the best suited variant was chosen for the motorization of the wheel-chair.

“FGM is with us Everyday“ Women and Girls Speak out about Female Genital Mutilation in the UK

There is inadequate information on the practice of female genital mutilation (FGM) in the UK, and there are often myths and perceptions within communities that influence the effectiveness of prevention programmes. This means it is difficult to address the trends and changes in the practice in the UK. To this end, FORWARD undertook novel and innovative research using the Participatory Ethnographic and Evaluative Research (PEER) method to explore the views of women from Eritrea, Sudan, Somalia and Ethiopia that live in London and Bristol (two UK cities). Women-s views, taken from PEER interviews, reflected reasons for continued practice of FGM: marriageability, the harnessing and control of female sexuality, and upholding traditions from their countries of origin. It was also clear that the main supporters of the practice were believed to be older women within families and communities. Women described the impact FGM was having on their lives as isolating. And although it was clearly considered a private and personal matter, they developed a real sense of connection with their peers within the research process. The women were overwhelmingly positive about combating the practice, although they believed it would probably take a while before it ends completely. They also made concrete recommendations on how to improve support services for women affected by FGM: Training for professionals (particularly in healthcare), increased engagement with, and outreach to, communities, culturally appropriate materials and information made available and accessible to communities, and more consequent implementation of legislation. Finally, the women asked for more empathy and understanding, particularly from health professionals. Rather than presenting FGM as a completely alien and inconceivable practice, it may help for those looking into these women-s lives and working with them to understand the social and economic context in which the practice takes place.

A Novel Hopfield Neural Network for Perfect Calculation of Magnetic Resonance Spectroscopy

In this paper, an automatic determination algorithm for nuclear magnetic resonance (NMR) spectra of the metabolites in the living body by magnetic resonance spectroscopy (MRS) without human intervention or complicated calculations is presented. In such method, the problem of NMR spectrum determination is transformed into the determination of the parameters of a mathematical model of the NMR signal. To calculate these parameters efficiently, a new model called modified Hopfield neural network is designed. The main achievement of this paper over the work in literature [30] is that the speed of the modified Hopfield neural network is accelerated. This is done by applying cross correlation in the frequency domain between the input values and the input weights. The modified Hopfield neural network can accomplish complex dignals perfectly with out any additinal computation steps. This is a valuable advantage as NMR signals are complex-valued. In addition, a technique called “modified sequential extension of section (MSES)" that takes into account the damping rate of the NMR signal is developed to be faster than that presented in [30]. Simulation results show that the calculation precision of the spectrum improves when MSES is used along with the neural network. Furthermore, MSES is found to reduce the local minimum problem in Hopfield neural networks. Moreover, the performance of the proposed method is evaluated and there is no effect on the performance of calculations when using the modified Hopfield neural networks.

Design of a 5-Joint Mechanical Arm with User-Friendly Control Program

This paper describes the design concepts and implementation of a 5-Joint mechanical arm for a rescue robot named CEO Mission II. The multi-joint arm is a five degree of freedom mechanical arm with a four bar linkage, which can be stretched to 125 cm. long. It is controlled by a teleoperator via the user-friendly control and monitoring GUI program. With Inverse Kinematics principle, we developed the method to control the servo angles of all arm joints to get the desired tip position. By clicking the determined tip position or dragging the tip of the mechanical arm on the computer screen to the desired target point, the robot will compute and move its multi-joint arm to the pose as seen on the GUI screen. The angles of each joint are calculated and sent to all joint servos simultaneously in order to move the mechanical arm to the desired pose at once. The operator can also use a joystick to control the movement of this mechanical arm and the locomotion of the robot. Many sensors are installed at the tip of this mechanical arm for surveillance from the high level and getting the vital signs of victims easier and faster in the urban search and rescue tasks. It works very effectively and easy to control. This mechanical arm and its software were developed as a part of the CEO Mission II Rescue Robot that won the First Runner Up award and the Best Technique award from the Thailand Rescue Robot Championship 2006. It is a low cost, simple, but functioning 5-Jiont mechanical arm which is built from scratch, and controlled via wireless LAN 802.11b/g. This 5-Jiont mechanical arm hardware concept and its software can also be used as the basic mechatronics to many real applications.

Mathematical Correlation for Brake Thermal Efficiency and NOx Emission of CI Engine using Ester of Vegetable Oils

The aim of this study is to develop mathematical relationships for the performance parameter brake thermal efficiency (BTE) and emission parameter nitrogen oxides (NOx) for the various esters of vegetable oils used as CI engine fuel. The BTE is an important performance parameter defining the ability of engine to utilize the energy supplied and power developed similarly it is indication of efficiency of fuels used. The esters of cottonseed oil, soybean oil, jatropha oil and hingan oil are prepared using transesterification process and characterized for their physical and main fuel properties including viscosity, density, flash point and higher heating value using standard test methods. These esters are tried as CI engine fuel to analyze the performance and emission parameters in comparison to diesel. The results of the study indicate that esters as a fuel does not differ greatly with that of diesel in properties. The CI engine performance with esters as fuel is in line with the diesel where as the emission parameters are reduced with the use of esters. The correlation developed between BTE and brake power(BP), gross calorific value(CV), air-fuel ratio(A/F), heat carried away by cooling water(HCW). Another equation is developed between the NOx emission and CO, HC, smoke density (SD), exhaust gas temperature (EGT). The equations are verified by comparing the observed and calculated values which gives the coefficient of correlation of 0.99 and 0.96 for the BTE and NOx equations respectively.

Quartic Nonpolynomial Spline Solutions for Third Order Two-Point Boundary Value Problem

In this paper, we develop quartic nonpolynomial spline method for the numerical solution of third order two point boundary value problems. It is shown that the new method gives approximations, which are better than those produced by other spline methods. Convergence analysis of the method is discussed through standard procedures. Two numerical examples are given to illustrate the applicability and efficiency of the novel method.

Extending E-learning systems based on Clause-Rule model

E-Learning systems are used by many learners and teachers. The developer is developing the e-Learning system. However, the developer cannot do system construction to satisfy all of users- demands. We discuss a method of constructing e-Learning systems where learners and teachers can design, try to use, and share extending system functions that they want to use; which may be nally added to the system by system managers.

Two Dimensional Simulation of Fluid Flow and Heat Transfer in the Transition Flow Regime using a Lattice Boltzmann Approach

The significant effects of the interactions between the system boundaries and the near wall molecules in miniaturized gaseous devices lead to the formation of the Knudsen layer in which the Navier-Stokes-Fourier (NSF) equations fail to predict the correct associated phenomena. In this paper, the well-known lattice Boltzmann method (LBM) is employed to simulate the fluid flow and heat transfer processes in rarefied gaseous micro media. Persuaded by the problematic deficiency of the LBM in capturing the Knudsen layer phenomena, present study tends to concentrate on the effective molecular mean free path concept the main essence of which is to compensate the incapability of this mesoscopic method in dealing with the momentum and energy transport within the above mentioned kinetic boundary layer. The results show qualitative and quantitative accuracy comparable to the solutions of the linearized Boltzmann equation or the DSMC data for the Knudsen numbers of O (1) .

Spacecraft Neural Network Control System Design using FPGA

Designing and implementing intelligent systems has become a crucial factor for the innovation and development of better products of space technologies. A neural network is a parallel system, capable of resolving paradigms that linear computing cannot. Field programmable gate array (FPGA) is a digital device that owns reprogrammable properties and robust flexibility. For the neural network based instrument prototype in real time application, conventional specific VLSI neural chip design suffers the limitation in time and cost. With low precision artificial neural network design, FPGAs have higher speed and smaller size for real time application than the VLSI and DSP chips. So, many researchers have made great efforts on the realization of neural network (NN) using FPGA technique. In this paper, an introduction of ANN and FPGA technique are briefly shown. Also, Hardware Description Language (VHDL) code has been proposed to implement ANNs as well as to present simulation results with floating point arithmetic. Synthesis results for ANN controller are developed using Precision RTL. Proposed VHDL implementation creates a flexible, fast method and high degree of parallelism for implementing ANN. The implementation of multi-layer NN using lookup table LUT reduces the resource utilization for implementation and time for execution.

Reducing Power in Error Correcting Code using Genetic Algorithm

This paper proposes a method which reduces power consumption in single-error correcting, double error-detecting checker circuits that perform memory error correction code. Power is minimized with little or no impact on area and delay, using the degrees of freedom in selecting the parity check matrix of the error correcting codes. The genetic algorithm is employed to solve the non linear power optimization problem. The method is applied to two commonly used SEC-DED codes: standard Hamming and odd column weight Hsiao codes. Experiments were performed to show the performance of the proposed method.

Numerical Analysis of Electrical Interaction between two Axisymmetric Spheroids

The electrical interaction between two axisymmetric spheroidal particles in an electrolyte solution is examined numerically. A Galerkin finite element method combined with a Newton-Raphson iteration scheme is proposed to evaluate the spatial variation in the electrical potential, and the result obtained used to estimate the interaction energy between two particles. We show that if the surface charge density is fixed, the potential gradient is larger at a point, which has a larger curvature, and if surface potential is fixed, surface charge density is proportional to the curvature. Also, if the total interaction energy against closest surface-to-surface curve exhibits a primary maximum, the maximum follows the order (oblate-oblate) > (sphere-sphere)>(oblate-prolate)>(prolate-prolate), and if the curve has a secondary minimum, the absolute value of the minimum follows the same order.

3D Brain Tumor Segmentation Using Level-Sets Method and Meshes Simplification from Volumetric MR Images

The main objective of this paper is to provide an efficient tool for delineating brain tumors in three-dimensional magnetic resonance images. To achieve this goal, we use basically a level-sets approach to delineating three-dimensional brain tumors. Then we introduce a compression plan of 3D brain structures based for the meshes simplification, adapted for time to the specific needs of the telemedicine and to the capacities restricted by network communication. We present here the main stages of our system, and preliminary results which are very encouraging for clinical practice.

A New Approach of Fuzzy Methods for Evaluating of Hydrological Data

The main criteria of designing in the most hydraulic constructions essentially are based on runoff or discharge of water. Two of those important criteria are runoff and return period. Mostly, these measures are calculated or estimated by stochastic data. Another feature in hydrological data is their impreciseness. Therefore, in order to deal with uncertainty and impreciseness, based on Buckley-s estimation method, a new fuzzy method of evaluating hydrological measures are developed. The method introduces triangular shape fuzzy numbers for different measures in which both of the uncertainty and impreciseness concepts are considered. Besides, since another important consideration in most of the hydrological studies is comparison of a measure during different months or years, a new fuzzy method which is consistent with special form of proposed fuzzy numbers, is also developed. Finally, to illustrate the methods more explicitly, the two algorithms are tested on one simple example and a real case study.

Quantifying and Adjusting the Effects of Publication Bias in Continuous Meta-Analysis

This study uses simulated meta-analysis to assess the effects of publication bias on meta-analysis estimates and to evaluate the efficacy of the trim and fill method in adjusting for these biases. The estimated effect sizes and the standard error were evaluated in terms of the statistical bias and the coverage probability. The results demonstrate that if publication bias is not adjusted it could lead to up to 40% bias in the treatment effect estimates. Utilization of the trim and fill method could reduce the bias in the overall estimate by more than half. The method is optimum in presence of moderate underlying bias but has minimal effects in presence of low and severe publication bias. Additionally, the trim and fill method improves the coverage probability by more than half when subjected to the same level of publication bias as those of the unadjusted data. The method however tends to produce false positive results and will incorrectly adjust the data for publication bias up to 45 % of the time. Nonetheless, the bias introduced into the estimates due to this adjustment is minimal

MRI Reconstruction Using Discrete Fourier Transform: A tutorial

The use of Inverse Discrete Fourier Transform (IDFT) implemented in the form of Inverse Fourier Transform (IFFT) is one of the standard method of reconstructing Magnetic Resonance Imaging (MRI) from uniformly sampled K-space data. In this tutorial, three of the major problems associated with the use of IFFT in MRI reconstruction are highlighted. The tutorial also gives brief introduction to MRI physics; MRI system from instrumentation point of view; K-space signal and the process of IDFT and IFFT for One and two dimensional (1D and 2D) data.

Ultrasonic System for Diagnosis of Functional Gastrointestinal Disorders: Development, Verification and Clinical Trials

Functional gastrointestinal disorders affect millions of people spread all age regardless of race and sex. There are, however, rare diagnostic methods for the functional gastrointestinal disorders because functional disorders show no evidence of organic and physical causes. Our research group identified recently that the gastrointestinal tract well in the patients with the functional gastrointestinal disorders becomes more rigid than healthy people when palpating the abdominal regions overlaying the gastrointestinal tract. Aim of this study is, therefore, to develop a diagnostic system for the functional gastrointestinal disorders based on ultrasound technique, which can quantify the characteristic above related to the rigidity of the gastrointestinal tract well. Ultrasound system was designed. The system consisted of transmitter, ultrasonic transducer, receiver, TGC, and CPLD, and verified via a phantom test. For the phantom test, ten soft-tissue specimens were harvested from porcine. Five of them were then treated chemically to mimic a rigid condition of gastrointestinal tract well, which was induced by functional gastrointestinal disorders. Additionally, the specimens were tested mechanically to identify if the mimic was reasonable. The customized ultrasound system was finally verified through application to human subjects with/without functional gastrointestinal disorders (Normal and Patient Groups). It was identified from the mechanical test that the chemically treated specimens were more rigid than normal specimen. This finding was favorably compared with the result obtained from the phantom test. The phantom test also showed that ultrasound system well described the specimen geometric characteristics and detected an alteration in the specimens. The maximum amplitude of the ultrasonic reflective signal in the rigid specimens (0.2±0.1Vp-p) at the interface between the fat and muscle layers was explicitly higher than that in the normal specimens (0.1±0.0Vp-p). Clinical tests using our customized ultrasound system for human subject showed that the maximum amplitudes of the ultrasonic reflective signals near to the gastrointestinal tract well for the patient group (2.6±0.3Vp-p) were generally higher than those in normal group (0.1±0.2Vp-p). Here, maximum reflective signals was appeared at 20mm depth approximately from abdominal skin for all human subjects, corresponding to the location of the boundary layer close to gastrointestinal tract well. These results suggest that newly designed diagnostic system based on ultrasound technique may diagnose enough the functional gastrointestinal disorders.