Neural Network Based Approach for the Generation of Road Feel in a Steer-By-Wire System

Steer-by-wire is an advanced steering system which connects the steering wheel with the front wheel by using motors and sensors. Generating the road feel in steer by wire system is an important criterion since there is no mechanical connection between the steering wheel and the front wheel. In present work, Neural Network method is proposed for generating artificial road feel to the driver using the vehicle dynamic parameters such as vertical displacement, self-aligning moment and front wheel angle as inputs. Proposed neural network model was trained using the vehicle dynamic models for estimating the current to be supplied to the feedback motor according to the changing road conditions. Three different road profiles are selected such as dry, wet and icy for the simulation purpose and the estimated motor current values for the road surfaces using neural network are presented. From the simulation results for the sinusoidal road surface and sinusoidal steering angle driver input, it is clear that the neural network based method is able to produce the varying road feel to the driver for the different road conditions

An Integrated Pedal Follower and Torque Based Approach for Electronic Throttle Control in a Motorcycle Engine

Nowadays, electronic throttle control system is widely adapted in the motorcycle for better drivability, fuel economy and reduces the emissions. In such systems, pedal follower or torque based approach are used for calculating the required throttle angle for the given torque demand by driver. This work presents a throttle control system for the precise estimation of throttle angle based on the integrated pedal follower and torque based approach for the given accelerator position and torque demand by the driver. A mathematical model for an electronic throttle body is developed to understand the effects of nonlinearities due to friction and limp home dual springs. A PID controller with compensators are developed to handle the nonlinearities due to the friction and limp home dual springs in the proposed electronic throttle control system. A simulation study has been carried out using software in loop and hardware in loop simulation approaches for step, sinusoidal, and ramp input signals. The responses of electronic throttle body for opening the throttle angle and error are analyzed for the given input signals. The simulation result shows that the proposed compensators has significant advantage in reducing the throttle angle error and gives the desired output

A Multi-Level Colour Thresholding Based Segmentation Approach for Improved Identification of the Defective Region in Leather Surfaces

Vision systems are recently adopted for defect detection in leather surface to overcome difficulties of labour intensive, time consuming manual inspection process. Suitable image processing techniques needs to be developed for accurate detection of leather defects. Existing research works have focused for gray scale based image processing techniques which requires conversion of colour images using an averaging method and it lacks sensitivity for detecting the leather defects due to the random and texture surface of the leather.  This work presents a colour processing approach for improved identification of leather defects using a multi-level thresholding function. In this work, the colour leather images are processed in ‘Lab’ colour domain for improving the human perception of discriminating the leather defects.  In the present work, the specific range of values for the colour attributes of different leather defect in colour leather samples are identified using the colour histogram.  MATLAB software routine is developed for identifying defects in specific ranges of colour attributes and the results are presented.  From the results, it is found that proposed provides a simpler approach for identifying the defective regions based on the colour attributes of the surface with improved human perception. The proposed methodology can be implemented in graphical processing units for efficiently detecting several types of defects using specific thresholds for the automated real-time inspection of leather defects

Fuzzy Logic based Modelling and Simulation Approach for the estimation of Tire Forces

AbstractTire modeling is an important aspect of vehicle dynamics as the forces and moments required to control the vehicle's motion are eventually transmitted through the tire and the tire road interface is also an important source for the dynamic excitation of the vehicle. This paper presents a fuzzy logic based approach for estimating tire forces, aligning moment of tire for the different slip ratio and slip angles. Proposed fuzzy logic approach requires slip angle and slip ratio, as the input variables, and estimates the longitudinal force, lateral force, aligning moment as the output variables. Membership functions of input, output variables and fuzzy rules are formulated based on the values obtained using the widely adopted Magic formula for tire model. Simulation values for longitudinal, lateral forces and aligning moment of the tire using the proposed fuzzy model is found to provide good correlation with the magic model. Proposed fuzzy logic frame work does not require the estimation of model parameters used in the Magic formula and it will be useful in developing vehicle control system

A Fuzzy Logic based Model to Predict the Improvement in Surface Roughness in Magnetic Field Assisted Abrasive Finishing

AbstractIn this paper the effect of process parameters during Magnetic Field Assisted Abrasive Micro Finishing (MFAAF) of SS316L material is reported. Based on the experimental results obtained, S/N ratio and ANOVA analyses were made to identify the significant process parameters to improve the percentage improvement of surface roughness (%ΔRa). From the results it is observed that the process parameters like voltage applied to the electromagnet, machining gap, rotational speed of electromagnet followed by abrasive size are significant to improve the %ΔRa. Based on the process parameters selected from the S/N ratio analysis and ANOVA analysis, a fuzzy logic model has been developed to predict the %ΔRa. To develop the fuzzy model, four membership functions based on the four process parameters are assigned to be connected with each input of the model. The developed fuzzy model is tested using three different set of process parameters values that are not used in already existing experimental data set. It is found that the developed fuzzy model has a close relation with the experimental values with the maximum deviations of 7.16%

Deep Learning Based Thermal Image Processing Approach for Detection of Buried Objects and Mines

Thermal imaging based mine detection technique is widely adopted due it suitability of detecting buried metallic and also non-metallic land mines in battle fields. Accurate mine detection using thermal images depends on thermal contrast between the soil and mine and it is affected by various factors such as the depth of burial; soil properties and attributes, water content in the soil, mine properties; as well as the time of day of image acquisition. With temporal temperature variations of the soil, it is difficult to distinguish and discriminate between the buried object and the background in the thermal image using the conventionally followed binary thresholding approach in gray scale. This paper presents deep learning region convolution based neural network approach to identify the buried objects in thermal images. A region interest selection using a bound box is followed for identifying the buried object in the thermal image.  From the experimental results, it is found that there is temperature variation in the thermal images of the buried objects due to the change in heat carrying capacity of the surround soil. Proposed neural network method showed 90% accuracy in predicting the target locations of buried objects in the thermal images and it can be extended for land mine detection using thermal image processing approach

Pulmonary veins to left atrium cycle length gradient predicts procedural and clinical outcomes of persistent atrial fibrillation ablation.

BACKGROUND Rapid pulmonary vein (PV) activity has been shown to maintain paroxysmal atrial fibrillation (AF). We evaluated in persistent AF the cycle length (CL) gradient between PVs and the left atrium (LA) in an attempt to identify the subset of patients where PVs play an important role. METHODS AND RESULTS Ninety-seven consecutive patients undergoing first ablation for persistent AF were studied. For each PV, the CL of the fastest activation was assessed over 1 minute (PVfast) using Lasso recordings. The PV to LA CL gradient was quantified by the ratio of PVfast to LA appendage (LAA) AF CL. Stepwise ablation terminated AF in 73 patients (75%). In the AF termination group, the PVfast CL was much shorter than the LAA CL resulting in lower PVfast/LAA ratios compared with the nontermination group (71±10% versus 92±7%; P<0.001). Within the termination group, PVfast/LAA ratios were notably lower if AF terminated after PV isolation or limited adjunctive substrate ablation compared with patients who required moderate or extensive ablation (63±6% versus 75±8%; P<0.001). PVfast/LAA ratio <69% predicted AF termination after PV isolation or limited substrate ablation with 74% positive predictive value and 95% negative predictive value. After a mean follow-up of 29±17 months, freedom from arrhythmia recurrence off-antiarrhythmic drugs was achieved in most patients with PVfast/LAA ratios <69% as opposed to the remaining population (80% versus 43%; P<0.001). CONCLUSIONS The PV to LA CL gradient may identify the subset of patients in whom persistent AF is likely to terminate after PV isolation or limited substrate ablation and better long-term outcomes are achieved

SAR Studies Leading to the Identification of a Novel Series of Metallo-β-lactamase Inhibitors for the Treatment of Carbapenem-Resistant Enterobacteriaceae Infections That Display Efficacy in an Animal Infection Model

The clinical effectiveness of carbapenem antibiotics such as meropenem is becoming increasingly compromised by the spread of both metallo-β-lactamase (MBL) and serine-β-lactamase (SBL) enzymes on mobile genetic elements, stimulating research to find new β-lactamase inhibitors to be used in conjunction with carbapenems and other β-lactam antibiotics. Herein, we describe our initial exploration of a novel chemical series of metallo-β-lactamase inhibitors, from concept to efficacy, in a survival model using an advanced tool compound (ANT431) in conjunction with meropenem

Measurements of branching fraction ratios and CP-asymmetries in suppressed B^- -> D(-> K^+ pi^-)K^- and B^- -> D(-> K^+ pi^-)pi^- decays

We report the first reconstruction in hadron collisions of the suppressed decays B^- -> D(-> K^+ pi^-)K^- and B^- -> D(-> K^+ pi^-)pi^-, sensitive to the CKM phase gamma, using data from 7 fb^-1 of integrated luminosity collected by the CDF II detector at the Tevatron collider. We reconstruct a signal for the B^- -> D(-> K^+ pi^-)K^- suppressed mode with a significance of 3.2 standard deviations, and measure the ratios of the suppressed to favored branching fractions R(K) = [22.0 \pm 8.6(stat)\pm 2.6(syst)]\times 10^-3, R^+(K) = [42.6\pm 13.7(stat)\pm 2.8(syst)]\times 10^-3, R^-(K)= [3.8\pm 10.3(stat)\pm 2.7(syst]\times 10^-3, as well as the direct CP-violating asymmetry A(K) = -0.82\pm 0.44(stat)\pm 0.09(syst) of this mode. Corresponding quantities for B^- -> D(-> K^+ pi^-)pi^- decay are also reported.Comment: 8 pages, 1 figure, accepted by Phys.Rev.D Rapid Communications for Publicatio