Location prediction algorithm for a nonlinear vehicular movement in VANET using extended Kalman filter

Vehicular ad-hoc network (VANET) is an essential component of the intelligent transportation system, that facilitates the road transportation by giving a prior alert on traffic condition, collision detection warning, automatic parking and cruise control using vehicle to vehicle (V2V) and vehicle to roadside unit (V2R) communication. The accuracy of location prediction of the vehicle is a prime concern in VANET which enhances the application performance such as automatic parking, cooperative driving, routing etc. to give some examples. Generally, in a developed country, vehicle speed varies between 0 and 60 km/h in a city due to traffic rules, driving skills and traffic density. Likewise, the movement of the vehicle with steady speed is highly impractical. Subsequently, the relationship between time and speed to reach the destination is nonlinear. With reference to the previous work on location prediction in VANET, nonlinear movement of the vehicle was not considered. Thus, a location prediction algorithm should be designed by considering nonlinear movement. This paper proposes a location prediction algorithm for a nonlinear vehicular movement using extended Kalman filter (EKF). EKF is more appropriate contrasted with the Kalman filter (KF), as it is designed to work with the nonlinear system. The proposed prediction algorithm performance is measured with the real and model based mobility traces for the city and highway scenarios. Also, EKF based prediction performance is compared with KF based prediction on average Euclidean distance error (AEDE), distance error (DE), root mean square error (RMSE) and velocity error (VE).     

Validation of biokinetic models of Cs and I using their daily dietary intakes and organ contents in an adult Indian population

The daily dietary intakes and total contents of Cs and I in skeletal muscle and thyroid, respectively, for an average Indian adult were estimated by determining their concentrations in the total cooked diet and tissue samples using instrumental neutron activation analysis. These data were then used to predict the biological half-lives of Cs and I and their radioactive counterparts for the Reference Indian Man. The predicted biological half-lives of Cs and I for Reference Indian Man were found to be comparable with the reported values for the ICRP Reference Man.     

Hardystonite improves biocompatibility and strength of electrospun polycaprolactone nanofibers over hydroxyapatite: A comparative study

The aim of this study was to compare physico-chemical and biological properties of hydroxyapatite (HA) and hardystonite (HS) based composite scaffolds. Hardystonite (Ca₂ZnSi₂O₇) powders were synthesized by a sol–gel method while polycaprolactone–hardystonite (PCL–HS) and polycaprolactone–hydroxyapatite (PCL–HA) were fabricated in nanofibrous form by electrospinning. The physico-chemical and biological properties such as tensile strength, cell proliferation, cell infiltration and alkaline phosphatase activity were determined on both kinds of scaffolds. We found that PCL–HS scaffolds had better mechanical strength compared to PCL–HA scaffolds. Addition of HA and HS particles to PCL did not show any inhibitory effect on blood biocompatibility of scaffolds when assessed by hemolysis assay. The in vitro cellular behavior was evaluated by growing murine adipose-tissue-derived stem cells (mE-ASCs) over the scaffolds. Enhanced cell proliferation and improved cellular infiltrations on PCL–HS scaffolds were observed when compared to HA containing scaffolds. PCL–HS scaffolds exhibited a significant increase in alkaline phosphatase (ALP) activity and better mineralization of the matrix in comparison to PCL–HA scaffolds. These results clearly demonstrate the stimulatory role of Zn and Si present in HS based composite scaffolds, suggesting their potential application for bone tissue engineering.     

Forensic image analysis using inconsistent noise pattern

With the advancement of image acquisition devices and social networking services, a huge volume of image data is generated. Using different image and video processing applications, these image data are manipulated, and thus, original images get tampered. These tampered images are the prime source of spreading fake news, defaming the personalities and in some cases (when used as evidence) misleading the law bodies. Hence before relying totally on the image data, the authenticity of the image must be verified. Works of the literature are reported for the verification of the authenticity of an image based on noise inconsistency. However, these works suffer from limitations of confusion between edges and noise, post-processing operation for localization and need of prior knowledge about an image. To handle these limitations, a noise inconsistency-based technique has been presented here to detect and localize a false region in an image. This work consists of three major steps of pre-processing, noise estimation and post-processing. For the experimental purpose two, publicly available datasets are used. The result is discussed in terms of precision, recall, accuracy and f1-score on the pixel level. The result of the presented work is also compared with the recent state-of-the-art techniques. The average accuracy of the proposed work on datasets is 91.70%, which is highest among state-of-the-art techniques.

     

Flow of power law liquids through particle assemblages at intermediate reynolds numbers

The complete equations of motion and continuity have been solved numerically using the finite element method for the flow of power law liquids through assemblages of rigid spherical particles. The inter-particle interactions have been simulated using the free surface cell model. Extensive results on drag coefficients have been obtained under a wide range of physical and operating conditions (0.9999 ≥ 0.3), 1 ≥ n ≥ 0.4 and 20 ≥ Re ≥ 1. The observed dependence of drag coefficient on voidage and non-Newtonian flow behaviour index have been explained qualitatively with the aid of order of magnitude considerations. Finally, the theoretical predictions have been validated using suitable experimental data available in the literature.