HOG, LBP and SVM based Traffic Density Estimation at Intersection

Increased amount of vehicular traffic on roads is a significant issue. High amount of vehicular traffic creates traffic congestion, unwanted delays, pollution, money loss, health issues, accidents, emergency vehicle passage and traffic violations that ends up in the decline in productivity. In peak hours, the issues become even worse. Traditional traffic management and control systems fail to tackle this problem. Currently, the traffic lights at intersections aren't adaptive and have fixed time delays. There's a necessity of an optimized and sensible control system which would enhance the efficiency of traffic flow. Smart traffic systems perform estimation of traffic density and create the traffic lights modification consistent with the quantity of traffic. We tend to propose an efficient way to estimate the traffic density on intersection using image processing and machine learning techniques in real time. The proposed methodology takes pictures of traffic at junction to estimate the traffic density. We use Histogram of Oriented Gradients (HOG), Local Binary Patterns (LBP) and Support Vector Machine (SVM) based approach for traffic density estimation. The strategy is computationally inexpensive and can run efficiently on raspberry pi board. Code is released at https://github.com/DevashishPrasad/Smart-Traffic-Junction.Comment: paper accepted at IEEE PuneCon 201

An Internally Consistent Approach for Modeling Solid-State Aggregation: II. Mean-Field Representation of Atomistic Processes

A detailed continuum (mean-field) model is presented that captures quantitatively the evolution of a vacancy cluster size distribution in crystalline silicon simulated directly by large-scale parallel molecular dynamics. The continuum model is parameterized entirely using the results of atomistic simulations based on the same empirical potential used to perform the atomistic aggregation simulation, leading to an internally consistent comparison across the two scales. It is found that an excellent representation of all measured components of the cluster size distribution can be obtained with consistent parameters only if the assumed physical mechanisms are captured correctly. In particular, the inclusion of vacancy cluster diffusion and a model to capture the dynamic nature of cluster morphology at high temperature are necessary to reproduce the results of the large-scale atomistic simulation. Dynamic clusters with large capture volumes at high temperature, which are the result of rapid cluster shape fluctuations, are shown to be larger than would be expected from static analyses, leading to substantial enhancement of the nucleation rate. Based on these results, it is shown that a parametrically consistent atomistic-continuum comparison can be used as a sensitive framework for formulating accurate continuum models of complex phenomena such as defect aggregation in solids

Internally Consistent Approach for Modeling Solid-State Aggregation: I. Atomistic Calculations of Vacancy Clustering in Silicon

A computational framework is presented for describing the nucleation and growth of vacancy clusters in crystalline silicon. The overall approach is based on a parametrically consistent comparison between two representations of the process in order to provide a systematic method for probing the details of atomic mechanisms responsible for aggregation. In this paper, the atomistic component of the overall framework is presented. First, a detailed set of targeted atomistic simulations are described that characterize fully the thermodynamic and transport properties of vacancy clusters over a wide range of sizes. It is shown that cluster diffusion is surprisingly favorable because of the availability of multiple, almost degenerate, configurations. A single large-scale parallel molecular dynamics simulation is then used to compute directly the evolution of the vacancy cluster size distribution in a supersaturated system initially containing 1000 uniformly distributed vacancies in a host lattice of 216,000 Si atoms at 1600 K. The results of this simulation are interpreted in the context of mean-field scaling theory based on the observed power-law evolution of the size distribution moments. It is shown that the molecular dynamics results for aggregation of vacancy clusters, particularly the evolution of the average cluster size, can be very well represented by a highly simplified mean-field model. A direct comparison to a detailed continuum model is made in a subsequent article

Feature Activated Molecular Dynamics: An Efficient Approach for Atomistic Simulation of Solid-State Aggregation Phenomena

A new approach is presented for performing efficient molecular dynamics simulations of solute aggregation in crystalline solids. The method dynamically divides the total simulation space into “active” regions centered about each minority species, in which regular molecular dynamics is performed. The number, size and shape of these regions is updated periodically based on the distribution of solute atoms within the overall simulation cell. The remainder of the system is essentially static except for periodic rescaling of the entire simulation cell in order to balance the pressure between the isolated molecular dynamics regions. The method is shown to be accurate and robust for the Environment-Dependant Interatomic Potential (EDIP) for silicon and an Embedded Atom Method (EAM) potential for copper. Several tests are performed beginning with the diffusion of a single vacancy all the way to large-scale simulations of vacancy clustering. In both material systems, the predicted evolutions agree closely with the results of standard molecular dynamics simulations. Computationally, the method is demonstrated to scale almost linearly with the concentration of solute atoms, but is essentially independent of the total system size. This scaling behavior allows for the full dynamical simulation of aggregation under conditions that are more experimentally realizable than would be possible with standard molecular dynamics

Impact of COVID-19 pandemic on women reproductive health and family planning services

Globally, women and adolescents health in the reproductive age group are heavily affected during the ongoing coronavirus disease - 2010 (COVID-19) pandemic. Contraception shortage across the world. Sustainable development goal, target 3.7 is “to ensure universal access to sexual and reproductive healthcare services, including for family planning, information and education and integration of reproductive health into national strategies and programmes.” The demand of health workers and supply chain are affected and impacted the availability and accessibility to the sexual and reproductive healt

Design and development of values education index and perceptual mapping in Indian perspective

The present research works explore the constructs contributing to the values of education in the Indian educational framework and make an effort to understand its perception among the stakeholders. We have made a scientific effort to explore various dimensions of value education constructs from available literature and shaped those constructs on the perceptual mapping framework that have created its positions on the graphic dimension of the frame. It explains how the value education contributes to shaping the mindset and personality amongst the students. We have developed a value education index on the identified constructs that shows the relative weights on each identified construct. The constructs identified as family cohesion, parent conflicts, parents expatiation, teachers' role, school administration, mass media and internet, social orientation, community structure, religious education, and public institution. Key words: Value education, perceptual map, value education index, higher education DOI: 10.7176/JEP/11-33-20 Publication date: November 30th 202

Driving--induced bistability in coupled chaotic attractors

We examine the effects of symmetry--preserving and breaking interactions in a drive--response system where the response has an invariant symmetry in the absence of the drive. Subsequent to the onset of generalized synchronization, we find that there can be more than one stable attractor. Numerical, as well as analytical results establish the presence of phase synchrony in such coexisting attractors. These results are robust to external noise.Comment: To be published in Phys. Rev. E. 201

Carbon-Mediated Aggregation of Self-Interstitials in Silicon

The carbon-mediated aggregation of silicon self-interstitials is investigated with a novel approach based on large-scale parallel molecular dynamics. The presence of carbon in the silicon matrix is shown to lead to concentration-dependent self-interstitial cluster pinning, dramatically reducing cluster coalescence and thereby inhibiting the nucleation process. The extent of cluster pinning increases with cluster size for the range of cluster sizes observed in the simulation. The effect of carbon on single self-interstitials is shown to be of secondary importance, and the concentration of single self-interstitials as a function of time is essentially unchanged in the presence of carbon. A quasi-single component mean-field interpretation of the atomistic simulation results further confirms these conclusions and suggests that the experimentally observed effect of carbon on transient-enhanced diffusion (TED) could be due to carbon-cluster interactions