Mechanism of Inbuilt Automatic Hydraulic Jack used for Light and Heavy Vehicles

This paper is about the new automatic technique of inbuilt hydraulic jack system. Whenever the tire failure is occurred in the vehicle then to lifting the vehicle from ground surface is the very difficult think for human being and also, huge human effort required and more time taking process. There, this inbuilt hydraulic jack system helps to lift the vehicle from the ground instead of conventional mechanical jack, and saves the time and excess effort. Separate buttons are provided in order to raise or lower the right and left side jacks. By pushing the given button in the dashboard, the inbuilt self-jacking component gets initiated. Main parts of this project are hydraulic jack, master cylinder, valves, manifold, and oil reservoir. The inbuilt hydraulic jack will be valuable to the senior residents and for women who discover it incredibly hard to work the jack physically in any breakdown of the vehicle. This hydraulic jack will have the option to lift the wheels as indicated by our prerequisite that is on the off chance that we need to lift just two wheels, at that point it tends to be finished by moving the cylinder as needs be on the rack with the assistance of the DC motor. Index Terms: Hydraulic Jack, Master Cylinder, Incompressible Hydraulic Oil, Pascal’s Law

Probabilistic modelling and verification using RoboChart and PRISM

RoboChart is a timed domain-specific language for robotics, distinctive in its support for automated verification by model checking and theorem proving. Since uncertainty is an essential part of robotic systems, we present here an extension to RoboChart to model uncertainty using probabilism. The extension enriches RoboChart state machines with probability through a new construct: probabilistic junctions as the source of transitions with a probability value. RoboChart has an accompanying tool, called RoboTool, for modelling and verification of functional and real-time behaviour. We present here also an automatic technique, implemented in RoboTool, to transform a RoboChart model into a PRISM model for verification. We have extended the property language of RoboTool so that probabilistic properties expressed in temporal logic can be written using controlled natural language.

Identificação e Classificação do relevo do município de São Martinho da Serra – RS

The relief is one of the main definers of the environmental units, so that its compartmentalization is closely related to the distribution of the other attributes of landscape genesis. The objective of this study is to establish a division of the relief of the municipality of São Martinho da Serra, Rio Grande do Sul. Cartographic bases in digital format associated with the Geographic Information System were used, through automated methods and with the integration of morphometric variables. For the definition of the relief forms, the combined analysis of the morphometric attributes amplitude and slope was considered, identifying flat areas, gentle hills of altitude, rolling hills, association of hills with large hills and buttes and isolated buttes. The relief elements were obtained through the automatic technique that consists of the analysis of the gray level of a central cell and its neighbors, determining topographic differences. The identified elements are flat, peak, ridge, shoulder, spur, slope, hollow, footslope, valley and pit. For the classification of the forms of the slopes, the profile and plane of curvature of the slopes were used, defining 4 geomorphometric units defined as Unit I convex-convergent, Unit II concave-convergent, Unit III convex-divergent and Unit IV concave-divergent. In general, the methodology used obtained satisfactory results, allowing a quick and consistent analysis of the relief of the municipality.

Role of Hybrid Level Set in Fetal Contour Extraction

Image processing technologies may be employed for quicker and accurate diagnosis in analysis and feature extraction of medical images. Here, existing level set algorithm is modified and it is employed for extracting contour of fetus in an image. In traditional approach, fetal parameters are extracted manually from ultrasound images. An automatic technique is highly desirable to obtain fetal biometric measurements due to some problems in traditional approach such as lack of consistency and accuracy. The proposed approach utilizes global & local region information for fetal contour extraction from ultrasonic images. The main goal of this research is to develop a new methodology to aid the analysis and feature extraction.

Universal Invariant Checking of Parametric Systems with Quantifier-free SMT Reasoning

The problem of invariant checking in parametric systems – which are required to operate correctly regardless of the number and connections of their components – is gaining increasing importance in various sectors, such as communication protocols and control software. Such systems are typically modeled using quantified formulae, describing the behaviour of an unbounded number of (identical) components, and their automatic verification often relies on the use of decidable fragments of first-order logic in order to effectively deal with the challenges of quantified reasoning.In this paper, we propose a fully automatic technique for invariant checking of parametric systems which does not rely on quantified reasoning. Parametric systems are modeled with array-based transition systems, and our method iteratively constructs a quantifier-free abstraction by analyzing, with SMT-based invariant checking algorithms for non-parametric systems, increasingly-larger finite instances of the parametric system. Depending on the verification result in the concrete instance, the abstraction is automatically refined by leveraging canditate lemmas from inductive invariants, or by discarding previously computed lemmas.We implemented the method using a quantifier-free SMT-based IC3 as underlying verification engine. Our experimental evaluation demonstrates that the approach is competitive with the state of the art, solving several benchmarks that are out of reach for other tools.

Biometric Foetal Contour Extraction using Hybrid Level Set

In medical imaging, accurate anatomical structure extraction is important for diagnosis and therapeutic interventional planning. So, for easier, quicker and accurate diagnosis of medical images, image processing technologies may be employed in analysis and feature extraction of medical images. In this paper, some modifications to level set algorithm are made and modified algorithm is used for extracting contour of foetal objects in an image. The proposed approach is applied on foetal ultrasound images. In traditional approach, foetal parameters are extracted manually from ultrasound images. Due to lack of consistency and accuracy of manual measurements, an automatic technique is highly desirable to obtain foetal biometric measurements. This proposed approach is based on global & local region information for foetal contour extraction from ultrasonic images. The primary goal of this research is to provide a new methodology to aid the analysis and feature extraction from foetal images.

Smart Leaf Recognition System

One of major issue nowadays is the agricultural productivity which is something our Nation’s economy highly depends. Technology based advancements may lead to detection of diseases in plants which are quite natural. Care should be taken in this area before it causes serious effects on plants which mainly affect the product quality, quantity or productivity. Early stage detection of diseases in plants through some automatic technique is beneficial as it reduces a huge work of monitoring in large acres of crops. When they appear on plant leaves, earlier detection helps us to increase the yield and productivity. This paper presents an algorithm for image processing technique which is used for automatic detection and classification of plant leaf diseases with the help of raspberry pi and sensors. This survey is about different diseases and its classification, techniques which are used for plant leaf disease detection and also its respective fertilizer sprayed on the leaves.

Disease Identification in Maize Plant Leaf

Agricultural productivity is that issue there on Indian Economy extremely depends. this is often the one altogether the reasons that malady detection in plants plays a really important role within the agriculture field, as having the malady in plants are quite natural. If correct care isn't taken during this space then it causes serious effects on plants and since of that various product quality, amount or productivity is affected. Detection of disease through some automatic technique is useful because it reduces an oversized work of watching in huge farms of crops, and at terribly early stage itself detects the symptoms of diseases means after they appear on plant leaves. This paper presents a neural network algorithm for image segmentation technique used for automatic detection still because the classification of plants and survey on completely different diseases classification techniques which will be used for plant disease detection. Image segmentation, that is a really important facet for malady detection in disease is completed by victimization genetic algorithm.

Plant Disease Detection using Image Processing Techniques

The Indian economy is highly dependent on Agriculture productivity. Having diseases in plants are natural, so disease detection in plant plays an important role in agriculture field. If proper care is not taken, then it causes very serious effects on plants, so that respective product quality and product quantity is affected. Plant disease detection using automatic technique is very useful because it reduces a large work of monitoring in big farms. At very early stage itself it detects the symptoms of diseases when they appear on plant leaves. This project focuses on an approach based on image processing techniques to detect the disease of plants.