Preparation of Gold Target through Electron Vapor Deposition and 'Paras' the Rutherford Back Scattering Experimental setup @ IUAC

International Journal For Scientific Research & Development :: IJSRD

Author(s):

Sarvesh Kumar , Inter University Accelerator Center, Aruna Asaf Ali Marg, New Delhi.; Tulika Sharmay, Amity Institute of Applied Sciences, Amity University, Noida, (U. P.); Pranav Bhardwaj, Department of Physics and Astrophysics, University of Delhi, New Delhi; Avnee Chauhan, Amity Institute of Applied Sciences, Amity University, Noida, (U. P.); Shruti Kapoor, Amity Institute of Applied Sciences, Amity University, Noida, (U. P.)

Keywords:

Rutherford Back Scattering, Electron Vapor Deposition

Abstract:

Rutherford Backscattering Spectrometry (RBS) is a widely used method for the surface layer analysis of solids. Lord Ernest Rutherford first used the backscattering of alpha particles from a gold film in 1911 to determine the fine structure of the atom, resulting in the discovery of the atomic nucleus. RBS includes all types of elastic ion scattering with incident ion energies in the range 500 keV ¬ several MeV. Usually protons, 4He, and sometimes lithium ions are used as projectiles at backscattering angles of typically 150¬ 170¦. Different angles or different projectiles are used in special cases. Rutherford backscattering spectroscopy is employed to detect the impurity present in target material and to test the amount and type of impurity present in any target sample to be used in any experiment of atomic physics/ nuclear physics or of material science. The detection of these impurities before conduction of any experiment is essential as the presence of impurity in target sample may hamper the results of the experiments. Thus, although being a traditional concept the use of Rutherford backscattering spectroscopy still prevails. One requires a target material to learn the working principle of Rutherford backscattering spectroscopy. INTER UNIVERSITY ACCELERATOR CENTER (IUAC) provides the facility for fabrication of the target and its analysis. This paper includes the fabrication of gold target of thickness 300mm and its analysis using Rutherford backscattering spectroscopy.

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Emergent Artificial Intelligence

What happens when a computer can learn on the job?

Artificial intelligence (AI) is, in simple terms, the science of doing by computer the things that people can do. Over recent years, AI has advanced significantly: most of us now use smartphones that can recognize human speech, or have travelled through an airport immigration queue using image-recognition technology. Self-driving cars and automated flying drones are now in the testing stage before anticipated widespread use, while for certain learning and memory tasks, machines now outperform humans. Watson, an artificially intelligent computer system, beat the best human candidates at the quiz game Jeopardy.

Artificial intelligence, in contrast to normal hardware and software, enables a machine to perceive and respond to its changing environment. Emergent AI takes this a step further, with progress arising from machines that learn automatically by assimilating large volumes of information. An example is NELL, the Never-Ending Language Learning project from Carnegie Mellon University, a computer system that not only reads facts by crawling through hundreds of millions of web pages, but attempts to improve its reading and understanding competence in the process in order to perform better in the future.

Like next-generation robotics, improved AI will lead to significant productivity advances as machines take over – and even perform better – at certain tasks than humans. There is substantial evidence that self-driving cars will reduce collisions, and resulting deaths and injuries, from road transport, as machines avoid human errors, lapses in concentration and defects in sight, among other problems. Intelligent machines, having faster access to a much larger store of information, and able to respond without human emotional biases, might also perform better than medical professionals in diagnosing diseases. The Watson system is now being deployed in oncology to assist in diagnosis and personalized, evidence-based treatment options for cancer patients.

Long the stuff of dystopian sci-fi nightmares, AI clearly comes with risks – the most obvious being that super-intelligent machines might one day overcome and enslave humans. This risk, while still decades away, is taken increasingly seriously by experts, many of whom signed an open letter coordinated by the Future of Life Institute in January 2015 to direct the future of AI away from potential pitfalls. More prosaically, economic changes prompted by intelligent computers replacing human workers may exacerbate social inequalities and threaten existing jobs. For example, automated drones may replace most human delivery drivers, and self-driven short-hire vehicles could make taxis increasingly redundant.

On the other hand, emergent AI may make attributes that are still exclusively human – creativity, emotions, interpersonal relationships – more clearly valued. As machines grow in human intelligence, this technology will increasingly challenge our view of what it means to be human, as well as the risks and benefits posed by the rapidly closing gap between man and machine.

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Special Issue For Image Processing

Best 25 papers will be published online.Participate in this special issue and get a chance to win the Best Paper Award for Image Processing. Also other authors will have special prizes to be won.

• Submit Special Issue Manuscript Online

• Last Date For Paper Submission of Special Issue : 25th August 2015

What is Image Processing?

Image processing is a method to convert an image into digital form and perform some operations on it, in order to get an enhanced image or to extract some useful information from it. It is a type of signal dispensation in which input is image, like video frame or photograph and output may be image or characteristics associated with that image. Usually Image Processingsystem includes treating images as two dimensional signals while applying already set signal processing methods to them. 
It is among rapidly growing technologies today, with its applications in various aspects of a business. Image Processing forms core research area within engineering and computer science disciplines too.Image processing usually refers to digital image processing, but optical and analog image processing also are possible.
Analog or visual techniques of image processing can be used for the hard copies like printouts and photographs. Image analysts use various fundamentals of interpretation while using these visual techniques. The image processing is not just confined to area that has to be studied but on knowledge of analyst. Association is another important tool in image processing through visual techniques. So analysts apply a combination of personal knowledge and collateral data to image processing.
Digital Processing techniques help in manipulation of the digital images by using computers. As raw data from imaging sensors from satellite platform contains deficiencies. To get over such flaws and to get originality of information, it has to undergo various phases of processing. The three general phases that all types of data have to undergo while using digital technique are Pre- processing, enhancement and display, information extraction.
If you have worked on any part of image processing prepare a research paper and submit to us

Image processing basically includes the following three steps.

• Importing the image with optical scanner or by digital photography.The acquisition of images (producing the input image in the first place) is referred to as imaging.
• Analyzing and manipulating the image which includes data compression and image enhancement and spotting patterns that are not to human eyes like satellite photographs.
• Output is the last stage in which result can be altered image or report that is based on image analysis.

Purpose of Image processing

The purpose of image processing is divided into various groups. They are:

• Visualization - Observe the objects that are not visible.
• Image sharpening and restoration - To create a better image.
• Image retrieval - Seek for the image of interest.
• Measurement of pattern – Measures various objects in an image.
• Image Recognition – Distinguish the objects in an image.

Applications of Image processing

Image processing has been an important stream of Research for various fields. Some of the application areas of Image processing are….

Intelligent Transportation Systems – E.g. Automatic Number Plate Recognition, Traffic Sign Recognition

Remote Sensing –E.g.Imaging of earth surfaces using multi Spectral Scanners/Cameras, Techniques to interpret captured images etc.

Object Tracking – E.g. Automated Guided Vehicles, Motion based Tracking, Object Recognition
 Defense surveillance – E.g. Analysis of Spatial Images, Object Distribution Pattern Analysis of Various wings of defense. Earth Imaging using UAV etc.

 Biomedical Imaging & Analysis – E.g. Various Imaging using X- ray, Ultrasound, computer aided tomography (CT) etc. Disease Prediction using acquired images, Digital mammograms.etc.

Automatic Visual Inspection System – E.g.Automatic inspection of incandescent lamp filaments, Automatic surface inspection systems,    Faulty component identification etc.

And many other applications…..

To contribute your research work in Image processing please prepare an article on it and submit to us. 

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