#Special Issue For Computer Networking#

#Special Issue For Computer Networking#

Dear Researchers/Authors,
IJSRD is promoting the field of this Digital Generation-“Computer Networking”. In accordance to it IJSRD is inviting research Papers from you on subject of Computer Networking. This is under special Issue Publication by IJSRD. In addition to this authors will have a chance to win the Best Paper Award under this category.The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.

Authors are solicited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the Computer Networks & Communications.

To submit your research paper on Computer Networking Click here

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What is Computer Network?
A computer network or data network is a telecommunications network which allows computers to exchangedata. In computer networks, networked computing devices exchange data with each other along network links(data connections). The connections between nodes are established using either cable media or wireless media. The best-known computer network is the Internet.

Topics of interest include but are not limited to, the following

  • Network Protocols & Wireless Networks
  • Network Architectures
  • High speed networks
  • Routing, switching and addressing techniques
  • Next Generation Internet
  • Next Generation Web Architectures
  • Network Operations & management
  • Adhoc and sensor networks
  • Internet and Web applications
  • Ubiquitous networks
  • Mobile networks & Wireless LAN
  • Wireless Multimedia systems
  • Wireless communications
  • Heterogeneous wireless networks
  • Measurement & Performance Analysis
  • Peer to peer and overlay networks
  • QoS and Resource Management
  • Network Based applications
  • Network Security
  • Self-Organizing Networks and Networked Systems
  • Optical Networking
  • Mobile & Broadband Wireless Internet
  • Recent trends & Developments in Computer Networks

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6) Read and revise your first draft.

7) Proofread carefully.

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Emergent Artificial Intelligence

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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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Fuel cell vehicles

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Zero-emission cars that run on hydrogen

Fuel cell” vehicles have been long promised, as they potentially offer several major advantages over electric and hydrocarbon-powered vehicles. However, the technology has only now begun to reach the stage where automotive companies are planning to launch them for consumers. Initial prices are likely to be in the range of $70,000, but should come down significantly as volumes increase within the next couple of years.

Unlike batteries, which must be charged from an external source, fuel cells generate electricity directly, using fuels such as hydrogen or natural gas. In practice, fuel cells and batteries are combined, with the fuel cell generating electricity and the batteries storing this energy until demanded by the motors that drive the vehicle. Fuel cell vehicles are therefore hybrids, and will likely also deploy regenerative braking – a key capability for maximizing efficiency and range.

Unlike battery-powered electric vehicles, fuel cell vehicles behave as any conventionally fuelled vehicle. With a long cruising range – up to 650 km per tank (the fuel is usually compressed hydrogen gas) – a hydrogen fuel refill only takes about three minutes. Hydrogen is clean-burning, producing only water vapour as waste, so fuel cell vehicles burning hydrogen will be zero-emission, an important factor given the need to reduce air pollution.

There are a number of ways to produce hydrogen without generating carbon emissions. Most obviously, renewable sources of electricity from wind and solar sources can be used to electrolyse water – though the overall energy efficiency of this process is likely to be quite low. Hydrogen can also be split from water in high-temperature nuclear reactors or generated from fossil fuels such as coal or natural gas, with the resulting CO2 captured and sequestered rather than released into the atmosphere.

As well as the production of cheap hydrogen on a large scale, a significant challenge is the lack of a hydrogen distribution infrastructure that would be needed to parallel and eventually replace petrol and diesel filling stations. Long distance transport of hydrogen, even in a compressed state, is not considered economically feasible today. However, innovative hydrogen storage techniques, such as organic liquid carriers that do not require high-pressure storage, will soon lower the cost of long-distance transport and ease the risks associated with gas storage and inadvertent release.

Mass-market fuel cell vehicles are an attractive prospect, because they will offer the range and fuelling convenience of today’s diesel and petrol-powered vehicles while providing the benefits of sustainability in personal transportation. Achieving these benefits will, however, require the reliable and economical production of hydrogen from entirely low-carbon sources, and its distribution to a growing fleet of vehicles (expected to number in the many millions within a decade).

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#IJSRD IMAGE PROCESSING CALL FOR PAPER : Special Issue

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

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image processing ijsrd call for paper

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 Processing system 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.

#IJSRD #New Milestone #Leading E-Journal #India

Thanks 2 all Authors For Making Fastest Growing E-Journal of INDIA.
IJSRD Successfully Completed 24 Issue.
Submission is open For Volume 3 – Issue 1 ,2015
Papers Received – More then 10000
Total Authors- More then 12000
Accepted Papers – More Then 3200