Perspectives on Intelligent system techniques used in Data Mining

IJSRD - International Journal for Scientific Research & Development | Data Mining 2015 | ISSN (online): 2321-0613

Author(s):
Poonam Verma

Keywords:
Intelligent Systems, Neural Networks, Data Mining

Abstract:

With the uprising trend of the social media, for marketing purposes and for personal communication, the data mining techniques used in the early decade can no longer handle the data for pattern recognition .It becomes necessity that the data mining techniques become intelligent enough to deal with the volume and variety of the data being searched for recognizing patterns or trends. Thus in this article, I have explored the various neural networks and their techniques being implemented on data to find a particular trend. Various applications of such hybrid intelligent systems have been discussed. Perceptron and it's varieties have been long used for machine learning without the human intervention. Moreover their various features are inspired by the biological strategies endowed by nature on humans to recognize, learn and innovative ideas to solve their problems. Humans have various sensory organs to help them receive their inputs from the surroundings, however it is their brain that helps them to process the large data and get the required data as an output. Neural Networks are based on the Human brain and the nervous system. So we shall explore various intelligent systems of Neural Networks to help in data mining.

I. INTRODUCTION

The field of the Intelligent Systems has phenomenally increased in the range of techniques and the applications. Intelligent Systems includes a range of techniques that are capable of the data processing capabilities in the real life situations. These intelligent systems techniques are inspired by the biologically strategies that are used in this universe to handle the real life situations. Major categories of the intelligent systems are the Neural Networks, Fuzzy Logics, Genetic algorithms. In most of the data rich environment, these techniques help in optimizing search criteria of different factors. Such techniques are useful in today's scenario as the data has grown exponentially. To recognize pattern from this data using the earlier techniques might not result into optimal results. 

II. INTRODUCTION TO NEURAL NETWORKS

An artificial Neural Network is an information processing model that is basically inspired by the nervous systems of the most important organ of human body that is brain. It consists of a large number of highly interconnected processing system that work together to solve pattern recognition or data classification problems. Human Brain consists of neurons that collect signals from dendrites and sends it to the required neuron with the help of axon, only when the neuron is excited enough to surpass the restraint activity on it. view more 

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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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All Color Detector Sensor AR001

IJSRD : International Journal for Scientific Research & Development
Author(s):
Aditya Kumar , DIT University Dehradun; Vivek Kumar, DIT University Dehradun; Sandeep Sharma, DIT University Dehradun; Vimal Kant Pandey, DIT University Dehradun
Keywords:
Color Detector Sensor, Color sensing, AR001
Abstract
The objective of the present paper is to explore an approach of constructing a simple, low cost colour sensor using filter model which defines all colours as an additive combination of the primary colours Red, Green and Blue. The sensor consists of low pass filter surrounded by all color and light source. The low pass filter and the amplifier are mounted in such a way so that the color intensity from the source get absorbed by low pass filter and its passes through amplifier circuits. Therefore the voltage drop across the amplifier is varied whenever the light of different intensities from the low pass filter falls upon it. According to the voltage drop we decide the color identity because we know that every color has own intensity that why its produce specific voltage drop. The experimental results show that the variation of the color intensity gives the color identity.
Preview: 1.INTRODUCTION:
Color sensing is one of the important subjects of optical sensors. Color sensors have a variety of applications including detection of environmental, biological, and chemical parameters and in future its also use in robot as a eye. Color detectionbased chemical sensing is mostly implemented with particular emphasis on colorimetric sensors because many parameters, like pH, concentration, and chemical gases can cause direct or indirect color changes in biological and chemical species. Optical sensors usually have a non-linear relationship between the sensor’s response and the effect to be sensed or the measured. Due to the fact that optical sensors have highly sensitive and non-linear nature, an unexpected change in the measured may cause considerably changes and measurement errors in the sensor’s responses. Furthermore, it is expected that in modern sensor technology, a sensor has to adapt itself to the changing or unexpected conditions. In order to meet the expectations and to predict the sensor’s response more accurately, filter techniques become a useful tool for the design of intelligent color sensors.
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IJSRD: Conference : “NATIONAL CONFERENCE ON ICT”

“NATIONAL CONFERENCE ON ICT”

Transforming ICT to IoT

In association with

IJSRD– International Journal for Scientific Research & Development

SAL Institute of Technology & Engineering Research, affiliated to the Gujarat Technological University, Ahmedabad., is organizing 1-day event named “National Conference on ICT”  on 20th January 2016 in association with IJSRD.
The conference aims to provide an opportunity to teachers/mentors/ educators and students to acknowledge, celebrate and showcase research being carried out by students by enabling them to engage with the wider communities to exchange ideas and share intellectual activity through paper presentations sessions. The event shall feature research papers presentations by eminent educators and students from all over India in the field of ICT (Information and Communication Technologies) & IoT (Internet of Things).

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SAL Institute of Technology & Engineering Research Opp, Science city, Sola Bhadaj Road, Ahmedabad, Gujarat 380060 Website : www.sal.edu.in

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NCIL – 2015 :Student-driven Research for Inspired Learning" in Science and Technology: #IJSRD

NCIL – 2015 #IJSRD Publication Partner

National Conference on "Student-driven Research for Inspired Learning" in Science and Technology

Organised by ESRC and Dept of Electronics

Publication Partner International Journal for scientific research & Development (IJSRD)

Date: 16-17 October 2015

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NCIL - 2015

Objective

We are pleased to announce the 2nd National Conference on “Student-driven Research for Inspired Learning” (NCIL 2015) in Science and Technology on 16 - 17 October 2015 being organized by Embedded Systems and Robotics Centre (ESRC) and Department of Electronics, Maharaja Agrasen College, University of Delhi.

The primary objective of this conference is to provide a forum to share the wide and varied practices and initiatives of the student driven and institutionally-supported research at the undergraduate/ postgraduate level which leads to the combination of factors necessary for pedagogical effectiveness, enhanced learning outcomes, research productivity, promote networking and stimulate discussion.

The spot light of the conference shall vary widely from broad research to technical skills with focus on group research where students are exposed to open-ended problems, but in a more structured and less resource intensive way than one-on-one mentoring typical of research experience for undergraduate/ postgraduate programs.

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IJSRD: INTERNATIONAL JOURNAL FOR SCIENCE RESEARCH AND DEVELOPMENT

IJSRD  is a leading e-journal, under which we are encouraging and exploring newer ideas of current trends in Engineering and Science by publishing papers containing pure knowledge. The Journal is started with noble effort to help the researchers in their work and also to share knowledge and research ideas. All research interested scholars are given best opportunity to make world aware of their work. With precise and analytical narration of knowledge by our reviewers, our journal is providing implemental economy and latest global transposition to research. This monthly journal is mainly started to help researching peers belongs to Undergraduate, Postgraduate and Research students.We publish original and high quality papers. We aim to cover the latest outstanding development in the fields of Engineering and Technologies. All the published papers are submitted to the major indexing services for indexing.

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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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Fuel cell vehicles

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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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. 

http://www.ijsrd.com/SpecialIssuehttp://www.ijsrd.com/SubmitManuscript

Image Processing Special Issue#IJSRD

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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