Top Engineering College in India - 2013.

The list of top engineering college in india is changed year by year. there is no static list of ranking. And also i would like to mention here, the ranking survey is conducted by the different magazines with different parameters. Here i have given the survey conducted by the Outlook at 2013. Even though the list is dynamic, all the listed colleges are very good in academic, infrastructure and placement. I hope it may helpful to you.

Engineering college	University	Location	Rank 2013
Indian Institute of Technology, Delhi	Indian Institute of Technology Delhi	New Delhi	1
Indian Institute of Technology, Kharagpur	Indian Institute of Technology Kharagpur	Kharagpur	2
Indian Institute of Technology, Bombay	Indian Institute of Technology Bombay	Mumbai	3
Indian Institute of Technology, Kanpur	Indian Institute of Technology Kanpur	Kanpur	4
Indian Institute of Technology, Madras	Indian Institute of Technology Madras	Chennai	5
Indian Institute of Technology (BHU), Varanasi	Indian Institute of Technology (BHU) Varanasi	Varanasi	6
Birla Institute of Technology and Science, Pilani	Birla Institute of Technology and Science, Pilani	Pilani,Goa,Hyderabad	7
Delhi Technological University	Delhi Technological University	New Delhi	9
Indian Institute of Technology, Guwahati	Indian Institute of Technology Guwahati	Guwahati	9
Mody Institute of Technology and Science	Mody Institute of Technology & Science	Lakshmangarh	10
National Institute of Technology, Tiruchirappalli	National Institute of Technology, Tiruchirappalli	Tiruchirappalli	10
Indian School of Mines	Indian School of Mines	Dhanbad	11
College of Engineering, Guindy	Anna University	Chennai	12
Visvesvaraya National Institute of Technology	Visvesvaraya National Institute of Technology	Nagpur	12
Birla Institute of Technology, Mesra	Birla Institute of Technology Mesra	Ranchi	13
National Institute of Technology Karnataka	National Institute of Technology Karnataka	Surathkal	13
International Institute of Information Technology, Hyderabad	International Institute of Information Technology Hyderabad	Hyderabad	14
Veermata Jijabai Technological Institute	University of Mumbai	Mumbai	15
National Institute of Technology, Warangal	National Institute of Technology, Warangal	Warangal	16
Netaji Subhas Institute of Technology	University of Delhi	New Delhi	17
Indian Institute of Information Technology, Allahabad	Indian Institute of Information Technology Allahabad	Allahabad	18
P.S.G. College of Technology	Anna University	Coimbatore	18
National Institute of Technology, Rourkela	National Institute of Technology, Rourkela	Rourkela	19
Indian Institute of Technology, Bhubaneswar	Indian Institute of Technology Bhubaneswar	Bhubaneswar	21
PEC University of Technology	PEC University of Technology	Chandigarh	21
College of Engineering, Pune	Pune University	Pune	22
National Institute of Technology, Hamirpur	National Institute of Technology, Hamirpur	Hamirpur	23
Harcourt Butler Technological Institute	Uttar Pradesh Technical University	Kanpur	24
Manipal Institute of Technology	Manipal University	Manipal	24
Shri Mata Vaishno Devi University	Shri Mata Vaishno Devi University	Jammu & Kashmir	25
Thadomal Shahani Engineering College	University of Mumbai	Mumbaii	25
Motilal Nehru National Institute of Technology, Allahabad	Motilal Nehru National Institute of Technology, Allahabad	Allahabad	27
Birsa Institute of Technology Sindri	Vinoba Bhave University	Dhanbad	28
Thapar University	Thapar University	Patiala	28
University Institute of Engineering and Technology, Panjab University	Panjab University, Chandigarh	Chandigarh	29
Jamia Millia University,New Delhi	Jamia Millia Islamia	Delhi	30
National Institute of Technology, Silchar	National Institute of Technology, Silchar	Silchar	31
R.V. College of Engineering	Visvesvaraya Technological University	Bangalore	33
Institute of Technology, Nirma University	Nirma University of Science and Technology	Ahmedabad	34
P.E.S. Institute of Technology	Visvesvaraya Technological University	Bangalore	35
National Institute of Engineering	Visvesvaraya Technological University	Mysore	36
University College of Engineering, Osmania University	Osmania University	Hyderabad	37
SSN College of Engineering	Anna University of Technology, Chennai	Chennai	39
Mepco Schlenk Engineering College	Anna University of Technology Tirunelveli	Sivakasi	40
Chaitanya Bharathi Institute of Technology	Osmania University	Hyderabad	41
Thiagarajar College of Engineering	Anna University of Technology, Chennai	Madurai	42
Indian Institute of Technology, Jodhpur	Indian Institute of Technology, Jodhpur	Jodhpur	44
Government College of Engineering, Amravati	Sant Gadge Baba Amravati University	Amravati	45
Government College of Engineering, Amravati	Sant Gadge Baba Amravati University	Amravati	45
Dwarkadas J. Sanghvi College of Engineering	University of Mumbai	Mumbai	46
Model Engineering College	Cochin University of Science and Technology	Kochi	46
P.E.S. College of Engineering	Visvesvaraya Technological University	Mandya	48
Dehradun Institute of Technology	Uttarakhand Technical University	Dehradun	49
Maharashtra Institute of Technology	University of Pune	Pune	50

Top Research Area's in Data Mining

Top Research area's in data mining is given below.

• Developing a unifying theory of data mining
• Scaling up for high dimensional data and high speed data streams
• Mining sequence data and time series data
• Mining complex knowledge from complex data
• Data mining in a network setting
• Distributed data mining and mining multi-agent data
• Data mining for biological and environmental problems
• Data Mining process-related problems
• Security, privacy and data integrity
• Dealing with non-static, unbalanced and cost-sensitive data

Overview

Generally, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases.

Continuous Innovation

Although data mining is a relatively new term, the technology is not. Companies have used powerful computers to sift through volumes of supermarket scanner data and analyze market research reports for years. However, continuous innovations in computer processing power, disk storage, and statistical software are dramatically increasing the accuracy of analysis while driving down the cost.

Example

For example, one Midwest grocery chain used the data mining capacity of Oracle software to analyze local buying patterns. They discovered that when men bought diapers on Thursdays and Saturdays, they also tended to buy beer. Further analysis showed that these shoppers typically did their weekly grocery shopping on Saturdays. On Thursdays, however, they only bought a few items. The retailer concluded that they purchased the beer to have it available for the upcoming weekend. The grocery chain could use this newly discovered information in various ways to increase revenue. For example, they could move the beer display closer to the diaper display. And, they could make sure beer and diapers were sold at full price on Thursdays.

Data, Information, and Knowledge

Data

Data are any facts, numbers, or text that can be processed by a computer. Today, organizations are accumulating vast and growing amounts of data in different formats and different databases. This includes:

• operational or transactional data such as, sales, cost, inventory, payroll, and accounting

• nonoperational data, such as industry sales, forecast data, and macro economic data

• meta data - data about the data itself, such as logical database design or data dictionary definitions

Information

The patterns, associations, or relationships among all this data can provide information. For example, analysis of retail point of sale transaction data can yield information on which products are selling and when.

Knowledge

Information can be converted into knowledge about historical patterns and future trends. For example, summary information on retail supermarket sales can be analyzed in light of promotional efforts to provide knowledge of consumer buying behavior. Thus, a manufacturer or retailer could determine which items are most susceptible to promotional efforts.

Data Warehouses

Dramatic advances in data capture, processing power, data transmission, and storage capabilities are enabling organizations to integrate their various databases into data warehouses. Data warehousing is defined as a process of centralized data management and retrieval. Data warehousing, like data mining, is a relatively new term although the concept itself has been around for years. Data warehousing represents an ideal vision of maintaining a central repository of all organizational data. Centralization of data is needed to maximize user access and analysis. Dramatic technological advances are making this vision a reality for many companies. And, equally dramatic advances in data analysis software are allowing users to access this data freely. The data analysis software is what supports data mining.

What can data mining do?

Data mining is primarily used today by companies with a strong consumer focus - retail, financial, communication, and marketing organizations. It enables these companies to determine relationships among "internal" factors such as price, product positioning, or staff skills, and "external" factors such as economic indicators, competition, and customer demographics. And, it enables them to determine the impact on sales, customer satisfaction, and corporate profits. Finally, it enables them to "drill down" into summary information to view detail transactional data.

With data mining, a retailer could use point-of-sale records of customer purchases to send targeted promotions based on an individual's purchase history. By mining demographic data from comment or warranty cards, the retailer could develop products and promotions to appeal to specific customer segments.

For example, Blockbuster Entertainment mines its video rental history database to recommend rentals to individual customers. American Express can suggest products to its cardholders based on analysis of their monthly expenditures.

WalMart is pioneering massive data mining to transform its supplier relationships. WalMart captures point-of-sale transactions from over 2,900 stores in 6 countries and continuously transmits this data to its massive 7.5 terabyte Teradata data warehouse. WalMart allows more than 3,500 suppliers, to access data on their products and perform data analyses. These suppliers use this data to identify customer buying patterns at the store display level. They use this information to manage local store inventory and identify new merchandising opportunities. In 1995, WalMart computers processed over 1 million complex data queries.

The National Basketball Association (NBA) is exploring a data mining application that can be used in conjunction with image recordings of basketball games. The Advanced Scout software analyzes the movements of players to help coaches orchestrate plays and strategies. For example, an analysis of the play-by-play sheet of the game played between the New York Knicks and the Cleveland Cavaliers on January 6, 1995 reveals that when Mark Price played the Guard position, John Williams attempted four jump shots and made each one! Advanced Scout not only finds this pattern, but explains that it is interesting because it differs considerably from the average shooting percentage of 49.30% for the Cavaliers during that game.

By using the NBA universal clock, a coach can automatically bring up the video clips showing each of the jump shots attempted by Williams with Price on the floor, without needing to comb through hours of video footage. Those clips show a very successful pick-and-roll play in which Price draws the Knick's defense and then finds Williams for an open jump shot.

UGC NET EXAMINATION 2013

University grants commission was established in 1950 for regulation and supervising the higher education recruitment and quality research work through grants and continuous academic staff training. UGC organizes the national eligibility test for qualifying criteria for lectureship as well as deciding the junior research fellowship to the further research in particular subjects. Net is held for some selected subjects of humanities and social sciences, environmental studies CS two times in a year, June and December.

About NET and its notification-

Earlier net was not the essential criteria for lectureship but now ministry of HRD with consultation of UGC it was decided to make it minimum compulsory eligibility for assistant professorship onwards.

In this year 2013 UGC has notified for the net examination with JRF too. Notification also mentioned the changed pattern of exam which was changed from descriptive paper 3 to objective nature. UGC also mentioned centers, subjects, eligibility, criteria for JRF and net in the notification which will be delineated in following topics

Syllabus and nature-

UGC NET exam has three different paper conducted in consecutive sessions. All are objective in nature with negative marking of one third. Paper 1 will be general mental ability and teaching aptitude test. Paper 2 will be the objective paper of the chosen subjects and finally third paper will also be the chosen subject But the nature of question will be more deep and broad. Paper 1 will have 60 question but applicants have relief that they have to answer any 50 question, paper 2 will have 50 questions and all are necessary and paper 3rd will have 75 question and all are necessary. All questions will carry 2 marks.

Criteria for NET and JRF-
Applicants have to pass all papers with 40 5 marks in each of them and 65 % marks cumulatively for net eligibility for general candidates and for the rest of the reserved category it sis 35 % each of the category and 60 % cumulatively.

Criteria for JRF in each subject is decided by UGC at the time declaring the result not before that..

Mode of submission of application form-

The submission of application for is bit lengthy. Candidates have to log on to UGC website www.ugc.ac.in and print the challan to pay the fee and then have to fill in the application form, attendance sheet, admit card with personal profile and submit it. After the submission they have to print all the documents and sent it to the UGC by post. Photograph has to be scanned while submitting the online form.

Important dates-

•Candidates have the option to pay the charges from 15TH march to 5 April through challan and date for submission of online form is also the same.
•Last date for sending the print out to UGC is 15th of April.
•The date of exam is 26th June 2013
Academic and other eligibility-
•All applicants have to be masters in their subjects with 55 marks if they are in general category and all other candidates have to be masters with 50% marks.
•There is no maximum age limit for net but for the JRF general candidate should not be above 28 years and for OBC 3 years relaxation and for SC and ST it sis 5 years relaxation.

Charges- 
For General and OBC candidates fee is 450RS +20 RS banking transaction charges and all other candidates have to pay only 250 Rs.

Results are generally published after two month of examination.

Cutoff of UGC NET exam will be evaluated on many factors some of factors are mentioned Below

Number of Candidate appeared for the UGC NET exam
No of candidates passed the exam
Difficulty level of question paper
No. Of vacancy for this exam
Cutoff may also be sectional wise

Candidates who applied for this recruitment/exam are advised to check the expected cut off marks of UGC NET on the official website. We are providing the official website address where you can check all the details.

  

Official website address: www.ugcnetonline.in/

Source: sarkariexam

Google Android Operating System

Android is a Linux-based operating system designed primarily for touchscreen mobile devices such as smartphones and tablet computers. Initially developed by Android, Inc., whom Google financially backed and later purchased in 2005, Android was unveiled in 2007 along with the founding of the Open Handset Alliance: a consortium of hardware, software, and telecommunication companies devoted to advancing open standards for mobile devices.The first Android-powered phone was sold in October 2008.

Android is open source and Google releases the code under the Apache License. This open source code and permissive licensing allows the software to be freely modified and distributed by device manufacturers, wireless carriers and enthusiast developers. Additionally, Android has a large community of developers writing applications ("apps") that extend the functionality of devices, written primarily in a customized version of the Java programming language. In October 2012, there were approximately 700,000 apps available for Android, and the estimated number of applications downloaded from Google Play, Android's primary app store, was 25 billion.

These factors have allowed Android to become the world's most widely used smartphone platform and the software of choice for technology companies who require a low-cost, customizable, lightweight operating system for high tech devices without developing one from scratch. As a result, despite being primarily designed for phones and tablets, it has seen additional applications on televisions, games consoles and other electronics. Android's open nature has further encouraged a large community of developers and enthusiasts to use the open source code as a foundation for community-driven projects, which add new features for advanced users or bring Android to devices which were officially released running other operating systems.

Android had a worldwide smartphone market share of 75% during the third quarter of 2012, with 500 million devices activated in total and 1.3 million activations per day. The operating system's success has made it a target for patent litigation as part of the so-called "smartphone wars" between technology companies.

      

The source code for Android is available under free and open source software licenses. Google publishes most of the code (including network and telephony stacks) under the Apache License version 2.0, and the rest, Linux kernel changes, under the GNU General Public License version 2. The Open Handset Alliance develops the changes to the Linux kernel, in public, with source code publicly available at all times. The rest of Android is developed in private by Google, with source code released publicly when a new version is released. Typically Google collaborates with a hardware manufacturer to produce a 'flagship' device (part of the Google Nexus series) featuring the new version of Android, then makes the source code available after that device has been released.

In early 2011, Google chose to temporarily withhold the Android source code to the tablet-only 3.0 Honeycomb release. The reason, according to Andy Rubin in an official Android blog post, was because Honeycomb was rushed for production of the Motorola Xoom, and they did not want third parties creating a "really bad user experience" by attempting to put onto smartphones a version of Android intended for tablets. The source code was once again made available in November 2011 with the release of Android 4.0.

Even though the software is open-source, device manufacturers cannot use Google's Android trademark unless Google certifies that the device complies with their Compatibility Definition Document (CDD). Devices must also meet this definition to be eligible to license Google's closed-source applications, including Google Play. As Android is not completely released under a GPL compatible license, e.g. Google's code is under the Apache license, and also because Google Play allows proprietary software, Richard Stallman and the Free Software Foundation have been critical of Android and have recommended the usage of alternatives such as Replicant.

Android Versions:

Version	Code Name	Release date	API level	Distribution (December 3, 2012)
4.2	Jelly Bean	November 13, 2012	17	0.8%
4.1	Jelly Bean	July 9, 2012	16	5.9%
4.0.x	Ice Cream Sandwich	December 16, 2011	15	27.5%
3.2	Honeycomb	July 15, 2011	13	1.2%
3.1	Honeycomb	May 10, 2011	12	0.4%
2.3.3–2.3.7	Gingerbread	February 9, 2011	10	50.6%
2.3–2.3.2	Gingerbread	December 6, 2010	9	0.2%
2.2	Froyo	May 20, 2010	8	10.3%
2.0–2.1	Éclair	October 26, 2009	7	2.7%
1.6	Donut	September 15, 2009	4	0.3%
1.5	Cupcake	April 30, 2009	3	0.1%

GATE 2013 Syllabus for COMPUTER SCIENCE AND INFORMATION TECHNOLOGY–CS & IT

Engineering Mathematics

Mathematical Logic: Propositional Logic; First Order Logic. Probability: Conditional Probability; Mean, Median, Mode and Standard Deviation; Random Variables; Distributions; uniform, normal, exponential, Poisson, Binomial. Set Theory & Algebra: Sets; Relations; Functions; Groups; Partial Orders; Lattice; Boolean Algebra. Combinatorics: Permutations; Combinations; Counting; Summation; generating functions; recurrence relations; asymptotics. Graph Theory: Connectivity; spanning trees; Cut vertices & edges; covering; matching; independent sets; Colouring; Planarity; Isomorphism. Linear Algebra: Algebra of matrices, determinants, systems of linear equations, Eigen values and Eigen vectors. Numerical Methods: LU decomposition for systems of linear equations; numerical solutions of non-linear algebraic equations by Secant, Bisection and Newton-Raphson Methods; Numerical integration by trapezoidal and Simpson's rules. Calculus: Limit, Continuity & differentiability, Mean value Theorems, Theorems of integral calculus, evaluation of definite & improper integrals, Partial derivatives, Total derivatives, maxima & minima.

GENERAL APTITUDE(GA):

Verbal Ability: English grammar, sentence completion, verbal analogies, word groups, instructions, critical reasoning and verbal deduction.

Computer Science and Information Technology

Digital Logic: Logic functions, Minimization, Design and synthesis of combinational and sequential circuits; Number representation and computer arithmetic (fixed and floating point). Computer Organization and Architecture: Machine instructions and addressing modes, ALU and data-path, CPU control design, Memory interface, I/O interface (Interrupt and DMA mode), Instruction pipelining, Cache and main memory, Secondary storage. Programming and Data Structures: Programming in C; Functions, Recursion, Parameter passing, Scope, Binding; Abstract data types, Arrays, Stacks, Queues, Linked Lists, Trees, Binary search trees, Binary heaps. Algorithms: Analysis, Asymptotic notation, Notions of space and time complexity, Worst and average case analysis; Design: Greedy approach, Dynamic programming, Divide-and-conquer; Tree and graph traversals, Connected components, Spanning trees, Shortest paths; Hashing, Sorting, Searching. Asymptotic analysis (best, worst, average cases) of time and space, upper and lower bounds, Basic concepts of complexity classes P, NP, NP-hard, NP-complete. Theory of Computation: Regular languages and finite automata, Context free languages and Push-down automata, Recursively enumerable sets and Turing machines, Undecidability. Compiler Design: Lexical analysis, Parsing, Syntax directed translation, Runtime environments, Intermediate and target code generation, Basics of code optimization. Operating System: Processes, Threads, Inter-process communication, Concurrency, Synchronization, Deadlock, CPU scheduling, Memory management and virtual memory, File systems, I/O systems, Protection and security. Databases: ER-model, Relational model (relational algebra, tuple calculus), Database design (integrity constraints, normal forms), Query languages (SQL), File structures (sequential files, indexing, B and B+ trees), Transactions and concurrency control. Information Systems and Software Engineering: information gathering, requirement and feasibility analysis, data flow diagrams, process specifications, input/output design, process life cycle, planning and managing the project, design, coding, testing, implementation, maintenance. Computer Networks: ISO/OSI stack, LAN technologies (Ethernet, Token ring), Flow and error control techniques, Routing algorithms, Congestion control, TCP/UDP and sockets, IP(v4), Application layer protocols (icmp, dns, smtp, pop, ftp, http); Basic concepts of hubs, switches, gateways, and routers. Network security basic concepts of public key and private key cryptography, digital signature, firewalls. Web technologies: HTML, XML, basic concepts of client-server computing.