Wednesday, February 9, 2011

Semantic Web

What is the Semantic Web?

       The Semantic Web is a web that is able to describe things in a way that computers can understand.
                             The Beatles was a popular band from Liverpool.
                             John Lennon was a member of the Beatles.
                             "Hey Jude" was recorded by the Beatles.

       Sentences like the ones above can be understood by people. But how can they be understood by computers?

       Statements are built with syntax rules. The syntax of a language defines the rules for building the language statements. But how can syntax become semantic?

       This is what the Semantic Web is all about. Describing things in a way that computers applications can understand it.

       The Semantic Web is not about links between web pages.

       The Semantic Web describes the relationships between things (like A is a part of B and Y is a member of  Z) and the properties of things (like size, weight, age, and price)

       The Semantic Web is an evolving development of the World Wide Web in which the meaning (semantics) of information and services on the web is defined, making it possible for the web to understand and satisfy the requests of people and machines to use the web content.

        It derives from World Wide Web Consortium director Sir Tim Berners-Lee's vision of the Web as a universal medium for data, information, and knowledge exchange.


       Humans are capable of using the Web to carry out tasks such as finding the Finnish word for "monkey", reserving a library book, and searching for a low price for a DVD. However, a computer cannot accomplish the same tasks without human direction because web pages are designed to be read by people, not machines. The semantic web is a vision of information that is understandable by computers, so that they can perform more of the tedious work involved in finding, sharing, and combining information on the web.

       In particular, the semantic web is expected to revolutionize scientific publishing, such as real-time publishing and sharing of experimental data on the Internet.

The Resource Description Framework
       The RDF (Resource Description Framework) is a language for describing information and resources on the web.
       Putting information into RDF files, makes it possible for computer programs ("web spiders") to search, discover, pick up, collect, analyze and process information from the web.
       The Semantic Web uses RDF to describe web resources.

How can it be used?
       If information about music, cars, tickets, etc. were stored in RDF files, intelligent web applications could collect information from many different sources, combine information, and present it to users in a meaningful way.

   Information like this:

  •                Car prices from different resellers
  •                              Information about medicines
  •                              Plane schedules
  •                              Spare parts for the industry
  •                              Information about books (price, pages, editor, year)
  •                              Dates of events
  •                              Computer updates

Can it be understood?

       The Semantic Web is not a very fast growing technology.
       One of the reasons for that is the learning curve. RDF was developed by people with academic background in logic and artificial intelligence. For traditional developers it is not very easy to understand.
       One fast growing language for building semantic web applications is RSS.

Simple semantic web application:

Buying and selling used cars

       Suppose a semantic web system was built to administer the selling and buying of used cars over the Internet.
       The system would contain two main applications:
                             One for people who wanted to buy a car
                             One for people who wanted to put up a car for sale

       Let's call the Internet applications for IBA (I Buy Application), and ISA (I Sell Application).

IBA - The I Buy Application

       People who want to buy a car could use an IBA application much like this:
       In a "real live" application you would be asked to identify yourself the first time you used it. Your ID would be stored in an RDF file. Your ID would identify you as a person with name, address, email, and ID number.
       When you submitted the query, the application would return a list of cars for sale, and the list could be drilled down and sorted by year, price, location and availability. This information would be returned from a web spider continuously searching the web for RDF files.

ISA - The I Sell Application

       People who want to sell a car could use an ISA application much like this:
       When you submitted the form, the application would ask you for more information and store your ID and the information in an RDF file made available to the web.
       The RDF file would contain information like:

Your ID: Name, address, email, ID number.
Your selling item: type, model, picture, price, description.

Behind the scenes

       Behind the scenes, the "ISA" application creates an RDF file with a lot of RDF pointers.
       It creates an RDF pointer to a file with information about you, an RDF pointer to information about Volvo and Volvo models, an RDF pointer to Volvo dealers and resellers, about parts, about prices, and much more.
       An RDF pointer is a pointer (actually an URL) to information about things (like a knowledge database).
       The beauty about this is that you don't have to describe yourself, or the car model. The RDF application will sort it out for you.


       Vastness: The World Wide Web contains at least 48 billion pages as of this writing (August 2, 2009). Any automated reasoning system will have to deal with truly huge inputs.

       Vagueness: These are imprecise concepts like "young" or "tall". This arises from the vagueness of user queries, of concepts represented by content providers, of matching query terms to provider terms and of trying to combine different knowledge bases with overlapping but subtly different concepts. Fuzzy logic is the most common technique for dealing with vagueness.

       Uncertainty: These are precise concepts with uncertain values. For example, a patient might present a set of symptoms which correspond to a number of different distinct diagnoses each with a different probability. Probabilistic reasoning techniques are generally employed to address uncertainty.

       Inconsistency: These are logical contradictions which will inevitably arise during the development of large ontologies, and when ontologies from separate sources are combined. Deductive reasoning fails catastrophically when faced with inconsistency, because "anything follows from a contradiction". Defeasible reasoning and paraconsistent reasoning are two techniques which can be employed to deal with inconsistency.

       Deceit: This is when the producer of the information is intentionally misleading the consumer of the information. Cryptography techniques are currently utilized to ameliorate this threat.

Semantic Web Agents

       The semantic web will not be searchable in free text. To search (or access) the semantic web, we will need some software to help us.
       To use the semantic web, we will need "Semantic Web Agents" or "Semantic Web Services". These "Agents" or "Services" will help us to find what we are looking for on the semantic web.
                             On the semantic web, we might want to look for information about:
  1.                              The cheapest airline tickets
  2.                              Styling that would fit my car
  3.                              Books, DVDs, and CDs
  4.                              Weather forecasts
  5.                              Time schedules and calendar events
  6.                              Stock prices and exchange rates

you can go through the blogs and tell me if you want more information.

some other unit topics are also uploaded by my friends 
links are given below 


Friday, February 4, 2011

Wireless Network

Wireless Networks
        A wireless LAN or WLAN is a wireless local area network that uses radio waves as its carrier. The last link with the users is wireless, to give a network connection to all users in a building or campus. The backbone network usually uses cables

Common Topologies:
         The wireless LAN connects to a wired LAN. There is a need of an access point that bridges wireless LAN traffic into the wired LAN.The access point (AP) can also act as a repeater for wireless nodes, effectively doubling the maximum possible distance between nodes. 
         The physical size of the network is determined by the maximum reliable propagation range of the radio signals. Referred to as ad hoc networks are self-organizing networks without any centralized control Suited for temporary situations such as meetings and conferences.

How do wireless LANs work?
          Wireless LANs operate in almost the same way a wired LANs, using the same networking protocols and supporting the most of the same applications.

How are WLANs Different?

        They use specialized physical and data link protocols.They integrate into existing networks through access points which provide a bridging function. They let you stay connected as you roam from one coverage area to another.They have unique security considerations .They have specific interoperability requirements. They require different hardware .They offer performance that differs from wired LANs.

Physical and Data Link Layers:

Physical Layer:
        The wireless NIC takes frames of data from the link layer, scrambles the data in a predetermined way, then uses the modified data stream to modulate a radio carrier signal.

Data Link Layer:
        Uses Carriers-Sense-Multiple-Access with Collision Avoidance (CSMA/CA).
Integration With Existing Networks:
         Wireless Access Points (APs) - a small device that bridges wireless traffic to your network. Most access points bridge wireless LANs into Ethernet networks, but Token-Ring options are available as well.
         Users maintain a continuous connection as they roam from one physical area to another Mobile nodes automatically register with the new access point.
Methods: Mobile IP
        IEEE 802.11 standard does no  address roaming, you may need to purchase equipment from one    vendor if your users need to roam  from one access point to another.

  • PC Card, either with integral antenna or with external antenna.
  • ISA Card with external antenna connected by cable.
  • Handheld terminals.

A family of wireless LAN (WLAN) specifications developed by a working group at the Institute of Electrical and Electronic Engineers (IEEE)
Versions: 802.11a, 802.11b, 802.11g, 802.11e, 802.11f, 802.11i
802.11a offers speeds with a theoretically maximum rate of 54Mbps in the 5 GHz band
802.11b offers speeds with a theoretically maximum rate of 11Mbps at in the 2.4 GHz spectrum band.
802.11g is a new standard for data rates of up to a theoretical maximum of 54 Mbps at 2.4 GHz.
Access Point Placement and Power:
Typically – mounted at ceiling height.Between 15 and 25 feet (4.5m to 8m)The greater the height, the greater the difficulty to get power to the unit. Solution: consider devices that can be powered using CAT5 Ethernet cable (CISCO Aironet 1200 Series).Access points have internal or external antennas.

you can go through the blogs and tell me if you want more information.

some other unit topics are also uploaded by my friends 
links are given below 


Saturday, January 29, 2011

IT Trends

Nagpur university syllabus (Revised) MBA 3 rd sem IT

Paper -III: Innovations in IT


Unit I: IT Enabled Services ((ITeS): Outsourcing - India as Ideal Destination, India Outsourcing History, Outsourcing Writing to India, Call Centers in India, Multilingual Call Centers, Voice/Non-Voice ITeS (BPO Services), HIPAA Compliance in India, Outsourcing Engineering Services, Radiology and Intellectual Property to India. BPO: BPO Concept, Offshoring, Nearshoring, Homeshoring, Medical / Legal Transcription, Back-Office Accounting, Insurance Claims, Credit Card Processing, BPO in India, BPO Security, BPO in India - Legal Issues
Unit II: Ntewroking Technology &Systems (NeTS) - Next Generation Multi-service Networks, Future INternet Design (FIND), IP Telephony (IPT): IPT Components, Soft Phones, Wireless IP Phones, Voice Gateways, Inter-cluster Call, Telco Signaling Protocols, VoIP, VoIP Protocols, Large-Scale IPT and Voice-Mail Network: Voice Network Architecture, Overview: Network Planning and Designing.

Unit III: Communication Technologies-I - Next Generation Mobile Networks, Heterogeneous Networks, Ad-Hoc & Sensor Networks, Wireless Networks: WiFi, WiMax, Cellular, 3G/4G.

Unit IV: Communication Technologies-II - Mobility Management and Mobile Computing, Technology Convergence: GSM/CDMA/TDMA, Quality of Service Issues, Network Security and Privacy, Grid Computing and Clustering, Mobile TV, MMIT.

Unit V: Web Applications and Services-I - Internet Services and Applications, Web Services, Internet Computing, E-Learning , Middleware , Web Information Systems.

Unit VI: Web Applications and Services-II - Web Based Software, Semantic Web, Agent-Oriented Computing, E-Business, E-Commerce & E-Government, Ontology Engineering, Portal Technologies.

Unit VII: Computing and Information Systems - Advanced Computer Architectures, Virtual Reality, Databases & Data Mining, Agile Information Systems, AI & DSS, High Performance & Cluster Computing, Real-Time and Embedded Systems, Information Systems Integration , Geographical Information Systems, Business Process Modeling.

Unit VIII: Pervasive and Ubiquitous Computing-I - Smart Appliances & Wearable Computers, Inter-Vehicular Communication, Personal Computing, Pervasive Wireless Networking, Opportunistic Systems, Ubiquitous Health Care.

Unit IX: Pervasive and Ubiquitous Computing-II - Ubiquitous Computing, Location-Based Services, Educational Gaming & Instructional Technologies, Context-Aware Environments and Devices, Personal Broadcasting, Autonomic Systems.

Unit X: IT Trends - Biometrics, Fuzzy Logic & Neural Networks, Organic Growth, Audio/Visuals: mp3, mpeg and IPOD, General Outline of IT Act’2000, Case Studies: Mobile Industry Market Players: Nokia, Motorola, Sony-Ericson, Samsung and LG.  GIS: Google Earth, E-Learning: Zee TV, E-Governance: Andhra Pradesh, Gadgets: Apple Store, Networking: Cisco.

Suggested Readings:
1.        Offshore Ready: Strategies to Plan & Profit from Offshore IT-enabled Services by Stuart Morstead
2.        Networking Infrastructure for Pervasive Computing: Enabling Technologies and Systems by Debashis Saha, Amitava Mukherjee, and Somprakash Bandyopadhyay
3.        Introduction to Mobile Communications: Technology, Services, Markets (Informa Telecoms & Media) by Tony Wakefield, Dave McNally, David Bowler, and Alan Mayne
4.        iPod & iTunes: The Missing Manual, Fourth Edition by Jude Biersdorfer
5.        Developing Web Services for Web Applications: A Guided Tour for Rational Application Developer and WebSphere Application Server (IBM Illustrated Guide Series) by Colette Burrus and Stephanie Parkin

Dear friends,

I have uploaded the 10th unit topics from the syllabus in my blogs. 

Unit 10:
you can go through the blogs and tell me if you want more information.

some other unit topics are also uploaded by my friends 
links are given below