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The research paper CSE Seminar Topics with PPT Bio Informatics The Emerging Discipline describes the emerging role of Bioinformatics in establishing the need to understand the code of life, DNA. DNA the basic molecule of life directly controls the fundamental biology of life. It codes for genes which code for proteins which determine the biological makeup of humans or any living organism. It is variations and errors in the genomic DNA which ultimately define the likelihood of developing diseases or resistance to these same disorders.

The scope of Bioinformatics: The research paper clearly elucidates the scope of Bioinformatics. It says that the science of bioinformatics or computational biology is increasingly being used to improve the quality of life and has developed out of the need to understand the code of life, DNA. Massive DNA sequencing projects have evolved and added in the growth of the science of bioinformatics. DNA the basic molecule of life directly controls the fundamental biology of life.

Application of Bioinformatics: The research paper talks about the various applications of Bioinformatics. It says that Bioinformatics is the applications of computer technologies to the biological sciences, particularly genomics, with the object of discovering knowledge. This is often understood to include high-through output screening of genes and proteins, chemical information system, clinical data, the activity of drugs in the body-all of that got lumped in.

Bioinformatics is any application of computation to the field of biology, including data management, algorithm development and data mining.

In the bioinformatics arena primary focus is on use of the information, as well as on acquisition, preparation, and storage. All needs to be considered within the framework of information for Acquisition of information and documents, including creation of meta-data, submission of electronic media, and communication interfaces.

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The research abstract Computer Science Seminar Topics Beowulf System clearly explains what clusters are. It later proceeds to explain the Beowulf system as an important breakthrough in the area. Clusters are essentially a group of computers connected over a network, which work in tandem to look like a single computer to an outside user. Clustering is most widely recognized, as the ability to combine multiple systems in such a way that they provide services a single system could not. Clustering is used to achieve higher availability, scalability and easier management.

What is Beowulf: Beowulf was a cluster developed by Thomas Sterling of Center Excellence in Space Data and Flight Information Sciences(CESDIS) at NASA Goddard Space Flight Center[1],in 1994.That cluster employed 16 Intel 100MHz DX4 PCs each with 16 MB RAM and 2 Ethernet cards.

A typical Beowulf system may comprise 16 nodes interconnected by 100 base T Fast Ethernet. Each node may include a single Intel Pentium II or Digital Alpha 21164PC processor, 128-512 MBytes of DRAM, 3-30 GBytes of EIDE disk, a PCI bus backplane, and an assortment of other devices. At least one node called master node will have video card, monitor, keyboard, CD-ROM, floppy drive and so forth.

 Beowulf is a parallel computer. It will not just run a uniprocessor “dusty deck” and benefit from all of the computing resources. A site must expect to run parallel programs, either acquired from others or developed in-house. A site without such skill base should probably not follow the Beowulf path. Beowulf is loosely coupled and is a distributed memory environment.

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The research abstract CSE seminar topics with abstract Bayou System elucidates the various functionalities of BAYOU a replicating system. The research paper explains that Bayou is a replicated, weakly consistent storage system designed to support collaborative application in distributed computing environment with varying network connectivity. A typical example of such an environment is a system with mobile hosts that may disconnect over period of time, connect only through low bandwidth, radio networks or connect occasionally with expensive cellular modems.

BAYOU System Model

In Bayou replication management is undertaken by Bayou servers. Each server holds a complete replica of the data. The data model provided by current implementation of Bayou is a ‘relational database’, although other data models could be used as well. Bayou is chosen as a relational model because of its power and flexibility. In particular it naturally supports fine-grained, structured access to the data, which is useful for application specific conflict detection and resolution mechanism, which is desired.

Bayou applications are free to run and update replicas without locking. Bayou guarantees that the distributed strong system will move towards eventually consistency by imposing a global order on write application and by providing propagation guarantees.

What BAYOU does

One feature of Bayou that application can impose its own semantics on the operation executed at a replica. To this end, Bayou reads and writes are not the simple operations supported by most databases.  Instead they include additional application supplied information, which ensures that application will receive the required level of services from the system.

Conclusion

The research paper suggests that Bayou model supports client-supplied anti-entropy policies. Thus clients can influence when to propagate their changes to other servers. The ability to regulate when updates are propagated is important for applications like collaborative software development where users must ensure that a coherent picture of the code base is available at specific times.

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The research paper seminar topics for cse 2011 Asynchronous Transfer Mode (ATM) Switching explains the functionality of ATM- Asynchronous Transfer Mode Switching. The research paper defines ATM. It suggests that ATM does not stand for automatic teller machine. In the telecommunication, it stands for Asynchronous Transfer Mode, in   which data is sent asynchronously.  This mode is another fast packet switching mode. Asynchronous  transfer  mode  (ATM)  is  a  technology  that  has  his  its  history  in  the  development  of  broadband  ISDN  in  the  1970s  and  980s.  Technically, ATM can be viewed as an evolution of pocket switching. The paper describes pocket switching in detail. ATM  is  also  a  set  of  international  interface  and  signaling standards  defined  by  the  International  Telecommunication  Union- Telecommunications  (ITU-T)  Standards  Sector  (formerly  the  CCITT).

The research paper talks in depth the various functionalities offered by ATM. ATM  provides  a  way  of  multiplexing  many  sources  of data  onto  a  common  cells  stream.  Regardless of  speed  of  the inputs.  This  greatly  improves   flexibility,  enabling  provision  of bandwidth  on  demand. ATM  is  a  cell-switching  and  multiplexing  technology  that  combines  the  benefits  of  circuit  switching  (guaranteed  capacity  and  constant transmission  delay)  with  those  of  packet  switching  (flexibility  and efficiency  for  intermittent  traffic).  It  provides  scalable  bandwidth  from a  few  megabits  per  second  (Mbps)  to  many  gigabits  per  second (Gbps).  Because  of  its  asynchronous  nature,  ATM  is  more  efficient than  synchronous  technologies,  such  as  time-division  multiplexing (TDM).

Three types of ATM services exist: permanent virtual circuits (PVC), switched virtual circuits (SVC), and connectionless service (which is similar to SMDS). ATM supports two types of connections: point-to-point and point-to-multipoint.

1. *High   performance via   hardware switching
2. Dynamic bandwidth for heavy traffic
3. *Class- of –service support for media
4. Scalability in speed and network size
5. Common LAN / WAN architecture
6. Opportunity for simplification via VC architecture
7. International standard compliance

Conclusion

The research paper concludes on a note that ATM  is  a  technology  that  can  handle  all  types  of traffic  ( voice,  video  and  data)  multiplexed  on  the  same  network  . In  an  ATM  network  band  width  can  be  reassigned  in  real  time  to different  traffic  based  on  demand.  ATM  is  the  only  technology  common   to  all  environments   from  LAN  to  GAN .

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The research paper on Seminar Topics for CSE Artificial Vision – A Bionic Eye Sheds New Light speaks about prosthetics that help to overcome handicaps. It posits that Bio medical engineers play a vital role in shaping the course of these prosthetics. Now it is the turn of artificial vision through bionic eyes. Chips designed specially to imitate the characteristics of the damaged retina and the cones and rods of the organ of sight are implanted with a microsurgery. Linking electronics and biotechnology, the scientists has made the commitment to the development of technology that will provide or restore vision for the visually impaired around the world.

Bionic eye,’ also called a Bio Electronic eye, is the electronic device that replaces functionality of a part or whole of the eye. It is still at a very early stage in its development, but if successful, it could restore vision to people who have lost sight during their lifetime. A bionic eye work by stimulating nerves, which are activated by electrical impulses. In this case the patient has a small device implanted into the body that can receive radio signals and transmit those signals to nerves. The research paper talks about the causes of blindness as follows:

CAUSES OF BLINDNESS

There are a number of retinal diseases that attack these cells, which can lead to blindness. The most notable of these diseases are

• Retinitis pigmentosa
• Age-related macular degeneration.

The research paper talks about how a “bionic eye” allows blind people to see.

Scope of Bionic eye: Researchers are already planning a third version that has 1,000 electrodes on the retinal implant, which they believe could allow for facial-recognition capabilities and hope to allow the user to see images.

Conclusion:

The research paper concludes by saying that the bionic eye has changed the world of the visually challenged people .We are sure that higher quality, better resolution, and even color are possible in the future.

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The research paper Engineering Seminar Topic on Artificial Olfactory System speaks about E-nose- a breakthrough in Artificial Olfactory System. The paper suggests and explains the development of highly sensitive, selective, reliable, and compact sensing systems to detect toxic chemical and biological agents are of great importance to national security. This paper examines the best such naturally occurring sensing system, the smell or “olfaction,” as well as artificial sensing systems built to emulate the nose. Electronic/artificial noses are being developed as systems for the automated detection and classification of odors, vapors, and gases. An electronic nose is generally composed of a chemical sensing system (e.g., sensor array or spectrometer) and a pattern recognition system (e.g., artificial neural network). . The response of all sensors in the e-nose together constitutes a unique profile that gives the “fingerprint” of odor. Electronic noses are intelligent instruments that are able to classify and quantify different gas/odors.

Architecture of E-nose:

• the sensors that collect and generate  Data
• software that interpret the data

Electronic nose is the colloquial name for an instrument made up of chemical sensors combined with a pattern recognition system . The reversible adsorption of volatile organic compounds (VOCs) to the sensor surface leads to a change of physical properties (conductivity, resistance, and frequency) of the sensor, which is measured. Remind that the main task in odor recognition to create a model as similar to the human model as it is possible. From this point of view electronic/artificial noses (so called E-Noses) are being developed as a system for the automated detection and classification of odors, vapors, gases. E-Nose is represented as a combination of two components: sensing system and Pattern recognition system.

APPLICATIONS

• Prospects for Clinical Application of Electronic-Nose Technology to Early     Detection of Mycobacterium tuberculosis in Culture and Sputum
• E-noses for medicine
• E-noses for the food industry
• E-noses for replacement of dog team

The Research paper identifies the following drawbacks

o   For different applications it requires special pattern reorganization system.

o   Computers are not as smart or flexible as dogs or humans or other biological creatures

“If we get a brand-new scent that we’ve never smelled before, we can learn what that means and recognize it the next time we encounter it”. Machines aren’t very good at being able to adjust to new conditions.

o   cameras can see outside the spectrum of the human eye and  microphones that can detect a vibration a mile away, but in terms of chemical sensing, we are far away from what biology can do

Conclusion:

The paper effectively discussed electronic nose and applications of electronic nose in the environmental, medical and food industries. The major differences between electronic noses and standard analytical chemistry equipment have been explained analytically. It has been suggested that by increasing compactness of E-nose and utilizing modern technologies like nanotechnology, an E-nose can be efficiently used in many fields to present technologies.

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The research paper Artificial Intelligence for Speech Recognition BE Seminar speaks of Speak Recognition as a domain within Artificial Intelligence. The paper talks about the study and design of intelligent agents & also used to describe a property of machines or programs. Among researchers hope machines will exhibit the faculties of reasoning, knowledge, planning, learning, communication, perception and the ability to move and manipulate.

Applications of AI

Pattern Recognition

Hand Recognition

Speech Recognition

Natural Language Processing

Face Recognition

Artificial Creativity

Non linear controls and Robotics

 Speech recognition converts spoken words to machine-readable input. It is also called Voice Recognition. The paper deals withvarious aspects of Speech recognition. Speech recognition includes-

•  Voice dialing
•  Content-based spoken audio search
•  Speech-to-text processing
• Performance of speech recognition systems

 The paper states that speech recognition is usually specified in terms of accuracy and speed. Accuracy may be measured in terms of performance accuracy which is usually rated with word error rate, whereas speed is measured with the real time factor. The paper suggests and explains different types of speech recognition models.

HMM – based Speech Recognition: These are statistical models which output a sequence of symbols or quantities.

DTW – based Speech Recognition – Dynamic time warping is an algorithm for measuring similarity between two sequences which may vary in time or speed. It is a historical approach.

 Applications of Speech Recognition: The application of Speech Recognition is diversified and penetrates into the fields of HealthCare and Military.

The paper also talks about Speech recognizers that have been operated successfully.

The paper concludes by quoting some effective findings.

Some important conclusions from the work are as follows:

1. Speech recognition has definite potential for reducing pilot workload, but this potential was not realized consistently.

2. Achievement of very high recognition accuracy (95% or more) was the most critical factor for making the speech recognition system useful – with lower recognition rates, pilots would not use the system.

3. More natural vocabulary and grammar, and shorter training times would be useful, but only if very high recognition rates could be maintained.

Drawbacks: The computer has trouble with “sound-alike” errors.  It’s hard to get mad at the computer for not recognizing mumbling.  But it can be frustrating when one thinks one is speaking clearly, and it just isn’t good enough.

Conclusion:

This paper presents the Speech Recognition in Artificial intelligence systems and it is important to consider the environment in which the speech recognition system has to work.

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Applications of Artificial Intelligence CSE Technical Report is the area of computer science focusing on creating machines that can engage on behaviors that humans consider intelligent. The ability to create intelligent machines has intrigued humans since ancient times and today with the advent of the computer and 50 years of research into AI programming techniques, the dream of smart machines is becoming a reality. Researchers are creating systems which can mimic human thought, understand speech, beat the best human chess player, and countless other feats never before possible. Actually, artificial intelligence can be defined in two ways

1.      An attempt to make computers more intelligent

1. An attempt to understand how humans think

The research paper highlights four different problems while dealing with systems and software. They are:

1) User interface problems

2) Turing test problems

3) Computationally complex problems

4) Rational agents

Artificial intelligence has applications in several fields. AI is applicable in linguistics and games. Linguistics includes natural languages and CPAN modules. Games include techniques which are developed by artificial intelligence.                    

Conclusion:

The research paper concludes by saying that there are now in the world, machines that can think that can learn and that can create. Moreover, their ability to do these things is going to increase rapidly until–in a visible future–the range of problems they can handle will be coextensive with the range to which the human mind has been applied.  Thus, AI programming techniques, the dream of smart machines is becoming a reality.

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The research paper CSE Btech Seminar Topic The History of Artificial Intelligence explains how Artificial Intelligence calls for formalization of the term “intelligence”. The paper sheds light on how Psychologist and Cognitive theorists are of the opinion that intelligence helps in identifying the right piece of knowledge at the appropriate instances of decision making. 

General Problem Solving Approaches in AI

To understand what exactly AI is, some common problems are illustrated. Problems dealt with in AI generally use a common term called ‘state’.

What is Artificial Intelligence

1. The branch of computer science that is concerned with the automation of intelligent behavior.

2. The study of computations that make it possible to perceive reason and act.

3. A field of study that seeks to explain and emulate intelligent behavior in terms of computational processes.

4. The study of mental faculties through the use of computational models.

The Subject of AI

The subject of AI was originated with game-playing and theorem-proving programs and was gradually enriched with theories from a number of parent disciplines. As a young discipline of science, the significance of the topics covered under the subject changes considerably with time. At present, the topics significant and worthwhile to understand the subject are outlined below:

1. Learning systems
2. Knowledge representation and Reasoning
3. Knowledge base
4. Planning
5. Knowledge acquisition
6. Intelligent search
7. Soft computing
8. Fuzzy logic
9. Artificial neural nets

Application of AI: The paper elucidates the various applications of AI. Image understanding and computer vision, Navigational planning for mobile robots, Speech and natural language understanding, intelligence control

Conclusion:

Knowledge representation, reasoning, planning, learning, intelligent search and uncertainty management of data and knowledge are the common areas covered under AI. Some of the applications areas of AI are speech and image understanding, expert systems, pattern classification and navigational planning of mobile robots. LISP and PROLOG are the usual languages for programming AI problems. Some of the above mentioned areas are discussed in the research paper.

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The Research Abstract Neural Networks and Artificial Intelligence Btech Seminar on Neural Networks and Artificial Intelligence talks about the human brain as an amazing processor. The research paper talks about the multiple challenges the human brain throws. The research abstract talks about the various applications that can be undertaken by Neural Networks not replacing the traditional standards of Artificial Intelligence. The paper talks about Neural Networks as an application used for processing large amounts of data. A considerable light is cast on Artificial Neural Networks as an emerging domain.

What is  Artificial Neural Network : An  artificial  neural  network  is, in  essence, an  attempt  to  simulate  the  brain. Neural  network  theory revolves  around  the  idea  that  certain  key  properties  of  biological  neurons  can  be  extracted  and  applied  to  simulations, thus  creating  a  simulated (and  very  much  simplified) brain. A neural network as defined Robert Hecht-Nielsen: “A neural network is a computing system which is made up of a number of simple, highly inter connected processing elements and which  processes  information  by  its  dynamical  state  response  to  external  inputs”.

Scope of Neural Networks:

Neural  networks  appear  to  be  able  to  solve  “monster”  problems  of  AI  that  traditional systems  have   found   difficulty  with. These  include ,  but  are  not  limited  to ,  speech recognition  and  synthesis ,  vision ,  and  pattern  recognition. Neural networks, with their remarkable ability to derive meaning from complicated or imprecise data, can be used to extract patterns and detect trends that are too complex to be noticed by either humans or other computer techniques.

Advantages of Neural Networks:

1. Adaptive learning: An ability to learn how to do tasks based on the data given for training or initial experience.
2. Self-Organization: An ANN can create its own organization or representation of the information it receives during learning time.
3. Real Time Operation: ANN computations may be carried out in parallel, and special hardware devices are being designed and manufactured which take advantage of this capability.
4. Fault Tolerance via Redundant Information Coding: Partial destruction of a network leads to the corresponding degradation of performance. However, some network capabilities may be retained even with major network damage

Conclusion :

The research abstract concludes positing that, artificial  neural  networks  are  one  of  the  promises  for  the  future  in computing. They  offer  an  ability  to   perform  tasks  outside  the  scope  of  traditional  processors. Neural  networks  can  now  pick  stocks ,  cull  marketing  prospects,  approve  loans,  deny  credit  cards,  tweak  control  systems, grade  coins, and  inspect  work. Though  neural  networks  have  a  huge  potential  we  will  only  get  the  best  of  them  when  they  are  integrated  with  computing ,  AI , fuzzy  logic  and related  subjects.

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