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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.

Download Seminar Topics for CSE Artificial Vision – A Bionic Eye Sheds New Light.

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.

Download Applications of Artificial Intelligence CSE Technical Report.

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.

Download CSE Btech Seminar Topic The History of Artificial Intelligence.

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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The research abstract Artificial Intelligence Final Seminar Topic focuses mainly on establishing the fact that ‘Intelligence’ is in the mind. The research abstract proposes a working hypothesis a Separability Hypothesis which posits that we can factor off an architecture for cognition from a more general architecture for mind, thus avoiding a number of philosophical objections that have been raised about the “Strong AI” hypothesis.

Challenges involved:

A major problem in the study of intelligence and cognition is the range of—often implicit—assumptions about what phenomena these terms are meant to cover. The research abstract raises some pertinent questions: Are we just talking about cognition as having and using knowledge, or are we also talking about other mental states such as emotions and subjective awareness? Are we talking about intelligence as an abstract set of capacities, or as a set of biological mechanisms and phenomena? These two questions set up two dimensions of discussion about intelligence.

Dimension 1: Is intelligence separable from other mental phenomena?

The research paper elucidates over Dimension 1 saying that – When people think of intelligence and cognition, they often think of an agent being in some knowledge state, that is, having thoughts, beliefs. They also think of the underlying process of cognition as something that changes knowledge states.

Dimension 2: Functional versus Biological

The second dimension in discussions about intelligence involves the extent to which we need to be tied to biology for understanding intelligence. Can intelligence be characterized abstractly as a functional capability which just happens to be realized more or less well by some biological organisms?

Conclusion:

The research abstract marches forth by asking how far intelligence or cognition can be separated from mental phenomena in general. The abstract then suggests that the problem of architecture for cognition is not really well-posed, since, depending upon what aspects of the behavior of biological agents are included in the functional specification; there can be different constraints on the architecture. The research abstract reviews a number of issues and proposals relevant to cognitive architectures.

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This research abstract Applications of Robotics in Medicine Computer Science Engineering Seminar talks about the multiple application benefits Robotics has to offer in the field of medicine. A survey conducted on Applications of Robotics in Medicine addresses sets of known achievements, singling out noteworthy autonomous in body devices, either co-robotic surgical aids, in view of recognizing shared benefits or hindrances, to explore how to conceive effective tools, tailored to answer given demands, while remaining within established technologies.

Applications in Medicine: The role of robots is a highly varied one. Robots in the field of medicine are used right from scrubbing the floors to collecting the blood samples of patients. The eminence of Robots has enhanced ever since and now the machine-man actually carries out a surgery. Robotic surgery is the process in which a robot actually carries out a surgical procedure under the control of its computer program. Although a surgeon certainly will be involved in the planning of the procedure to be performed and will also observe the implementation of that

plan, the execution of the plan will not be accomplished by them – but by the robot.

Robots in Tele-Surgery: In a method like this one an expert surgeon actually maneuvers the movements of the Robot from a distance. A robot, local to the patient, becomes the surgeon’s hands, while an intricate interface conveys the robot’s senses to the surgeon (making use of while an intricate interface conveys the robot’s senses to the surgeon (making use of visual, aural, force and tactile feedback).

Conclusion:

Although Medical Robotics is a highly challenging field, still it is in its embryonic state. There are several methods and security measures that ensue to see the field bloom to its full potential. Inclusion of Robots in surgery specifically is a matter that has lot many ideas to be considered. These range from The development, and international adoption, of safety standards the aim of task-specific, as opposed to general-purpose, robots the education of the medical community in the acceptance and integration of Robots.

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The research paper An Overview of Secure Shell CSIT Paper Presentation deals in creating greater security measures while working over internet. Internet- that has now almost become inevitable to the entire process of communication. A vast overflow of information in a given scenario like this needs an equally efficient security back-up. Secure Shell is a protocol that provides authentication, encryption and data integrity to secure network communications. This research paper elucidates the various security measures.

Scope of Secure Shell Protocol: Implementations of Secure Shell offer the following capabilities: a secure command-shell, secure file transfer, and remote access to a variety of TCP/IP applications via a secure tunnel. Secure Shell client and server applications are widely available for most popular operating systems.

Security Requirements: The research paper talks about the following security requirements.

1. Confidentiality: the information being transmitted should not be accessible to unauthorized third parties.
2. Integrity: Unauthorized parties must not be able to incorporate modifications in the data.
3. Authentication: Both the parties must identify each other and must abide by the norms thoroughly.

Benefits of Secure Shell: The research paper identifies various benefits of Secure Shell Protocol. Secure Shell offers a good solution for the problem of securing data sent over a public network. The research paper talks about using Secure Shell and the Internet for securely transferring documents and work products electronically. It also talks about cost saving over other traditional methods of data/information transmission.

Conclusion:

The research paper talks about the Secure Shell technology and its indispensable value in providing with network security tools that help compliment system and data security. Secure Shell encrypts remote connections and helps administrators decide which means of authentication they require. Additionally, Secure Shell enables to create secure remote backups and tunnel other TCP-based traffic. Secure Shell secures your mission-critical data from eavesdropping.

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The research paper Developing a High Performance Cache System Paper Presentation describes the cache memory as a key mechanism in improving the overall performance of the system. The paper aims at developing a high performance cache system.

 What cache does: Cache exploits the reference stream of the typical application. The research paper describes how cache functions in a given locality. Two types of localities are discussed in the research paper

1. Temporal locality
2. Spatial locality

The research paper also talks about ‘prefetching mechanism’ that reduces cache misses. Hardware-based prefetching requires some modification to the cache, but almost no modification to the processor core. Its main advantage is that prefetches are handled dynamically at run time without compiler intervention. In contrast software-based approaches rely on compiler technology to perform static program analysis and to selectively insert prefetch instructions.

A SMI cache is constructed in three parts; a conventional direct mapped cache With a small block size, a fully associative buffer with a large block size at the same cache level, and a hardware prefetching unit. The improvement in performance is achieved by exploiting the basic characteristic of locality.

Benefits of cache: Common design objective for the cache are to improve utilization of the temporal and spatial locality inherent in applications. However no single cache organization exploit both temporal and spatial locality optimally because of their contradictory characteristics.

Conclusion:

The research paper basically aims at designing a simple but high performance cache system with low cost, a new caching mechanism for exploiting two types of locality effectively and adaptively is designed: A direct mapped cache with a small block size for exploiting temporal locality and a fully associative spatial buffer with a large block size for exploiting spatial buffer.

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