T. V. Prasad

T. Kameswara Rao, M. Rajya Lakshmi, T. V. Prasad

Detailed exploration on Brain Computer Interface (BCI) and its recent trends has been done in this paper. Work is being done to identify objects, images, videos and their color compositions. Efforts are on the way in understanding speech, words, emotions, feelings and moods. When humans watch the surrounding environment, visual data is processed by the brain, and it is possible to reconstruct the same on the screen with some appreciable accuracy by analyzing the physiological data. This data is acquired by using one of the non-invasive techniques like electroencephalography (EEG) in BCI. The acquired signal is to be translated to produce the image on to the screen. This paper also lays suitable directions for future work.

Sachin Lakra, T. V. Prasad, G. Ramakrishna

A semantic net can be used to represent a sentence. A sentence in a language contains semantics which are polar in nature, that is, semantics which are positive, neutral and negative. Neutrosophy is a relatively new field of science which can be used to mathematically represent triads of concepts. These triads include truth, indeterminacy and falsehood, and so also positivity, neutrality and negativity. Thus a conventional semantic net has been extended in this paper using neutrosophy into a Polar Fuzzy Neutrosophic Semantic Net. A Polar Fuzzy Neutrosophic Semantic Net has been implemented in MATLAB and has been used to illustrate a polar sentence in English language. The paper demonstrates a method for the representation of polarity in a computers memory. Thus, polar concepts can be applied to imbibe a machine such as a robot, with emotions, making machine emotion representation possible.

Kamlesh Sharma, T. Suryakanthi, T. V. Prasad

This paper presents exploration of speech enable operating systems, software, and applications. It begins with a description of how such systems work, and the level of accuracy that can be expected. It explains the applications of speech recognition technology in different areas education, medical, mobile computing, railway reservation, dictation, and web browsing. A brief comparison of the operating systems supported for voice, speech recognition software or tool. It gives the brief introduction about the potential of voice/speech recognition software. It explains the feature of different speech enable Operating system and speech recognition software. Windows speech recognition have many innovative features for Windows operating system and efficiently assist the computer to control, dictate, navigate, selecting the words, sending emails and correcting the words or sentences. It also explains the benefits and issue related to speech technology. In last era speech recognition technology grew tremendously. There are large number of companies who are working in these area and developing software for the people who are not able to control the system through keyboard or mouse such as physically impaired and senior citizens. This paper gives a brief introduction of speech enabled OS and speech recognition software.

M. Rajyalakshmi, T. Kameswara Rao, T. V. Prasad

A new approach for implementing number of expressions, emotions and, actions to operate objects through the thoughts of brain using a Non-Invasive Brain Computing Interface (BCI) technique has been proposed. In this paper a survey on brain and its operations are presented. The steps involved in the brain signal processing are discussed. The current systems are able to present few expressions and emotions on a single device. The proposed system provides the extended number of expressions on multiple numbers of objects.

Sachin Lakra, T. V. Prasad, G. Ramakrishna

The paper describes some recent developments in neural networks and discusses the applicability of neural networks in the development of a machine that mimics the human brain. The paper mentions a new architecture, the pulsed neural network that is being considered as the next generation of neural networks. The paper also explores the use of memristors in the development of a brain-like computer called the MoNETA. A new model, multi/infinite dimensional neural networks, are a recent development in the area of advanced neural networks. The paper concludes that the need of neural networks in the development of human-like technology is essential and may be non-expendable for it.

Sachin Lakra, T. V. Prasad, Deepak Kumar Sharma et al.

For the past few decades, man has been trying to create an intelligent computer which can talk and respond like he can. The task of creating a system that can talk like a human being is the primary objective of Automatic Speech Recognition. Various Speech Recognition techniques have been developed in theory and have been applied in practice. This paper discusses the problems that have been encountered in developing Speech Recognition, the techniques that have been applied to automate the task, and a representation of the core problems of present day Speech Recognition by using Fuzzy Mathematics.

T. V. Prasad, Sachin Lakra, G. Ramakrishna

This paper discusses the merits and demerits of crisp logic and fuzzy logic with respect to their applicability in intelligent response generation by a human being and by a robot. Intelligent systems must have the capability of taking decisions that are wise and handle situations intelligently. A direct relationship exists between the level of perfection in handling a situation and the level of completeness of the available knowledge or information or data required to handle the situation. The paper concludes that the use of crisp logic with complete knowledge leads to perfection in handling situations whereas fuzzy logic can handle situations imperfectly only. However, in the light of availability of incomplete knowledge fuzzy theory is more effective but may be disadvantageous as compared to crisp logic.

Sachin Lakra, T. V. Prasad, Deepak Sharma et al.

A Neural Network, in general, is not considered to be a good solver of mathematical and binary arithmetic problems. However, networks have been developed for such problems as the XOR circuit. This paper presents a technique for the implementation of the Half-adder circuit using the CoActive Neuro-Fuzzy Inference System (CANFIS) Model and attempts to solve the problem using the NeuroSolutions 5 Simulator. The paper gives the experimental results along with the interpretations and possible applications of the technique.

Sachin Lakra, T. V. Prasad, Shree Harsh Atrey et al.

This paper makes an attempt to analyze the Activeness of a Distributed Object Oriented Component Library and develops a software metric called Distributed Component Activeness Quotient which is defined as the degree of readiness of a DOOCL. The advantages of the DCAQ include a possible comparison between various DOOCLs leading to selection of the best DOOCL for use during the development task, and providing a measure for gauging the usefulness of the DOOCL as indicated by the value of the DCAQ. The disadvantage of the DCAQ is that it may have some error because of its subjective and random nature. The Stability of a DOOCL is another characteristic which is indicated by the DCAQ. The greater the value of the DCAQ, greater will be the stability of the corresponding DOOCL.

Sachin Lakra, T. V. Prasad, G. Ramakrishna

The paper presents a comparison of various soft computing techniques used for filtering and enhancing speech signals. The three major techniques that fall under soft computing are neural networks, fuzzy systems and genetic algorithms. Other hybrid techniques such as neuro-fuzzy systems are also available. In general, soft computing techniques have been experimentally observed to give far superior performance as compared to non-soft computing techniques in terms of robustness and accuracy.

Poonam Tanwar, T. V. Prasad, Dr. Kamlesh Datta

Knowledge representation (KR) and inference mechanism are most desirable thing to make the system intelligent. System is known to an intelligent if its intelligence is equivalent to the intelligence of human being for a particular domain or general. Because of incomplete ambiguous and uncertain information the task of making intelligent system is very difficult. The objective of this paper is to present the hybrid KR technique for making the system effective & Optimistic. The requirement for (effective & optimistic) is because the system must be able to reply the answer with a confidence of some factor. This paper also presents the comparison between various hybrid KR techniques with the proposed one.