Computational linguistic helps in understanding the meaning of sentence given by an individual as per situation. Our work of Descriptive examination comes under experiential cognition as we are modeling & finding correct meaning of answer given by any individual. In this paper we have explained how we used HMM to reduce the complexity of variation in answer and shown knowledge representational method for representing the answer. In our work even the context of the question is given a real importance & thus our representation has impact of Chomsky context sensitive grammar.

In this paper we show some results on Epipolar Geometry applying on various images using MATLAB. The Fundamental matrix is give to the depth information on the images we get the critical view of images that can be transfer in to the Grayscale image in to binary image. Matlab is an ideal tool for simulating digital communication system, its gates easy scripting language and excellent data visualization capabilities. Images breaking them up in to their bit- planes images are collecting their pixel values the grey value of each image of an 8- bit image an 8- bit binary word. The binary image will have only given the two values 0 and 1 and hence the image shows best clarity results is fine. The Epipolar geometry is a key point in computer vision and the fundamental matrix estimation, computer vision and the fundamental matrix estimation is the unique way to compute it.

In this paper we are collecting 100 Devnagri numerals from 10 different persons belonging to three different states of India. The data collected in a plane paper is scanned in the form of a bit map image. The collected data has to undergo the preprocessing steps first and then some morphological operations like opening, edge detection, dilation, hole filling and numerals detection are performed. After numerals detection the boundary of the numerals in row, are calculated and stored in the database. Calculating the total number of numerals in a row, the individual width and height of each numeral are measured. The features can be extracted by three steps; first the extreme coordinates of the numerals can be measured, then grabbing the numerals into grids and finally numerals digitization. Digitized numerals are then further trained with multilayer neural network. The proposed research work gives us 100 % accuracy and hence recognized all 100 numerals correctly.

A novel multi resolution watermarking method has been introduced for digital images. The proposed method is based on 2-level discrete wavelet transform (DWT) and alpha blending technique. In this technique the insertion and extraction of the watermark in the grayscale cover image is found to be simpler than other transform techniques. We have successfully implemented the digital watermarking technique on digital images based on 2-level discrete wavelet transform and compared the performance of proposed method with 1-level DWT by using statistical parameters peak signal to noise ratio (PSNR) and mean square error (MSE).

In this paper, we present a method for single channel noise reduction of heart sound recordings. Multiple noise sources, such as lung sounds, muscle contraction and background noise can contaminate the heart sound collection making subsequent analysis difficult. This method uses a “decision-directed” approach to estimate the noise without the need for a separate reference signal. The wavelet de-noising method based on three thresholding functions is used for heart sound signals de-noising; soft-thresholding and hard-thresholding functions are traditional and an improved novel thresholding function with double variables parameters is novel. The critical point of the wavelet based de-nosing of signals is the choice of the wavelet and thresholds. The change of wavelet can give different results. It can overcome the shortcoming discontinuous function in hard-thresholding and also can eliminate the permanent bias in soft-thresholding. We have developed the function this denoises the PCG signal by different wavelets and results the selection of suitable wavelet that is best for a complex signal.

Mango fruit is one of the most popular, nutritionally rich fruit with unique flavor, fragrance, taste, and heath promoting qualities making it a common ingredient in new functional fruits often called “super fruits”. The Edge detection process detects outlines of mangos, mango quality evaluation and mango types, counting mangos, check Inflorescence quality. An edge is the boundary between mangos and the background. Simulink is a simulation modeling and design tool and GUI based diagram environment. The Simulink based customizable framework is designed for rapid simulation, implementation, and verification of video processing systems. In this work the comparative analysis of various mangos video edge detection methods is like Sobel, Prewitt, and Canny is presented.

Script identification is required for a multilingual OCR system. In this paper, we present a novel and efficient technique for Kannada/English script identification. The proposed approach is based upon the analysis of Kannada pages and English pages. Experimental results demonstrate that the proposed techniques are capable of identifying Kannada/English scripts from the real handwritten Kannada and English pages.

Spoken language is the most natural way used by human to communicate information. Speech signal conveys linguistic information as well as speaker information (e.g. Emotional, regional and physiological characteristics). Such human ability has inspired many researches to understand production for developing the system that automatically process the richness of information in speech, this speech technology has many applications to find out “who is speaking” means speaker recognition system. This paper gives an overview of major techniques developed in each stage of speaker recognition. This paper has a list of techniques along with their results, merits and demerits. This also includes comparative study of different techniques, which are helping us to choose the technique for developing different language speaker recognition system like Marathi, Hindi and English. Time alignment of different utterances is a serious problem for distance measures and small shift would lead to incorrect identification. Dynamic time warping (DTW) is effective method. Vector quantization (VQ) is the classical quantization technique from signal processing. HMM is used for pattern matching. This paper shows the comparative result of PLC, PLPC and MFCC. MFCC have 73.62% is better result for Marathi language and 64.69% for Hindi language than PLC and PLPC techniques.

Telecommunication industry believes that the video-on-demand market will expand heavily in the near future. The service providers are interested in the deployment of video-on-demand (VoD) systems with large numbers of videos. As the number of videos and customers increases at a VoD system, two problems are faced. The first problem is the manual video allocation of multiple copies of videos to the disks, called video placement. The second problem is where to forward a newly arrived request to play a video so that the dynamic loads amongst disks or arrays of disks of video servers are balanced. Video-on-demand (VoD) has become one of the essential parts in telecommunication industry and the most crucial service of the broadband network applications. An important issue in the design and operation of the VoD system is to distribute the movie traffic load evenly across the disks in the system. In this paper, we provide a survey on the existing Load Balancing architectures, their performance and identify their tradeoffs, based on the analysis of an existing deployment of a Video on demand service.

This paper focuses on number recognition from feature extracted using Electroencephalogram (EEG) readings. EEG signals were recorded at Department of Computer Science and IT, Dr. B. A. M. University, India, from 6 volunteer subjects. A random number generator Graphics User Interface was developed in VB7. It is used to display numbers from 0 to 9 which worked as Visually Evoked Potential (VEP) for the experiment. The database of 6 male right-handed subjects in the age group of (20-25) was created and used as training data set. By exposing the same set of subjects to the GUI again, new EEG recordings were collected. This new set of EEG readings was considered as testing data set. The testing data was searched and matched with trained data set for recognizing pattern of each number. The experiments were conducted by concentrating on Beta signal and Linear discriminate analysis (LDA) was implemented to classify the data. The recognition rate observed was different for different numbers. Overall recognition rate observed was 68.33%. It is also seen that there exist a unique pattern for each number.

Gender is an important and most diffrentiative characteristic of a speech. Gender information can also be used to improve the performance of speech and speaker recognition systems. Automatic gender classification is a technique that aims to determine the sex of the speaker through speech signal analysis. However with the increase in biometric security application, practical application of gender identification increased the many fold .The need of gender identification from speech arises several situation such as sorting telephonic call. Many methods of gender identification have been proposed in literature. We implemented the gender classification method and gender dependant feature such as pitch, roll of and energy in combination with MFCC. The clustered approach of above said parameter is implemented using SVM. We also present the experimental result of the proposed approach .It is observed that the accuracy of gender identification system is improved on the basis of size of codebook. The high accuracy is got at 25 codebook size with greater time slice. The accuracy of system tested with respective to gender and age .The efficient recognition rate of 95% is achieved in the age group of 25-30.

Software Reliability is defined as the probability of free-failure operation for a specified period of time in a specified environment. Software Reliability Growth models (SRGM) have been developed to estimate software reliability measures such as number of remaining faults, software failure rate and Software Reliability. Imperfect debugging models are considered in these models. However, most SRGM assume that faults will eventually be removed. Fault removal efficiency in the existing models is limited. This paper aims to incorporate the fault removal efficiency in software reliability growth modeling. In this paper imperfect debugging is considered in the sense that new faults can be introduced into the software during debugging and the detected faults may not be removed completely.

When we use web service, we should add it in the web reference and then call its methods statically. This way of calling web services has lots of limitations. In order to take maximum advantage of the flexibility and power of Web services, the user must be able to dynamically discover and invoke a Web service. We need to dynamically discover and invoke the service because the information returned from web services can be used by heterogeneous applications which are executed on different machines. As our business world is dynamic and heterogeneous, a client often needs to invoke an unfamiliar web service at run time. However, current web services technology pays little attention to this issue. In this paper, we propose a framework for a client to dynamically invoke web services. The framework can increase the use and reliability of web services invocation in a dynamic, heterogeneous environment. Web Service has been widely accepted by industry. How to find and integrate existing Web Service is a crucial work. Client finds Web Service from UDDI Registry and invokes it directly as described in a contract, web service description language, WSDL. It is difficult for an enterprise user to dynamically invoke the most appropriate Web Service. This paper briefly introduces Service-Oriented Architecture and discusses advantages and disadvantages of UDDI, then puts forward a dynamic Web Service framework that extends the SOA.

The main objective is to develop an automated system that would help in analytics the website performance efficiently. Web analytics will register the organizations or the websites & maintain their information. It will also provide the real time information about the number of visitors, visitors from a certain country etc. The software will provide the breakup of the user’s interest in the organization’s website. If the popularity is too low, then it would provide a template having the suggestions to improve the popularity. The main concept here is that a piece of code is placed on your webpage which enables us to analyze and monitor all the visitors to the website at run-time. The system takes as input the users login when he visits the website. Every website is provided with a piece of code and a log space. You put the piece of code on the webpage, and every time the visitor visits the webpage the code sends the valuable information about the visitor back to the log. Web tracker organizes this information into charts and lists to make your analysis easier. Web analytics is the practice of measuring, collecting, analyzing and reporting on Internet data for the purposes of understanding how a web site is used by its audience and how to optimize its usage. The study of visitor, navigation, and traffic patterns to determine the success of a given web site. Web Analytics does not purely focus on the amount of traffic which might only be helpful in evaluating your bandwidth usage and server’s capabilities. Instead it focuses on in-depth comparison of available visitor data, referral data, and site navigation patterns as well as being able to tell us the amount of traffic we receive over any specified period of time. Modern web analytics tools collect vast amounts of information about website visitors; these reporting systems make it difficult to identify trends in data due to the number of reports available. By developing a system that logically presents automated analysis based on trends and patterns, web analytics users will be able to implement improvements to their websites. In order to develop the web analytics dashboard and analysis system, data will be collected by a third party web analytics tool. Research will be undertaken into existing web analytics dashboards used to visualize data. The paper will consider the collection, use and display of data and how these elements can be automated. Major need for developing such a project is to create a general template which can be used by any website owner to check performance of his website. If website is very popular, website owner may decide to assign efficient servers which can handle more load. In some organizations, it may be necessary to view from which region more users are accessing the website. The solution to all these problems is obtained by web analytics.

Wireless Sensor Network (WSN) is an emerging technology that shows great promise for various futuristic applications both for mass public and military. A wireless sensor node consists of sensing, computing, communication, actuation, and power components. These sensing devices have the opportunity of collaboration amongst themselves to improve the target localization and tracking accuracies. Distributed data fusion architecture provides a collaborative tracking framework. Due to the present energy constraints of these small sensing and wireless communicating devices, a common trend is to put some of them into a dormant state. The problem of obtaining a minimum cost topology for a wireless sensor network given matrices specifying the cost of links between all pairs of nodes and the internodes requirements is considered. This paper discusses the optimizing strategy for routing and selecting optimum number of nodes using MENTOR algorithm. In this we find the path with minimum cost between numbers of nodes in the network. It is closely related to decision on what speed links to use and how to route traffic through the network.

We have proposed a recommender system UseLibrary, helping users of library to get proper journal articles, books and other library resources. Profile generation & maintenance and profile exploitation are two main tasks to develop the system. Currently in this system, dataset consists of 790 books and journal articles in PDF and TXT format. System learns the profiles of users and then provides recommendations. Information filtering is required for providing recommendations. Similarity between interest of user and available resources can be computed by different approaches. In this paper, we have compared two approaches, cosine similarity measure and ontology based measure. It is found that use of ontology based measure outperforms cosine similarity measure.

This paper address review of new methodologies for postmortem Identification Using dental records that means the Automated Dental Identification System (ADIS) can be used by Law enforcement agencies to locate missing persons also to identify Victims in Mass disasters (e.g. earthquakes, Tsunami, airplane Crash etc.) Using databases of dental X-rays. In PM identification, forensic odontologists rely mainly on dental radiographs, among other types of records (e.g., oral photographs, denture models, and CAT scans) to compare the morphology of dental restorations of unidentified individuals to choose those of candidates in the missing persons file. This paper reviews the new methods & techniques in which Identification is carried out by Comparing post Mortem (PM) images with Ante mortem (AM) dental records of missing people to find similar records.

A multimodal biometric system combines the different biometric traits and provides better recognition performance as compared to the systems based on single biometric trait or modality. In multimodal biometric system the fusion of the information can be done at various levels, but due to the ease in combining and accessing the scores generated by different matchers, the most common approach is the integration at the matching score level. Before combining, the scores should alter into a common domain, since different matchers generate heterogeneous scores. In this paper, we have studied performance of a single fast normalized cross-correlation matcher and simple sum-rule fusion technique based on face and signature traits of a user. The experiments conducted on a database of 17 users indicate that simple sum of score fusion method results in better recognition performance than using single face or single signature based biometric system. However, experiments also reveal that the normalized cross-correlation based matcher gives better results, highlighting the need for a robust and efficient feature extraction technique.

Abstract- In every enterprise, data leakage is very serious problem faced by it. An owner of enterprise has given sensitive data to its employee but in most of the situation employee leak the data. That leak data found in unauthorized place such as on the web of comparator enterprise or on laptop of employee of comparator enterprise or the owner of comparators laptop. It is either observed or sometimes not observed by owner. Leak data may be source code or design specifications, price lists, intellectual property and copy rights data, trade secrets, forecasts and budgets. In this case the data leaked out it leaves the company goes in unprotected the influence of the corporation. This uncontrolled data leakage puts business in a backward position. To find the solution on this problem we develop two models. First, when any employee of enterprise access sensitive data without the consent of owner in that case ,we developed data watcher model to identifying data leaker and suppose employee given data outside the enterprise for that we devolved second model for assessing the “guilt” of agents. guilt model are used to improve the probability of identifying guilty third parties. For implementing this system, we used SSBT’S COET, Bambhori, Jalgaon college database. In this system we consider, data owner is college management called as distributor and other employee is called as agents. For that we considered two condition sample or explicit condition because agents want data in sample or condition.

The search of an image in image database using keywords is made powerful due to automatic image annotation. In this paper, an automatic image annotation using K- Nearest Neighbor (K-NN) is presented. The categorization based approach is presented for annotation. Images are first segmented using k-means clustering and then processed to form feature vector. Local features are extracted from the regions of the image. The feature vectors are experimented using K-NN. Our system is validated using ten categories from the COREL images. It is observed that in multiple instance learning using K-NN with color and texture features outperforms for all type of feature vectors.

IPv6 is of considerable importance to businesses, consumers, and network access providers of all sizes. IPv6 is designed to improve upon IPv4's scalability, security, ease-of-configuration, and network management; these issues are central to the competitiveness and performance of all types of network-dependent businesses. IPv6 aims to preserve existing investment as much as possible. End users, industry executives, network administrators, protocol engineers, and many others will benefit from understanding the ways that IPv6 will affect future internetworking and distributed computing application like cloud computing ,Grid computing etc. Every individual is to be identified as the requirement of today’s Science and Technology. In this paper, we present a platform providing a problem solving environment for patients or persons among multiple application domains of Grid computing especially in medical and scientific study, using the collaborative relationship and also fostering interoperability in Grid infrastructure. The proposed work is based on IPv6 address scheme providing seamless, secure, and intuitive access to distributed Grid resources.

This paper presents an approach for recognition of offline handwritten isolated Urdu character based on Invariant Moments. Handwritten Urdu character recognition is lagging behind due to segmentation dilemma and complexity of Urdu letter writing. An attempt is made to apply Moment Invariant technique followed by Primary and secondary component separation. The Urdu letters were grouped into single component and multi-component characters. If letter is multi-component then Secondary component were separated from primary component. SVM is adopted for classification and position of secondary component (Above, Below and middle) is considered for recognition. For each of 46 characters 200 image samples were used for training and 600 for testing respectively. In this manner overall 36800 handwritten characters were used to apply the technique. Overall performance rate is found to be 93.59% for all offline handwritten isolated Urdu characters. It is possible to enhance the accuracy of system by combining more structural and statistical features.

This paper presents the denoising technique based on spectral subtraction for speech synthesis of the Marathi numerals. Numerals are recorded through mice and normalized the signals with PRAAT tools. Different form of speech signals were analyzed by added noise in original speech signals. The voice activity detection (VAD) algorithm estimate the noise spectrum of original speech signal. Spectral Subtraction technique is adopted to reduce the noise. It exploits the ability of actively unwanted signals of speech. Spectral Subtraction method has reduced noise and improved the quality of speech signals. This paper concentrates on the application of quality speech signals for speech synthesis and the results found to be satisfactory.

SMS based information retrieval is one of the challenging research driven application of information and communication technology. “A flexible natural language query in the form of an SMS could also be answered by applying information retrieval theory and practices”, is our research theme. In the initial phase, we have formulated a preparatory experimentation on SMS based Marathi query to retrieve Marathi literature documents. This paper presents the details about the ITRANS Marathi literature documents followed by the description of an appropriate Vector Space Model (VSM) to represent the documents and the queries. We designed a GUI and asked a group of hundred students to formulate an SMS query for 30 different questions in order to obtain user specific variations among typed in queries. A collection of sample Marathi documents in the ITRANS form and a set of acquired queries is processed using the system developed to retrieve relevant documents. The system uses the Cosine Similarity to rank the documents according to the relevance for each selected query. Experimental results of the system are presented in the paper. This is the first such type information retrieval model for the ITRANS Marathi documents.