Real Time Raga Detection and Analysis Using Computer

Department of Computer Applications, Cochin University of Science and Technology

A Study of Morphological Operators with Applications

The present work deals with the A study of morphological opertors with applications. Morphology is now a.necessary tool for engineers involved with imaging applications. Morphological operations have been viewed as filters the properties of which have been well studied (Heijmans, 1994). Another well-known class of non-linear filters is the class of rank order filters (Pitas and Venetsanopoulos, 1990). Soft morphological filters are a combination of morphological and weighted rank order filters (Koskinen, et al., 1991, Kuosmanen and Astola, 1995). They have been introduced to improve the behaviour of traditional morphological filters in noisy environments. The idea was to slightly relax the typical morphological definitions in such a way that a degree of robustness is achieved, while most of the desirable properties of typical morphological operations are maintained. Soft morphological filters are less sensitive to additive noise and to small variations in object shape than typical morphological filters. They can remove positive and negative impulse noise, preserving at the same time small details in images. Currently, Mathematical Morphology allows processing images to enhance fuzzy areas, segment objects, detect edges and analyze structures. The techniques developed for binary images are a major step forward in the application of this theory to gray level images. One of these techniques is based on fuzzy logic and on the theory of fuzzy sets.Fuzzy sets have proved to be strongly advantageous when representing in accuracies, not only regarding the spatial localization of objects in an image but also the membership of a certain pixel to a given class. Such inaccuracies are inherent to real images either because of the presence of indefinite limits between the structures or objects to be segmented within the image due to noisy acquisitions or directly because they are inherent to the image formation methods.

Secret Sharing Schemes Using Visual Cryptography

Secret sharing schemes allow a secret to be shared among a group of participants so that only qualified subsets of participants can recover the secret. A visual cryptography scheme (VCS) is a special kind of secret sharing scheme in which the secret to share consists of an image and the shares consist of xeroxed transparencies which are stacked to recover the shared image. In this thesis we have given the theoretical background of Secret Sharing Schemes and the historical development of the subject. We have included a few examples to improve the readability of the thesis. We have tried to maintain the rigor of the treatment of the subject. The limitations and disadvantages of the various forms secret sharing schemes are brought out. Several new schemes for both dealing and combining are included in the thesis. We have introduced a new number system, called, POB number system. Representation using POB number system has been presented. Algorithms for finding the POB number and POB value are given.We have also proved that the representation using POB number system is unique and is more efficient. Being a new system, there is much scope for further development in this area.

Re-engineering and Re-defining University Libraries in the context of modern Information and Communication Technologies: a study with special reference to the University Libraries in Kerala

Information and communication technologies are the tools that underpin the emerging “Knowledge Society”. Exchange of information or knowledge between people and through networks of people has always taken place. But the ICT has radically changed the magnitude of this exchange, and thus factors such as timeliness of information and information dissemination patterns have become more important than ever.Since information and knowledge are so vital for the all round human development, libraries and institutions that manage these resources are indeed invaluable. So, the Library and Information Centres have a key role in the acquisition, processing, preservation and dissemination of information and knowledge. ln the modern context, library is providing service based on different types of documents such as manuscripts, printed, digital, etc. At the same time, acquisition, access, process, service etc. of these resources have become complicated now than ever before. The lCT made instrumental to extend libraries beyond the physical walls of a building and providing assistance in navigating and analyzing tremendous amounts of knowledge with a variety of digital tools. Thus, modern libraries are increasingly being re-defined as places to get unrestricted access to information in many formats and from many sources.The research was conducted in the university libraries in Kerala State, India. lt was identified that even though the information resources are flooding world over and several technologies have emerged to manage the situation for providing effective services to its clientele, most of the university libraries in Kerala were unable to exploit these technologies at maximum level. Though the libraries have automated many of their functions, wide gap prevails between the possible services and provided services. There are many good examples world over in the application of lCTs in libraries for the maximization of services and many such libraries have adopted the principles of reengineering and re-defining as a management strategy. Hence this study was targeted to look into how effectively adopted the modern lCTs in our libraries for maximizing the efficiency of operations and services and whether the principles of re-engineering and- redefining can be applied towards this.Data‘ was collected from library users, viz; student as well as faculty users; library ,professionals and university librarians, using structured questionnaires. This has been .supplemented by-observation of working of the libraries, discussions and interviews with the different types of users and staff, review of literature, etc. Personal observation of the organization set up, management practices, functions, facilities, resources, utilization of information resources and facilities by the users, etc. of the university libraries in Kerala have been made. Statistical techniques like percentage, mean, weighted mean, standard deviation, correlation, trend analysis, etc. have been used to analyse data.All the libraries could exploit only a very few possibilities of modern lCTs and hence they could not achieve effective Universal Bibliographic Control and desired efficiency and effectiveness in services. Because of this, the users as well as professionals are dissatisfied. Functional effectiveness in acquisition, access and process of information resources in various formats, development and maintenance of OPAC and WebOPAC, digital document delivery to remote users, Web based clearing of library counter services and resources, development of full-text databases, digital libraries and institutional repositories, consortia based operations for e-journals and databases, user education and information literacy, professional development with stress on lCTs, network administration and website maintenance, marketing of information, etc. are major areas need special attention to improve the situation. Finance, knowledge level on ICTs among library staff, professional dynamism and leadership, vision and support of the administrators and policy makers, prevailing educational set up and social environment in the state, etc. are some of the major hurdles in reaping the maximum possibilities of lCTs by the university libraries in Kerala. The principles of Business Process Re-engineering are found suitable to effectively apply to re-structure and redefine the operations and service system of the libraries. Most of the conventional departments or divisions prevailing in the university libraries were functioning as watertight compartments and their existing management system was more rigid to adopt the principles of change management. Hence, a thorough re-structuring of the divisions was indicated. Consortia based activities and pooling and sharing of information resources was advocated to meet the varied needs of the users in the main campuses and off campuses of the universities, affiliated colleges and remote stations. A uniform staff policy similar to that prevailing in CSIR, DRDO, ISRO, etc. has been proposed by the study not only in the university libraries in kerala but for the entire country.Restructuring of Lis education,integrated and Planned development of school,college,research and public library systems,etc.were also justified for reaping maximum benefits of the modern ICTs.

Statistical Machine Learning Techniques for the Prediction of Learning Disabilities in School-Age Children

Learning Disability (LD) is a general term that describes specific kinds of learning problems. It is a neurological condition that affects a child's brain and impairs his ability to carry out one or many specific tasks. The learning disabled children are neither slow nor mentally retarded. This disorder can make it problematic for a child to learn as quickly or in the same way as some child who isn't affected by a learning disability. An affected child can have normal or above average intelligence. They may have difficulty paying attention, with reading or letter recognition, or with mathematics. It does not mean that children who have learning disabilities are less intelligent. In fact, many children who have learning disabilities are more intelligent than an average child. Learning disabilities vary from child to child. One child with LD may not have the same kind of learning problems as another child with LD. There is no cure for learning disabilities and they are life-long. However, children with LD can be high achievers and can be taught ways to get around the learning disability. In this research work, data mining using machine learning techniques are used to analyze the symptoms of LD, establish interrelationships between them and evaluate the relative importance of these symptoms. To increase the diagnostic accuracy of learning disability prediction, a knowledge based tool based on statistical machine learning or data mining techniques, with high accuracy,according to the knowledge obtained from the clinical information, is proposed. The basic idea of the developed knowledge based tool is to increase the accuracy of the learning disability assessment and reduce the time used for the same. Different statistical machine learning techniques in data mining are used in the study. Identifying the important parameters of LD prediction using the data mining techniques, identifying the hidden relationship between the symptoms of LD and estimating the relative significance of each symptoms of LD are also the parts of the objectives of this research work. The developed tool has many advantages compared to the traditional methods of using check lists in determination of learning disabilities. For improving the performance of various classifiers, we developed some preprocessing methods for the LD prediction system. A new system based on fuzzy and rough set models are also developed for LD prediction. Here also the importance of pre-processing is studied. A Graphical User Interface (GUI) is designed for developing an integrated knowledge based tool for prediction of LD as well as its degree. The designed tool stores the details of the children in the student database and retrieves their LD report as and when required. The present study undoubtedly proves the effectiveness of the tool developed based on various machine learning techniques. It also identifies the important parameters of LD and accurately predicts the learning disability in school age children. This thesis makes several major contributions in technical, general and social areas. The results are found very beneficial to the parents, teachers and the institutions. They are able to diagnose the child’s problem at an early stage and can go for the proper treatments/counseling at the correct time so as to avoid the academic and social losses.

lntemet utilization and academic activities of faculty members in the universities of Kerala : an analytical study

This thesis Entitled Internet Utilization and Academic Activities of Faculty Members in the Universities of kerala: an analytical study. Today, scientific research is throwing up new discoveries, inventions and vistas by the hour. We are witnessing a veritable knowledge explosion. It is important for members of university faculty members to keep abreast of it for giving up-t-date information to their students about the new development in the subject of their study. The internet is an invaluable tool for achieving it. Most of the universities have sufficient internet facility, but the accessibility to all the faculty members is not adequate. University Libraries also provides standard supplementary service in the internet area. This study indicates differential level of awareness and utilization of the internet services by the faculty members in the areas of teaching, research and publication. However the overall impression is that the awareness and utilization is inadequate. This point to the urgent need to devise programs and schemes to promote internet utilization among the faculty members. The suggestions indicate the key areas that deserve attention by policy makers and administrators. Thanks to the internet, every new development in every field of study is just a click away for faculty members, research scholars and students.

Document Image Segmentation and Compression using Artificial Neural Networks and Evolutionary Methods

The work is intended to study the following important aspects of document image processing and develop new methods. (1) Segmentation ofdocument images using adaptive interval valued neuro-fuzzy method. (2) Improving the segmentation procedure using Simulated Annealing technique. (3) Development of optimized compression algorithms using Genetic Algorithm and parallel Genetic Algorithm (4) Feature extraction of document images (5) Development of IV fuzzy rules. This work also helps for feature extraction and foreground and background identification. The proposed work incorporates Evolutionary and hybrid methods for segmentation and compression of document images. A study of different neural networks used in image processing, the study of developments in the area of fuzzy logic etc is carried out in this work

“Improved Feature Extraction and Classification Techniques for Multispectral Brain Magnetic Resonance Images”

Magnetic Resonance Imaging (MRI) is a multi sequence medical imaging technique in which stacks of images are acquired with different tissue contrasts. Simultaneous observation and quantitative analysis of normal brain tissues and small abnormalities from these large numbers of different sequences is a great challenge in clinical applications. Multispectral MRI analysis can simplify the job considerably by combining unlimited number of available co-registered sequences in a single suite. However, poor performance of the multispectral system with conventional image classification and segmentation methods makes it inappropriate for clinical analysis. Recent works in multispectral brain MRI analysis attempted to resolve this issue by improved feature extraction approaches, such as transform based methods, fuzzy approaches, algebraic techniques and so forth. Transform based feature extraction methods like Independent Component Analysis (ICA) and its extensions have been effectively used in recent studies to improve the performance of multispectral brain MRI analysis. However, these global transforms were found to be inefficient and inconsistent in identifying less frequently occurred features like small lesions, from large amount of MR data. The present thesis focuses on the improvement in ICA based feature extraction techniques to enhance the performance of multispectral brain MRI analysis. Methods using spectral clustering and wavelet transforms are proposed to resolve the inefficiency of ICA in identifying small abnormalities, and problems due to ICA over-completeness. Effectiveness of the new methods in brain tissue classification and segmentation is confirmed by a detailed quantitative and qualitative analysis with synthetic and clinical, normal and abnormal, data. In comparison to conventional classification techniques, proposed algorithms provide better performance in classification of normal brain tissues and significant small abnormalities.

classification and content based retrieval of digital mammograms and placental sonograms

Image processing has been a challenging and multidisciplinary research area since decades with continuing improvements in its various branches especially Medical Imaging. The healthcare industry was very much benefited with the advances in Image Processing techniques for the efficient management of large volumes of clinical data. The popularity and growth of Image Processing field attracts researchers from many disciplines including Computer Science and Medical Science due to its applicability to the real world. In the meantime, Computer Science is becoming an important driving force for the further development of Medical Sciences. The objective of this study is to make use of the basic concepts in Medical Image Processing and develop methods and tools for clinicians’ assistance. This work is motivated from clinical applications of digital mammograms and placental sonograms, and uses real medical images for proposing a method intended to assist radiologists in the diagnostic process. The study consists of two domains of Pattern recognition, Classification and Content Based Retrieval. Mammogram images of breast cancer patients and placental images are used for this study. Cancer is a disaster to human race. The accuracy in characterizing images using simplified user friendly Computer Aided Diagnosis techniques helps radiologists in detecting cancers at an early stage. Breast cancer which accounts for the major cause of cancer death in women can be fully cured if detected at an early stage. Studies relating to placental characteristics and abnormalities are important in foetal monitoring. The diagnostic variability in sonographic examination of placenta can be overlooked by detailed placental texture analysis by focusing on placental grading. The work aims on early breast cancer detection and placental maturity analysis. This dissertation is a stepping stone in combing various application domains of healthcare and technology.

A Comparative Study of Convective Parameterization Schemes in WRF-NMM Model

Severe local storms, including tornadoes, damaging hail and wind gusts, frequently occur over the eastern and northeastern states of India during the pre-monsoon season (March-May). Forecasting thunderstorms is one of the most difficult tasks in weather prediction, due to their rather small spatial and temporal extension and the inherent non-linearity of their dynamics and physics. In this paper, sensitivity experiments are conducted with the WRF-NMM model to test the impact of convective parameterization schemes on simulating severe thunderstorms that occurred over Kolkata on 20 May 2006 and 21 May 2007 and validated the model results with observation. In addition, a simulation without convective parameterization scheme was performed for each case to determine if the model could simulate the convection explicitly. A statistical analysis based on mean absolute error, root mean square error and correlation coefficient is performed for comparisons between the simulated and observed data with different convective schemes. This study shows that the prediction of thunderstorm affected parameters is sensitive to convective schemes. The Grell-Devenyi cloud ensemble convective scheme is well simulated the thunderstorm activities in terms of time, intensity and the region of occurrence of the events as compared to other convective schemes and also explicit scheme

A Data Mining Approach for the Identification of Adverse Drug Events (ADE) resulting from Drug-Drug Interactions (DDI) to improve pharmacovigilance

In the current study, epidemiology study is done by means of literature survey in groups identified to be at higher potential for DDIs as well as in other cases to explore patterns of DDIs and the factors affecting them. The structure of the FDA Adverse Event Reporting System (FAERS) database is studied and analyzed in detail to identify issues and challenges in data mining the drug-drug interactions. The necessary pre-processing algorithms are developed based on the analysis and the Apriori algorithm is modified to suit the process. Finally, the modules are integrated into a tool to identify DDIs. The results are compared using standard drug interaction database for validation. 31% of the associations obtained were identified to be new and the match with existing interactions was 69%. This match clearly indicates the validity of the methodology and its applicability to similar databases. Formulation of the results using the generic names expanded the relevance of the results to a global scale. The global applicability helps the health care professionals worldwide to observe caution during various stages of drug administration thus considerably enhancing pharmacovigilance

Automated Transcription System for Malayalam Language

Malayalam is one of the 22 scheduled languages in India with more than 130 million speakers. This paper presents a report on the development of a speaker independent, continuous transcription system for Malayalam. The system employs Hidden Markov Model (HMM) for acoustic modeling and Mel Frequency Cepstral Coefficient (MFCC) for feature extraction. It is trained with 21 male and female speakers in the age group ranging from 20 to 40 years. The system obtained a word recognition accuracy of 87.4% and a sentence recognition accuracy of 84%, when tested with a set of continuous speech data.

Pattern Analysis Techniques for the Recognition of Unconstrained Handwritten Malayalam Character Images

The objective of the study is to develop a hand written character recognition system that could recognisze all the characters in the mordern script of malayalam language at a high recognition rate

Matrix based Key Generation to Enhance Key Avalanche in Advanced Encryption Standard

In symmetric block ciphers, substitution and diffusion operations are performed in multiple rounds using sub-keys generated from a key generation procedure called key schedule. The key schedule plays a very important role in deciding the security of block ciphers. In this paper we propose a complex key generation procedure, based on matrix manipulations, which could be introduced in symmetric ciphers. The proposed key generation procedure offers two advantages. First, the procedure is simple to implement and has complexity in determining the sub-keys through crypt analysis. Secondly, the procedure produces a strong avalanche effect making many bits in the output block of a cipher to undergo changes with one bit change in the secret key. As a case study, matrix based key generation procedure has been introduced in Advanced Encryption Standard (AES) by replacing the existing key schedule of AES. The key avalanche and differential key propagation produced in AES have been observed. The paper describes the matrix based key generation procedure and the enhanced key avalanche and differential key propagation produced in AES. It has been shown that, the key avalanche effect and differential key propagation characteristics of AES have improved by replacing the AES key schedule with the Matrix based key generation procedure

Measuring the Maturity of Open Source Software for Digital Libraries: a Case Study of DSpace

The assessment of maturity of software is an important area in the general software sector. The field of OSS also applies various models to measure software maturity. However, measuring maturity of OSS being used for several applications in libraries is an area left with no research so far. This study has attempted to fill the research gap. Measuring maturity of software contributes knowledge on its sustainability over the long term. Maturity of software is one of the factors that positively influence adoption. The investigator measured the maturity of DSpace software using Woods and Guliani‟s Open Source Maturity Model-2005. The present study is significant as it addresses the aspects of maturity of OSS for libraries and fills the research gap on the area. In this sense the study opens new avenues to the field of library and information science by providing an additional tool for librarians in the selection and adoption of OSS. Measuring maturity brings in-depth knowledge on an OSS which will contribute towards the perceived usefulness and perceived ease of use as explained in the Technology Acceptance Model theory.