Impact of Information Communication Technology (ICT) on Professional Development and Educational Needs of Library Professionals in the Universities of Kerala

The shift from print to digital information has a high impact on all components of the academic library system in India especially the users, services and the staff. Though information is considered as an important resource, the use of ICT tools to collect and disseminate information has been in a slow pace in majority of the University libraries This may be due to various factors like insufficient funds, inadequate staff trained in handling computers and software packages, administrative concerns etc. In Kerala, automation has been initiated in almost all University libraries using library automation software and is under different stages of completion. There are not much studies conducted about the effects of information communication technologies on the professional activities of library professionals in the universities in Kerala. It is important to evaluate whether progress in ICT has had any impact on the library profession in these highest educational institutions. The aim of the study is to assess whether the developments in information communication technologies have any influence on the library professionals’ professional development, and the need for further education and training in the profession and evaluate their skills in handling developments in ICT. The total population of the study is 252 including the permanently employed professional library staff in central libraries and departmental libraries in the main campuses of the universities under study. This is almost a census study of the defined population of users. The questionnaire method was adopted for collection of data for this study, supplemented by interviews of Librarians to gather additional information. Library Professionals have a positive approach towards ICT applications and services in Libraries, but majority do not have the opportunities to develop their skills and competencies in their work environment. To develop competitive personnel in a technologically advanced world, high priority must be given to develop competence in ICT applications, library management and soft skills in library professionals, by the University administrators and Library associations. Library science schools and teaching departments across the country have to take significant steps to revise library science curriculum, and incorporate significant changes to achieve the demands and challenges of library science profession.

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.

A study of the information seeking bebavior of science and technology teachers and researchers of Cocbin University of Science and Technology and University of Kerala in the cbanged library environment

Information communication technology (IC T) has invariably brought about fundamental changes in the way in which libraries gather. preserve and disseminate information. The study was carried out with an aim to estimate and compare the information seeking behaviour (ISB) of the academics of two prominent universities of Kerala in the context of advancements achieved through ICT. The study was motivated by the fast changing scenario of libraries with the proliferation of many high tech products and services. The main purpose of the study was to identify the chief source of information of the academics, and also to examine academics preference upon the form and format of information source. The study also tries to estimate the adequacy of the resources and services currently provided by the libraries.The questionnaire was the central instrument for data collection. An almost census method was adopted for data collection engaging various methods and tools for eliciting data.The total population of the study was 957, out of which questionnaire was distributed to 859 academics. 646 academics responded to the survey, of which 564 of them were sound responses. Data was coded and analysed using Statistical Package for Social Sciences (SPSS) software and also with the help of Microsofl Excel package. Various statistical techniques were engaged to analyse data. A paradigm shift is evident by the fact that academies push themselves towards information in internet i.e. they prefer electronic source to traditional source and the very shift is coupled itself with e-seeking of information. The study reveals that ISB of the academics is influenced priman'ly by personal factors and comparative analysis shows that the ISB ofthc academics is similar in both universities. The productivity of the academics was tested to dig up any relation with respect to their ISB, and it is found that productivity of the academics is extensively related with their ISB. Study also reveals that the users ofthe library are satisfied with the services provided but not with the sources and in conjunction, study also recommends ways and means to improve the existing library system.

Marketing of Library Services in an Academic Environment

Marketing of information services is now an important goal of librarians all over the ~orld t? attract mor~ users to the libr~ry. thereby promoting user satisfaction. Marketing IS considered ~s ~n Integr~1 part of libraries and information centres mainly due to the developments In information t.echnology, information explosion, and declining library budgets. Kotler defines marketing as the "analysis, planning, implementation and control o~ carefully formulated programs designed to bring about voluntary exchanges of values WIth target markets fo~ the ~~rpos~ of~chievingorganizational objectives". Organizations suc.h as museums, unrversittes, libraries, and charities need to market their causes and their products to gain. political and social support as well as economic support (Kotler, 1995). In the marketing world people are now migrating from the traditional Four P ~lodelto th~ S~VE mode! (Alt~ns~n, 2013). According to the SAVE model, marketing III an orgarusanon must grve pnonty to 'Solutions' instead of the features or functions of~he.'Product" Similarily it is to focus on 'Access', instead of ,Place'; 'Value' instead of Price" so that the benefits are more stressed, rather than production costs. Instead of :Proliloti.on', marketi~g has. to conc~ntrate on 'Educating' the customers, providing lJlfo~mahol~ about t~eJr specific req~lrements, instead of relying on advertising, public rel~tlons, direct selling etc. From a library point ofview, to ensure maximum utilization of library ~ervices there is an increasing need for definite marketing plans to exploit the techn.ologlcal dcvelop",len~s so ~s to entice the users. By anticipating their changing needs and ~y co.mmulllcatl~g WIth them it should be possible to devise strategies to present various library services and products in a perceptive style.

Syntactic Based Machine Translation from English to Malayalam

Due to the emergence of multiple language support on the Internet, machine translation (MT) technologies are indispensable to the communication between speakers using different languages. Recent research works have started to explore tree-based machine translation systems with syntactical and morphological information. This work aims the development of Syntactic Based Machine Translation from English to Malayalam by adding different case information during translation. The system identifies general rules for various sentence patterns in English. These rules are generated using the Parts Of Speech (POS) tag information of the texts. Word Reordering based on the Syntax Tree is used to improve the translation quality of the system. The system used Bilingual English –Malayalam dictionary for translation.

A Framework of Statistical Machine Translator from English to Malayalam

In this paper we describe the methodology and the structural design of a system that translates English into Malayalam using statistical models. A monolingual Malayalam corpus and a bilingual English/Malayalam corpus are the main resource in building this Statistical Machine Translator. Training strategy adopted has been enhanced by PoS tagging which helps to get rid of the insignificant alignments. Moreover, incorporating units like suffix separator and the stop word eliminator has proven to be effective in bringing about better training results. In the decoder, order conversion rules are applied to reduce the structural difference between the language pair. The quality of statistical outcome of the decoder is further improved by applying mending rules. Experiments conducted on a sample corpus have generated reasonably good Malayalam translations and the results are verified with F measure, BLEU and WER evaluation metrics

Handling OOV Words in Phrase-Based Statistical Machine Translation for Malayalam

Statistical Machine Translation (SMT) is one of the potential applications in the field of Natural Language Processing. The translation process in SMT is carried out by acquiring translation rules automatically from the parallel corpora. However, for many language pairs (e.g. Malayalam- English), they are available only in very limited quantities. Therefore, for these language pairs a huge portion of phrases encountered at run-time will be unknown. This paper focuses on methods for handling such out-of-vocabulary (OOV) words in Malayalam that cannot be translated to English using conventional phrase-based statistical machine translation systems. The OOV words in the source sentence are pre-processed to obtain the root word and its suffix. Different inflected forms of the OOV root are generated and a match is looked up for the word variants in the phrase translation table of the translation model. A Vocabulary filter is used to choose the best among the translations of these word variants by finding the unigram count. A match for the OOV suffix is also looked up in the phrase entries and the target translations are filtered out. Structuring of the filtered phrases is done and SMT translation model is extended by adding OOV with its new phrase translations. By the results of the manual evaluation done it is observed that amount of OOV words in the input has been reduced considerably

Extension schemes for the Alignment Model of English-Malayalam Statistical Machine Translator

In Statistical Machine Translation from English to Malayalam, an unseen English sentence is translated into its equivalent Malayalam sentence using statistical models. A parallel corpus of English-Malayalam is used in the training phase. Word to word alignments has to be set among the sentence pairs of the source and target language before subjecting them for training. This paper deals with certain techniques which can be adopted for improving the alignment model of SMT. Methods to incorporate the parts of speech information into the bilingual corpus has resulted in eliminating many of the insignificant alignments. Also identifying the name entities and cognates present in the sentence pairs has proved to be advantageous while setting up the alignments. Presence of Malayalam words with predictable translations has also contributed in reducing the insignificant alignments. Moreover, reduction of the unwanted alignments has brought in better training results. Experiments conducted on a sample corpus have generated reasonably good Malayalam translations and the results are verified with F measure, BLEU and WER evaluation metrics.

Techniques to Improve the word alignments in Statistical Machine Translation from English to Malayalam

In Statistical Machine Translation from English to Malayalam, an unseen English sentence is translated into its equivalent Malayalam translation using statistical models like translation model, language model and a decoder. A parallel corpus of English-Malayalam is used in the training phase. Word to word alignments has to be set up among the sentence pairs of the source and target language before subjecting them for training. This paper is deals with the techniques which can be adopted for improving the alignment model of SMT. Incorporating the parts of speech information into the bilingual corpus has eliminated many of the insignificant alignments. Also identifying the name entities and cognates present in the sentence pairs has proved to be advantageous while setting up the alignments. Moreover, reduction of the unwanted alignments has brought in better training results. Experiments conducted on a sample corpus have generated reasonably good Malayalam translations and the results are verified with F measure, BLEU and WER evaluation metrics

Unconstrained Handwritten Malayalam Character Recognition using Wavelet Transform and Support vector Machine Classifier

This paper presents the application of wavelet processing in the domain of handwritten character recognition. To attain high recognition rate, robust feature extractors and powerful classifiers that are invariant to degree of variability of human writing are needed. The proposed scheme consists of two stages: a feature extraction stage, which is based on Haar wavelet transform and a classification stage that uses support vector machine classifier. Experimental results show that the proposed method is effective

Using Neural Network Classifier Support Vector Machine Regression for the prediction of Melting Point of Drug – like compounds

In our study we use a kernel based classification technique, Support Vector Machine Regression for predicting the Melting Point of Drug – like compounds in terms of Topological Descriptors, Topological Charge Indices, Connectivity Indices and 2D Auto Correlations. The Machine Learning model was designed, trained and tested using a dataset of 100 compounds and it was found that an SVMReg model with RBF Kernel could predict the Melting Point with a mean absolute error 15.5854 and Root Mean Squared Error 19.7576

Impact of ICT on Library and Information Science: Major Shifts and Practices in CUSAT Central Library

Information is knowledge, facts or data. For the purpose of enabling the users to assimilate information, it should be repacked. Knowledge becomes information when it is externalized i.e. put in to the process of communication. The effectiveness of communication technology depends how well it provides its clients with information rapidly, economically and authentically. A large number of ICT enabled services including OPAC; e-resources etc. are available in the university library. Studies have been done to find the impact of ICT on different sections of CUSAT library by observing the activities of different sections; discussions with colleagues and visitors; and analyzing the entries in the library records. The results of the studies are presented here in the form of a paper.

Professional Development of Academic Library Professionals in Kerala

The paper aims to bring out the problems and prospects of the professional development opportunities of academic library professionals in the Universities in Kerala. The study is a part of research undertaken to survey the professional development activities and educational needs of library professionals in the major Universities of Kerala because of the developments in Information communication technology. The study recommends methods for improving the knowledge/skills of library professionals. The aim of the study is to evaluate the professional development activities of Library professionals and their attitude towards continuing education programmes. In order to achieve the objectives of the study a survey was conducted with the help of structured questionnaires distributed to 203 library professionals in seven major universities in Kerala, (South India) of which 185 questionnaires were returned. Results of the analysis show that majority of the professionals have pursued higher degrees in library science or IT allied courses after entering the profession, and that they have a positive attitude towards participation in training programmes and workshops. The results show that developments in ICT have a positive influence on majority of library professionals‘ attitude towards continuing education programmes.

Use of Online Information Resources for Knowledge Organisation in Library and Information Centres: A Case Study of CUSAT

The paper discusses the use of online information resources for organising knowledge in library and information centres in Cochin University of Science and Technology (CUSAT). The paper discusses the status and extent of automation in CUSAT library. The use of different online resources and the purposes for which these resources are being used, is explained in detail. Structured interview method was applied for collecting data. It was observed that 67 per cent users consult online resources for assisting knowledge organisation. Library of Congress catalogue is the widely used (100 per cent) online resource followed by OPAC of CUSAT and catalogue of British Library. The main purposes for using these resources are class number building and subject indexing