Search results

The purpose of the study is to assess the familiarity and utilization of open access resources among library users of Cochin University of Science and Technology (CUSAT), Kochi, and Pondicherry University (PU), Puducherry.

Data for the study were collected via a well-structured questionnaire. For this study, 250 questionnaires were administered among library users of each CUSAT and PU through incidental sampling. From CUSAT and PU, 180 and 160 questionnaires, respectively, were considered for data analysis.

The study reveals that majority of the respondents, i.e. 77.78 and 80 per cent of CUSAT and PU, respectively, believe that they are familiar with the concept of open access (OA). 70.56 per cent respondents from CUSAT and 71.88 per cent users from PU are aware that their library has an OA repository. However, majority of the respondents, i.e. 65 and 70.63 per cent users from CUSAT and PU, respectively, use OA resources. Among OA resources, electronic theses and dissertations are the most preferred ones consulted by 56.67 and 62.50 per cent respondents, respectively, from CUSAT and PU. 60.56 per cent respondents from CUSAT followed by PU (52.50 per cent) cited “screen reading” as a main barrier in accessing OA resources.

Both the universities under study have created and maintained the OA institutional repository for disseminating their institutional intellectual output. This study explores awareness and use of OA resources among library users of CUSAT and PU. The study concludes with some suggestions for utmost utilization of OA resources among library users.

The purpose of this paper is to describe the design and development of a digital library at Cochin University of Science and Technology (CUSAT), India, using DSpace open source software. The study covers the structure, contents and usage of CUSAT digital library.

This paper examines the possibilities of applying open source in libraries. An evaluative approach is carried out to explore the features of the CUSAT digital library. The Google Analytics service is employed to measure the amount of use of digital library by users across the world.

CUSAT has successfully applied DSpace open source software for building a digital library. The digital library has had visits from 78 countries, with the major share from India. The distribution of documents in the digital library is uneven. Past exam question papers share the major part of the collection. The number of research papers, articles and rare documents is less.

The study is the first of its type that tries to understand digital library design and development using DSpace open source software in a university environment with a focus on the analysis of distribution of items and measuring the value by usage statistics employing the Google Analytics service. The digital library model can be useful for designing similar systems.

Telecommunication has a decisive role in the development of technology in the current era. The number of mobile users with multiple SIM cards is increasing every second. Hence, telecommunication is a significant area in which big data technologies are needed. Competition among the telecommunication companies is high due to customer churn. Customer retention in telecom companies is one of the major problems. The paper aims to discuss this issue.

The authors recommend an Intersection-Randomized Algorithm (IRA) using MapReduce functions to avoid data duplication in the mobile user call data of telecommunication service providers. The authors use the agent-based model (ABM) to predict the complex mobile user behaviour to prevent customer churn with a particular telecommunication service provider.

The agent-based model increases the prediction accuracy due to the dynamic nature of agents. ABM suggests rules based on mobile user variable features using multiple agents.

The authors have not considered the microscopic behaviour of the customer churn based on complex user behaviour.

This paper shows the effectiveness of the IRA along with the agent-based model to predict the mobile user churn behaviour. The advantage of this proposed model is as follows: the user churn prediction system is straightforward, cost-effective, flexible and distributed with good business profit.

This paper shows the customer churn prediction of complex human behaviour in an effective and flexible manner in a distributed environment using Intersection-Randomized MapReduce Algorithm using agent-based model.

Vocabulary learning is a difficult task for children without hearing ability. Absence of enough learning centers and effective learning tools aggravate the problem. Modern technology can be utilized fruitfully to find solutions to the learning difficulties experienced by the deaf. The purpose of this paper is to present SiLearn – a novel technology based tool for teaching/learning sign vocabulary.

The proposed mobile application can act as a visual dictionary for deaf people. SiLearn is equipped with features that can automatically detect both text and physical objects and convert them to their corresponding signs. For testing the effectiveness of the proposed mobile application quantitative analyses were done. Quantitative analysis is based on testing a class of 28 students belonging to St Clare Oral School for the Deaf, Kerala, India. This group consisted of 17 boys and 11 girls. Analysis was also done through questionnaire. Questionnaires were given to teachers, parents of deaf students learning sign language and other sign language learners.

Results indicate that as SiLearn is very effective in sign vocabulary development. It can enhance vocabulary learning rate considerably.

This is the first time that artificial intelligence (AI) based techniques are used for early stage sign language learning. SiLearn can equally be used by children, parents and teachers for learning sign language.

This study aims to examine if there exists a relation between scholarly output and institutional ranking based on National Institutional Ranking Framework (NIRF) of India. This paper also aims to analyze and compare the parameters of NIRF with those of leading world ranking university rankings.

The data for the study were collected through Web content analysis. The major parts of data were collected from the official websites of NIRF, Times Higher Education World University Rankings and QS World University rankings.

The study found that the parameters fixed for the assessment of Indian institutions under NIRF are par with those of other world university ranking agencies. Scholarly output of a university is one of the major parameters of university ranking schemes. Indian universities who scored high for research productivity came top in NIRF. These universities were also figured in world university rankings. Universities from South India excel in NIRF and there is a close relationship between scholarly productivity and institutional ranking.

Correlation between h-index and scholarly productivity has been dealt with in several studies. This paper is the first attempt to find the relationship between scholarly productivity and ranking of universities in India based on NIRF.

Total quality management (TQM) has been a universally applienod management strategy to improve organizational performance and thereby to achieve competitiveness. Compared with the scholarly and practical attention paid to identify the consequences of implementing TQM practices, little is known about how those practices enhance organizational image and employee satisfaction. This paper aims to address that research gap and is designed to empirically prove the relationship between TQM practices, organizational image and employee satisfaction.

A questionnaire-based survey of 285 employees including administrators, managers and heads of departments of 21 National Accreditation Board for Hospital and Healthcare providers-accredited hospitals in India was conducted. The proposed research model was tested using partial least squares based structural equation modelling.

The results revealed that TQM practices have positive direct and indirect effects on employee satisfaction, confirming the partial mediation role played by organizational image in the relationship between TQM practices and employee satisfaction.

From the findings, leaders can understand that by implementing TQM practices, organizations can enhance image of the organization and bring high level of employee satisfaction.

The study tries to answer questions largely ignored in the TQM literature: the effect of TQM practices on organizational image and employee satisfaction, and the mediating role of organizational image on TQM practices and employee satisfaction.

This study aims to bring awareness to the developing of fault detection systems using the data collected from sensor devices/physical devices of various systems for predictive maintenance. Opportunities and challenges in developing anomaly detection algorithms for predictive maintenance and unexplored areas in this context are also discussed.

For conducting a systematic review on the state-of-the-art algorithms in fault detection for predictive maintenance, review papers from the years 2017–2021 available in the Scopus database were selected. A total of 93 papers were chosen. They are classified under electrical and electronics, civil and constructions, automobile, production and mechanical. In addition to this, the paper provides a detailed discussion of various fault-detection algorithms that can be categorised under supervised, semi-supervised, unsupervised learning and traditional statistical method along with an analysis of various forms of anomalies prevalent across different sectors of industry.

Based on the literature reviewed, seven propositions with a focus on the following areas are presented: need for a uniform framework while scaling the number of sensors; the need for identification of erroneous parameters; why there is a need for new algorithms based on unsupervised and semi-supervised learning; the importance of ensemble learning and data fusion algorithms; the necessity of automatic fault diagnostic systems; concerns about multiple fault detection; and cost-effective fault detection. These propositions shed light on the unsolved issues of predictive maintenance using fault detection algorithms. A novel architecture based on the methodologies and propositions gives more clarity for the reader to further explore in this area.

Papers for this study were selected from the Scopus database for predictive maintenance in the field of fault detection. Review papers published in this area deal only with methods used to detect anomalies, whereas this paper attempts to establish a link between different industrial domains and the methods used in each industry that uses fault detection for predictive maintenance.

Graduates' attitudes towards learning, although subject to change, is a crucial indicator of their understanding and involvement in lifelong learning activities. The purpose of this paper is to explore whether lifelong learning enhances human capital worth to predict perceived employability. An enquiry into the attitudinal differences on lifelong learning among male and female students was also looked into.

An empirical examination using Warp-PLS was conducted on the propositions among 286 engineering graduate students in Kerala, India, from January 2020 to March 2020.

The Warp-PLS examination reveals a positive association between lifelong learning and perceived employability and warrants the mediating role of lifelong learning in the association between human capital and perceived employability. A gendered variation on attitudinal differences towards lifelong learning is also looked into, and no difference between males and females is found.

The impact of lifelong learning on employability has been conceptually discussed before. This paper is the first attempt to empirically prove the same with a proper theoretical explanation.

Prospective students and other stakeholders in the education system use global and national rankings as a measure of the quality of education offered by different higher educational institutions. The ranking of an Institution is seen as a measure of reputation and has a significant role in attracting students. But are students happy in the top-ranked institutions? Does a high rank translate into high student satisfaction? This study answers this question taking data from top educational institutions in India.

This study examines how the top-ranked higher education institutions in India fare on student satisfaction. Using the data on key performance indicators published by the National Institutional Ranking Framework (NIRF) and student satisfaction scores of these institutions reported by NAAC, the study explores a possible relationship between the ranking of an institution and its student satisfaction score.

The study finds no significant relationship between the ranking of an institution and its student satisfaction score. The only institutional performance dimension which has a positive correlation with student satisfaction is graduate outcome. The diversity dimension is seen to be negatively correlated with student satisfaction.

The importance of modifying the ranking frameworks to account for the real drivers of student satisfaction is highlighted. The items in the student satisfaction survey should be regularly updated to reflect the actual concerns of the students. This is very important given the fact that the number of Indian students going abroad for higher education recorded a six-year high in 2022 at 750,365.

With more than 50,000 institutions catering to over 40 million students, India has the largest higher education system in the world. Given the high level of competition among these institutions, ranking and accreditation have become important parameters used by students for selection of an institution. But do top-ranked higher education institutions have the most satisfied student community? The assumption is disproved using the most credible secondary data. This study is the first of its kind in the Indian context. It has huge implications for the most respected ranking frameworks.

The purpose of this paper is to design an electromechanical actuator which can inherently tolerate a stuck or loose failure without any need for fault detection isolation and reconfiguration.

Generalized design methodology for a thrust vector control application is adopted to reduce the design iterations during the initial stages of the design. An optimum ball screw pitch is selected to minimize the motor sizing and maximize the load acceleration.

A high redundancy electromechanical actuator for thrust vector control has lower self-inertia and higher reliability than a direct drive simplex configuration. This configuration is a feasible solution for thrust vector control application because it offers a more acceptable and graceful degradation than a complete failure.

Future work will include testing on actual hardware to study the transient disturbances caused by a fault and their effect on launch vehicle dynamics.

High redundancy electromechanical actuator concept can be extended to similar applications such as solid motor nozzle in satellite launch vehicles and primary flight control system in aircraft.

High redundancy actuators can be useful in safety critical applications involving human beings. It can also reduce the machine downtime in industrial process automation.

The jam tolerant electromechanical actuator proposed for the launch vehicle application has a unique configuration which does not require a complex fault detection isolation and reconfiguration logic in the controller. This enhances the system reliability and allows a simplex controller having a lower cost.