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2. The Four Pillars of Peer Assessment for Collaborative Teamwork in Higher Education

Author

Sridharan, Bhavani, McKay, Jade, Boud, David, Baucal, Aleksandar, Series Editor, Arcidiacono, Francesco, Series Editor, Daiute, Colette, Editorial Board Member, Grossen, Michèle, Editorial Board Member, Kumpulainen, Kristiina, Editorial Board Member, Perret-Clermont, Anne-Nelly, Editorial Board Member, Psaltis, Charis, Editorial Board Member, Säljö, Roger, Editorial Board Member, Schwarz, Baruch, Editorial Board Member, Tartas, Valerie, Editorial Board Member, Noroozi, Omid, editor, and De Wever, Bram, editor

Published
2023
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4. Does the Use of Summative Peer Assessment in Collaborative Group Work Inhibit Good Judgement?

Author

Sridharan, Bhavani, Tai, Joanna, and Boud, David

Abstract

The accuracy and consistency of peer marking, particularly when students have the power to reward (or penalise) during formative and summative assessment regimes, is largely unknown. The objective of this study is to evaluate students' ability and behaviour in marking their peers' teamwork performance in a collaborative group assessment context both when the mark is counted and not counted towards their final grade. Formative and summative assessment data were obtained from 98 participants in anonymous self and peer assessment of team members' contributions to a group assessment in business courses. The findings indicate that students are capable of accurately and consistently judging their peers' performance to a large extent, especially in the formative evaluation of the process component of group work. However, the findings suggest significant peer grading bias when peer marks contribute to final grades. Overall, findings suggest that students are reluctant to honestly assess their peers when they realise that their actions can penalise non-contributing students. This raises questions about the appropriateness of using peer marks for summative assessment purposes. To overcome the problems identified, this paper proposes a number of measures to guide educators in effectively embedding summative peer assessment in a group assessment context.

Published
2019
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5. The Effects of Peer Judgements on Teamwork and Self-Assessment Ability in Collaborative Group Work

Author

Sridharan, Bhavani and Boud, David

Abstract

A crucial determinant of the success or failure of collaborative group work is the effect of peer feedback interventions on learning. Research exploring such effects on developing soft skills is sparse. This study seeks to address whether peer feedback leads to enhanced teamwork behaviour and self-assessment ability, two skills highly sought after by employers. Specifically, this study examines the direct effect of formative performance rating and the mediating effect of praise and criticism in peer feedback messages on achievement in teamwork and self-assessment skills. The sample consists of quantitative and qualitative data from 98 students enrolled in business programmes using a particular form of collaborative group work. The paper finds a direct positive relationship between formative performance rating and summative self-assessment ability. It also finds that praise negatively mediates the relationship between formative performance rating and summative teamwork. Further analyses suggest that a significant proportion of comments provided is past rather than future-oriented. Potential strategies to overcome the limitations of current practices are discussed.

Published
2019
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9. Students' Perceptions of Peer Assessment Effectiveness: An Explorative Study

Author

Sridharan, Bhavani, Muttakin, Mohammad Badrul, and Mihret, Dessalegn Getie

Abstract

Despite increasing demands by stakeholders to instil teamwork skills in accounting graduates, the assessment practices associated with teamwork in the accounting curricula are not yet well developed. This study examined the association between students' perceptions of peer assessment attributes (i.e. anonymity, question relevance and mark allocation) and the perceived effectiveness of peer assessment in preventing free riding, reducing conflict, improving communication and enhancing the quality of contributions to teamwork. A peer assessment approach was trialled at a master's accounting course at an Australian university and data were collected via a survey of students' perceptions of their experiences. Quantitative and qualitative data were gathered to address the research objectives. The results suggested that students who found the mark allocation appropriate, also found that the peer evaluation system had a positive effect in reducing free riding, improving communication within the team and enhancing the quality of contribution of the team members. Students who highly valued the anonymity in peer assessment, also found that peer assessment reduced free riding among team members. Students' qualitative comments suggested that additional mechanisms are needed in peer assessment, including formative feedback from peers and having teaching staff moderate the marks for summative assessment purposes.

Published
2018
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10. Internet Based Learning and Knowledge Management.

Author

Sridharan, Bhavani, Kinshuk, Patel, Ashok, and Hong, Hong

Abstract

This paper presents the research and development of knowledge management system for Internet based intellectual assets to leverage the learning process for individual learners. The literature review reveals that corporate solutions of knowledge management are not directly applicable due to the lack of adaptivity needed to provide individualized feedback to the learner, and their localized nature does not directly deal with authentication and verification of distributed information. Architecture has therefore been formulated for the knowledge management system that specifically supports Web-based learning. (Author)

Published
2002

11. Student perceptions of collaborative group work (CGW) in higher education.

Author

McKay, Jade and Sridharan, Bhavani

Subjects
*HIGHER education, *STUDENT development, *HIDDEN curriculum, *ONLINE education, *DIGITAL learning
Abstract

Despite the vast body of research surrounding collaborative group work (CGW) and its potential to enhance learning and engagement, questions persist in relation to the effectiveness of CGW initiatives in the development of teamwork skills amongst students in higher education. Prior studies have tended to measure the effectiveness of teamwork and group work through student grades, however, this is increasingly seen as problematic, with more researchers stressing the importance of student perceptions as a better measure of the efficaciousness of CGW. This paper presents the findings from an Australian study which set out to investigate student perceptions of the effectiveness of a technology-enhanced groupwork assessment on student learning outcomes, including teamwork skills and self-evaluative judgement skills. An unexpected event in the beginning of 2020, that being the global COVID-19 pandemic, affected learning and teaching in significant ways, with all students forced to learn online, inevitably impacting their experience with this CGW initiative. Adopting a qualitative inductive research methodology, the findings suggest that students perceive collaborative group work as beneficial in many ways, though it is not without its challenges, one of those being the global pandemic and its ripple effect of remote learning, isolation and increased difficulty with collaboration. This unforeseen event and its impact on the delivery of education elicited interesting results about CGW in the online context. Findings may advance the understanding and implementation of CGW in higher education, particularly in an online learning context. [ABSTRACT FROM AUTHOR]

Published
2024
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12. Evidencing Learning Outcomes: A Multi-Level, Multi-Dimensional Course Alignment Model

Author

Sridharan, Bhavani, Leitch, Shona, and Watty, Kim

Abstract

This conceptual framework proposes a multi-level, multi-dimensional course alignment model to implement a contextualised constructive alignment of rubric design that authentically evidences and assesses learning outcomes. By embedding quality control mechanisms at each level for each dimension, this model facilitates the development of an aligned curriculum. The use of rubrics is a crucial theme for many higher education institutions owing to the binding requirement by universities to provide evidence to quality assurance agencies. The success of evidencing learning outcomes through rubrics, however, is only one piece of the puzzle. The other is the contextualised constructive alignment of intertwined factors. Despite the significance of embedding these factors, there has been little, if any, systematic framework in this area. The two key instrumental forces underpinning the conception of this model are: seeking external accreditation and the implementation of programme enhancement thus realising the strategic agenda for an Australian university.

Published
2015
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16. Performance Improvement of SIMD Processor for High-Speed end Devices in IoT Operation Based on Reversible Logic with Hybrid Adder Configuration

Author

Kalimuthu*, Vinoth Kumar, Somasundaram, Karthikeyan, Sridharan, Bhavani, and Chockalingam, Vennila

Subjects
IoT, quantum, Kogge-Stone carry look-ahead, reversible logic, single instruction-multiple data, Hardware_ARITHMETICANDLOGICSTRUCTURES, TA1-2040, Engineering (General). Civil engineering (General)
Abstract

The reversible logic function is gaining significant consideration as a style for the logic design by implementing modern Nano and quantum computing with minimal impact on physical entropy. Recent advances in reversible logic allow for computer design applications using advanced quantum computer algorithms. In the literature, significant contributions have been made towards reversible logic gate structures and arithmetic units. However, there are many attempts to dictate the design of Single Instruction-Multiple Data (SIMD) processors. In this research work, a novel programmable reversible logic gate design is verified and a reversible processor design suggests its implementation of SIMD processor. Then, implementing the ripple-carry, carry-select and Kogge-Stone carry look-ahead adders using reversible logic and the performance is compared. The proposed reversible logic-based architecture has a minimum fan out with binary tree structure and minimum logic depth. The simulation result of the proposed design is obtained from Xilinx 14.5 software. From the simulated result, the computational path net delay for 16 × 16 reversible logic with Kogge Stone Adder is 17.247 ns. Compared with 16-bit Kogge Stone Adder, the reversible logic-based 16-bit Kogge Stone Adder gives low power and low time delay. By looking at the speed, energy and area parameters, including fast applications in which two smaller delay and low power adders are required, the effectiveness, including the proper area use of the hybrid adder recommended by it is evaluated.

Published
2022

17. Does Supply Always Come on the Heels of Demand? Matches and Mismatches in E-Learning

Author

Sridharan, Bhavani, Deng, Hepu, and Kinshuk

Abstract

Developing sustainable e-learning requires a better understanding of the perceptions and preferences of e-learning providers and e-learners on the four crucial dimensions for elearning success including pedagogies, technologies, learning resources and management of learning resources. There is, however, little research on evaluating whether these critical dimensions are perceived as critical by e-learning providers and e-learners. To address this issue, this study investigates the gap between e-learners' and e-learning providers' perceptions and preferences on these critical dimensions for e-learning effectiveness. Such an investigation paves the way for developing appropriate measures to reduce the gap between the supply and the demand for sustainable e-learning.

Published
2014

18. CO-CREATING SUSTAINABLE AND DYNAMIC CURRICULUM: A DECISION SUPPORT SYSTEM FOR ASSURING GRADUATE CAPABILITY.

Author

Sridharan, Bhavani and Mustard, Jamie

Subjects
DECISION support systems, CURRICULUM change, HIGHER education administration, MULTIPLE criteria decision making, SOFT skills, SUSTAINABILITY
Abstract

An important challenge facing higher education institutions is authentically assuring graduate capabilities, including the assessment of 'softer skills'. Many institutions have developed procedures through curriculum reform and renewal processes, but too often these processes involve isolated approaches such as 'ticking the box', use of summary statistics and gap analysis which are both imprecise and piecemeal. Despite growing interest in assuring employable graduate capabilities, there has been little research into using a structured holistic approach engaging with multiple key stakeholders. This research proposes a decision support system adopting a multi-criteria decision approach (MCDA) to appraise whole of degree level outcomes and the robustness of assessment policy decisions. The objective is to authentically assure graduate capability by considering multiple key criteria to reduce arbitrariness of current approaches to assessment design. Multiple scenarios are presented to explain the application of MCDA in evaluating assessment benchmarks using simple to complex criteria. [ABSTRACT FROM AUTHOR]

Published
2023

20. DEEP PERONA--MALIK DIFFUSIVE MEAN SHIFT IMAGE CLASSIFICATION FOR EARLY GLAUCOMA AND STARGARDT DISEASE DETECTION.

Author

Arunachalam, Senthil kumar, Devaraj, Somasundaram, and Sridharan, Bhavani

Subjects
IMAGE recognition (Computer vision), STARGARDT disease, RETINAL imaging, GLAUCOMA, IMAGE analysis, FEATURE extraction, TONOMETERS
Abstract

Glaucoma and Stargardt's, an inherited disease predominantly affect the retinal portion of the eye. The diagnosis of Glaucoma in a fundus image is an arduous, time consuming process. There were many research works carried out to detect early stages of Glaucoma and Stargardt's disease. However, the accuracy, diagnostic time and performance were not improved. To resolve the above said problems, a computational method called Deep Neural Perona--Malik Diffusive Mean Shift Mode Seeking Segmented Image Classification (DNP-MDMSMSIC) is introduced for the early detection of Glaucoma and Stargardt's disease with retinal fundus images. The DNP-MDMSMSIC method comprises diverse types of layers that support to identify early detection of disease with improved accuracy and less time. Process as explained; initially, numerous qualified retinal images are given as input to the input layer. These input images are transmitted further to the hidden layer 1 to perform image pre-processing. In DNP-MDMSMSIC, Space-Variant Perona--Malik Diffusive Image Preprocessing is carried out to decrease the noise from input image without removing contents like edges, lines, etc., for image interpretation with a higher peak signal-to-noise ratio. This preprocessed image is further processed in the hidden layer 2 where the feature extraction process is performed to extract features like color, texture, and intensity with a higher degree of accuracy. Based on the extracted features, an input feature image gets segmented in hidden layer 3. Mean Shift Mode Seeking Segmentation algorithm is employed to segment the pixels in image space with corresponding feature space points. Then the segmented images are given to the output layer to perform retinal fundus image classification using Bregman Divergence Function. During the image classification, the distance between two segmented regions (i.e., testing image region of particular class and training image region) with convex is measured. In this way, the retinal fundus images get classified with higher accuracy. Experimental evaluation is performed by considering the metrics such as peak signal-to-noise, disease detection accuracy, disease detection time, and error rate corresponding to the number of retina fundus images and image size. DNP-MDMSMSIC method is designed to detect Glaucoma and Stargardt's disease at an earlier stage with higher accuracy by 8% and less time by 20% with aid of ACRIMA database. [ABSTRACT FROM AUTHOR]

Published
2023
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27. Grid & Force Based Sensor Deployment Methods in WSN Using PSO

Author

DeepaliParag Adhyapak, Sridharan Bhavani, and Aparna Pradeep Laturkar

Subjects
Control and Optimization, Computer Networks and Communications, Computer science, Network packet, Distributed computing, Probabilistic logic, Grid, Scheduling (computing), VFCPSO, Local optimum, MDBPSO, Hardware and Architecture, Signal Processing, Electrical and Electronic Engineering, Wireless sensor network, Flocking (texture), Wireless Sensor Network, Information Systems
Abstract

Wireless Sensor Network (WSN) is emergingtechnology and has wide range of applications, such as environment monitoring, industrial automation and numerous military applications. Hence, WSN is popular among researchers. WSN has several constraints such as restricted sensing range, communication range and limited battery capacity. These limitations bring issues such as coverage, connectivity, network lifetime and scheduling & data aggregation. There are mainly three strategies for solving coverage problems namely; force, grid and computational geometry based. PSO is a multidimensional optimization method inspired from the social behavior of birds called flocking. Basic version of PSO has the drawback of sometimes getting trapped in local optima as particles learn from each other and past solutions. This issue is solved by discrete version of PSO known as Modified Discrete Binary PSO (MDBPSO) as it uses probabilistic approach. This paper discusses performance analysis of random; grid based MDBPSO (Modified Discrete Binary Particle Swarm Optimization), Force Based VFCPSO and Combination of Grid & Force Based sensor deployment algorithms based on interval and packet size. From the results of Combination of Grid & Force Based sensor deployment algorithm, it can be concluded that its performance is best for all parameters as compared to rest of the three methods when interval and packet size is varied.

Published
2018

28. Ant Based Cross Layered Optimization Protocol for WMSN with Fuzzy Clustering

Author

Sridharan Bhavani, DipaliParag Adhyapak, and Aparna Pradeep Laturkar

Subjects
Routing protocol, WMSN, Control and Optimization, Fuzzy clustering, Computer Networks and Communications, business.industry, Network packet, Computer science, Quality of service, ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS, FCAXL, QoS, Cross-layer optimization, Throughput, Hardware and Architecture, Signal Processing, Network performance, Electrical and Electronic Engineering, business, Cluster analysis, Information Systems, Computer network
Abstract

Wireless Multimedia Sensor Network (WMSN) is embedded with large number of Audio, Video and scalar sensor nodes which can able to retrieve the multimedia information from the environment. WMSN has several challenges such as life time of the network, Memory requirement, Coverage, Bandwidth and QoS metrics. Hence selection of routing algorithm is crucial in WMSN. Again interdependencies of the protocol layer cannot be neglected to improve the network performance. Clustering in WMSN is challenging task in order to increase network lifetime and to improve the communication. Hence Fuzzy clustered Ant based cross layer protocol (FCAXL) is proposed. In this paper performance analysis of ant based cross layer optimization protocol with fuzzy clustering based on number of nodes and packet size is done. Simulation results shows that Fuzzy clustered ant based cross layer optimization protocol performs best as compared to AntSenseNet routing protocol, Cross layer routing protocol and Ant based cross layer routing protocol in terms of QoS parameters such as Throughput, Packet delivery ratio and delay. Hence the life time of the network increases.

Published
2018

31. The impact of learner engagement on performance outcomes: a longitudinal study in accounting education.

Author

Castro, Vincent Bicudo, Sridharan, Bhavani, Watty, Kim, and Safari, Maryam

Subjects
STUDENT engagement, ACCOUNTING education, UNIVERSITIES & colleges, LONGITUDINAL method, FOREIGN students
Abstract

This study explores the efficacy of vodcasting, as one of the advanced means of lecture recording, and discussion forums using retrospective engagement analytics data and performance outcome data on 1,172 unique students. The results provide partial support for the research hypotheses, particularly for international students, with learner engagement as a strong predictor of enhanced performance outcomes. However, no support was found for domestic students, with no significant impact of engagement on performance outcomes. That is, learner engagement may be more beneficial for international students than for domestic students. The findings support the implementation of discussion forums for enabling meaningful conversation, knowledge acquisition and peer engagement. This could pave the way for a knowledge‐sharing culture as opposed to a knowledge‐hoarding culture. Overall, the findings offer insights for higher education providers who have large international student enrolments and are interested in diversity management strategies and enhanced student engagement using disruptive technology. [ABSTRACT FROM AUTHOR]

Published
2021
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35. Comparison of fractal coding methods for medical image compression

Author

Sridharan Bhavani and Kepanna Gowder Thanushkodi

Subjects
business.industry, Fractal transform, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Pattern recognition, Data_CODINGANDINFORMATIONTHEORY, Peak signal-to-noise ratio, Fractal, Fractal compression, Signal Processing, Compression ratio, Computer vision, Computer Vision and Pattern Recognition, Artificial intelligence, Electrical and Electronic Engineering, business, Software, Context-adaptive binary arithmetic coding, ComputingMethodologies_COMPUTERGRAPHICS, Mathematics, Image compression, Data compression
Abstract

In this study, the performance of fractal-based coding algorithms such as standard fractal coding, quasi-lossless fractal coding and improved quasi-lossless fractal coding are evaluated by investigating their ability to compress magnetic resonance images (MRIs) based on compression ratio, peak signal-to-noise ratio and encoding time. For this purpose, MRI head scan test sets of 512 × 512 pixels have been used. A novel quasi-lossless fractal coding scheme, which preserves important feature-rich portions of the medical image, such as domain blocks and generates the remaining part of the image from it, has been proposed using fractal transformations. One of the biggest tasks in fractal image compression is reduction of encoding computation time. A machine learning-based model is used for reducing the encoding time and also for improving the performance of the quasi-lossless fractal coding scheme. The results show a better performance of improved quasi-lossless fractal compression method. The quasi-lossless and improved quasi-lossless fractal coding algorithms are found to outperform standard fractal coding thereby proving the possibility of using fractal-based image compression algorithms for medical image compression. The proposed algorithm allows significant reduction of encoding time and also improvement in the compression ratio.

Published
2013

36. Random, PSO and MDBPSO based Sensor Deployment in Wireless Sensor Network

Author

DeepaliParag Adhyapak, Aparna Pradeep Laturkar, and Sridharan Bhavani

Subjects
Control and Optimization, Computer Networks and Communications, Computer science, Real-time computing, PSO, Particle swarm optimization, Grid, DBPSO, Scheduling (computing), MDBPSO, Hardware and Architecture, Region of interest, Software deployment, Signal Processing, Electrical and Electronic Engineering, Wireless sensor network, Wireless Sensor Network, Information Systems
Abstract

Wireless Sensor Network (WSN) is emergingtechnology and has wide range of applications, such as environment monitoring, industrial automation and numerous military applications. Hence, WSN is popular among researchers. WSN has several constraints such as restricted sensing range, communication range and limited battery capacity. These limitations bring issues such as coverage, connectivity, network lifetime and scheduling and data aggregation. There are mainly three strategies for solving coverage problems namely; force, grid and computational geometry based. This paper discusses sensor deployment using Random; Particle Swarm Optimization (PSO) and grid based MDBPSO (Modified Discrete Binary Particle Swarm Optimization) methods. This paper analyzes the performance of Random, PSO based and MDBPSO based sensor deployment methods by varying different grid sizes and the region of interest (ROI). PSO and MDBPSO based sensor deployment methods are analyzed based on number of iterations. From the simulation results; it can be concluded that MDBPSO performs better than other two methods.

Published
2018

37. Grid and Force Based Sensor Deployment Methods in Wireless Sensor Network using Particle Swarm Optimization

Author

DeepaliParag Adhyapak, Sridharan Bhavani, and Aparna Pradeep Laturkar

Subjects
Control and Optimization, Computer Networks and Communications, Computer science, Network packet, Distributed computing, 010401 analytical chemistry, Probabilistic logic, Particle swarm optimization, 020206 networking & telecommunications, 02 engineering and technology, Grid, 01 natural sciences, 0104 chemical sciences, Scheduling (computing), VFCPSO, Local optimum, MDBPSO, Hardware and Architecture, Signal Processing, 0202 electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, Wireless sensor network, Flocking (texture), Wireless Sensor Network, Information Systems
Abstract

Wireless Sensor Network (WSN) is emergingtechnology and has wide range of applications, such as environment monitoring, industrial automation and numerous military applications. Hence, WSN is popular among researchers. WSN has several constraints such as restricted sensing range, communication range and limited battery capacity. These limitations bring issues such as coverage, connectivity, network lifetime and scheduling & data aggregation. There are mainly three strategies for solving coverage problems namely; force, grid and computational geometry based. PSO is a multidimensional optimization method inspired from the social behavior of birds called flocking. Basic version of PSO has the drawback of sometimes getting trapped in local optima as particles learn from each other and past solutions. This issue is solved by discrete version of PSO known as Modified Discrete Binary PSO (MDBPSO) as it uses probabilistic approach. This paper discusses performance analysis of random; grid based MDBPSO (Modified Discrete Binary Particle Swarm Optimization), Force Based VFCPSO and Combination of Grid & Force Based sensor deployment algorithms based on interval and packet size. From the results of Combination of Grid & Force Based sensor deployment algorithm, it can be concluded that its performance is best for all parameters as compared to rest of the three methods when interval and packet size is varied.

Published
2018

38. Ant Based Cross Layered Optimization Protocol for Wireless Multimedia Sensor Network with Fuzzy Clustering

Author

Aparna Pradeep Laturkar, Sridharan Bhavani, and Dipali Adhyapak

Subjects
WMSN, Routing protocol, Control and Optimization, Fuzzy clustering, Computer Networks and Communications, Computer science, FCAXL, QoS, Throughput, Cross-layer optimization, 02 engineering and technology, 0202 electrical engineering, electronic engineering, information engineering, Network performance, Electrical and Electronic Engineering, Cluster analysis, Network packet, business.industry, Quality of service, ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS, 020206 networking & telecommunications, Hardware and Architecture, Signal Processing, 020201 artificial intelligence & image processing, business, Information Systems, Computer network
Abstract

Wireless Multimedia Sensor Network (WMSN) is embedded with large number of Audio, Video and scalar sensor nodes which can able to retrieve the multimedia information from the environment. WMSN has several challenges such as life time of the network, Memory requirement, Coverage, Bandwidth and QoS metrics. Hence selection of routing algorithm is crucial in WMSN. Again interdependencies of the protocol layer cannot be neglected to improve the network performance. Clustering in WMSN is challenging task in order to increase network lifetime and to improve the communication. Hence Fuzzy clustered Ant based cross layer protocol (FCAXL) is proposed. In this paper performance analysis of ant based cross layer optimization protocol with fuzzy clustering based on number of nodes and packet size is done. Simulation results shows that Fuzzy clustered ant based cross layer optimization protocol performs best as compared to AntSenseNet routing protocol, Cross layer routing protocol and Ant based cross layer routing protocol in terms of QoS parameters such as Throughput, Packet delivery ratio and delay. Hence the life time of the network increases.

Published
2018

39. Random, PSO & MDBPSO based Sensor Deployment in WSN

Author

Sridharan Bhavani, DeepaliParag Adhyapak, and Aparna Pradeep Laturkar

Subjects
Control and Optimization, Computer Networks and Communications, Computer science, Distributed computing, PSO, Particle swarm optimization, Grid, DBPSO, Scheduling (computing), MDBPSO, Hardware and Architecture, Software deployment, Region of interest, Signal Processing, Electrical and Electronic Engineering, Wireless sensor network, Wireless Sensor Network, Information Systems
Abstract

Wireless Sensor Network (WSN) is emergingtechnology and has wide range of applications, such as environment monitoring, industrial automation and numerous military applications. Hence, WSN is popular among researchers. WSN has several constraints such as restricted sensing range, communication range and limited battery capacity. These limitations bring issues such as coverage, connectivity, network lifetime and scheduling and data aggregation. There are mainly three strategies for solving coverage problems namely; force, grid and computational geometry based. This paper discusses sensor deployment using Random; Particle Swarm Optimization (PSO) and grid based MDBPSO (Modified Discrete Binary Particle Swarm Optimization) methods. This paper analyzes the performance of Random, PSO based and MDBPSO based sensor deployment methods by varying different grid sizes and the region of interest (ROI). PSO and MDBPSO based sensor deployment methods are analyzed based on number of iterations. From the simulation results; it can be concluded that MDBPSO performs better than other two methods.

Published
2018

40. Swarm Based Cross Layer Optimization Protocol for WMSN

Author

Aparna Pradeep Laturkar, Sridharan Bhavani, and Deepali Parag Adhyapak

Subjects
Routing protocol, WMSN, Control and Optimization, Computer science, Computer Networks and Communications, QoS, Throughput, Cross-layer optimization, Scheduling (computing), Protocol, Electrical and Electronic Engineering, Routing, Jitter, Network packet, business.industry, Quality of service, AntSenseNet, ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS, Swarm behaviour, Hardware and Architecture, Multipath routing, Signal Processing, business, Efficient energy use, Computer network, Information Systems
Abstract

Wireless Multimedia Sensor Network (WMSN) is comprised of tiny, low cost multimedia devices such as video cameras and microphones. These networks can transfer scalar as well as multimedia data into real time as well as non-real time applications. However addition of such devices exposes additional challenges on both QoS assurance and energy efficiency for efficient use of resources. This paper presents cross layer based AntSenseNet protocol to meet various QoS requirements such as throughput, jitter, lifetime and packet delivery ratio in order to improve network lifetime. Cross layer routing protocol utilizes scheduling algorithm and AntSenseNet protocol builds hierarchical structure and able to use multipath routing protocol. Simulation results shows Cross layer based AntSenseNet protocol outperforms Ant Sense routing protocol and cross layer routing protocol in terms of throughput and packet delivery ratio.

Published
2018

43. The perceptions of learners on the effectiveness of e-learning in higher education: An empirical study

Author

[Unknown], Sridharan, Bhavani, Deng, Hepu, Corbitt, Brian, [Unknown], Sridharan, Bhavani, Deng, Hepu, and Corbitt, Brian

Abstract

This paper examines the critical dimensions of the effectiveness of e-learning from the perspective of e-learners within the framework of pedagogy, technology and management of learning resources in higher education. A survey is conducted in an Australian University for exploring the association between the critical dimensions of e-learning and the learners' perceived impact of these dimensions on the e-learning effectiveness using multiple regression analysis. The results show that technology, management of learning resources, metadata and management effectiveness of learning resources positively influence the effectiveness of e-learning in higher education.

Published
2010

44. Structural equation modeling for evaluating the user perceptions of E-learning effectiveness in higher education

Author

[Unknown], Sridharan, Bhavani, Deng, Hepu, Kirk, Joyce, Corbitt, Brian, [Unknown], Sridharan, Bhavani, Deng, Hepu, Kirk, Joyce, and Corbitt, Brian

Abstract

A crucial prerequisite for sustainable e-learning is the understanding of learners’ preferences for various pedagogical strategies, technologies, and the management of learning resources. This paper presents an empirical study aiming to empirically test the theoretical (pedagogies, technologies and management) (PTM) model on the preference of learners and on the perceived impact of the effectiveness of e-learning. This study uses structural equation modelling (SEM) to identify the critical dimensions in the PTM model for augmenting the effectiveness of e-learning. This leads to the development of a PTM model with the path coefficients showing weak to strong relationships ranging from 0.15 to 0.42 with acceptable significance levels. The results support the hypothesis that management, technology, resources and metadata ontology dimensions affect the effectiveness of elearning both directly and indirectly through enhancing the management effectiveness of learning resources. However, the result does not support positive influence of pedagogical strategy per se on e-learning effectiveness. The implications of this study indicate the criticality of effective management of learning resources to enhance e-learning effectiveness.

Published
2010

45. An ontology-driven topic mapping approach to multi-level management of e-learning resources

Author

[Unknown], Sridharan, Bhavani, Deng, Hepu, Corbitt, Brian, [Unknown], Sridharan, Bhavani, Deng, Hepu, and Corbitt, Brian

Abstract

An appropriate use of various pedagogical strategies is fundamental for the effective transfer of knowledge in a flourishing e-learning environment. The resultant information superfluity, however, needs to be tackled for developing sustainable e-learning. This necessitates an effective representation and intelligent access to learning resources. Topic maps address these problems of representation and retrieval of information in a distributed environment. The former aspect is particularly relevant where the subject domain is complex and the later aspect is important where the amount of resources is abundant but not easily accessible. Conversely, effective presentation of learning resources based on various pedagogical strategies along with global capturing and authentication of learning resources are an intrinsic part of effective management of learning resources. Towards fulfilling this objective, this paper proposes a multi-level ontology-driven topic mapping approach to facilitate an effective visualization, classification and global authoring of learning resources in e-learning.

Published
2009

49. An Ontology-Based Learning Resources Management Framework for Exploratory E-learning.

Author

Sridharan, Bhavani, Deng, Hepu, and Corbitt, Brian

Subjects
ONTOLOGY, RESOURCE management, MOBILE learning, INFORMATION retrieval, DATABASE management, COMPUTER assisted instruction, KNOWLEDGE acquisition (Expert systems), SOCIAL learning
Abstract

This paper presents an ontology-based conceptual framework for effectively managing exploratory e-learning resources. The proposed framework has five significant novel features including authentication of retrieved resources, automatic ontology-based query refinement, reuse-oriented management of retrieved resources, adaptive retrieval of learning resources based on the style and preference of individual learners, and synthesisation of retrieval and management activities for creating reusable learning repositories. The applicability of the framework is demonstrated using a sample fragment of an ontology developed in the database domain. [ABSTRACT FROM AUTHOR]

Published
2011

50. Does supply always come on the heels of demand? Matches and mismatches in e-learning

Author

Sridharan, Bhavani, Deng, Hepu, and Kinshuk

Abstract

Developing sustainable e-learning requires a better understanding of the perceptions and preferences of e-learning providers and e-learners on the four crucial dimensions for elearning success including pedagogies, technologies, learning resources and management of learning resources. There is, however, little research on evaluating whether these critical dimensions are perceived as critical by e-learning providers and e-learners. To address this issue, this study investigates the gap between e-learners’ and e-learning providers’ perceptions and preferences on these critical dimensions for e-learning effectiveness. Such an investigation paves the way for developing appropriate measures to reduce the gap between the supply and the demand for sustainable e-learning.

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