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All Outputs (58)

Speech to text translation enabling multilingualism. (2020)
Conference Proceeding
BANO, S., JITHENDRA, P., NIHARIKA, G.L. and SIKHI, Y. 2020. Speech to text translation enabling multilingualism. In Proceedings of the 2020 International conference for innovation in technology (INOCON 2020), 6-8 November 2020, Bangluru, India. Piscataway: IEEE [online]. Available from: https://doi.org/10.1109/INOCON50539.2020.9298280

Speech acts as a barrier to communication between two individuals and helps them in expressing their feelings, thoughts, emotions, and ideologies among each other. The process of establishing a communicational interaction between the machine and mank... Read More about Speech to text translation enabling multilingualism..

Cognitive model for object detection based on speech-to-text conversion. (2020)
Conference Proceeding
PAVULURI, J., SAI, T.V., MANNAM, R.K., MANIDEEP, R. and BANO, S. 2020. Cognitive model for object detection based on speech-to-text conversion. In Proceedings of the 3rd International conference on intelligent sustainable systems (ICISS 2020), 3-5 December 2020, Thoothukudi, India. Piscataway: IEEE [online], pages 843-847. Available from: https://doi.org/10.1109/ICISS49785.2020.9315985

The goal of this paper is to develop a model which is the integrated version of both SpeechRecognition and Object detection. This model is developed after undergoing the literature survey and the existing models that are related to Object Detection a... Read More about Cognitive model for object detection based on speech-to-text conversion..

Stock price prognosticator using machine learning techniques. (2020)
Conference Proceeding
NISHITHA, S.N.T., BANO, S., REDDY, G.G., ARJA, P. and NIHARIKA, G.L. 2020. Stock price prognosticator using machine learning techniques. In Proceedings of the 4th International conference on electronics, communication and aerospace technology (ICECA 2020), 5-7 November 2020, Coimbatore, India. Piscataway: IEEE [online], pages 1636-1642. Available from: https://doi.org/10.1109/ICECA49313.2020.9297644

Stock market price prediction is one of the favourite research topics under consideration for professionals from various fields like mathematics, statistics, history, finance, computer science engineering etc., as it requires a set of skills to predi... Read More about Stock price prognosticator using machine learning techniques..

Character recognition using tesseract enabling multilingualism. (2020)
Conference Proceeding
NIHARIKA, G.L, BANO, S., KUMAR, P.S., DEEPIKA, T. and THUMATI, H. 2020. Character recognition using tesseract enabling multilingualism. In Proceedings of the 4th International conference on electronics, communication and aerospace technology (ICECA 2020), 5-7 November 2020, Coimbatore, India. Piscataway: IEEE [online], pages 1321-1327. Available from: https://doi.org/10.1109/ICECA49313.2020.9297609

Character recognition builds a recognizing factor for identifying the accuracy in characters. The accuracy of classifying the recognizing characters in an image is applied through deep learning methods. The character recognition is mainly focusing on... Read More about Character recognition using tesseract enabling multilingualism..

Wifi-based human activity recognition using Raspberry Pi. (2020)
Conference Proceeding
FORBES, G., MASSIE, S. and CRAW, S. 2020. Wifi-based human activity recognition using Raspberry Pi. In Alamaniotis, M. and Pan, S. (eds.) Proceedings of Institute of Electrical and Electronics Engineers (IEEE) 32nd Tools with artificial intelligence international conference 2020 (ICTAI 2020), 9-11 Nov 2020, [virtual conference]. Piscataway: IEEE [online], pages 722-730. Available from: https://doi.org/10.1109/ICTAI50040.2020.00115

Ambient, non-intrusive approaches to smart home health monitoring, while limited in capability, are preferred by residents. More intrusive methods of sensing, such as video and wearables, can offer richer data but at the cost of lower resident uptake... Read More about Wifi-based human activity recognition using Raspberry Pi..

Identifying implicit vulnerabilities through personas as goal models. (2020)
Conference Proceeding
FAILY, S., IACOB, C., ALI, R. and KI-ARIES, D. 2020. Identifying implicit vulnerabilities through personas as goal models. In Katsikas, S., Cuppens, F., Cuppens, N., Lambrinoudakis, C., Kalloniatis, C., Mylopoulos, J., Antón, A., Gritzalis, S., Meng, W. and Furnell, S. (eds.) Computer security: ESORICS 2020 international workshops, CyberICPS, SECPRE, and ADIoT: revised selected papers from the 4th International workshop on security and privacy requirements engineering (SECPRE 2020), co-located with the 25th European symposium on research in computer security (ESORICS 2020), 14-18 September 2020, Guildford, UK. Lecture notes in computer science, 12501. Cham: Springer [online], pages 185-202. Available from: https://doi.org/10.1007/978-3-030-64330-0_12

When used in requirements processes and tools, personas have the potential to identify vulnerabilities resulting from misalignment between user expectations and system goals. Typically, however, this potential is unfulfilled as personas and system go... Read More about Identifying implicit vulnerabilities through personas as goal models..

A pipeline framework for robot maze navigation using computer vision, path planning and communication protocols. (2020)
Conference Proceeding
RODRIGUEZ-TIRADO, A., MAGALLAN-RAMIREZ, D., MARTINEZ-AGUILAR, J.D., MORENO-GARCIA, C.F., BALDERAS, D. and LOPEZ-CAUDANA, E. 2020. A pipeline framework for robot maze navigation using computer vision, path planning and communication protocols. In Proceedings of 13th Developments in eSystems engineering international conference 2020 (DeSe 2020), 13-17 December 2020, [virtual conference]. Piscataway: IEEE [online], pages 152-157. Available from: https://doi.org/10.1109/DeSE51703.2020.9450731

Maze navigation is a recurring challenge in robotics competitions, where the aim is to design a strategy for one or several entities to traverse the optimal path in a fast and efficient way. To do so, numerous alternatives exist, relying on different... Read More about A pipeline framework for robot maze navigation using computer vision, path planning and communication protocols..

Performance analysis of different loss function in face detection architectures. (2020)
Conference Proceeding
FERDOUS, R.H., ARIFEEN, M.M., EIKO, T.S. and AL MAMUN, S. 2020. Performance analysis of different loss function in face detection architectures. In Kaiser, M.S., Bandyopadhyay, A., Muhmad, M. and Ray, K. (eds.) Proceedings of International conference on trends in computational and cognitive engineering 2020 (TCCE-2020), 17-18 December 2020, Dhaka, Bangladesh. Singapore: Springer [online], 659-669. Available from: https://doi.org/10.1007/978-981-33-4673-4_54

Masked face detection is a challenging task due to the occlusions created by the masks. Recent studies show that deep learning models can achieve effective performance for not only occluded faces but also for unconstrained environments, illuminations... Read More about Performance analysis of different loss function in face detection architectures..

Ensemble-based relationship discovery in relational databases. (2020)
Conference Proceeding
OGUNSEMI, A., MCCALL, J., KERN, M., LACROIX, B., CORSAR, D. and OWUSU, G. 2020. Ensemble-based relationship discovery in relational databases. In Bramer, M. and Ellis, R. (eds.) Artificial intelligence XXXVII: proceedings of 40th British Computer Society's Specialist Group on Artificial Intelligence (SGAI) Artificial intelligence international conference 2020 (AI-2020), 15-17 December 2020, [virtual conference]. Lecture notes in artificial intelligence, 12498. Cham: Springer [online], pages 286-300. Available from: https://doi.org/10.1007/978-3-030-63799-6_22

We performed an investigation of how several data relationship discovery algorithms can be combined to improve performance. We investigated eight relationship discovery algorithms like Cosine similarity, Soundex similarity, Name similarity, Value ran... Read More about Ensemble-based relationship discovery in relational databases..

Personalised meta-learning for human activity recognition with few-data. (2020)
Conference Proceeding
WIJEKOON, A. and WIRATUNGA, N. 2020. Personalised meta-learning for human activity recognition with few-data. In Bramer, M. and Ellis, R. (eds.) Artificial intelligence XXXVII: proceedings of 40th British Computer Society's Specialist Group on Artificial Intelligence (SGAI) Artificial intelligence international conference 2020 (AI-2020), 15-17 December 2020, [virtual conference]. Lecture notes in artificial intelligence, 12498. Cham: Springer [online], pages 79-93. Available from: https://doi.org/10.1007/978-3-030-63799-6_6

State-of-the-art methods of Human Activity Recognition(HAR) rely on a considerable amount of labelled data to train deep architectures. This becomes prohibitive when tasked with creating models that are sensitive to personal nuances in human movement... Read More about Personalised meta-learning for human activity recognition with few-data..

Professional communication tools in higher education: a case study in implementing slack in the curriculum. (2020)
Conference Proceeding
MENZIES, R. and ZARB, M. 2020. Professional communication tools in higher education: a case study in implementing slack in the curriculum. In Proceedings of 2020 Institute of Electrical and Electronics Engineers (IEEE) Frontiers in education conference (FIE 2020), 21-24 October 2020, [virtual conference]. Piscataway: IEEE [online], article ID 9273906. Available from: https://doi.org/10.1109/FIE44824.2020.9273906

This Innovative Practice Full Paper presents a study which considers the implications of embedding professional communication tools within the computing curriculum. Computing students are comfortable using various communication tools such as social m... Read More about Professional communication tools in higher education: a case study in implementing slack in the curriculum..

Analysing the learning by developing action model in HE computing. (2020)
Conference Proceeding
LINTILÄ, T. and ZARB, M. 2020. Analysing the learning by developing action model in HE computing. In Proceedings of 2020 Institute of Electrical and Electronics Engineers (IEEE) Frontiers in education conference (FIE 2020), 21-24 October 2020, [virtual conference]. Piscataway: IEEE [online], article ID 9274282. Available from: https://doi.org/10.1109/FIE44824.2020.9274282

This Research to Practice Working Process presents the first phase of the study, in which background information was sought from the literature and by interviews pedagogical experts from Laurea University of Applied Sciences (Laurea). The background... Read More about Analysing the learning by developing action model in HE computing..

Computing degree apprenticeships: an opportunity to address gender imbalance in the IT sector? (2020)
Conference Proceeding
SMITH, S., TAYLOR-SMITH, E., FABIAN, K., BARR, M., BERG, T., CUTTING, D., PATERSON, J., YOUNG, T. and ZARB, M. 2020. Computing degree apprenticeships: an opportunity to address gender imbalance in the IT sector? In Proceedings of 2020 Institute of Electrical and Electronics Engineers (IEEE) Frontiers in education conference (FIE 2020), 21-24 October 2020, [virtual conference]. Piscataway: IEEE [online], article ID 9274144. Available from: https://doi.org/10.1109/FIE44824.2020.9274144

This paper explores the potential for new work-based apprenticeship degrees to encourage more women into computing degrees and the IT sector. In the UK, women are currently under-represented on computing courses. Meanwhile the IT industry requires mo... Read More about Computing degree apprenticeships: an opportunity to address gender imbalance in the IT sector?.

Object recognition using enhanced particle swarm optimization. (2020)
Conference Proceeding
WILLIS, M., ZHANG, L., LIU, H., XIE, H. and MISTRY, L. 2020. Object recognition using enhanced particle swarm optimization. In Proceedings of 2020 International conference machine learning and cybernetics (ICMLC 2020), 4 December 2020, [virtual conference]. Piscataway: IEEE [online], pages 241-246. Available from: https://doi.org/10.1109/ICMLC51923.2020.9469584

The identification of the most discriminative features in an explainable AI decision-making process is a challenging problem. This research tackles such challenges by proposing Particle Swarm Optimization (PSO) variants embedded with novel mutation a... Read More about Object recognition using enhanced particle swarm optimization..

In-house deep environmental sentience for smart homecare solutions toward ageing society. (2020)
Conference Proceeding
EASOM, P., BOURIDANE, A., QIANG, F., DOWNS, C. and JIANG, R. 2020. In-house deep environmental sentience for smart homecare solutions toward ageing society. In Proceedings of 2020 International conference machine learning and cybernetics (ICMLC 2020), 4 December 2020, [virtual conference]. Piscataway: IEEE [online], pages 261-266. Available from: https://doi.org/10.1109/ICMLC51923.2020.9469531

With an increasing amount of elderly people needing home care around the clock, care workers are not able to keep up with the demand of providing maximum support to those who require it. As medical costs of home care increase the quality is care suff... Read More about In-house deep environmental sentience for smart homecare solutions toward ageing society..

Applying acceptance requirements to requirements modeling tools via gamification: a case study on privacy and security. (2020)
Conference Proceeding
PIRAS, L., CALABRESE, F. and GIORGINI, P. 2020. Applying acceptance requirements to requirements modeling tools via gamification: a case study on privacy and security. In Grabis, J. and Bork, D. (eds.) The practice of enterprise modeling: proceedings of 13th International Federation for Information Processing (IFIP) Practice of enterprise modelling working conference 2020 (Poem 2020), 25-27 November 2020, Riga, Latvia. Lecture notes in business information processing, 400. Cham: Springer [online], pages 366-376. Available from: https://doi.org/10.1007/978-3-030-63479-7_25

Requirements elicitation, analysis and modeling are critical activities for software success. However, software systems are increasingly complex, harder to develop due to an ever-growing number of requirements from numerous and heterogeneous stakehol... Read More about Applying acceptance requirements to requirements modeling tools via gamification: a case study on privacy and security..

A homogeneous-heterogeneous ensemble of classifiers. (2020)
Conference Proceeding
LUONG, A.V., VU, T.H., NGUYEN, P.M., VAN PHAM, N., MCCALL, J., LIEW, A.W.-C. and NGUYEN, T.T. 2020. A homogeneous-heterogeneous ensemble of classifiers. In Yang, H., Pasupa, K., Leung, A.C.-S., Kwok, J.T., Chan, J.H. and King, I. (eds.) Neural information processing: proceedings of 27th International conference on neural information processing 2020 (ICONIP 2020), part 5. Communications in computer and information science, 1333. Cham: Springer [online], pages, 251-259. Available from: https://doi.org/10.1007/978-3-030-63823-8_30

In this study, we introduce an ensemble system by combining homogeneous ensemble and heterogeneous ensemble into a single framework. Based on the observation that the projected data is significantly different from the original data as well as each ot... Read More about A homogeneous-heterogeneous ensemble of classifiers..

Toward an ensemble of object detectors. (2020)
Conference Proceeding
DANG, T., NGUYEN, T.T. and MCCALL, J. 2020. Toward an ensemble of object detectors. In Yang, H., Pasupa, K., Leung, A.C.-S., Kwok, J.T., Chan, J.H. and King, I. (eds.) Neural information processing: proceedings of 27th International conference on neural information processing 2020 (ICONIP 2020), part 5. Communications in computer and information science, 1333. Cham: Springer [online], pages, 458-467. Available from: https://doi.org/10.1007/978-3-030-63823-8_53

The field of object detection has witnessed great strides in recent years. With the wave of deep neural networks (DNN), many breakthroughs have achieved for the problems of object detection which previously were thought to be difficult. However, ther... Read More about Toward an ensemble of object detectors..

Computing students learning outcomes in learning by developing action model. (2020)
Conference Proceeding
LINTILÄ, T. and ZARB, M. 2020. Computing students learning outcomes in learning by developing action model. In Gómez Chova, L., López Martínez, A. and Candel Torres, I. (eds.) Proceedings of 13th International conference of education, research and innovation 2020 (ICERI2020), 9-10 November 2020, [virtual conference]. Valencia: IATED [online], pages 1936-1945. Available from: https://doi.org/10.21125/iceri.2020.0477

The purpose of this paper is to present the results of research aimed at finding out the learning outcomes of computing students with a study module implementation based on the Learning by Developing (LbD) Action Model used in Laurea University of Ap... Read More about Computing students learning outcomes in learning by developing action model..

Contextualisation of data flow diagrams for security analysis. (2020)
Conference Proceeding
FAILY, S., SCANDARIATO, R., SHOSTACK, A., SION, L. and KI-ARIES, D. 2020. Contextualisation of data flow diagrams for security analysis. In Eades, H. III and Gadyatskaya, O. (eds.) Graphical models for security: revised selected papers from the proceedings of the 7th International workshop on graphical models for security (GraMSec 2020), 22 June 2020, Boston, USA. Lecture notes in computer science, 12419. Cham: Springer [online], pages 186-197. Available from: https://doi.org/10.1007/978-3-030-62230-5_10

Data flow diagrams (DFDs) are popular for sketching systems for subsequent threat modelling. Their limited semantics make reasoning about them difficult, but enriching them endangers their simplicity and subsequent ease of take up. We present an appr... Read More about Contextualisation of data flow diagrams for security analysis..