All Outputs (526)

Performance analysis of vertical handover using predictable LGD event based on IEEE 802.21. (2021)
Conference Proceeding
HAJAR, M.S., CHAHINE, M.K., HAMDAN, R. and QDAH, M.S. 2021. Performance analysis of vertical handover using predictable LGD event based on IEEE 802.21. In Proceedings of the 2021 IEEE International conference on communications workshops (ICC workshops 2021), 14-23 June 2021, Montreal, Canada. Piscataway: IEEE [online], 9473639. Available from: https://doi.org/10.1109/ICCWorkshops50388.2021.9473639

Next Generation Wireless Networks (NGWN) aim to provide any service at any time and anywhere with seamless mobility between homogeneous and heterogeneous networks. IEEE defines the IEEE 802.21 standard to facilitate seamless handover, namely, Media I... Read More about Performance analysis of vertical handover using predictable LGD event based on IEEE 802.21..

Non-deterministic solvers and explainable AI through trajectory mining. (2021)
Conference Proceeding
FYVIE, M., MCCALL, J.A.W. and CHRISTIE, L.A. 2021. Non-deterministic solvers and explainable AI through trajectory mining. In Martin, K., Wiratunga, N. and Wijekoon, A. (eds.) SICSA XAI workshop 2021: proceedings of 2021 SICSA (Scottish Informatics and Computer Science Alliance) eXplainable artificial intelligence workshop (SICSA XAI 2021), 1st June 2021, [virtual conference]. CEUR workshop proceedings, 2894. Aachen: CEUR-WS [online], session 4, pages 75-78. Available from: http://ceur-ws.org/Vol-2894/poster2.pdf

Traditional methods of creating explanations from complex systems involving the use of AI have resulted in a wide variety of tools available to users to generate explanations regarding algorithm and network designs. This however has traditionally bee... Read More about Non-deterministic solvers and explainable AI through trajectory mining..

Counterfactual explanations for student outcome prediction with Moodle footprints. (2021)
Conference Proceeding
WIJEKOON, A., WIRATUNGA, N., NKILSI-ORJI, I., MARTIN, K., PALIHAWADANA, C. and CORSAR, D. 2021. Counterfactual explanations for student outcome prediction with Moodle footprints. In Martin, K., Wiratunga, N. and Wijekoon, A. (eds.) SICSA XAI workshop 2021: proceedings of 2021 SICSA (Scottish Informatics and Computer Science Alliance) eXplainable artificial intelligence workshop (SICSA XAI 2021), 1st June 2021, [virtual conference]. CEUR workshop proceedings, 2894. Aachen: CEUR-WS [online], session 1, pages 1-8. Available from: http://ceur-ws.org/Vol-2894/short1.pdf

Counterfactual explanations focus on “actionable knowledge” to help end-users understand how a machine learning outcome could be changed to one that is more desirable. For this purpose a counterfactual explainer needs to be able to reason with simila... Read More about Counterfactual explanations for student outcome prediction with Moodle footprints..

ConfIs: a tool for privacy and security analysis and conflict resolution for supporting GDPR compliance through privacy-by-design. (2021)
Conference Proceeding
ALKUBAISY, D., PIRAS, L., AL-OBEIDALLAH, M.G., COX, K. and MOURATIDIS, H. 2021. ConfIs: a tool for privacy and security analysis and conflict resolution for supporting GDPR compliance through privacy-by-design. In Ali, R., Kaindl, H. and Maciaszek, L. (eds.) Proceedings of 16th Evaluation of novel approaches to software engineering international conference 2021 (ENASE 2021), 26-27 April 2021, [virtual conference]. Setúbal, Portugal: SciTePress [online], pages 80-91. Available from: https://doi.org/10.5220/0010406100800091

Privacy and security requirements, and their potential conflicts, are increasingly having more and more importance. It is becoming a necessary part to be considered, starting from the very early stages of requirements engineering, and in the entire s... Read More about ConfIs: a tool for privacy and security analysis and conflict resolution for supporting GDPR compliance through privacy-by-design..

Effective detection of cyber attack in a cyber-physical power grid system. (2021)
Conference Proceeding
OTOKWALA, U., PETROVSKI, A. and KALUTARAGE, H. 2021. Effective detection of cyber attack in a cyber-physical power grid system. In Arai, K. (ed) Advances in information and communication: proceedings of Future of information and communication conference (FICC 2021), 29-30 April 2021, Vancouver, Canada. Advances in intelligent systems and computing, 1363. Cham: Springer [online], 1, pages 812-829. Available from: https://doi.org/10.1007/978-3-030-73100-7_57

Advancement in technology and the adoption of smart devices in the operation of power grid systems have made it imperative to ensure adequate protection for the cyber-physical power grid system against cyber-attacks. This is because, contemporary cyb... Read More about Effective detection of cyber attack in a cyber-physical power grid system..

VEGAS: a variable length-based genetic algorithm for ensemble selection in deep ensemble learning. (2021)
Conference Proceeding
HAN, K., PHAM, T., VU, T.H., DANG, T., MCCALL, J. and NGUYEN, T.T. 2021. VEGAS: a variable length-based genetic algorithm for ensemble selection in deep ensemble learning. In Nguyen, N.T., Chittayasothorn, S., Niyato, D. and Trawiński, B. (eds.) Intelligent information and database systems: proceedings of the 13th Asian conference on intelligent information and database systems 2021 (ACCIIDS 2021), 7-10 April 2021, [virtual conference]. Lecture Notes in Computer Science, 12672. Cham: Springer [online], pages 168–180. Available from: https://doi.org/10.1007/978-3-030-73280-6_14

In this study, we introduce an ensemble selection method for deep ensemble systems called VEGAS. The deep ensemble models include multiple layers of the ensemble of classifiers (EoC). At each layer, we train the EoC and generates training data for th... Read More about VEGAS: a variable length-based genetic algorithm for ensemble selection in deep ensemble learning..

Convolutional network based animal recognition using YOLO and darknet. (2021)
Conference Proceeding
REDDY, B.K., BANO, S., REDDY, G.G., KOMMINENI, R. and REDDY, P.Y. 2021. Convolutional network based animal recognition using YOLO and darknet. In Proceedings of the 6th International conference on inventive computation technologies (ICICT 2021), 20-22 January 2021, Coimbatore, India. Piscataway: IEEE [online], pages 1198-1203. Available from: https://doi.org/10.1109/ICICT50816.2021.9358620

In general, the manual detection of animals with their names is a very tedious task. To overcome this challenge, this research work has developed a YOLOV3 model to identify the animal present in the image given by user. The algorithm used in YOLOV3 m... Read More about Convolutional network based animal recognition using YOLO and darknet..

Similarity score of two images using different measures. (2021)
Conference Proceeding
APPANA, V., GUTTIKONDA, T.M., SHREE, D., BANO, S. and KURRA, H. 2021. Similarity score of two images using different measures. In Proceedings of the 6th International conference on inventive computation technologies (ICICT 2021), 20-22 January 2021, Coimbatore, India. Piscataway: IEEE [online], pages 741-746. Available from: https://doi.org/10.1109/ICICT50816.2021.9358789

In the field of computer vision and image processing, image similarity has been a central concern for decades. If you compare two pictures, Image Similarity returns a value that tells you how physically they are close. A quantitative measure of the d... Read More about Similarity score of two images using different measures..

LTMS: a lightweight trust management system for wireless medical sensor networks. (2021)
Conference Proceeding
HAJAR, M.S., AL-KADRI, M.O. and KALUTARAGE, H. 2020. LTMS: a lightweight trust management system for wireless medical sensor networks. In Wang, G., Ko, R., Bhuiyan, M.Z.A. and Pan, Y. (eds.). Proceedings of 19th Institute of Electrical and Electronics Engineers (IEEE) Trust, security and privacy in computing and communication international conference 2020 (TrustCom 2020), 29 Dec 2020 - 1 Jan 2021, Guangzhou, China. Piscataway: IEEE [online], pages 1783-1790. Available from: https://doi.org/10.1109/TrustCom50675.2020.00245

Wireless Medical Sensor Networks (WMSNs) offer ubiquitous health applications that enhance patients' quality of life and support national health systems. Detecting internal attacks on WMSNs is still challenging since cryptographic measures can not pr... Read More about LTMS: a lightweight trust management system for wireless medical sensor networks..

Resource efficient boosting method for IoT security monitoring. (2021)
Conference Proceeding
ZAKARIYYA, I., AL-KADRI, M.O. and KALUTARAGE, H. 2021. Resource efficient boosting method for IoT security monitoring. In Proceedings of 18th Institute of Electrical and Electronics Engineers (IEEE) Consumer communications and networking conference 2021 (CCNC 2021), 9-12 January 2021, [virtual conference]. Piscataway: IEEE [online], article 9369620. Available from: https://doi.org/10.1109/ccnc49032.2021.9369620

Machine learning (ML) methods are widely proposed for security monitoring of Internet of Things (IoT). However, these methods can be computationally expensive for resource constraint IoT devices. This paper proposes an optimized resource efficient ML... Read More about Resource efficient boosting method for IoT security monitoring..

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..

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..

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..

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..

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..

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..