All Outputs (1018)

The Architecture Decentralised Autonomous Organisation: a stigmergic exploration in architectural collaboration. (2022)
Conference Proceeding
DOUNAS, T., VOELLER, E., PROKOP, S. and VELE, J. 2022. The Architecture Decentralised Autonomous Organisation: a stigmergic exploration in architectural collaboration. In Pak, B., Wurzer, G. and Stouffs, R. (eds.) Co-creating the future: inclusion in and through design: proceedings of the 40th eCCADe (Education and Research in Computer Aided Architectural Design), 13-16 September 2022, Ghent, Belgium. Ghent: eCAADe, volume 1, pages 567-576. Hosted on CumInCad [online]. Available from: http://papers.cumincad.org/cgi-bin/works/Show?ecaade2022_246

We present "ArchiDAO", a decentralised Autonomous Organisation, i.e an architecture studio run on via smart contracts on the Ethereum blockchain. The objective of the paper is to offer a concise framework for the transformation of the way architectur... Read More about The Architecture Decentralised Autonomous Organisation: a stigmergic exploration in architectural collaboration..

Explaining and upsampling anomalies in time-series sensor data. (2022)
Conference Proceeding
PIRIE, C. 2022. Explaining and upsampling anomalies in time-series sensor data. In Reuss, P. and Schönborn, J. (eds.) Proceedings of the 30th Doctoral consortium of the international conference on case-based reasoning (ICCBR-DC 2022), co-located with the 30th International conference on case-based reasoning (ICCBR 2022), 12-15 September 2022, Nancy, France. CEUR workshop proceedings, 3418. Aachen: CEUR-WS [online], pages 16-21. Available from: https://ceur-ws.org/Vol-3418/ICCBR_2022_DC_paper13.pdf

The aims of this research was to improve anomaly detection methods in multi-sensor data by extending current re-sampling and explanation methods to work in a time-series setting. While there is a plethora of literature surrounding XAI for tabular dat... Read More about Explaining and upsampling anomalies in time-series sensor data..

Addressing trust and mutability issues in XAI utilising case based reasoning. (2022)
Conference Proceeding
SALIMI, P. 2022. Addressing trust and mutability issues in XAI utilising case based reasoning. In Reuss, P. and Schönborn, J. (eds.) Proceedings of the 30th Doctoral consortium of the international conference on case-based reasoning (ICCBR-DC 2022), co-located with the 30th International conference on case-based reasoning (ICCBR 2022), 12-15 September 2022, Nancy, France. CEUR workshop proceedings, 3418. Aachen: CEUR-WS [online], pages 22-27. Available from: https://ceur-ws.org/Vol-3418/ICCBR_2022_DC_paper19.pdf

Explainable AI (XAI) research is required to ensure that explanations are human readable and understandable. The present XAI approaches are useful for observing and comprehending some of the most important underlying properties of any Black-box AI mo... Read More about Addressing trust and mutability issues in XAI utilising case based reasoning..

CBR for interpretable response selection in conversational modelling. (2022)
Conference Proceeding
SURESH, M. 2022. CBR for interpretable response selection in conversational modelling. In Reuss, P. and Schönborn, J. (eds.) Proceedings of the 30th Doctoral consortium of the international conference on case-based reasoning (ICCBR-DC 2022), co-located with the 30th International conference on case-based reasoning (ICCBR 2022), 12-15 September 2022, Nancy, France. CEUR workshop proceedings, 3418. Aachen: CEUR-WS [online], pages 28-33. Available from: https://ceur-ws.org/Vol-3418/ICCBR_2022_DC_paper25.pdf

Current state-of-the-art dialogue systems are increasingly complex. When used in applications such as motivational interviewing, the lack of interpretability is a concern. CBR offers to bridge this gap by using the most similar past cases to decide t... Read More about CBR for interpretable response selection in conversational modelling..

Cross domain evaluation of text detection models. (2022)
Conference Proceeding
ALI-GOMBE, A., ELYAN, E., MORENO-GARCÍA, C. and JAYNE, C. 2022. Cross domain evaluation of text detection models. In Pimenidis, E., Angelov, P., Jayne, C., Papaleonidas, A. and Aydin, M. (eds.) Artificial neural networks and machine learning - ICANN 2022: proceedings of the 31st International conference on artificial neural networks (ICANN 2022), 6-9 September 2022, Bristol, UK, part III. Lecture notes in computer science, 13531. Cham: Springer [online], pages 50-61. Available from: https://doi.org/10.1007/978-3-031-15934-3_5

Text detection is a very common task across a wide range of domains, such as document image analysis, remote identity verification, amongst others. It is also considered an integral component of any text recognition system, where the performance of r... Read More about Cross domain evaluation of text detection models..

Reconsidering RepStat rules in dialectic games. (2022)
Conference Proceeding
WELLS, S. and SNAITH, M. 2022. Reconsidering RepStat rules in dialectical games. In Grasso, F., Green, N.L., Schneider, J. and Wells, S. (eds.) Proceedings of the 22nd Workshop on computational models of natural argument (CMNA 2022), 12 September 2022, Cardiff, UK. CEUR workshop proceedings, 3205. Aachen: CEUR-WS [online], pages 18-28. Available from: http://ceur-ws.org/Vol-3205/paper3.pdf

Prohibition of repeated statements has benefits for the tractability and predictability of dialogues carried out by machines, but doesn't match the real world behaviour of people. This gap between human and machine behaviour leads to problems when fo... Read More about Reconsidering RepStat rules in dialectic games..

Speckle pattern analysis of security holograms and related foils for quality assessment and authentication. (2022)
Conference Proceeding
KRISHNAN S., K., AMBADIYIL, S., JHA, A.K. and PRABHU, R. 2022. Speckle pattern analysis of security holograms and related foils for quality assessment and authentication. In Bouma, H., Prabhu, R., Stokes, R.J. and Yitzhaky, Y. (eds.) Counterterrorism, crime fighting, forensics, and surveillance technologies VI: proceedings of the 6th Counterterrorism, crime fighting, forensics, and surveillance technologies, co-located with SPIE (Society of Photo-optical Instrumentation Engineers) Security + defence conference 2022, 5-6 September 2022, Berlin, Germany. Proceedings of SPIE, 12275. Bellingham, WA: SPIE [online], article 1227509. Available from: https://doi.org/10.1117/12.2635446

A speckle pattern is produced by the mutual interference of a set of coherent wavefronts. Speckle patterns typically occur in diffuse reflections of monochromatic light such a laser light. When a rough surface is illuminated by a coherent light is im... Read More about Speckle pattern analysis of security holograms and related foils for quality assessment and authentication..

A simulation into the physical and network layers of optical communication network for the subsea video surveillance of illicit activity. (2022)
Conference Proceeding
STEWART, C., FOUGH, N. and PRABHU, R. 2022. A simulation into the physical and network layers of optical communication network for the subsea video surveillance of illicit activity. In Bouma, H., Prabhu, R., Stokes, R.J. and Yitzhaky, Y. (eds.) Counterterrorism, crime fighting, forensics, and surveillance technologies VI: proceedings of the 6th Counterterrorism, crime fighting, forensics, and surveillance technologies, co-located with SPIE (Society of Photo-optical Instrumentation Engineers) Security + defence conference 2022, 5-6 September 2022, Berlin, Germany. Proceedings of SPIE, 12275. Bellingham, WA: SPIE [online], article 1227508. Available from: https://doi.org/10.1117/12.2641374

Criminal activity is increasingly entering the ocean subsurface with acts such as illegal fishing and narco-submarining becoming points of contention. This among other illicit acts taking place in this domain imply a need for surveillance to render t... Read More about A simulation into the physical and network layers of optical communication network for the subsea video surveillance of illicit activity..

An investigation into routing protocols for real-time sensing of subsurface oil wells. (2022)
Conference Proceeding
STEWART, C., FOUGH, N. and PRABHU, R. 2022. An investigation into routing protocols for real-time sensing of subsurface oil wells. In Valle, M., Lehmhus, D., Gianoglio, C. et al. (eds.) Advances in system-integrated intelligence: proceedings of the 6th International conference on system-integrated intelligence 2022 (SysInt 2022), 7-9 September 2022, Genova, Italy. Lecture notes in networks and systems (LNNS), 546. Cham: Springer [online], pages 689-699. Available from: https://doi.org/10.1007/978-3-031-16281-7_65

Pervasive computing has transformed society, and there is a desire to extend this mass data connectivity to the ocean, especially by energy companies seeking real-time sensor data from assets such as oil wells and pipelines. As evidenced by the Deepw... Read More about An investigation into routing protocols for real-time sensing of subsurface oil wells..

Automated tonic-clonic seizure detection using random forests and spectral analysis on electroencephalography data. (2022)
Conference Proceeding
STEWART, C., FUNG, W.K., FOUGH, N. and PRABHU, R. 2022. Automated tonic-clonic seizure detection using random forests and spectral analysis on electroencephalography data. In Valle, M., Lehmhus, D., Gianoglio, C. et al. (eds.) Advances in system-integrated intelligence: proceedings of the 6th International conference on system-integrated intelligence 2022 (SysInt 2022), 7-9 September 2022, Genova, Italy. Lecture notes in networks and systems (LNNS), 546. Cham: Springer [online], pages 679-688. Available from: https://doi.org/10.1007/978-3-031-16281-7_64

Artificial intelligence (AI) has a potential for impact in the diagnosis of neurological conditions, the academic consensus generally has a positive outlook regarding how AI can improve the care of stroke victims and those who suffer from neuro-degen... Read More about Automated tonic-clonic seizure detection using random forests and spectral analysis on electroencephalography data..

Cutting strategy of polymer composite material for aerospace engineering application. (2022)
Conference Proceeding
SANI, A.S.A., ZAINUDDIN, A.Z. and SAHARUDIN, M.S. 2022. Cutting strategy of polymer composite material for aerospace engineering application. In Sani, A.S.A., Zahid, M.N.O., Yasin, M.R.M., Ismail, S.Z., Zawawi, M.Z.M., Manaf, A.R.A., Saffe, S.N.M., Aziz, R.A. and Turan, F.M. (eds.) Enabling industry 4.0 through advances in manufacturing and materials: selected articles from the proceedings of the 2021 Innovative manufacturing, mechatronics and materials forum (iM3F 2021), 20 September 2021, Pekan, Malaysia. Singapore: Springer [online], pages 543-552. Available from: https://doi.org/10.1007/978-981-19-2890-1_51

Despite the popular use of hybrid fibers in polymer composite in aerospace applications, it comes with a price where it is expensive and has a complex process to produce. A new alternative method of using nanocomposite using natural fiber such as Epo... Read More about Cutting strategy of polymer composite material for aerospace engineering application..

A case-based approach for content planning in data-to-text generation. (2022)
Conference Proceeding
UPADHYAY, A. and MASSIE, S. 2022. A case-based approach for content planning in data-to-text generation. In Keane, M.T. and Wiratunga, N. (eds.) Case-based reasoning research and development: proceedings of the 30th International conference on case-based reasoning (ICCBR 2022), 12-15 September 2022, Nancy, France. Lecture notes in computer science, 13405. Cham: Springer [online], pages 380-394. Available from: https://doi.org/10.1007/978-3-031-14923-8_25

The problem of Data-to-Text Generation (D2T) is usually solved using a modular approach by breaking the generation process into some variant of planning and realisation phases. Traditional methods have been very good at producing high quality texts b... Read More about A case-based approach for content planning in data-to-text generation..

How close is too close? Role of feature attributions in discovering counterfactual explanations. (2022)
Conference Proceeding
WIJEKOON, A., WIRATUNGA, N., NKISI-ORJI, I., PALIHAWADANA, C., CORSAR, D. and MARTIN, K. 2022. How close is too close? Role of feature attributions in discovering counterfactual explanations. In Keane, M.T. and Wiratunga, N. (eds.) Case-based reasoning research and development: proceedings of the 30th International conference on case-based reasoning (ICCBR 2022), 12-15 September 2022, Nancy, France. Lecture notes in computer science, 13405. Cham: Springer [online], pages 33-47. Available from: https://doi.org/10.1007/978-3-031-14923-8_3

Counterfactual explanations describe how an outcome can be changed to a more desirable one. In XAI, counterfactuals are "actionable" explanations that help users to understand how model decisions can be changed by adapting features of an input. A cas... Read More about How close is too close? Role of feature attributions in discovering counterfactual explanations..

Adapting semantic similarity methods for case-based reasoning in the Cloud. (2022)
Conference Proceeding
NKISI-ORJI, I., PALIHAWADANA, C., WIRATUNGA, N., CORSAR, D. and WIJEKOON, A. 2022. Adapting semantic similarity methods for case-based reasoning in the Cloud. In Keane, M.T. and Wiratunga, N. (eds.) Case-based reasoning research and development: proceedings of the 30th International conference on case-based reasoning (ICCBR 2022), 12-15 September 2022, Nancy, France. Lecture notes in computer science, 13405. Cham: Springer [online], pages 125-139. Available from: https://doi.org/10.1007/978-3-031-14923-8_9

CLOOD is a cloud-based CBR framework based on a microservices architecture, which facilitates the design and deployment of case-based reasoning applications of various sizes. This paper presents advances to the similarity module of CLOOD through the... Read More about Adapting semantic similarity methods for case-based reasoning in the Cloud..

Analysing the fitness landscape rotation for combinatorial optimisation. (2022)
Conference Proceeding
ALZA, J., BARTLETT, M., CEBERIO, J. and MCCALL, J. 2022. Analysing the fitness landscape rotation for combinatorial optimisation. In Rudolph, G., Kononova, A.V., Aguirre, H., Kerschke, P., Ochoa, G. and Tušar, T. (eds.) Parallel problem solving from nature (PPSN XVII): proceedings of 17th Parallel problem solving from nature international conference 2022 (PPSN 2022), 10-14 September 2022, Dortmund, Germany. Lecture notes in computer science, 13398. Cham: Springer [online], pages 533-547. Available from: https://doi.org/10.1007/978-3-031-14714-2_37

Fitness landscape rotation has been widely used in the field of dynamic combinatorial optimisation to generate test problems with academic purposes. This method changes the mapping between solutions and objective values, but preserves the structure o... Read More about Analysing the fitness landscape rotation for combinatorial optimisation..

Case-based reasoning research and development: proceedings of the 30th International conference on case-based reasoning (ICCBR 2022). (2022)
Conference Proceeding
KEANE, M.T. and WIRATUNGA, N. (eds.) 2022. Case-based reasoning research and development: proceedings of the 30th International conference on case-based reasoning (ICCBR 2022), 12-15 September 2022, Nancy, France. Lecture notes in computer science, 13405. Cham: Springer [online]. Available from: https://doi.org/10.1007/978-3-031-14923-8

This volume contains the papers presented at the 30th International Conference on Case-Based Reasoning (ICCBR 2022), which was held during September 12–15, 2022, at LORIA in Nancy, France. ICCBR is the premier annual meeting of the Case-Based Reasoni... Read More about Case-based reasoning research and development: proceedings of the 30th International conference on case-based reasoning (ICCBR 2022)..

MIRATAR: a virtual caregiver for active and healthy ageing. (2022)
Conference Proceeding
SANTOFIMIA, M.J., VILLANUEVA, F.J., DORADO, J., RUBIO, A., FERNÁNDEZ-BERMEJO, J., LLUMIGUANO, H., DEL TORO, X., WIRATUNGA, N. and LOPEZ, J.C. 2022. MIRATAR: a virtual caregiver for active and healthy ageing. In Mazzeo, P.L., Frontoni, E., Sclaroff, S. and Distante, C. (eds.) Image analysis and processing: ICIAP 2022 workshops; revised selected papers from the proceedings of the 21st International conference on image analysis and processing (ICIAP 2022) international workshops, 23-27 May 2022, Lecce, Italy, part I. Lecture notes in computer science, 13373. Cham: Springer [online], pages 49-58. Available from: https://doi.org/10.1007/978-3-031-13321-3_5

Despite the technology advances in the field of virtual assistant and activity monitoring devices, older adults are still reluctant to embrace this technology, specially when it comes to employ it to manage health-related issues. This paper presents... Read More about MIRATAR: a virtual caregiver for active and healthy ageing..

Sentiment analysis of ASOS product reviews using machine learning algorithms by comparing several models. (2022)
Conference Proceeding
SOUNDEARAJAH, S. and ASANKA, P.P.G.D. 2022. Sentiment analysis of ASOS product reviews using machine learning algorithms by comparing several models. In Proceedings of 2022 International research conference on Smart computing and systems engineering (SCSE 2022), 1 September 2022, Colombo, Sri Lanka. Hosted on IEEE [online], pages 143-150. Available from: https://doi.org/10.1109/scse56529.2022.9905147

Digital ratings are crucial in improving international customer communications and impacting consumer purchasing trends. To obtain important data from a massive number of customer reviews, they must be sorted into positive and negative opinions. Sent... Read More about Sentiment analysis of ASOS product reviews using machine learning algorithms by comparing several models..

TransSLC: skin lesion classification in dermatoscopic images using transformers. (2022)
Conference Proceeding
SARKER, M.M.K., MORENO-GARCÍA, C.F., REN, J. and ELYAN, E. 2022. TransSLC: skin lesion classification in dermatoscopic images using transformers. In Yang, G., Aviles-Rivero, A., Roberts, M. and Schönlieb, C.-B. (eds.) Medical image understanding and analysis: proceedings of 26th Medical image understanding and analysis 2022 (MIUA 2022), 27-29 July 2022, Cambridge, UK. Lecture notes in computer sciences, 13413. Cham: Springer [online], pages 651-660. Available from: https://doi.org/10.1007/978-3-031-12053-4_48

Early diagnosis and treatment of skin cancer can reduce patients' fatality rates significantly. In the area of computer-aided diagnosis (CAD), the Convolutional Neural Network (CNN) has been widely used for image classification, segmentation, and rec... Read More about TransSLC: skin lesion classification in dermatoscopic images using transformers..

Ensemble of deep learning models with surrogate-based optimization for medical image segmentation. (2022)
Conference Proceeding
DANG, T., LUONG, A.V., LIEW, A.W.C., MCCALL, J. and NGUYEN, T.T. 2022. Ensemble of deep learning models with surrogate-based optimization for medical image segmentation. In 2022 IEEE (Institute of Electrical and Electronics Engineers) Congress on evolutionary computation (CEC 2022), co-located with 2022 IEEE International joint conferences on neural networks (IJCNN 2022), 2022 IEEE International conference on fuzzy systems (FUZZ-IEEE 2022), 18-23 July 2022, Padua, Italy. Piscataway: IEEE (online), article #1030. Available from: https://doi.org/10.1109/CEC55065.2022.9870389

Deep Neural Networks (DNNs) have created a breakthrough in medical image analysis in recent years. Because clinical applications of automated medical analysis are required to be reliable, robust and accurate, it is necessary to devise effective DNNs... Read More about Ensemble of deep learning models with surrogate-based optimization for medical image segmentation..