Computer Science
| Title | Computer Science |
|---|---|
| Alternative | S&T - CS |
| Faculty | Faculty of Science and Technology |
Latest research outputs
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Malignant Mesothelioma subtyping of tissue images via sampling driven multiple instance prediction
Eastwood, M., Marc, S., Gao, X., Sailem, H., Offman, J., Karteris, E., Montero Fernandez, A., Jonigk, D., Cookson, W., Moffatt, M., Popat, S., Minhas, F. and Robertus, J. 2022. Malignant Mesothelioma subtyping of tissue images via sampling driven multiple instance prediction. Michalowski, M., Abidi, S. and Abidi, S. (ed.) 20th International Conference on Artificial Intelligence in Medicine. Halifax, Canada 14 - 17 Jun 2022 Springer. https://doi.org/10.1007/978-3-031-09342-5_25Conference paper
Cyber-threat detection system using a hybrid approach of transfer learning and multi-model image representation
Ullah, F., Ullah, S., Naeem, M., Mostarda, L., Rho, S. and Cheng, X. 2022. Cyber-threat detection system using a hybrid approach of transfer learning and multi-model image representation. Sensors. 22 (15), pp. 1-26. https://doi.org/10.3390/s22155883Article
Visual analytics of contact tracing policy simulations during an emergency response
Sondag, M., Turkay, C., Xu, K., Matthews, L., Mohr, S. and Archambault, D. 2022. Visual analytics of contact tracing policy simulations during an emergency response. Computer Graphics Forum. 41 (3), pp. 29-41. https://doi.org/10.1111/cgf.14520Article
A deep convolutional neural network stacked ensemble for malware threat classification in internet of things
Naeem, H., Cheng, X., Ullah, F., Jabbar, S. and Dong, S. 2022. A deep convolutional neural network stacked ensemble for malware threat classification in internet of things. Journal of Circuits, Systems and Computers. 31 (17). https://doi.org/10.1142/s0218126622503029Article
An introduction of a modular framework for securing 5G networks and beyond
Edris, E., Aiash, M. and Loo, J. 2022. An introduction of a modular framework for securing 5G networks and beyond. Network. 2 (3), pp. 419-439. https://doi.org/10.3390/network2030026Article
Novel group handover mechanism for cooperative and coordinated mobile femtocells technology in railway environment
Raheem, R., Lasebae, A. and Raheem, A. 2022. Novel group handover mechanism for cooperative and coordinated mobile femtocells technology in railway environment. Array. 15. https://doi.org/10.1016/j.array.2022.100223Article
RFAP: a revocable fine-grained access control mechanism for autonomous vehicle platoon
Zhao, Y., Wang, Y., Cheng, X., Chen, H., Yu, H. and Ren, Y. 2022. RFAP: a revocable fine-grained access control mechanism for autonomous vehicle platoon. IEEE Transactions on Intelligent Transportation Systems. 23 (7), pp. 9668-9679. https://doi.org/10.1109/TITS.2021.3105458Article
Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning
Pavlović, T., Azevedo, F., De, K., Riaño-Moreno, J., Maglić, M., Gkinopoulos, T., Donnelly-Kehoe, P., Payán-Gómez, C., Huang, G., Kantorowicz, J., Birtel, M., Schönegger, P., Capraro, V., Santamaría-García, H., Yucel, M., Ibanez, A., Rathje, S., Wetter, E., Stanojević, D., van Prooijen, J., Hesse, E., Elbaek, C., Franc, R., Pavlović, Z., Mitkidis, P., Cichocka, A., Gelfand, M., Alfano, M., Ross, R., Sjåstad, H., Nezlek, J., Cislak, A., Lockwood, P., Abts, K., Agadullina, E., Amodio, D., Apps, M., Aruta, J., Besharati, S., Bor, A., Choma, B., Cunningham, W., Ejaz, W., Farmer, H., Findor, A., Gjoneska, B., Gualda, E., Huynh, T., Imran, M., Israelashvili, J., Kantorowicz-Reznichenko, E., Krouwel, A., Kutiyski, Y., Laakasuo, M., Lamm, C., Levy, J., Leygue, C., Lin, M., Mansoor, M., Marie, A., Mayiwar, L., Mazepus, H., McHugh, C., Olsson, A., Otterbring, T., Packer, D., Palomäki, J., Perry, A., Petersen, M., Puthillam, A., Rothmund, T., Schmid, P., Stadelmann, D., Stoica, A., Stoyanov, D., Stoyanova, K., Tewari, S., Todosijević, B., Torgler, B., Tsakiris, M., Tung, H., Umbreș, R., Vanags, E., Vlasceanu, M., Vonasch, A., Zhang, Y., Abad, M., Adler, E., Mdarhri, H., Antazo, B., Ay, F., Ba, M., Barbosa, S., Bastian, B., Berg, A., Białek, M., Bilancini, E., Bogatyreva, N., Boncinelli, L., Booth, J., Borau, S., Buchel, O., de Carvalho, C., Celadin, T., Cerami, C., Chalise, H., Cheng, X., Cian, L., Cockcroft, K., Conway, J., Córdoba-Delgado, M., Crespi, C., Crouzevialle, M., Cutler, J., Cypryańska, M., Dabrowska, J., Davis, V., Minda, J., Dayley, P., Delouvée, S., Denkovski, O., Dezecache, G., Dhaliwal, N., Diato, A., Di Paolo, R., Dulleck, U., Ekmanis, J., Etienne, T., Farhana, H., Farkhari, F., Fidanovski, K., Flew, T., Fraser, S., Frempong, R., Fugelsang, J., Gale, J., García-Navarro, E., Garladinne, P., Gray, K., Griffin, S., Gronfeldt, B., Gruber, J., Halperin, E., Herzon, V., Hruška, M., Hudecek, M., Isler, O., Jangard, S., Jørgensen, F., Keudel, O., Koppel, L., Koverola, M., Kunnari, A., Leota, J., Lermer, E., Li, C., Longoni, C., McCashin, D., Mikloušić, I., Molina-Paredes, J., Monroy-Fonseca, C., Morales-Marente, E., Moreau, D., Muda, R., Myer, A., Nash, K., Nitschke, J., Nurse, M., de Mello, V., Palacios-Galvez, M., Pan, Y., Papp, Z., Pärnamets, P., Paruzel-Czachura, M., Perander, S., Pitman, M., Raza, A., Rêgo, G., Robertson, C., Rodríguez-Pascual, I., Saikkonen, T., Salvador-Ginez, O., Sampaio, W., Santi, G., Schultner, D., Schutte, E., Scott, A., Skali, A., Stefaniak, A., Sternisko, A., Strickland, B., Thomas, J., Tinghög, G., Traast, I., Tucciarelli, R., Tyrala, M., Ungson, N., Uysal, M., Van Rooy, D., Västfjäll, D., Vieira, J., von Sikorski, C., Walker, A., Watermeyer, J., Willardt, R., Wohl, M., Wójcik, A., Wu, K., Yamada, Y., Yilmaz, O., Yogeeswaran, K., Ziemer, C., Zwaan, R., Boggio, P., Whillans, A., Van Lange, P., Prasad, R., Onderco, M., O'Madagain, C., Nesh-Nash, T., Laguna, O., Kubin, E., Gümren, M., Fenwick, A., Ertan, A., Bernstein, M., Amara, H. and Van Bavel, J. 2022. Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning. PNAS Nexus. 1 (3), pp. 1-15. https://doi.org/10.1093/pnasnexus/pgac093Article
Securing future healthcare environments in a post-COVID-19 world: moving from frameworks to prototypes
Vithanwattana, N., Karthick, G., Mapp, G., George, C. and Samuels, A. 2022. Securing future healthcare environments in a post-COVID-19 world: moving from frameworks to prototypes. Journal of Reliable Intelligent Environments. 8 (3), pp. 299-315. https://doi.org/10.1007/s40860-022-00180-7Article
Adaptive weighted dynamic differential evolution algorithm for emergency material allocation and scheduling
Wang, T., Wu, K., Du, T. and Cheng, X. 2022. Adaptive weighted dynamic differential evolution algorithm for emergency material allocation and scheduling. Computational Intelligence. 38 (3), pp. 714-730. https://doi.org/10.1111/coin.12389Article
An explainable AI-based intrusion detection system for DNS over HTTPS (DoH) attacks
Zebin, T., Rezvy, S. and Luo, Y. 2022. An explainable AI-based intrusion detection system for DNS over HTTPS (DoH) attacks. IEEE Transactions on Information Forensics and Security. 17, pp. 2339-2349. https://doi.org/10.1109/TIFS.2022.3183390Article
Introduction to the Proceedings of WoRIE’22
Rodríguez-Domínguez, C., Santokhee, A., Hornos, M. and Augusto, J. 2022. Introduction to the Proceedings of WoRIE’22. in: Alvarez Valera, H. and Luštrek, M. (ed.) Intelligent Environments 2022: Workshops at 18th International Conference on Intelligent Environments (IE2022) IOS Press.Book chapter
Communicating the standardisation process and cybersecurity standards to undergraduate students
Whitney, G. 2022. Communicating the standardisation process and cybersecurity standards to undergraduate students. Jakobs, K. (ed.) 26th EURAS (European Academy for Standardisation e.V) Conference. Glasgow, UK 08 - 10 Jun 2022 Aachen, Germany Mainz Publishers. pp. 365-373Conference paper
Explanation by automated reasoning using the Isabelle Infrastructure framework
Kammueller, F. 2022. Explanation by automated reasoning using the Isabelle Infrastructure framework. Chen, J.Y.C., Fragomeni, G., Degen, H. and Ntoa, S. (ed.) HCII 2022: 24th International Conference on Human-Computer Interaction. Virtual 26 Jun - 01 Jul 2022 Springer. pp. 307-318 https://doi.org/10.1007/978-3-031-21707-4_22Conference paper
Identification of human papillomavirus from super resolution microscopic images generated using deep learning architectures
Gao, X., Wen, S., Li, D., Liu, W., Xiong, J., Xu, B., Liu, J., Zhang, H. and Liu, X. 2022. Identification of human papillomavirus from super resolution microscopic images generated using deep learning architectures. in: Wani, M. and Palade, V. (ed.) Deep Learning Applications, Volume 4 Springer.Book chapter
Differential cost analysis with simultaneous potentials and anti-potentials
Žikelić, Ð., Chang, B., Bolignano, P. and Raimondi, F. 2022. Differential cost analysis with simultaneous potentials and anti-potentials. 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation. San Diego, USA 13 - 17 Jun 2022 Association for Computing Machinery (ACM). pp. 442-457 https://doi.org/10.1145/3519939.3523435Conference paper
Exploring new traffic prediction models to build an intelligent transport system for Smart Cities
Mehta, V., Mapp, G. and Gandhi, V. 2022. Exploring new traffic prediction models to build an intelligent transport system for Smart Cities. NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium. Budapest, Hungary 25 - 29 Apr 2022 IEEE. pp. 1-6 https://doi.org/10.1109/NOMS54207.2022.9789926Conference paper
RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses
Chen, M., Abdul-Rahman, A., Archambault, D., Dykes, J., Ritsos, P., Slingsby, A., Torsney-Weir, T., Turkay, C., Bach, B., Borgo, R., Brett, A., Fang, H., Jianu, R., Khan, S., Laramee, R., Matthews, L., Nguyen, P., Reeve, R., Roberts, J., Vidal, F., Wang, Q., Wood, J. and Xu, K. 2022. RAMPVIS: Answering the challenges of building visualisation capabilities for large-scale emergency responses. Epidemics. 39. https://doi.org/10.1016/j.epidem.2022.100569Article
Engineering context updates
Augusto, J. 2022. Engineering context updates. 5th Citizen-Centric Smart Cities Services (CCSCS'2022) Workshop. Biarritz, France 20 - 21 Jun 2022 IOS Press. pp. 293-301 https://doi.org/10.3233/aise220056Conference paper
National identity predicts public health support during a global pandemic
Van Bavel, J., Cichocka, A., Capraro, V., Sjåstad, H., Nezlek, J., Pavlović, T., Alfano, M., Gelfand, M., Azevedo, F., Birtel, M., Cislak, A., Lockwood, P., Ross, R., Abts, K., Agadullina, E., Aruta, J., Besharati, S., Bor, A., Choma, B., Crabtree, C., Cunningham, W., De, K., Ejaz, W., Elbaek, C., Findor, A., Flichtentrei, D., Franc, R., Gjoneska, B., Gruber, J., Gualda, E., Horiuchi, Y., Huynh, T., Ibanez, A., Imran, M., Israelashvili, J., Jasko, K., Kantorowicz, J., Kantorowicz-Reznichenko, E., Krouwel, A., Laakasuo, M., Lamm, C., Leygue, C., Lin, M., Mansoor, M., Marie, A., Mayiwar, L., Mazepus, H., McHugh, C., Minda, J., Mitkidis, P., Olsson, A., Otterbring, T., Packer, D., Perry, A., Petersen, M., Puthillam, A., Riaño-Moreno, J., Rothmund, T., Santamaría-García, H., Schmid, P., Stoyanov, D., Tewari, S., Todosijević, B., Tsakiris, M., Tung, H., Umbreș, R., Vanags, E., Vlasceanu, M., Vonasch, A., Yucel, M., Zhang, Y., Abad, M., Adler, E., Akrawi, N., Mdarhri, H., Amara, H., Amodio, D., Antazo, B., Apps, M., Ay, F., Ba, M., Barbosa, S., Bastian, B., Berg, A., Bernal-Zárate, M., Bernstein, M., Białek, M., Bilancini, E., Bogatyreva, N., Boncinelli, L., Booth, J., Borau, S., Buchel, O., Cameron, C., Carvalho, C., Celadin, T., Cerami, C., Chalise, H., Cheng, X., Cian, L., Cockcroft, K., Conway, J., Córdoba-Delgado, M., Crespi, C., Crouzevialle, M., Cutler, J., Cypryańska, M., Dabrowska, J., Daniels, M., Davis, V., Dayley, P., Delouvee, S., Denkovski, O., Dezecache, G., Dhaliwal, N., Diato, A., Di Paolo, R., Drosinou, M., Dulleck, U., Ekmanis, J., Ertan, A., Etienne, T., Farhana, H., Farkhari, F., Farmer, H., Fenwick, A., Fidanovski, K., Flew, T., Fraser, S., Frempong, R., Fugelsang, J., Gale, J., Garcia-Navarro, E., Garladinne, P., Ghajjou, O., Gkinopoulos, T., Gray, K., Griffin, S., Gronfeldt, B., Gümren, M., Gurung, R., Halperin, E., Harris, E., Herzon, V., Hruška, M., Huang, G., Hudecek, M., Isler, O., Jangard, S., Jørgensen, F., Kachanoff, F., Kahn, J., Dangol, A., Keudel, O., Koppel, L., Koverola, M., Kubin, E., Kunnari, A., Kutiyski, Y., Laguna, O., Leota, J., Lermer, E., Levy, J., Levy, N., Li, C., Long, E., Longoni, C., Maglić, M., McCashin, D., Metcalf, A., Mikloušić, I., El Mimouni, S., Miura, A., Molina-Paredes, J., Monroy-Fonseca, C., Morales-Marente, E., Moreau, D., Muda, R., Myer, A., Nash, K., Nesh-Nash, T., Nitschke, J., Nurse, M., Ohtsubo, Y., Oldemburgo de Mello, V., O’Madagain, C., Onderco, M., Palacios-Galvez, M., Palomäki, J., Pan, Y., Papp, Z., Pärnamets, P., Paruzel-Czachura, M., Pavlović, Z., Payán-Gómez, C., Perander, S., Pitman, M., Prasad, R., Pyrkosz-Pacyna, J., Rathje, S., Raza, A., Rêgo, G., Rhee, K., Robertson, C., Rodríguez-Pascual, I., Saikkonen, T., Salvador-Ginez, O., Sampaio, W., Santi, G., Santiago-Tovar, N., Savage, D., Scheffer, J., Schönegger, P., Schultner, D., Schutte, E., Scott, A., Sharma, M., Sharma, P., Skali, A., Stadelmann, D., Stafford, C., Stanojević, D., Stefaniak, A., Sternisko, A., Stoica, A., Stoyanova, K., Strickland, B., Sundvall, J., Thomas, J., Tinghög, G., Torgler, B., Traast, I., Tucciarelli, R., Tyrala, M., Ungson, N., Uysal, M., Van Lange, P., van Prooijen, J., van Rooy, D., Västfjäll, D., Verkoeijen, P., Vieira, J., von Sikorski, C., Walker, A., Watermeyer, J., Wetter, E., Whillans, A., Willardt, R., Wohl, M., Wójcik, A., Wu, K., Yamada, Y., Yilmaz, O., Yogeeswaran, K., Ziemer, C., Zwaan, R. and Boggio, P. 2022. National identity predicts public health support during a global pandemic. Nature Communications. 13 (1), pp. 1-14. https://doi.org/10.1038/s41467-021-27668-9Article
Author Correction: National identity predicts public health support during a global pandemic
Van Bavel, J., Cichocka, A., Capraro, V., Sjåstad, H., Nezlek, J., Pavlović, T., Alfano, M., Gelfand, M., Azevedo, F., Birtel, M., Cislak, A., Lockwood, P., Ross, R., Abts, K., Agadullina, E., Aruta, J., Besharati, S., Bor, A., Choma, B., Crabtree, C., Cunningham, W., De, K., Ejaz, W., Elbaek, C., Findor, A., Flichtentrei, D., Franc, R., Gjoneska, B., Gruber, J., Gualda, E., Horiuchi, Y., Huynh, T., Ibanez, A., Imran, M., Israelashvili, J., Jasko, K., Kantorowicz, J., Kantorowicz-Reznichenko, E., Krouwel, A., Laakasuo, M., Lamm, C., Leygue, C., Lin, M., Mansoor, M., Marie, A., Mayiwar, L., Mazepus, H., McHugh, C., Minda, J., Mitkidis, P., Olsson, A., Otterbring, T., Packer, D., Perry, A., Petersen, M., Puthillam, A., Riaño-Moreno, J., Rothmund, T., Santamaría-García, H., Schmid, P., Stoyanov, D., Tewari, S., Todosijević, B., Tsakiris, M., Tung, H., Umbreș, R., Vanags, E., Vlasceanu, M., Vonasch, A., Yucel, M., Zhang, Y., Abad, M., Adler, E., Akrawi, N., Mdarhri, H., Amara, H., Amodio, D., Antazo, B., Apps, M., Ay, F., Ba, M., Barbosa, S., Bastian, B., Berg, A., Bernal-Zárate, M., Bernstein, M., Białek, M., Bilancini, E., Bogatyreva, N., Boncinelli, L., Booth, J., Borau, S., Buchel, O., Cameron, C., Carvalho, C., Celadin, T., Cerami, C., Chalise, H., Cheng, X., Cian, L., Cockcroft, K., Conway, J., Córdoba-Delgado, M., Crespi, C., Crouzevialle, M., Cutler, J., Cypryańska, M., Dabrowska, J., Daniels, M., Davis, V., Dayley, P., Delouvee, S., Denkovski, O., Dezecache, G., Dhaliwal, N., Diato, A., Di Paolo, R., Drosinou, M., Dulleck, U., Ekmanis, J., Ertan, A., Etienne, T., Farhana, H., Farkhari, F., Farmer, H., Fenwick, A., Fidanovski, K., Flew, T., Fraser, S., Frempong, R., Fugelsang, J., Gale, J., Garcia-Navarro, E., Garladinne, P., Ghajjou, O., Gkinopoulos, T., Gray, K., Griffin, S., Gronfeldt, B., Gümren, M., Gurung, R., Halperin, E., Harris, E., Herzon, V., Hruška, M., Huang, G., Hudecek, M., Isler, O., Jangard, S., Jørgensen, F., Kachanoff, F., Kahn, J., Dangol, A., Keudel, O., Koppel, L., Koverola, M., Kubin, E., Kunnari, A., Kutiyski, Y., Laguna, O., Leota, J., Lermer, E., Levy, J., Levy, N., Li, C., Long, E., Longoni, C., Maglić, M., McCashin, D., Metcalf, A., Mikloušić, I., El Mimouni, S., Miura, A., Molina-Paredes, J., Monroy-Fonseca, C., Morales-Marente, E., Moreau, D., Muda, R., Myer, A., Nash, K., Nesh-Nash, T., Nitschke, J., Nurse, M., Ohtsubo, Y., Oldemburgo de Mello, V., O’Madagain, C., Onderco, M., Palacios-Galvez, M., Palomäki, J., Pan, Y., Papp, Z., Pärnamets, P., Paruzel-Czachura, M., Pavlović, Z., Payán-Gómez, C., Perander, S., Pitman, M., Prasad, R., Pyrkosz-Pacyna, J., Rathje, S., Raza, A., Rêgo, G., Rhee, K., Robertson, C., Rodríguez-Pascual, I., Saikkonen, T., Salvador-Ginez, O., Sampaio, W., Santi, G., Santiago-Tovar, N., Savage, D., Scheffer, J., Schönegger, P., Schultner, D., Schutte, E., Scott, A., Sharma, M., Sharma, P., Skali, A., Stadelmann, D., Stafford, C., Stanojević, D., Stefaniak, A., Sternisko, A., Stoica, A., Stoyanova, K., Strickland, B., Sundvall, J., Thomas, J., Tinghög, G., Torgler, B., Traast, I., Tucciarelli, R., Tyrala, M., Ungson, N., Uysal, M., Van Lange, P., van Prooijen, J., van Rooy, D., Västfjäll, D., Verkoeijen, P., Vieira, J., von Sikorski, C., Walker, A., Watermeyer, J., Wetter, E., Whillans, A., Willardt, R., Wohl, M., Wójcik, A., Wu, K., Yamada, Y., Yilmaz, O., Yogeeswaran, K., Ziemer, C., Zwaan, R. and Boggio, P. 2022. Author Correction: National identity predicts public health support during a global pandemic. Nature Publishing Group. https://doi.org/10.1038/s41467-022-29658-xOther
A novel kernel based approach to arbitrary length symbolic data with application to type 2 diabetes risk
Nwegbu, N., Tirunagari, S. and Windridge, D. 2022. A novel kernel based approach to arbitrary length symbolic data with application to type 2 diabetes risk. Scientific Reports. 12 (1), pp. 1-16. https://doi.org/10.1038/s41598-022-08757-1Article
VANT-GAN: adversarial learning for discrepancy-based visual attribution in medical imaging
Zia, T., Murtaza, S., Bhatti, N., Windridge, D. and Nisar, Z. 2022. VANT-GAN: adversarial learning for discrepancy-based visual attribution in medical imaging. Pattern Recognition Letters. 156, pp. 112-118. https://doi.org/10.1016/j.patrec.2022.02.005Article
Detection of human papillomavirus (HPV) from super resolution microscopic images applying an explainable deep learning network
Gao, X., Wen, S., Li, D., Liu, W., Xiong, J., Xu, B., Liu, J., Zhang, H. and Liu, X. 2022. Detection of human papillomavirus (HPV) from super resolution microscopic images applying an explainable deep learning network. SPIE Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging. San Diego, USA 20 - 22 Feb 2022 Society of Photo-Optical Instrumentation Engineers. https://doi.org/10.1117/12.2624423Conference item
Early detection of oesophageal cancer through colour contrast enhancement for data augmentation
Gao, X., Taylor, S., Pang, W., Lu, X. and Braden, B. 2022. Early detection of oesophageal cancer through colour contrast enhancement for data augmentation. SPIE Medical Imaging: Computer-Aided Diagnosis. San Diego, USA 21 - 24 Feb 2022 Society of Photo-Optical Instrumentation Engineers. https://doi.org/10.1117/12.2611409Conference paper
Gold-viral particle identification by deep learning in wide-field photon scattering parametric images
Zhao, H., Ni, B., Jin, X., Zhang, H., Hou, J., Hou, L., Marsh, J., Dong, L., Li, S., Gao, X., Shi, D., Liu, X. and Xiong, J. 2022. Gold-viral particle identification by deep learning in wide-field photon scattering parametric images. Applied Optics. 61 (2), pp. 546-553. https://doi.org/10.1364/AO.445953Article
CroLSSim: Cross‐language software similarity detector using hybrid approach of LSA‐based AST‐MDrep features and CNN‐LSTM model
Ullah, F., Naeem, M., Naeem, H., Cheng, X. and Alazab, M. 2022. CroLSSim: Cross‐language software similarity detector using hybrid approach of LSA‐based AST‐MDrep features and CNN‐LSTM model. International Journal of Intelligent Systems. 37 (9), pp. 5768-5795. https://doi.org/10.1002/int.22813Article
Contexts and context-awareness revisited from an intelligent environments perspective
Augusto, J. 2022. Contexts and context-awareness revisited from an intelligent environments perspective. Applied Artificial Intelligence. 36 (1), pp. 694-725. https://doi.org/10.1080/08839514.2021.2008644Article
Signal denoising of viral particle in wide-field photon scattering parametric images using deep learning
Zhao, H., Ni, B., Liu, W., Jin, X., Zhang, H., Gao, X., Wen, S., Shi, D., Dong, L., Xiong, J. and Liu, X. 2022. Signal denoising of viral particle in wide-field photon scattering parametric images using deep learning. Optics Communications. 503. https://doi.org/10.1016/j.optcom.2021.127463Article
A new privacy framework for the management of chronic diseases via mHealth in a post-Covid-19 world
Jusob, F., George, C. and Mapp, G. 2022. A new privacy framework for the management of chronic diseases via mHealth in a post-Covid-19 world. Journal of Public Health. 30 (1), pp. 37-47. https://doi.org/10.1007/s10389-021-01608-9Article
3D analytical modelling and iterative solution for high performance computing clusters
Kirsal, Y., Kirsal Ever, Y., Mapp, G. and Raza, M. 2022. 3D analytical modelling and iterative solution for high performance computing clusters. IEEE Transactions on Cloud Computing. 10 (4), pp. 2238-2251. https://doi.org/10.1109/TCC.2021.3055119Article
Modeling and verifying a resource allocation algorithm for secure service migration for commercial cloud systems
Karthick, G., Mapp, G., Kammueller, F. and Aiash, M. 2022. Modeling and verifying a resource allocation algorithm for secure service migration for commercial cloud systems. Computational Intelligence. 38 (3), pp. 811-828. https://doi.org/10.1111/coin.12421Article
MobiScan: an enhanced invisible screen‐camera communication system for IoT applications
Zhang, X., Liu, J., Ba, Z., Tao, Y. and Cheng, X. 2022. MobiScan: an enhanced invisible screen‐camera communication system for IoT applications. Transactions on Emerging Telecommunications Technologies. 33 (4). https://doi.org/10.1002/ett.4151Article
Secure smart contracts for cloud-based manufacturing using Ethereum blockchain
Kumar, A., Abhishek, K., Nerurkar, P., Ghalib, M., Shankar, A. and Cheng, X. 2022. Secure smart contracts for cloud-based manufacturing using Ethereum blockchain. Transactions on Emerging Telecommunications Technologies. 33 (4). https://doi.org/10.1002/ett.4129Article
AnAbEL: Towards empowering people living with dementia in ambient assisted living
Gimenez Manuel, J., Augusto, J. and Stewart, J. 2022. AnAbEL: Towards empowering people living with dementia in ambient assisted living. Universal Access in the Information Society. 21 (2), pp. 457-476. https://doi.org/10.1007/s10209-020-00760-5Article
Dependability engineering in Isabelle
Kammueller, F. 2021. Dependability engineering in Isabelle. arxiv.org.Working paper
Exploring a new security framework for future healthcare systems
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