Computer Science
| Title | Computer Science |
|---|---|
| Alternative | S&T - CS |
| Faculty | Faculty of Science and Technology |
Latest research outputs
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Towards resolving challenges associated with climate change modelling in Africa
Oluwagbemi, O., Hamutoko, J.T., Fotso-Nguemo, T.C., Lokonon, B.O.K., Emebo, O. and Kirsten, K.L. 2022. Towards resolving challenges associated with climate change modelling in Africa. Applied Sciences. 12 (14). https://doi.org/10.3390/app12147107Article
Molecular dynamic simulation reveals structure differences in APOL1 variants and implication on pathogenesis of chronic kidney disease
Mayanja, R., Kintu, C., Diabate, O., Soremekun, O., Oluwagbemi, O., Wele, M., Kalyesubula, R., Jjingo, D., Chikowore, T. and Fatumo, S. 2022. Molecular dynamic simulation reveals structure differences in APOL1 variants and implication on pathogenesis of chronic kidney disease. Genes. 13 (8). https://doi.org/10.3390/genes13081460Article
Bioinformatics, computational informatics, and modeling approaches to the design of mRNA COVID-19 vaccine candidates
Oluwagbemi, O., Oladipo, E.K., Kolawole, O.M., Oloke, J.K., Adelusi, T.I., Irewolede, B.A., Dairo, E.O, Ayeni, A.E., Kolapo, K.T., Akindiya, O.E., Oluwasegun, J.A., Oluwadara, B.F. and Fatumo, S. 2022. Bioinformatics, computational informatics, and modeling approaches to the design of mRNA COVID-19 vaccine candidates. Computation. 10 (7). https://doi.org/10.3390/computation10070117Article
Ensemble machine learning for Monkeypox transmission time series forecasting
Dada, E.G., Oyewola, D.O., Joseph, S.B., Emebo, O. and Oluwagbemi, O. 2022. Ensemble machine learning for Monkeypox transmission time series forecasting. Applied Sciences. 12 (23). https://doi.org/10.3390/app122312128Article
Application of deep learning techniques and Bayesian optimization with tree parzen estimator in the classification of supply chain pricing datasets of health medications
Oyewola, D., Dada, E., Omotehinwa, T., Emebo, O. and Oluwagbemi, O. 2022. Application of deep learning techniques and Bayesian optimization with tree parzen estimator in the classification of supply chain pricing datasets of health medications. Applied Sciences. 12 (19). https://doi.org/10.3390/app121910166Article
Computational construction of a glycoprotein multi-epitope subunit vaccine candidate for old and new South-African SARS-CoV-2 virus strains
Oluwagbemi, O., Oladipo, E., Dairo, E., Ayeni, A., Irewolede, B., Jimah, E., Oyewole, M., Olawale, B., Adegoke, H. and Ogunleye, A. 2022. Computational construction of a glycoprotein multi-epitope subunit vaccine candidate for old and new South-African SARS-CoV-2 virus strains. Informatics in Medicine Unlocked . 28. https://doi.org/10.1016/j.imu.2022.100845Article
Using deep 1D convolutional grated recurrent unit neural network to optimize quantum molecular properties and predict intramolecular coupling constants of molecules of potential health medications and other generic molecules
Oyewola, D.O., Dada, E.G., Emebo, O. and Oluwagbemi, O. 2022. Using deep 1D convolutional grated recurrent unit neural network to optimize quantum molecular properties and predict intramolecular coupling constants of molecules of potential health medications and other generic molecules. Applied Sciences. 12 (14). https://doi.org/10.3390/app12147228Article
Insights into the impacts of and responses to COVID-19 pandemic: The South African food retail supply chains perspective
Omoruyi, O., Dakora, E.A. and Oluwagbemi, O. 2022. Insights into the impacts of and responses to COVID-19 pandemic: The South African food retail supply chains perspective. Journal of Transport and Supply Chain. 16. https://doi.org/10.4102/jtscm.v16i0.739Article
A framework for privacy and security requirements analysis and conflict resolution for supporting GDPR compliance through privacy-by-design
Alkubaisy, D., Piras, L., Al-Obeidallah, M., Cox, K. and Mouratidis, H. 2022. A framework for privacy and security requirements analysis and conflict resolution for supporting GDPR compliance through privacy-by-design. Ali, R., Kaindl, H. and Maciaszek, L. (ed.) 16th International Conference on Evaluation of Novel Approaches to Software Engineering. Virtual 26 - 27 Apr 2021 Cham Springer. pp. 67-87 https://doi.org/10.1007/978-3-030-96648-5_4Conference paper
Developing secured Android applications by mitigating code vulnerabilities with machine learning
Senanayake, J., Kalutarage, H., Al-Kadri, M., Petrovski, A. and Piras, L. 2022. Developing secured Android applications by mitigating code vulnerabilities with machine learning. ACM Asia Conference on Computer and Communications Security (ASIA CCS '22). Nagasaki, Japan 30 May - 03 Jun 2022 Association for Computing Machinery (ACM). pp. 1255–1257 https://doi.org/10.1145/3488932.3527290Conference poster
The quantum path kernel: A generalized quantum neural tangent kernel for deep quantum machine learning
Incudini, M., Grossi, M., Mandarino, A., Vallecorsa, S., Di Pierro, A. and Windridge, D. 2022. The quantum path kernel: A generalized quantum neural tangent kernel for deep quantum machine learning. https://doi.org/10.48550/arXiv.2212.11826Pre-print
Digital twin as an aid for decision-making in the face of uncertainty
Kulkarni, V., Barat, S., Clark, T. and Barn, B. 2022. Digital twin as an aid for decision-making in the face of uncertainty. 2022 Winter Simulation Conference (WSC). Singapore 11 - 14 Dec 2022 IEEE. pp. 1371-1385 https://doi.org/10.1109/wsc57314.2022.10015528Conference paper
A convex selective segmentation model based on a piece-wise constant metric guided edge detector function
Khan, M., Ali, H., Zakarya, M., Tirunagari, S., Khan, A., Khan, R., Ahmed, A. and Rada, L. 2022. A convex selective segmentation model based on a piece-wise constant metric guided edge detector function. https://doi.org/10.21203/rs.3.rs-2391118/v1Pre-print
A framework for strategic planning of data analytics in the educational sector
Tsiakara, A. 2022. A framework for strategic planning of data analytics in the educational sector. Masters thesis Middlesex UniversityMasters thesis
Supporting the individuation, analysis and gamification of software components for acceptance requirements fulfilment
Calabrese, F., Piras, L. and Giorgini, P. 2022. Supporting the individuation, analysis and gamification of software components for acceptance requirements fulfilment. Barn, B. and Sandkuhl, K (ed.) IFIP Working Conference on The Practice of Enterprise Modeling. London, UK 23 - 25 Nov 2022 Springer. pp. 33-48 https://doi.org/10.1007/978-3-031-21488-2_3Conference paper
Smart technologies and beyond: exploring how a smart band can assist in monitoring children’s independent mobility & well-being
Mistry, K. 2022. Smart technologies and beyond: exploring how a smart band can assist in monitoring children’s independent mobility & well-being. Masters thesis Middlesex UniversityMasters thesis
Value of information in the binary case and confusion matrix
Belavkin, R., Pardalos, P. and Principe, J. 2022. Value of information in the binary case and confusion matrix. 41st International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering. Paris, France 18 - 22 Jul 2022 MDPI. pp. 1-9 https://doi.org/10.3390/psf2022005008Conference paper
A tagging SNP set method based on network community partition of linkage disequilibrium and node centrality
Wan, Q., Cheng, X., Zhang, Y., Lu, G., Wang, S. and He, S. 2022. A tagging SNP set method based on network community partition of linkage disequilibrium and node centrality. Current Bioinformatics. 17 (9), pp. 825-834. https://doi.org/10.2174/1574893617666220324155813Article
An efficient quality of services based wireless sensor network for anomaly detection using soft computing approaches
Mittal, M., Kobielnik, M., Gupta, S., Cheng, X. and Wozniak, M. 2022. An efficient quality of services based wireless sensor network for anomaly detection using soft computing approaches. Journal of Cloud Computing. 11 (1), pp. 1-21. https://doi.org/10.1186/s13677-022-00344-zArticle
Formalization and evaluation of EAP-AKA’ protocol for 5G network access security
Edris, E., Aiash, M. and Loo, J. 2022. Formalization and evaluation of EAP-AKA’ protocol for 5G network access security. Array. 16. https://doi.org/10.1016/j.array.2022.100254Article
Factors affecting the deployment of learning analytics in developing countries: case of Egypt
Mahmoud, M., Dafoulas, G., Abd ElAziz, R. and Saleeb, N. 2022. Factors affecting the deployment of learning analytics in developing countries: case of Egypt. International Journal of Emerging Technologies in Learning (iJET). 17 (03), pp. 279-298. https://doi.org/10.3991/ijet.v17i03.24405Article
Achieving sustainability: from innovation to valorisation and continuous improvement
Georgiadou, E., Siakas, K., Ross, M. and Rahanu, H. 2022. Achieving sustainability: from innovation to valorisation and continuous improvement. Yilmaz, M., Clarke, P., Messanarz, R. and Woran, B. (ed.) EuroSPI 2022: European Systems, Software and Services Process Improvement and Innovation Conference. Salzburg, Austria 31 Aug - 02 Sep 2022 Springer. pp. 763-778 https://doi.org/10.1007/978-3-031-15559-8_53Conference paper
Requirements volatility in multicultural situational contexts
Siakas, E., Rahanu, H., Georgiadou, E. and Siakas, K. 2022. Requirements volatility in multicultural situational contexts. Yilmaz, M., Clarke, P., Messanarz, R. and Woran, B. (ed.) EuroSPI 2022: European Systems, Software and Services Process Improvement and Innovation Conference. Salzburg, Austria 31 Aug - 02 Sep 2022 Springer. pp. 633-655 https://doi.org/10.1007/978-3-031-15559-8_45Conference paper
The proposal of adding a society value to the software process improvement manifesto
Rahanu, H., Loveday, J., Siakas, E., Georgiadou, E., Siakas, K. and Ross, M. 2022. The proposal of adding a society value to the software process improvement manifesto. Yilmaz, M., Clarke, P., Messanarz, R. and Wöran, B. (ed.) EuroSPI 2022: European Systems, Software and Services Process Improvement and Innovation Conference. Salzburg, Austria 31 Aug - 02 Sep 2022 Springer. pp. 673-687 https://doi.org/10.1007/978-3-031-15559-8_47Conference paper
Explanation of black box AI for GDPR related privacy using Isabelle
Kammueller, F. 2022. Explanation of black box AI for GDPR related privacy using Isabelle. Garcia-Alfaro, J., Navarro-Arribas, G. and Dragoni, N. (ed.) 17th DPM International Workshop on Data Privacy Management. Copenhagen, Denmark 29 - 30 Sep 2022 Cham Springer. https://doi.org/10.1007/978-3-031-25734-6_5Conference paper
Endoscopic image analysis using deep convolutional GAN and traditional data augmentation
Auzine, M., Khan, M., Baichoo, S., Gooda Sahib, N., Gao, X. and Bissoonauth-Daiboo, P. 2022. Endoscopic image analysis using deep convolutional GAN and traditional data augmentation. International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME). Maldives 16 - 18 Nov 2022 IEEE. https://doi.org/10.1109/ICECCME55909.2022.9988503Conference paper
COVID-VIT: classification of Covid-19 from 3D CT chest images based on vision transformer model
Gao, X., Khan, M., Hui, R., Tian, Z., Qian, Y., Gao, A. and Baichoo, S. 2022. COVID-VIT: classification of Covid-19 from 3D CT chest images based on vision transformer model. 3rd International Conference on Next Generation Computing Applications (NextComp). Flic-en-Flac, Mauritius 06 - 08 Oct 2022 IEEE. https://doi.org/10.1109/NextComp55567.2022.9932246Conference paper
Digital twins: a survey on enabling technologies, challenges, trends and future prospects
Mihai, S., Yaqoob, M., Hung, D., Davis, W., Towakel, P., Raza, M., Karamanoglu, M., Barn, B., Shetve, D., Prasad, R., Venkataraman, H., Trestian, R. and Nguyen, H. 2022. Digital twins: a survey on enabling technologies, challenges, trends and future prospects. IEEE Communications Surveys and Tutorials. 24 (4), pp. 2255-2291. https://doi.org/10.1109/COMST.2022.3208773Article
Developing testing frameworks for AI cameras
Herdzik, A. and James-Reynolds, C. 2022. Developing testing frameworks for AI cameras. Bramer, M. and Stahl, F. (ed.) 42nd Annual International Conference of the British Computer Society's Specialist Group on Artificial Intelligence (SGAI). Cambridge, UK 13 - 15 Dec 2022 Cham Springer. https://doi.org/10.1007/978-3-031-21441-7_28Conference paper
Discriminator-based adversarial networks for knowledge graph completion
Tubaishat, A., Zia, T., Faiz, R., Al Obediat, F., Shah, B. and Windridge, D. 2022. Discriminator-based adversarial networks for knowledge graph completion. Neural Computing and Applications. https://doi.org/10.1007/s00521-022-07680-wArticle
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. pp. 263-272 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
The sociotechnical digital twin: on the gap between social and technical feasibility
Barn, B. 2022. The sociotechnical digital twin: on the gap between social and technical feasibility. 2022 IEEE 24th Conference on Business Informatics (CBI). Amsterdam, Netherlands 15 - 17 Jun 2022 IEEE. pp. 11-20 https://doi.org/10.1109/CBI54897.2022.00009Conference paper
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