Computer Science
| Title | Computer Science |
|---|---|
| Alternative | S&T - CS |
| Faculty | Faculty of Science and Technology |
Latest research outputs
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HANNA: Human-friendly provisioning and configuration of smart devices
Fortuna, C., Yetgin, H., Ogrizek, L., Municio, E., Marquez-Barja, J.M. and Mohorcic, M. 2023. HANNA: Human-friendly provisioning and configuration of smart devices. Engineering Applications of Artificial Intelligence. 126 (Part A). https://doi.org/10.1016/j.engappai.2023.106745Article
Joint energy and spectral optimization in Heterogeneous Vehicular Network
Alam, A., Ali, K., Trestian, R., Shah, P. and Mapp, G. 2023. Joint energy and spectral optimization in Heterogeneous Vehicular Network. Computer Networks. 238. https://doi.org/10.1016/j.comnet.2023.110111Article
Artificial intelligence and automation in endoscopy and surgery
Chadebecq, F., Lovat, L. and Stoyanov, D. 2023. Artificial intelligence and automation in endoscopy and surgery. Nature Reviews Gastroenterology and Hepatology. 20 (3), pp. 171-182. https://doi.org/10.1038/s41575-022-00701-yArticle
Identifying key mechanisms leading to visual recognition errors for missed colorectal polyps using eye-tracking technology
Ahmad, O., Mazomenos, E., Chadebecq, F., Kader, R., Hussein, M., Haidry, R., Puyal, J., Brandao, P., Toth, D. and Mountney, P. 2023. Identifying key mechanisms leading to visual recognition errors for missed colorectal polyps using eye-tracking technology. Journal of Gastroenterology and Hepatology. 38 (5), pp. 768-774. https://doi.org/10.1111/jgh.16127Article
Sociotechnical digital twin: public policy evaluation and a research roadmap for the digital society
Barn, B. 2023. Sociotechnical digital twin: public policy evaluation and a research roadmap for the digital society. 2nd International Workshop on Digital Twin Engineering (DTE) . Vienna, Austria 29 - 29 Nov 2023Conference item
Explanation of student attendance AI prediction with the Isabelle Infrastructure Framework
Kammueller, F. and Satija, D. 2023. Explanation of student attendance AI prediction with the Isabelle Infrastructure Framework. Information. 14 (8). https://doi.org/10.3390/info14080453Article
Knowledge management for the micro enterprise: a taxonomy
Hall, S., Smith, S., Baskent, C. and De Raffaele, C. 2023. Knowledge management for the micro enterprise: a taxonomy. Matos, F. and Rosa, A. (ed.) 24th European Conference on Knowledge Management. Lisboa, Portugal 07 - 08 Sep 2023 Academic Conferences International (ACI). https://doi.org/10.34190/eckm.24.1.1268Conference paper
A novel scheduling algorithm for improved performance of multi-objective safety-critical wireless sensor networks using long short-term memory
Al-Nader, I., Lasebae, A., Raheem, R. and Khoshkholghi, A. 2023. A novel scheduling algorithm for improved performance of multi-objective safety-critical wireless sensor networks using long short-term memory. Electronics. 12 (23). https://doi.org/10.3390/electronics12234766Article
Online tutoring system for programming courses to improve exam pass rate
Nalli, G., Culmone, R., Perali, A. and Amendola, D. 2023. Online tutoring system for programming courses to improve exam pass rate. Journal of E-Learning and Knowledge Society. 19 (1), pp. 27-35. https://doi.org/10.20368/1971-8829/1135704Article
Machine Learning model for student drop-out prediction based on student engagement
Brezočnik, L., Nalli, G., De Leone, R., Val, S., Podgorelec, V. and Karakatič, S. 2023. Machine Learning model for student drop-out prediction based on student engagement. Karabegovic, I., Kovačević, A. and Mandzuka, S. (ed.) 9th International Conference on New Technologies, Development and Application. Sarajevo, Bosnia and Herzegovina 22 - 24 Jun 2023 Cham Springer. pp. 486–496 https://doi.org/10.1007/978-3-031-31066-9_54Conference paper
Comparison of the effectiveness and performance of student workgroups in online wiki activities with and without AI
Nalli, G. and Smith, S. 2023. Comparison of the effectiveness and performance of student workgroups in online wiki activities with and without AI. 4th International Electronic Conference on Applied Sciences. Online 27 Oct - 10 Nov 2023 MDPI. https://doi.org/10.3390/ASEC2023-16273Conference paper
Machine-learning-based software to group heterogeneous students for online peer assessment activities
Amendola, D., Nalli, G. and Miceli, C. 2023. Machine-learning-based software to group heterogeneous students for online peer assessment activities. Fulantelli, G., Burgos, D., Casalino, G., Cimitile, M., Lo Bosco, G. and Taibi, D. (ed.) 4th International Conference on Higher Education Learning Methodologies and Technologies Online. Palermo, Italy 21 - 23 Sep 2022 Cham Springer. https://doi.org/10.1007/978-3-031-29800-4_2Conference paper
Bridging neuroscience and robotics: spiking neural networks in action
Jones, A., Gandhi, V., Mahiddine, A. and Huyck, C. 2023. Bridging neuroscience and robotics: spiking neural networks in action. Sensors. 23 (21), pp. 1-14. https://doi.org/10.3390/s23218880Article
Building an intelligent edge environment to provide essential services in smart cities
Karthick, G., Mapp, G. and Crowcroft, J. 2023. Building an intelligent edge environment to provide essential services in smart cities. 18th Workshop on Mobility in the Evolving Internet Architecture . Madrid, Spain 06 - 06 Oct 2023 New York, NY, United States Association for Computing Machinery (ACM). pp. 13-18 https://doi.org/10.1145/3615587.3615987Conference paper
Facial emotion recognition and classification using the Convolutional Neural Network-10 (CNN-10)
Dada, E., Oyewola, D., Joseph, S., Emebo, O. and Oluwagbemi, O. 2023. Facial emotion recognition and classification using the Convolutional Neural Network-10 (CNN-10). Applied Computational Intelligence and Soft Computing. 2023. https://doi.org/10.1155/2023/2457898Article
Digital exclusion and relative digital deprivation: exploring factors and moderators of internet non-use in the UK
Ueno, A., Dennis, C. and Dafoulas, G. 2023. Digital exclusion and relative digital deprivation: exploring factors and moderators of internet non-use in the UK. Technological Forecasting and Social Change. 197. https://doi.org/10.1016/j.techfore.2023.122935Article
Leveraging oversampling techniques in machine learning models for multi-class malware detection in smart home applications
Chowdhury, A., Isalm, M., Kaisar, S., Naha, R., Khoshkholghi, A., Aiash, M. and Khoda, M.E. 2023. Leveraging oversampling techniques in machine learning models for multi-class malware detection in smart home applications. IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications. Exeter, United Kingdom 01 - 03 Nov 2023 IEEE. pp. 2216-2221Conference paper
A topological features based quantum kernel [Presentation]
Incudini, M., Martini, F., Di Pierro, A. and Windridge, D. 2023. A topological features based quantum kernel [Presentation]. 7th International Conference on Quantum Techniques in Machine Learning. CERN, Geneva 19 - 24 Nov 2023Conference item
MesoGraph: automatic profiling of mesothelioma subtypes from histological images
Eastwood, M., Sailem, H., Marc, S., Gao, X., Offman, J., Karteris, E., Fernandez, A., Jonigk, D., Cookson, W., Moffatt, M., Popat, S., Minhas, F. and Robertus, J. 2023. MesoGraph: automatic profiling of mesothelioma subtypes from histological images. Cell Reports Medicine. 4 (10). https://doi.org/10.1016/j.xcrm.2023.101226Article
Interpretable chronic kidney disease risk prediction from clinical data using machine learning
Chennareddy, V., Tirunagari, S., Mohan, S., Windridge, D. and Balla, Y. 2023. Interpretable chronic kidney disease risk prediction from clinical data using machine learning. 16th Multi-Disciplinary International Conference on Artificial Intelligence (MIWAI 2023). Hyderabad, India 21 2023 - 22 Jul 2024 Springer. https://doi.org/10.1007/978-3-031-36402-0_63Conference paper
Multi-disciplinary Trends in Artificial Intelligence: 16th International Conference, MIWAI 2023, Hyderabad, India, July 21–22, 2023, Proceedings
Morusupalli, R., Dandibhotla, T., Atluri, V., Windridge, D., Lingras, P. and Komati, V. (ed.) 2023. Multi-disciplinary Trends in Artificial Intelligence: 16th International Conference, MIWAI 2023, Hyderabad, India, July 21–22, 2023, Proceedings. Springer.Conference Proceedings
Addressing challenges in healthcare big data analytics
Tirunagari, S., Mohan, S., Windridge, D. and Balla, Y. 2023. Addressing challenges in healthcare big data analytics. 16th Multi-Disciplinary International Conference on Artificial Intelligence (MIWAI 2023). Hyderabad, India 21 2023 - 22 Jul 2024 Springer. https://doi.org/10.1007/978-3-031-36402-0_70Conference paper
Review of parameter tuning methods for nature-inspired algorithms
Joy, G., Huyck, C. and Yang, X. 2023. Review of parameter tuning methods for nature-inspired algorithms. in: Yang, X. (ed.) Benchmarks and Hybrid Algorithms in Optimization and Applications Singapore Springer. pp. 33-47Book chapter
Using Hidden Markov Chain for improving the dependability of safety-critical WSNs
Al-Nader, I., Lasebae, A. and Raheem, R. 2023. Using Hidden Markov Chain for improving the dependability of safety-critical WSNs. Barolli, L. (ed.) 37th International Conference on Advanced Information Networking and Applications. Federal University of Juiz de Fora, Brazil 29 - 31 Mar 2023 Cham, Switzerland. Springer. pp. 460–472 https://doi.org/10.1007/978-3-031-29056-5_40Conference paper
Visual attribution using Adversarial Latent Transformations
Zia, T., Wahab, A., Windridge, D., Tirunagari, S. and Bhatti, N. 2023. Visual attribution using Adversarial Latent Transformations. Computers in Biology and Medicine. 166. https://doi.org/10.1016/j.compbiomed.2023.107521Article
Performance and cryptographic evaluation of security protocols in distributed networks using applied pi calculus and Markov Chain
Edris, E., Aiash, M., Khoshkholghi, A., Naha, R., Chowdhury, A. and Loo, J. 2023. Performance and cryptographic evaluation of security protocols in distributed networks using applied pi calculus and Markov Chain. Internet of Things. 24. https://doi.org/10.1016/j.iot.2023.100913Article
Adaptation of enterprise modeling methods for large language models
Barn, B., Barat, S. and Sandkuhl, K. 2023. Adaptation of enterprise modeling methods for large language models. Almeida, J., Kaczmarek-Heß, M., Koschmider, A. and Proper, H. (ed.) 16th IFIP WG 8.1 Working Conference on the Practice of Enterprise Modeling. Vienna, Austria 28 Nov - 01 Dec 2023 Cham Springer. pp. 3-18 https://doi.org/10.1007/978-3-031-48583-1_1Conference paper
Intelligence and consciousness in natural and artificial systems
Gamez, D. 2023. Intelligence and consciousness in natural and artificial systems. in: Chella, A. (ed.) Computational Approaches to Conscious Artificial Intelligence World Scientific Publishing Co. Pte Ltd.Book chapter
Deep combination of radar with optical data for gesture recognition: role of attention in fusion architectures
Towakel, P., Windridge, D. and Nguyen, H. 2023. Deep combination of radar with optical data for gesture recognition: role of attention in fusion architectures. IEEE Transactions on Instrumentation and Measurement. 72, pp. 1-15. https://doi.org/10.1109/TIM.2023.3307768Article
Malignant Mesothelioma subtyping via sampling driven multiple instance prediction on tissue image and cell morphology data
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. 2023. Malignant Mesothelioma subtyping via sampling driven multiple instance prediction on tissue image and cell morphology data. Artificial Intelligence in Medicine. 143. https://doi.org/10.1016/j.artmed.2023.102628Article
Neural text generators in enterprise modeling: can ChatGPT be used as proxy domain expert?
Sandkuhl, K., Barn, B. and Barat, S. 2023. Neural text generators in enterprise modeling: can ChatGPT be used as proxy domain expert? da Silva, A.R., da Silva, M.M., Estima, J., Barry, C., Lang, M., Linger, H. and Schneider, C. (ed.) 31st International Conference on Information Systems Development. Lisbon, Portugal 30 Aug - 01 Sep 2023 Lisbon, Portugal Association for Information Systems (AIS). https://doi.org/10.62036/ISD.2023.44Conference paper
Android code vulnerabilities early detection using AI-powered ACVED plugin
Senanayake, J., Kalutarage, H., Al-Kadri, M.O., Petrovski, A. and Piras, L. 2023. Android code vulnerabilities early detection using AI-powered ACVED plugin. Atluri, V. and Ferrara, A. (ed.) 37th Annual IFIP WG 11.3 Conference (DBSec 2023). Sophia-Antipolis, France 19 - 21 Jul 2023 Cham, Switzerland Springer. pp. 339–357 https://doi.org/10.1007/978-3-031-37586-6_20Conference paper
Labelled vulnerability dataset on Android source code (LVDAndro) to develop AI-based code vulnerability detection models
Senanayake, J., Kalutarage, H., Al-Kadri, M.O., Piras, L. and Petrovski, A. 2023. Labelled vulnerability dataset on Android source code (LVDAndro) to develop AI-based code vulnerability detection models. Vimercati, S. and Samarati, P. (ed.) International Conference on Security and Cryptography (SECRYPT) 2023. Rome, Italy 10 - 12 Jul 2023 SCITEPRESS - Science and Technology Publications. pp. 659-666 https://doi.org/10.5220/0012060400003555Conference paper
Goal-modeling privacy-by-design patterns for supporting GDPR compliance
Al-Obeidallah, M., Piras, L., Iloanugo, O., Mouratidis, H., Alkubaisy, D and Dellagiacoma, D. 2023. Goal-modeling privacy-by-design patterns for supporting GDPR compliance. Fill, H.-G., Domínguez-Mayo, F.J., van Sinderen, M. and Maciaszek, L. (ed.) International Conference on Software Technologies (ICSOFT). Rome, Italy 10 - 12 Jul 2023 SCITEPRESS - Science and Technology Publications. pp. 361-368 https://doi.org/10.5220/0012080700003538Conference paper
The quantum path kernel: a generalized neural tangent kernel for deep quantum machine learning
Incudini, M., Grossi, M., Mandarino, A., Vallecorsa, S., Di Pierro, A. and Windridge, D. 2023. The quantum path kernel: a generalized neural tangent kernel for deep quantum machine learning. IEEE Transactions on Quantum Engineering. 4. https://doi.org/10.1109/TQE.2023.3287736Article
A.I.: Artificial Intelligence as philosophy: machine consciousness and intelligence
Gamez, D. 2023. A.I.: Artificial Intelligence as philosophy: machine consciousness and intelligence. in: Johnson, D., Kowalski, D., Lay, C. and Engels, K. (ed.) The Palgrave Handbook of Popular Culture as Philosophy Palgrave Macmillan.Book chapter
IoT-based emergency vehicle services in intelligent transportation system
Chowdhury, A., Kaisar, S., Khoda, M., Naha, R., Khoshkholghi, A. and Aiash, M. 2023. IoT-based emergency vehicle services in intelligent transportation system. Sensors. 23 (11). https://doi.org/10.3390/s23115324Article
Pediatrics in artificial intelligence era: a systematic review on challenges, opportunities, and explainability
Balla, Y., Tirunagari, S. and Windridge, D. 2023. Pediatrics in artificial intelligence era: a systematic review on challenges, opportunities, and explainability. Indian Pediatrics. 60 (7), pp. 561-569. https://doi.org/10.1007/s13312-023-2936-8Article
Resource saving via ensemble techniques for quantum neural networks
Incudini, M., Grossi, M., Ceschini, A., Mandarino, A., Panella, M., Vallecorsa, S. and Windridge, D. 2023. Resource saving via ensemble techniques for quantum neural networks. https://doi.org/10.48550/arXiv.2303.11283Pre-print
Social and moral psychology of COVID-19 across 69 countries
Azevedo, F., Pavlović, T., Rêgo, G., Ay, F., Gjoneska, B., Etienne, T., Ross, R., Schönegger, P., Riaño-Moreno, J., Cichocka, A., Capraro, V., Cian, L., Longoni, C., Chan, H., Van Bavel, J., Sjåstad, H., Nezlek, J., Alfano, M., Gelfand, M., Birtel, M., Cislak, A., Lockwood, P., 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., 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., Rothmund, T., Santamaría-García, H., Schmid, P., Stoyanov, D., Tewari, S., Todosijević, B., Tsakiris, M., Tung, H., Umbres, 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., 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., Cockcroft, K., Conway, J., Córdoba-Delgado, M., Crespi, C., Crouzevialle, M., Cutler, J., Cypryańska, M., Dabrowska, J., Daniels, M., Davis, V., Dayley, P., Delouvée, S., Denkovski, O., Dezecache, G., Dhaliwal, N., Diato, A., Di Paolo, R., Drosinou, M., Dulleck, U., Ekmanis, J., Ertan, A., 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., Jorgensen, 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., 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., de Mello, V., O’Madagain, C., Onderco, M., Palacios-Galvez, M., Palomöki, 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., Rhee, K., Robertson, C., Rodríguez-Pascual, I., Saikkonen, T., Salvador-Ginez, O., Santi, G., Santiago-Tovar, N., Savage, D., Scheffer, J., 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., White, K., Habib, R., Willardt, R., Wohl, M., Wójcik, A., Wu, K., Yamada, Y., Yilmaz, O., Yogeeswaran, K., Ziemer, C., Zwaan, R., Boggio, P. and Sampaio, W. 2023. Social and moral psychology of COVID-19 across 69 countries. Scientific Data. 10 (1), p. 272. https://doi.org/10.1038/s41597-023-02080-8Article
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