Computing, Informatics and Applications Research Group

Close-up of IT equipment

Our Computing, Informatics and Applications (CIA) research group has a wide remit that includes scientific data processing, smart technology and web/internet technologies. We are particularly interested in how computational and artificial intelligence (AI) methods can be used to improve people's lives and increase productivity.

The group has specific expertise in image and signal processing, data visualisation, mobile devices, 2D/3D modelling, distributed computing, wireless environments, the application of sound and imaging technology in assisted living, online virtual environments, the Internet of Things (IoT), and sensor technology. Much of the research the group undertakes is applied/collaborative, and includes links with industrial partners.

If you would like to find out more about our research, please contact Dr Lakshmi Babu-Saheer at

For postgraduate research enquiries, please contact Dr Christina Luca at

For external income generation, please contact Dr George Wilson at

Research areas

Our work is primarily focussed in the following research areas:

Imaging Technologies, Vision, Acoustics and Digital Systems

Dr Ian van der Linde, Dr Silvia Cirstea, Dr Domenico Vicinanza, Dr Jin Zhang, Dr Marcian Cirstea, Prof Lakshmi Babu Saheer.

Our Imaging Technologies and Acoustics team focuses on AI-based navigation, image and signal processing systems, 2D/3D image modelling, neural networks, inverse problems, numerical modelling of physical processes (electromagnetics, acoustics, psychoacoustics, quantum mechanics), statistical methods, ray-tracing, architectural acoustics, data sonification, data visualisation, auditory display, sound synthesis, mobile devices and technologies for supporting visual impairment. It also looks at computer aided design (CAD) tools and methods applied to digital systems modelling and rapid prototyping using VHDL and FPGAs..

Read more about read more about imaging technologies, vision, acoustics and digital systems.

Artificial Intelligence, Machine Learning, Data Science and Applications

Dr Ian van der Linde, Dr Silvia Cirstea, Dr Domenico Vicinanza, Dr Jin Zhang, Dr Cristina Luca, Dr Arooj Fatima, Prof Lakshmi Babu Saheer, Dr Stiphen Chowdhury.

Our AI, Machine Learning, Data Science and Applications team has a wide range of research interests that include: data analysis and machine learning techniques; up-to-date theoretical and practical developments and hardware platforms for AI; signal processing; remote sensing for the IoT and how these converge in the emergence of intelligent systems; advanced statistics; machine learning for structured data and graphs; data integration, probabilistic system;, algorithms for massive datasets; large-scale optimisation.

Read more about read more about artificial intelligence, machine learning, data science and applications.

IoT, Machine Learning and Cloud Computing

Dr Mahdi Maktab-Dar-Oghaz, Prof Lakshmi Babu Saheer, Dr Razvan-Ioan Dinita.

Our IoT, Machine Learning and Cloud Computing team is interested in IoT, smart environments, pervasive healthcare, Human Computer Interaction (HCI), adaptive computational systems, advanced internet and mobile technologies, AI, smart sensors and advanced spectral analysis in biomechanics and biomedical sciences.

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Semantic Web and Educational Technologies

Dr Cristina Luca, Dr Razvan-Ioan Dinita, Dr Arooj Fatima, Dr George Wilson.

Our Semantic Web and Educational Technologies team investigates business information systems, open linked data, intelligent internet search and knowledge modelling, online virtual environments, image processing and data visualisation.

AI for Sustainability

Prof Lakshmi Babu Saheer, Dr Mahdi Maktab-Dar-Oghaz, Dr Cristina Luca

Our sustainability group focuses on use of data analysis and machine learning techniques to aid climate change related problems of air pollution, natural disasters, vegetation, food production, healthcare, transportation, and agricultural and industrial sustainability. It proposes sustainable solutions in different domains with the help of AI, IoT and emerging technologies such as Blockchain and Fog Computing. In the healthcare domain, the group also looks at sustainable care for all. In the agricultural domain, it looks at smart farming, precision agriculture and precision livestock farming.

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Our people

Academic staff

Dr Jin Zhang - Research Group Director and contact

Jin Zhang

Jin Zhang (PhD Fixed Broadband Wireless Communications) has expertise in signal processing, data communications, remote sensing and the IoTs. Her research interests include electronic systems modelling, the study and design for development of novel artificial metamaterials components in the mid-infrared range and lower spectral range, the design of quasi-optical components for millimetre-wave astronomy and the electromagnetic modelling and the simulations.

Her work has been published in high impact journals and conference publications and reflects continued collaborative work with other HE institutes (Cardiff, UCL). She has secured external funding as principle investigator for two Royal Society China-UK Science Network Grants on behalf of the UK Government Office for Science (GO-Science) and by the China Scholarship Council (CSC) on behalf of the Ministry of Education in China. She has recently been awarded European Space Agency (ESA) funding as co-investigator for a major collaborative research project.

Find out more about Dr Jin Zhang.

Dr George Wilson - Contact for external income generation

Image of Dr George Wilson

George Wilson (PhD Isotope Geochemistry) teaches courses in programming techniques, artificial intelligence and distributed computing, whilst his research is focused on spatial data processing, search semantics, Bayesian techniques and fuzzy rule-based systems. He has academically refereed journal and conference publications in most areas of his expertise.

George has jointly managed a number of successful KTP/KEEP/InnovateUK income generating initiatives, promoted training courses for schools and industry (networking, neural networks), and has been involved in EU funding bid preparation, all reflecting an interest in external income generation from alternative sources.

Find out more about Dr George Wilson.

Dr Cristina Luca - contact for postgraduate research student enquiries

Dr Cristina Luca

Cristina Luca (PhD Formal Languages) worked for several years in industry as a senior software engineer prior to her academic career. Experienced in ontological modelling and mobile development, she teaches programming, software engineering and Web application development. Her research interests are in the semantic web and the integration of ontologies in software applications utilising machine learning.

Cristina has co-authored several textbooks on programming and algorithms and published and peer reviewed papers on semantic query languages, linked data, and formal languages. She is interested in promoting income generation through knowledge transfer (involvement in European and KTP projects) and other sources (BCS funding for educational school support).

Find out more about Dr Cristina Luca.

Dr Lakshmi Babu Saheer

Headshot photo of Lakshmi Babu Saheer

Lakshmi Saheer (PhD Computer Science and Artificial Intelligence) has international industrial and academic research experience in AI, especially in the fields of data science and machine learning. She has successfully applied data analysis, machine learning and signal processing techniques on diverse domains like air quality, climate change and sustainability, various speech and audio applications, affective computing, medical & healthcare and IoT.

Lakshmi has several awards and grants worth more than £150K under her belt. She is the author and reviewer of several international conference and journal publications. She has been involved in various European projects with international collaborations.

Find out more about Prof Lakshmi Babu Saheer.

Prof Marcian Cirstea

Marcian Cirstea

Marcian Cirstea (Professor, PhD Digital Control) has interests mainly in digital systems, with a focus on artificial intelligence and the use of computer aided design tools and methods applied to digital systems modelling and rapid prototyping using VHDL and FPGAs, including generative design. He has co-authored over 145 peer reviewed papers and several technical books, and has delivered several international tutorials in these subject areas.

Aside from his duties as Head of School, Marican's professional activities include coordinating an European project consortium, participating in several knowledge transfer partnerships, chairing a few IEEE international conferences and acting as Associate Editor for the IEEE Transactions on Industrial Informatics. He is interested in knowledge transfer schemes and short training courses.

Find out more about Dr Marcian Cirstea.

Dr Silvia Cirstea

Silvia Cirstea

Silvia Cirstea (PhD Imaging Technologies) has more than fifteen years’ research experience in mathematical and software modelling for imaging technologies, acoustics, radio communications and medical applications. Her areas of expertise include image and signal processing, neural networks, inverse problems, numerical modelling of physical processes (electromagnetics, acoustics, psycho-acoustics, quantum mechanics), statistical methods, SLAM and ray tracing.

Silvia has a keen interest in assisted living applications for the visually impaired and has been involved in successful EU and Innovate UK projects.

Find out more about Dr Silvia Cirstea.

Dr Stiphen Chowdhury

Headshot photo of Stiphen Chowdhury, wearing a blue shirt

Stiphen Chowdhury (MSc Software Engineering) has a mix of academic and commercial experience involving various Java/C++ programming projects. His research interests are in Artificial Intelligence especially feature weighting in clustering algorithms, supervised and unsupervised learning.

Find out more about Dr Stiphen Chowdhury

Dr Razvan-Ioan Dinita

Image of Dr Razvan-Ioan Dinita

Razvan-Ioan Dinita (PhD Cloud Computing) has expertise in Cloud software development, optimisation and security, web and software engineering/security and programming languages. His research is focused in these areas and he has authored a number of relevant peer-reviewed publications and presented his work at international conferences. He is interested in generating external income through EU and other sources, delivery of short training courses, and knowledge transfer schemes (recently involved in several KEEP projects).

Find out more about Dr Razvan-Ioan Dinita.

Dr Arooj Fatima

Arooj Fatima Head Shot

Arooj Fatima (PhD The Semantic Web) has 12 years' industrial background in the IT sector (database design, evaluation of user interfaces for software applications) and is an experienced programmer in web and mobile application development. Her research interests include AI (semantic data technologies, natural language software interfaces) and user experience design techniques. She is interested in generating external income in these areas of research through the delivery of short training courses and knowledge transfer schemes.

Find out more about Dr Arooj Fatima.

Dr Mahdi Maktab-Dar-Oghaz

Profile picture Mahdi Maktabdar Oghaz

Mahdi Maktab-Dar-Oghaz's (PhD Computer Vision and Machine Learning) expertise includes use of video analytics, artificial intelligence, and computer vision used in both small scale (medical image processing) and largescale (crowd safety and security) applications. His interests extend to deep learning and convolutional neural networks applied to these scenarios. He has published several articles in various international journals and conferences, and has been involved in collaborative projects (cyber Security, video analytics) including a European (H2020) project.

Find out more about Dr Mahdi Maktab-Dar-Oghaz.

Dr Ian van der Linde

Ian van der Linde

Ian van der Linde (PhD Human/Computer Vision) has research interests that include image processing and vision science, computing methods in psychology, neuropsychological testing, and evolutionary algorithms. Ian is particularly interested in external income generation to fund research studentships and fellowships.

Find out more about Dr Ian van der Linde.

Dr Domenico Vicinanza

Domenico Vicinanza (PhD Physics) is a public speaker and professional music composer and orchestrator. He worked for seven years at CERN as a scientific associate. He is a co-author of more than 130 publications and his expertise includes high-energy particle detector and grid technology, network-enabled audio-video communication, audio-music technology and smart sensors.

Domenico's main research interest is in auditory display (sound engineering for scientific data analysis, including space, satellite and biomechanics) and non-linear dynamics with applications to human movement science, sport science and experimental psychology. He has active collaborations with CERN and NASA and is interested in generating external income through professional consultancy, delivery of short training courses and knowledge transfer schemes in all areas of his expertise/research.

Find out more about Dr Domenico Vicinanza.

PhD Researchers

  • Agborubere, B. 'Securing SDN Communication between the Control Plane and Data Plane in Software Defined Networks'. 1st supervisor Erika Sanchez-Velazquez.
  • Bagnoli, M. 'Simulation and Use of Reverberation in Virtual Environments as A Wayfinding Aid for Visually Impaired Users'. 1st supervisor Silvia Cirstea.
  • Chakraborty, A. 'Mobile Enabled Intelligent Retinal Image Base Diagnosis (Mi-Retina)'. 1st supervisor George Wilson.
  • Egan, D. 'A model for decision-making on the priority of requirements for software product lines with multiple target markets and business stakeholders'. 1st supervisor Cristina Luca.
  • Ehsaniamrehee, S. 'Modelling and Optimizing Carbon Emission Factors in Food Supply Chain using AI'. 1st supervisor Lakshmi Babu-Saheer.
  • Fitzjohn, J. 'Emulating a traditional CPU with a Quantum Computer'. 1st supervisor Adrian Winckles.
  • Milke, V. 'Intraday Machine Learning for the Securities Market'. 1st supervisor Cristina Luca.
  • Mkpa, A. 'Dynamic Configurable Model for Addressing Trust, Security, and Privacy in Ubiquitous IoT Network'. 1st supervisor George Wilson.
  • O'Reilly, J. 'Artificial Intelligence‐Based Navigation Aid for Indoor and Low‐Light Environments'. 1st supervisor Silvia Cirstea.
  • Payne, P. 'Intelligent Control System Development for Electric Powered Wheelchairs'. 1st supervisor Erika Sanchez-Velazquez.
  • Sanaei, A. 'A Novel Multisensory System with an Original Predictive Algorithm to Provide Auditory Feedback of Multidimensional Advanced Coordination and Gait Movement'. 1st supervisor Domenico Vicinanza.
  • Shaikh, A. 'An Intelligent Real-Time Anti-Phishing System to Protect Internet Users.' 1st supervisor Michael Cole.
  • Wamambo, T. 'Predictive Product Review Analysis Using Sentiment Analysis and Machine Learning'. 1st supervisor Cristina Luca.
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Activities, projects and partnerships

Members of our research group have participated in the following projects and partnerships:

  • Development of pre-emptive decision making on clinical and operational issues, and apply AI algorithms to identify parties (people) at risk, KTP with AT Medics, October 2019 – March 2022. £200k.
  • Development of large anti-reflection coated lenses for passive (sub)millimetre-wave science instruments‘, European Space Agency funded, led by Cardiff University, in collaboration with University College London (UCL), Mullard Space Science Laboratory (MSSL), Anglia Ruskin University (ARU) and Stockholm University. November 2019 – November 2021. 51.4k € of 600k €.
  • ‘BIMformed - Adaptive learning for zero defects in buildings’ (development of a data collection and machine learning framework to predict and prevent errors in the construction industry), Innovate UK project with TR Control Solutions, February 2019 – April 2020. £120K.
  • Development of a ‘real time’ web-based software platform to replace the current, legacy costing and warehousing program, KEEP+ with Prime Accounting Software Ltd. May 2018-September 2019. £69k.
  • Development of a secure Instant Messaging social media app for healthcare professionals, KEEP+ with Lane Data Solutions. September 2017-September 2018. £54k.
  • Urban Living: Integrated Products and Services CR&D, "Hyperlocal Rainfall", InnovateUK. 2015-2017. £33.81k of £230,566.00.
  • Development of a new high performance low cost acoustic absorber for use in new and existing buildings, Echo2Eco. 2014. Total 1.1 million € for three universities and five companies across Europe.

We have also undertaken other KTPs and KEEPs worth up to £130k with many local and national companies including Sovereign Installations Ltd, Glazing Vision, LMK Thermosafe, Papershrink Ltd, Calex Electronics and I-Dash Ltd.

Members of our research group have also organised the following:

  • NPAPW2019 – The international conference on network and technology applied to performing arts, Prague 2-4 April 2019.
  • ISIE 2017 – the 26th IEEE International Symposium on Industrial Electronics, Edinburgh, June 2017. Prof Marcian Cirstea was General Chairman.
  • INDIN 2015 – the 13th IEEE International Conference on Industrial Informatics in Cambridge in July 2015. Prof Marcian Cirstea was General Chairman.
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ARU is helping protect the region from cyber-crime

Government funding allows ARU to support businesses across East of England

UK Government funding means businesses across the East of England can contact Anglia Ruskin University (ARU) for advice and support to help protect themselves from cyber-crime.

Dr Christian Kemp and Adrian Winckles from ARU are working in partnership with the Eastern Region Special Operations Unit and Essex Police to examine the vulnerabilities and cyber-security practices of the region’s small and medium-sized businesses and organisations. The year-long project is supported by funding from the National Cyber Security Programme, via the Home Office.

The widespread nature of the problem was highlighted by a Government survey released this year, which showed that almost half of all UK businesses (46%) and a quarter of all charities (26%) had reported cyber-security breaches or attacks in the previous 12 months. Since that survey was carried out, an increase in remote working is likely to have put further strain on already stretched IT systems.

The project, which is being led by Dr Christian Kemp and Adrian Winckles, is bringing together ARU’s specialisms in cyber-criminology, digital policing, and cyber-security and technology.

Adrian is a Senior Lecturer in Computing and Information Science, and the Director of ARU's Cyber Security and Networking Research Group, while Christian is Course Leader for the BA (Hons) in Criminology and Policing, and has researched Dark Web networks and new patterns of online human trafficking.

Read more about read more about how aru is helping protect the region from cyber-crime.

BIMformed: Machine learning framework for predicting and preventing defects in buildings

Funded by Innovate UK, Silvia Cirstea, Razvan Dinita and Javad Zarrin from the School of Computing and Information Science worked with industry partner TR Control Solutions to tackle the challenge of reducing errors in the construction industry.

Availability of data in the construction industry is a major barrier, as most building workers do not get their instructions via digital devices and records of errors are not kept in digital form linked to the construction specification. To address this problem, the project developed a framework to collect and link up data from a number of sources, including workers’ profiles and understanding of task, captured via a web app, and construction task information extracted from specification models and design documents. Artificial Intelligence techniques were used to devise automatic generation of questionnaires to assess operatives' knowledge and understanding of the task.

A machine learning framework, based on Support Vector Machines, was developed and shown to be able to predict the likelihood of construction defects with sufficient reliability and accuracy on a pilot data set. Following the successful completion of this feasibility study with our partners in April 2020, collaboration continues to develop the framework into a commercial product.

Read more about read more about the project bimformed: machine learning framework for predicting and preventing defects in buildings.

Recent publications

Bednarik, R., …, van der Linde, I., 2020. EMIP: The eye-movements in programming dataset. Science of Computer Programming. >doi: 10.1016/j.scico.2020.102520

Viera, A., van der Linde, I., Bright, P., Wilkins, A., 2020. Preference for lighting chromaticity in migraine with aura. Headache, 60(6), pp. 1124-1131.doi: 10.1111/head.13801

Sapkota, R. P., van der Linde, I., & Pardhan, S., 2020. How does aging influence object-location and name-location binding during a visual short-term memory task? Aging & Mental Health, 24(1), pp. 63-72, doi: 10.1080/13607863.2018.1515887

Bright, P., & van der Linde, I., 2020. Comparison of methods for estimating premorbid intelligence. Neuropsychological Rehabilitation, 30(1), pp. 1-14, doi: 10.1080/09602011.2018.1445650

Aggius-Vella, E., Kolarik, A. J., Gori, M., Cirstea, S., Campus, C., Moore, B. C. J., Pardhan, S., 2020. Comparison of auditory spatial bisection and minimum audible angle in front, lateral, and back space. Scientific Reports, 10, p. 6279. doi: 10.1038/s41598-020-62983-z

Kolarik, A. J., Raman, R., Moore, B. C. J., Cirstea, S., Gopalakrishnan, S., Pardhan, S., 2020. The accuracy of auditory spatial judgments in the visually impaired is dependent on sound source distance. Scientific Reports, 10, p. 7169, doi: 10.1038/s41598-020-64306-8

Hameed, N., Shabut, A., Hameed, F., Cirstea, S., Harriet, S., Hossain, A., 2020. Mobile-based Skin Lesions Classification Using Convolution Neural Network. Annals of Emerging Technologies in Computing, 4(2), pp. 26-37. doi: 10.33166/AETiC.2020.02.003

Smith, L., Stubbs, B., Hu, L., Veronese, N., Vancampfort, D., Williams, G., Vicinanza, D., Jackson, S., Ying, L., López Sánchez, G. F., and Yang, L., 2019. Is active transport and leisure time physical activity associated with inflammatory markers in US adults: Cross-sectional analyses from NHANES. Journal of Physical Activity and Health, 16(7), pp. 540-546, doi: 10.1123/jpah.2018-0423

Moseley, P., Savini, G., Saenz, E., Zhang, J., and Ade, P., 2019. Detailed characterization of a lenster - A mm-wave flat lens. IEEE Transactions on Antennas and Propagation, 67(5), pp. 3178-3184 doi: 10.1109/TAP.2019.2902435

Zhao, G., Savini, G., Saenz, E., Zhang, J., Ade, P., 2019. A dual-port THz time domain spectroscopy system optimized for recovery of a sample's Jones matrix. Scientific Reports, 9. doi: 10.1038/s41598-019-39322-y

Oghaz, M. M., Maarof, M. A., Rohani, M. F., Zainal, A., & Shaid, S. Z. M., 2019. An optimized skin texture model using gray-level co-occurrence matrix. Neural Computing and Applications, 31, pp. 1835-1853. doi: 10.1007/s00521-017-3164-8

Hameed N., Hameed F., Shabut A., Khan S., Cirstea S., Hossain A., 2019, An Intelligent Computer-Aided Scheme for Classifying Multiple Skin Lesions. Computers, 8(3), p. 62. doi: 10.3390/computers8030062

Vicinanza, D., Newell, K. M., Irwin, G., Smith, L., & Williams, G. K., 2018. Limit cycle dynamics of the gymnastics longswing. Human Movement Science, 57, pp. 217-226. doi: 10.1016/j.humov.2017.12.014

van der Linde, I., Bright, P., 2018. A genetic algorithm to find optimal reading test word subsets for estimating full-scale IQ. PLOS ONE, 13(10), e0205754. doi: 10.1371/journal.pone.0205754

Bright, P., Hale, E., Gooch, V. J., Myhill, T., & van der Linde, I., 2018. The National Adult Reading Test: Restandardisation against the Wechsler Adult Intelligence Scale—Fourth edition. Neuropsychological Rehabilitation, 28(6), pp. 1019-1027. doi: 10.1080/09602011.2016.1231121

Kettouch, M. Luca, C., Hobbs, M., 2018. Mediator-based framework for keyword search over semi-structured and linked data. Journal of Intelligent Information Systems, 52(2), pp. 311-335. doi: 10.1007/s10844-018-0536-1

Zarrin, J., L. Aguiar, R., P. Barraca, J., 2018. Resource discovery for distributed computing systems: A comprehensive survey. Journal of Parallel and Distributed Computing, 113, pp. 127-166. doi: 10.1016/j.jpdc.2017.11.010

Williams, G. K., & Vicinanza, D., 2017. Coordination in gait: Demonstration of a spectral approach. Journal of Sports Sciences, 36(15), pp. 1768-1775. doi: 10.1080/02640414.2017.1416974

Moseley, P., Savini, G., Zhang, J., Ade, P., 2017. Dual focus polarisation splitting lens. Optics Express, 25(21), pp. 25363-25373. doi: 10.1364/OE.25.025363

Sapkota, R. P., van der Linde, I., Lamichhane, N., Upadhyaya, T., & Pardhan, S., 2017. Patients with Mild Cognitive Impairment Show Lower Visual Short-Term Memory Performance in Feature Binding Tasks. Dementia and Geriatric Cognitive Disorders Extra, 7(1), pp. 74-86, doi: 10.1159/000455831

Campbell, W., Paterson, J., & van der Linde, I., 2017. Listener preferences for alternative dynamic-range-compressed audio configurations. Journal of the Audio Engineering Society, 65(7/8), pp. 540-551. doi: 10.17743/jaes.2017.0019

Kolarik, A. J., Raman, R., Moore, B. C., Cirstea, S., Gopalakrishnan, S., & Pardhan, S., 2017. Partial visual loss affects self-reports of hearing abilities measured using a modified version of the speech, spatial, and qualities of hearing questionnaire. Frontiers in Psychology, 8, p. 561. doi: 10.3389/fpsyg.2017.00561

Kolarik, A. J., Pardhan, S., Cirstea, S., & Moore, B. C., 2017. Auditory spatial representations of the world are compressed in blind humans. Experimental Brain Research, 235(2), pp. 597-606. doi: 10.1007/s00221-016-4823-1

Williams, G., Aggio, D., Vicinanza, D., Stubbs, B., Kerr, C., Johnstone, J., Roberts, J., Smith, L., 2017. Prospective associations between measures of gross and fine motor coordination in infants and objectively measured physical activity and sedentary behaviour in childhood. Medicine, 96(46), e8424. doi: 10.1097/MD.0000000000008424

Zarrin, J., Aguiar, R. L., Barraca, J. P., 2017. HARD: Hybrid Adaptive Resource Discovery for Jungle Computing. Journal of Network and Computer Applications, 90, pp. 42-73. doi: 10.1016/j.jnca.2017.04.014

Zarrin, J., Aguiar, R. L., Barraca, J. P., 2017. Manycore simulation for peta-scale system design: Motivation, tools, challenges and prospects. Simulation Modelling Practice and Theory, 72, pp. 168-201. doi: 10.1016/j.simpat.2016.12.014

Oghaz, M. M., Maarof, M. A., Rohani, M. F., Zainal, A., & Shaid, S. Z. M., 2017. A Hybrid Color Space for Skin Recognition for Real-Time Applications. Journal of Computational and Theoretical Nanoscience, 14(4), pp. 1852-1861. doi: 10.1166/jctn.2017.6516

Sapkota, R. P., Pardhan, S., & van der Linde, I., 2016. Spatiotemporal proximity effects in visual short-term memory examined by target–nontarget analysis. Journal of Experimental Psychology: Learning, Memory and Cognition, 42(8), pp. 1304-1315. doi: 10.1037/xlm0000238

McGonigle, C., van der Linde, I., Pardhan, S., Engel, S. A., Mallen, E. A., & Allen, P. M., 2016. Myopes experience greater contrast adaptation during reading. Vision Research, 121, pp. 1-9. doi: 10.1016/j.visres.2016.01.001

Kolarik, A. J., Moore, B. C., Zahorik, P., Cirstea, S., & Pardhan, S., 2016. Auditory distance perception in humans: a review of cues, development, neuronal bases, and effects of sensory loss. Attention, Perception, & Psychophysics, 78(2), pp.373-395. doi: 10.3758/s13414-015-1015-1

Stanciu, A., Cirstea, M. N., & Moldoveanu, F. D., 2016. Analysis and evaluation of PUF-based SoC designs for security applications. IEEE Transactions on Industrial Electronics, 63(9), pp. 5699-5708. doi: 10.1109/TIE.2016.2570720

Folea, S. C., Mois, G., Muresan, C. I., Miclea, L., De Keyser, R., & Cirstea, M. N., 2016. A portable implementation on industrial devices of a predictive controller using graphical programming. IEEE Transactions on Industrial Informatics, 12(2), pp. 736-744. doi: 10.1109/TII.2016.2532118

Zarrin, J., Aguiar, R. L., Barraca, J. P., 2016. ElCore: Dynamic elastic resource management and discovery for future large-scale manycore enabled distributed systems. Microprocessors and Microsystems, 46(B), pp. 221-239. doi: 10.1016/j.micpro.2016.06.007

Yaghoubyan, S. H., Maarof, M. A., Zainal, A., Kiani, M. J., Rad, F., & Oghaz, M. M., 2016. A Robust Keypoint Descriptor Based on Tomographic Image Reconstruction Using Heuristic Genetic Algorithm and Principal Component Analysis Techniques. Journal of Computational and Theoretical Nanoscience, 13(8), pp. 5554-5568. doi: 10.1166/jctn.2016.5453

Zarrin, J. L., Aguiar, R. L., Barraca, J. P., 2015. Dynamic, scalable and flexible resource discovery for large-dimension many-core systems. Future Generation Computer Systems, 53, pp. 119-129. doi: 10.1016/j.future.2014.12.011

Oghaz, M. M., Maarof, M. A., Zainal, A., Rohani, M. F., & Yaghoubyan, S. H., 2015. A hybrid color space for skin detection using genetic algorithm heuristic search and principal component analysis technique. PLOS ONE, 10(8), e0134828. doi: 10.1371/journal.pone.0134828

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