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All Outputs (33)

Rectangular antenna with vertical slots implemented for WLAN applications (2019)
Conference Proceeding
Awais, Q., Khan, M. N., Zahid, T., Mehboob, K., Malik, M. H., Jamil, M., & Farasat, M. (2019). Rectangular antenna with vertical slots implemented for WLAN applications.

In this paper slot lines are introduced in WLAN antenna that has compact size of 97mm x80 to enhance the bandwidth. CPW feed mechanism is implemented which enables the system to be tuned at wide range of frequencies. The size of capacitive slots is o... Read More about Rectangular antenna with vertical slots implemented for WLAN applications.

Tying together solutions for digital manufacturing: Assessment of connectivity technologies & approaches (2019)
Conference Proceeding
Hawkridge, G., Hernandez, M. P., De Silva, L., Terrazas, G., Tlegenov, Y., McFarlane, D., & Thorne, A. (2019). Tying together solutions for digital manufacturing: Assessment of connectivity technologies & approaches. In 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) (1383-1387). https://doi.org/10.1109/ETFA.2019.8869411

This paper concerns the development of low-cost solutions to address challenges in digital manufacturing (DM). Service Oriented Architectures (SOAs) are a promising approach for addressing the requirements of a low-cost DM architecture. Interaction b... Read More about Tying together solutions for digital manufacturing: Assessment of connectivity technologies & approaches.

Printing the Muses: Reimaging digital musical instruments through 2.5D printing (2019)
Conference Proceeding
Parraman, C., & Gaster, B. (2019). Printing the Muses: Reimaging digital musical instruments through 2.5D printing

The objective is to explore cross-disciplinary methods of converting musical terms for tactile interfaces, thus enabling people unfamiliar in creating music to be explorative through the development of novel musical interfaces. The project involves w... Read More about Printing the Muses: Reimaging digital musical instruments through 2.5D printing.

Further lower bounds for structure-preserving signatures in asymmetric bilinear groups (2019)
Conference Proceeding
Ghadafi, E. (2019). Further lower bounds for structure-preserving signatures in asymmetric bilinear groups. In J. Buchmann, N. Abderrahmane, & R. Tajjeeddine (Eds.), 11th International Conference on Cryptology, AFRICACRYPT 2019. https://doi.org/10.1007/978-3-030-23696-0

Structure-Preserving Signatures (SPSs) are a useful tool for the design of modular cryptographic protocols. Recent series of works have shown that by limiting the message space of those schemes to the set of Diffie-Hellman (DH) pairs, it is possible... Read More about Further lower bounds for structure-preserving signatures in asymmetric bilinear groups.

Audio reproduction in virtual reality cinemas – Position paper (2019)
Conference Proceeding
Reed, L., & Phelps, P. (2019). Audio reproduction in virtual reality cinemas – Position paper. In 2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR). , (1513-1516). https://doi.org/10.1109/VR.2019.8797904

Virtual Reality (VR) and 360 film have caught the attention of audiences and content creators and emerged as a new media, however, the market penetration of VR and head mounted hardware has remained slow despite the availability of more affordable mo... Read More about Audio reproduction in virtual reality cinemas – Position paper.

A novel parallel framework for metaheuristic-based frequent itemset mining (2019)
Conference Proceeding
Djenouri, Y., Djenouri, D., Belhadi, A., Chun-Wei Lin, J., Bendjoudi, A., & Fournier-Viger, P. (2019). A novel parallel framework for metaheuristic-based frequent itemset mining. https://doi.org/10.1109/cec.2019.8790116

Frequent Itemset Mining (FIM) is an important but very time-consuming data mining task. As a result, traditional FIM algorithms are often not scalable to large databases. To address this issue, several metaheuristics have been developed in recent yea... Read More about A novel parallel framework for metaheuristic-based frequent itemset mining.

Machine learning: An ethical, social & political perspective (2019)
Conference Proceeding
Mageswaran, G., Nagappan, S. D., Hamzah, N., & Brohi, S. (2019). Machine learning: An ethical, social & political perspective. In 2018 Fourth International Conference on Advances in Computing, Communication & Automation (ICACCA). https://doi.org/10.1109/ICACCAF.2018.8776702

Machine Learning is an emerging field which has created a significant positive and undesirable impact too many industries. This technology has been well received and widely used for precise decision making as its ability to process, analyze and visua... Read More about Machine learning: An ethical, social & political perspective.

Transparent workflow system to eliminate biasness in assessing final year projects (2019)
Conference Proceeding
Kaur, S., Angelina, N., Hon, S. S. K., Ntambo, M., Brohi, S., & Hashem, I. A. T. (2019). Transparent workflow system to eliminate biasness in assessing final year projects. In Proceedings - 2018 4th International Conference on Advances in Computing, Communication and Automation, ICACCA 2018. https://doi.org/10.1109/ICACCAF.2018.8776759

The purpose of this study is to understand the Final Year Project System existences and to find improvement in their workflow process. The observation made was based on a case-study workflow conducted by the final year student. In this paper the prop... Read More about Transparent workflow system to eliminate biasness in assessing final year projects.

Middleware power saving scheme for mobile applications (2019)
Conference Proceeding
Jhanjhi, N. Z., Almusalli, F. A., Brohi, S., & Abdullah, A. (2019). Middleware power saving scheme for mobile applications. In 2018 Fourth International Conference on Advances in Computing, Communication & Automation (ICACCA). https://doi.org/10.1109/ICACCAF.2018.8776711

Smartphones popularity, usage and users dependency has been increased over the years. The popularity increase is linked with several factors such as smartphones size, ease in use, and several supported multipurpose apps. This all is enable due to the... Read More about Middleware power saving scheme for mobile applications.

Credit card fraud detection using deep learning technique (2019)
Conference Proceeding
Pillai, T. R., Hashem, I. A. T., Brohi, S., Kaur, S., & Marjani, M. (2019). Credit card fraud detection using deep learning technique. In 2018 Fourth International Conference on Advances in Computing, Communication & Automation (ICACCA). https://doi.org/10.1109/ICACCAF.2018.8776797

Credit card fraud detection is growing due to the increase and the popularity of online banking. The need to detect fraudulent within credit card has become as a serious problem among the online shoppers. The multi-layer perceptron (MLP) machine lear... Read More about Credit card fraud detection using deep learning technique.

Data science methodology for Internet-of-Things (2019)
Conference Proceeding
Brohi, S., Marjani, M., Hashem, I. A. T., Pillai, T. R., Kaur, S., & Amalathas, S. S. (2019). Data science methodology for Internet-of-Things. In M. H. Miraz, P. S. Excell, A. Ware, S. Soomro, & M. Ali (Eds.), International Conference for Emerging Technologies in Computing (178-186). https://doi.org/10.1007/978-3-030-23943-5_13

The journey of data from the state of being valueless to valuable has been possible due to powerful analytics tools and processing platforms. Organizations have realized the potential of data, and they are looking far ahead from the traditional relat... Read More about Data science methodology for Internet-of-Things.

Incremental development of business process architecture using the design science research methodology (2019)
Conference Proceeding
Sabri, M., Odeh, M., & Saad, M. (2019). Incremental development of business process architecture using the design science research methodology

This paper presents a new approach to developing a business process architecture using the design science research methodology. It is also part of the research framework development that generates a business process architecture using semantic knowle... Read More about Incremental development of business process architecture using the design science research methodology.

ICT Sustainability from Day One: Introducing New Computer Science Students at a UK University to Sustainability (2019)
Conference Proceeding
Brooks, I. (2019). ICT Sustainability from Day One: Introducing New Computer Science Students at a UK University to Sustainability

As ICT impacts dramatically on the sustainability of the world and of individuals, both positive and negative, there is an urgent need to educate Computer Science students about Sustainability. This paper assesses the experience of a project to intro... Read More about ICT Sustainability from Day One: Introducing New Computer Science Students at a UK University to Sustainability.

Enhancing user fairness in OFDMA radio access networks through machine learning (2019)
Conference Proceeding
Comsa, I., Zhang, S., Aydin, M., Kuonen, P., Trestian, R., & Ghinea, G. (2019). Enhancing user fairness in OFDMA radio access networks through machine learning. In 2019 Wireless Days (WD). , (1-8). https://doi.org/10.1109/WD.2019.8734262

The problem of radio resource scheduling subject to fairness satisfaction is very challenging even in future radio access networks. Standard fairness criteria aim to find the best trade-off between overall throughput maximization and user fairness sa... Read More about Enhancing user fairness in OFDMA radio access networks through machine learning.

Classification of eye-state using EEG recordings: Speed-up gains using signal epochs and mutual information measure (2019)
Conference Proceeding
Asquith, P. M., & Ihshaish, H. (2019). Classification of eye-state using EEG recordings: Speed-up gains using signal epochs and mutual information measure. https://doi.org/10.1145/3331076.3331095

© 2019 Copyright held by the owner/author(s). Publication rights licensed to ACM. The classification of electroencephalography (EEG) signals is useful in a wide range of applications such as seizure detection/prediction, motor imagery classification,... Read More about Classification of eye-state using EEG recordings: Speed-up gains using signal epochs and mutual information measure.

FABIoT: A Flexible Agent-Based Simulation Model for IoT Environments (2019)
Conference Proceeding
Perez Hernandez, M., Alturki, B., & Reiff-Marganiec, S. (2019). FABIoT: A Flexible Agent-Based Simulation Model for IoT Environments. In 2018 IEEE International Conference on Internet of Things (iThings); IEEE Green Computing and Communications (GreenCom); IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) (66-73). https://doi.org/10.1109/Cybermatics_2018.2018.00045

The Internet of Things aims to digitize everyday physical objects by connecting them to the internet. As a result, cyber-physical environments of multiple sizes emerge, imposing new requirements on applications and software systems in regards support... Read More about FABIoT: A Flexible Agent-Based Simulation Model for IoT Environments.

Tools and techniques for improving cyber situational awareness of targeted phishing attacks (2019)
Conference Proceeding
Legg, P., & Blackman, T. (2019). Tools and techniques for improving cyber situational awareness of targeted phishing attacks. . https://doi.org/10.1109/CyberSA.2019.8899406

© 2019 IEEE. Phishing attacks continue to be one of the most common attack vectors used online today to deceive users, such that attackers can obtain unauthorised access or steal sensitive information. Phishing campaigns often vary in their level of... Read More about Tools and techniques for improving cyber situational awareness of targeted phishing attacks.

Efficient and interpretable real-time malware detection using random-forest (2019)
Conference Proceeding
Mills, A., Spyridopoulos, T., & Legg, P. (2019). Efficient and interpretable real-time malware detection using random-forest. . https://doi.org/10.1109/CyberSA.2019.8899533

© 2019 IEEE. Malicious software, often described as malware, is one of the greatest threats to modern computer systems, and attackers continue to develop more sophisticated methods to access and compromise data and resources. Machine learning methods... Read More about Efficient and interpretable real-time malware detection using random-forest.