Exploring coupled images fusion based on joint tensor decomposition (2020)
Journal Article
Lu, L., Ren, X., Yeh, K.-H., Tan, Z., & Chanussot, J. (2020). Exploring coupled images fusion based on joint tensor decomposition. Human-Centric Computing and Information Sciences, 10, Article 10 (2020). https://doi.org/10.1186/s13673-020-00215-z

Data fusion has always been a hot research topic in human-centric computing and extended with the development of artificial intelligence. Generally, the coupled data fusion algorithm usually utilizes the information from one data set to improve the e... Read More about Exploring coupled images fusion based on joint tensor decomposition.

Using MAP-Elites to support policy making around Workforce Scheduling and Routing (2020)
Journal Article
Urquhart, N., Hart, E., & Hutcheson, W. (2020). Using MAP-Elites to support policy making around Workforce Scheduling and Routing. Automatisierungstechnik, 68(2), https://doi.org/10.1515/auto-2019-0107

English abstract: Algorithms such as MAP-Elites provide a means of allowing users to explore a solution space by returning an archive of high-performing solutions. Such an archive, can allow the user an overview of the solution space which may be use... Read More about Using MAP-Elites to support policy making around Workforce Scheduling and Routing.

Fast Forensic Triage Using Centralised Thumbnail Caches on Windows Operating Systems (2020)
Journal Article
Mckeown, S., Russell, G., & Leimich, P. (2020). Fast Forensic Triage Using Centralised Thumbnail Caches on Windows Operating Systems. Journal of Digital Forensics, Security and Law, 14(3), Article 1

A common investigative task is to identify known contraband images on a device, which typically involves calculating cryptographic hashes for all the files on a disk and checking these against a database of known contraband. However, modern drives ar... Read More about Fast Forensic Triage Using Centralised Thumbnail Caches on Windows Operating Systems.

Double-Arc Parallel Coordinates and its Axes re-Ordering Methods (2020)
Journal Article
Lu, L., Wang, W., & Tan, Z. (2020). Double-Arc Parallel Coordinates and its Axes re-Ordering Methods. Mobile Networks and Applications, 25(4), 1376-1391. https://doi.org/10.1007/s11036-019-01455-9

The Parallel Coordinates Plot (PCP) is a popular technique for the exploration of high-dimensional data. In many cases, researchers apply it as an effective method to analyze and mine data. However, when today's data volume is getting larger, visual... Read More about Double-Arc Parallel Coordinates and its Axes re-Ordering Methods.

PTAOD: A Novel Framework For Supporting Approximate Outlier Detection over Streaming Data for Edge Computing (2019)
Journal Article
Zhu, R., Yu, T., Tan, Z., Du, W., Zhao, L., Li, J., & Xia, X. (2020). PTAOD: A Novel Framework For Supporting Approximate Outlier Detection over Streaming Data for Edge Computing. IEEE Access, 8, 1475-1485. https://doi.org/10.1109/ACCESS.2019.2962066

Outlier detection over sliding window is a fundamental problem in the domain of streaming data management, which has been studied over 10 years. The key of supporting outlier detection is to construct a neighbour-list for each object. It is used for... Read More about PTAOD: A Novel Framework For Supporting Approximate Outlier Detection over Streaming Data for Edge Computing.

Fuzzy-Based Distributed Protocol for Vehicle-to-Vehicle Communication (2019)
Journal Article
Hawbani, A., Torbosh, E., Wang, X., Sincak, P., Zhao, L., & Al-Dubai, A. (2021). Fuzzy-Based Distributed Protocol for Vehicle-to-Vehicle Communication. IEEE Transactions on Fuzzy Systems, 29(3), 612-626. https://doi.org/10.1109/tfuzz.2019.2957254

This paper modeled the multihop data-routing in Vehicular Ad-hoc Networks(VANET) as Multiple Criteria Decision Making (MCDM) in four steps. First, the criteria which have an impact on the performance of the network layer are captured and transformed... Read More about Fuzzy-Based Distributed Protocol for Vehicle-to-Vehicle Communication.

Novel Fuzzy and Game Theory Based Clustering and Decision Making for VANETs (2019)
Journal Article
Alsarhan, A., Kilani, Y., Al-Dubai, A., Zomaya, A. Y., & Hussain, A. (2020). Novel Fuzzy and Game Theory Based Clustering and Decision Making for VANETs. IEEE Transactions on Vehicular Technology, 69(2), 1568-1581. https://doi.org/10.1109/TVT.2019.2956228

Different studies have recently emphasized the importance of deploying clustering schemes in Vehicular ad hoc Network (VANET) to overcome challenging problems related to scalability, frequent topology changes, scarcity of spectrum resources, maintain... Read More about Novel Fuzzy and Game Theory Based Clustering and Decision Making for VANETs.

PFARS: Enhancing Throughput and Lifetime of Heterogeneous WSNs through Power-aware Fusion, Aggregation and Routing Scheme (2019)
Journal Article
Khan, R., Zakarya, M., Tan, Z., Usman, M., Jan, M. A., & Khan, M. (2019). PFARS: Enhancing Throughput and Lifetime of Heterogeneous WSNs through Power-aware Fusion, Aggregation and Routing Scheme. International Journal of Communication Systems, 32(18), Article e4144. https://doi.org/10.1002/dac.4144

Heterogeneous wireless sensor networks (WSNs) consist of resource-starving nodes that face a challenging task of handling various issues such as data redundancy, data fusion, congestion control, and energy efficiency. In these networks, data fusion a... Read More about PFARS: Enhancing Throughput and Lifetime of Heterogeneous WSNs through Power-aware Fusion, Aggregation and Routing Scheme.

A Quality of Service-Aware Secured Communication Scheme for Internet of Things-Based Networks (2019)
Journal Article
Khan, F., Ur Rehman, A., Yahya, A., Jan, M. A., Chuma, J., Tan, Z., & Hussain, K. (2019). A Quality of Service-Aware Secured Communication Scheme for Internet of Things-Based Networks. Sensors, 19, Article 4321. https://doi.org/10.3390/s19194321

The Internet of Things (IoT) is an emerging technology that aims to enable the interconnection of a large number of smart devices and heterogeneous networks. Ad hoc networks play an important role in the designing of IoT-enabled platforms due to thei... Read More about A Quality of Service-Aware Secured Communication Scheme for Internet of Things-Based Networks.

A Lightweight and Efficient Digital Image Encryption Using Hybrid Chaotic Systems for Wireless Network Applications (2019)
Journal Article
Almalkawi, I. T., Halloush, R., Alsarhan, A., Al-Dubai, A., & Al-karaki, J. N. (2019). A Lightweight and Efficient Digital Image Encryption Using Hybrid Chaotic Systems for Wireless Network Applications. Journal of Information Security and Applications, 49, https://doi.org/10.1016/j.jisa.2019.102384

Due to limited processing capabilities and other constraints of most wireless networks, many existing security algorithms do not consider the network efficiency. This is because most of these security solutions exhibit intolerable overhead and consid... Read More about A Lightweight and Efficient Digital Image Encryption Using Hybrid Chaotic Systems for Wireless Network Applications.

An AI approach to Collecting and Analyzing Human Interactions with Urban Environments (2019)
Journal Article
Ferrara, E., Fragale, L., Fortino, G., Song, W., Perra, C., di Mauro, M., & Liotta, A. (2019). An AI approach to Collecting and Analyzing Human Interactions with Urban Environments. IEEE Access, 7, 141476-141486. https://doi.org/10.1109/access.2019.2943845

Thanks to advances in Internet of Things and crowd-sensing, it is possible to collect vast amounts of urban data, to better understand how citizens interact with cities and, in turn, improve human well-being in urban environments. This is a scientifi... Read More about An AI approach to Collecting and Analyzing Human Interactions with Urban Environments.

Outlier Detection of Time Series with A Novel Hybrid Method in Cloud Computing (2019)
Journal Article
Liu, Q., Wang, Z., Liu, X., & Linge, N. (2019). Outlier Detection of Time Series with A Novel Hybrid Method in Cloud Computing. International Journal of High Performance Computing and Networking, 14(4), 435-443. https://doi.org/10.1504/IJHPCN.2019.102350

In the wake of the development in science and technology, Cloud Computing has obtained more attention in different field. Meanwhile, outlier detection for data mining in Cloud Computing is playing more and more significant role in different research... Read More about Outlier Detection of Time Series with A Novel Hybrid Method in Cloud Computing.

Deriving ChaCha20 Key Streams From Targeted Memory Analysis (2019)
Journal Article
McLaren, P., Buchanan, W. J., Russell, G., & Tan, Z. (2019). Deriving ChaCha20 Key Streams From Targeted Memory Analysis. Journal of Information Security and Applications, 48, Article 102372. https://doi.org/10.1016/j.jisa.2019.102372

There can be performance and vulnerability concerns with block ciphers, thus stream ciphers can used as an alternative. Although many symmetric key stream ciphers are fairly resistant to side-channel attacks, cryptographic artefacts may exist in memo... Read More about Deriving ChaCha20 Key Streams From Targeted Memory Analysis.

Non-intrusive load monitoring and its challenges in a NILM system framework (2019)
Journal Article
Liu, Q., Lu, M., Liu, X., & Linge, N. (2019). Non-intrusive load monitoring and its challenges in a NILM system framework. International Journal of High Performance Computing and Networking, 14(1), 102-111. https://doi.org/10.1504/IJHPCN.2019.099748

With the increasing of energy demand and electricity price, researchers gain more and more interest among the residential load monitoring. In order to feed back the individual appliance’s energy consumption instead of the whole-house energy consumpti... Read More about Non-intrusive load monitoring and its challenges in a NILM system framework.

Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks (2019)
Journal Article
Savaglio, C., Pace, P., Aloi, G., Liotta, A., & Fortino, G. (2019). Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks. IEEE Access, 7, 29355-29364. https://doi.org/10.1109/access.2019.2902371

High-density communications in wireless sensor networks (WSNs) demand for new approaches to meet stringent energy and spectrum requirements. We turn to reinforcement learning, a prominent method in artificial intelligence, to design an energy-preserv... Read More about Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks.

Analyzing Objective and Subjective Data in Social Sciences: Implications for Smart Cities (2019)
Journal Article
Erhan, L., Ndubuaku, M., Ferrara, E., Richardson, M., Sheffield, D., Ferguson, F. J., Brindley, P., & Liotta, A. (2019). Analyzing Objective and Subjective Data in Social Sciences: Implications for Smart Cities. IEEE Access, 7, 19890-19906. https://doi.org/10.1109/access.2019.2897217

The ease of deployment of digital technologies and the Internet of Things gives us the opportunity to carry out large-scale social studies and to collect vast amounts of data from our cities. In this paper, we investigate a novel way of analyzing dat... Read More about Analyzing Objective and Subjective Data in Social Sciences: Implications for Smart Cities.

Short-long term anomaly detection in wireless sensor networks based on machine learning and multi-parameterized edit distance (2018)
Journal Article
Cauteruccio, F., Fortino, G., Guerrieri, A., Liotta, A., Mocanu, D. C., Perra, C., Terracina, G., & Torres Vega, M. (2019). Short-long term anomaly detection in wireless sensor networks based on machine learning and multi-parameterized edit distance. Information Fusion, 52, 13-30. https://doi.org/10.1016/j.inffus.2018.11.010

Heterogeneous wireless sensor networks are a source of large amount of different information representing environmental aspects such as light, temperature, and humidity. A very important research problem related to the analysis of the sensor data is... Read More about Short-long term anomaly detection in wireless sensor networks based on machine learning and multi-parameterized edit distance.

Interference graphs to monitor and control schedules in low-power WPAN (2018)
Journal Article
van der Lee, T., Liotta, A., & Exarchakos, G. (2019). Interference graphs to monitor and control schedules in low-power WPAN. Future Generation Computer Systems, 93, 111-120. https://doi.org/10.1016/j.future.2018.10.014

Highlights
• This study presents the complete and slotted interference graph model.
• The service uses the complete interference graph to evaluate the network.
• Slotted interference graphs are used to reschedule problematic connections.
• Rea... Read More about Interference graphs to monitor and control schedules in low-power WPAN.

A Survey of Limitations and Enhancements of the IPv6 Routing Protocol for Low-power and Lossy Networks: A Focus on Core Operations (2018)
Journal Article
Ghaleb, B., Al-Dubai, A. Y., Ekonomou, E., Alsarhan, A., Nasser, Y., Mackenzie, L. M., & Boukerche, A. (2019). A Survey of Limitations and Enhancements of the IPv6 Routing Protocol for Low-power and Lossy Networks: A Focus on Core Operations. Communications Surveys and Tutorials, IEEE Communications Society, 21(2), 1607-1635. https://doi.org/10.1109/COMST.2018.2874356

Driven by the special requirements of the Low-power and Lossy Networks (LLNs), the IPv6 Routing Protocol for LLNs (RPL) was standardized by the IETF some six years ago to tackle the routing issue in such networks. Since its introduction, however, num... Read More about A Survey of Limitations and Enhancements of the IPv6 Routing Protocol for Low-power and Lossy Networks: A Focus on Core Operations.

Cloud-based video analytics using convolutional neural networks (2018)
Journal Article
Yaseen, M. U., Anjum, A., Farid, M., & Antonopoulos, N. (2019). Cloud-based video analytics using convolutional neural networks. Software: Practice and Experience, 49(4), 565-583. https://doi.org/10.1002/spe.2636

Object classification is a vital part of any video analytics system, which could aid in complex applications such as object monitoring and management. Traditional video analytics systems work on shallow networks and are unable to harness the power of... Read More about Cloud-based video analytics using convolutional neural networks.