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Experimental investigation of a novel vertical loop-heat-pipe PV/T heat and power system under different height differences (2022)
Journal Article
Yu, M., Chen, F., Zhou, J., Yuan, Y., Fan, Y., Li, G., Zhao, X., Wang, Z., Li, J., & Zheng, S. (2022). Experimental investigation of a novel vertical loop-heat-pipe PV/T heat and power system under different height differences. Energy, 254, Part A, Article 124193. https://doi.org/10.1016/j.energy.2022.124193

For a novel vertical solar loop-heat-pipe photovoltaic/thermal system, the height difference between evaporator and condenser plays an important role in the heat transport capacity, which has significant impact on the solar thermal efficiency and par... Read More about Experimental investigation of a novel vertical loop-heat-pipe PV/T heat and power system under different height differences.

Locally fitting hyperplanes to high-dimensional data (2022)
Journal Article
Hou, M., & Kambhampati, C. (2022). Locally fitting hyperplanes to high-dimensional data. Neural Computing and Applications, 34(11), 8885-8896. https://doi.org/10.1007/s00521-022-06909-y

Problems such as data compression, pattern recognition and artificial intelligence often deal with a large data sample as observations of an unknown object. An effective method is proposed to fit hyperplanes to data points in each hypercubic subregio... Read More about Locally fitting hyperplanes to high-dimensional data.

Consensus Adversarial Defense Method Based on Augmented Examples (2022)
Journal Article
Ding, X., Cheng, Y., Luo, Y., Li, Q., & Gope, P. (2022). Consensus Adversarial Defense Method Based on Augmented Examples. IEEE Transactions on Industrial Informatics, https://doi.org/10.1109/TII.2022.3169973

Deep learning has been used in many computer-vision-based industrial Internet of Things applications. However, deep neural networks are vulnerable to adversarial examples that have been crafted specifically to fool a system while being imperceptible... Read More about Consensus Adversarial Defense Method Based on Augmented Examples.

Computing on Wheels: A Deep Reinforcement Learning-Based Approach (2022)
Journal Article
Ahsan Kazmi, S. M., Ho, T. M., Nguyen, T. T., Fahim, M., Khan, A., Piran, M. J., & Baye, G. (2022). Computing on Wheels: A Deep Reinforcement Learning-Based Approach. IEEE Transactions on Intelligent Transportation Systems, 23(11), 22535-22548. https://doi.org/10.1109/TITS.2022.3165662

Future generation vehicles equipped with modern technologies will impose unprecedented computational demand due to the wide adoption of compute-intensive services with stringent latency requirements. The computational capacity of the next generation... Read More about Computing on Wheels: A Deep Reinforcement Learning-Based Approach.

Performance comparison of structured H∞ based looptune and LQR for a 4-DOF robotic manipulator (2022)
Journal Article
Asghar, A., Iqbal, M., Khaliq, A., Rehman, S. U., & Iqbal, J. (2022). Performance comparison of structured H∞ based looptune and LQR for a 4-DOF robotic manipulator. PLoS ONE, 17(4), Article e0266728. https://doi.org/10.1371/journal.pone.0266728

We explore looptune, a MATLAB-based structured H1 synthesis technique in the context of robotics. Position control of a 4 Degree of Freedom (DOF) serial robotic manipulator developed using Simulink is the problem under consideration. Three full state... Read More about Performance comparison of structured H∞ based looptune and LQR for a 4-DOF robotic manipulator.

Theory and practice for autonomous formation flight of quadrotors via distributed robust sliding mode control protocol with fixed-time stability guarantee (2022)
Journal Article
Mechali, O., Xu, L., Xie, X., & Iqbal, J. (2022). Theory and practice for autonomous formation flight of quadrotors via distributed robust sliding mode control protocol with fixed-time stability guarantee. Control engineering practice, 123, Article 105150. https://doi.org/10.1016/j.conengprac.2022.105150

A detailed theoretical design and technological implementation aspects are presented in this paper to address the aerial formation control problem of networked quadrotors with a fixed-time stability property. The control algorithm is embedded in a di... Read More about Theory and practice for autonomous formation flight of quadrotors via distributed robust sliding mode control protocol with fixed-time stability guarantee.

An AI-Driven Secure and Intelligent Robotic Delivery System (2022)
Journal Article
Wang, W., Gope, P., & Cheng, Y. (in press). An AI-Driven Secure and Intelligent Robotic Delivery System. IEEE Transactions on Engineering Management, https://doi.org/10.1109/TEM.2022.3142282

Last-mile delivery has gained much popularity in recent years, it accounts for about half of the whole logistics cost. Unlike container transportation, companies must hire significant number of employees to deliver packages to the customers. Therefor... Read More about An AI-Driven Secure and Intelligent Robotic Delivery System.

Dynamic Data Streams for Time-Critical IoT Systems in Energy-Aware IoT Devices Using Reinforcement Learning (2022)
Journal Article
Habeeb, F., Szydlo, T., Kowalski, L., Noor, A., Thakker, D., Morgan, G., & Ranjan, R. (2022). Dynamic Data Streams for Time-Critical IoT Systems in Energy-Aware IoT Devices Using Reinforcement Learning. Sensors, 22, Article 2375. https://doi.org/10.3390/s22062375

Thousands of energy-aware sensors have been placed for monitoring in a variety of scenarios, such as manufacturing, control systems, disaster management, flood control and so on, requiring time-critical energy-efficient solutions to extend their life... Read More about Dynamic Data Streams for Time-Critical IoT Systems in Energy-Aware IoT Devices Using Reinforcement Learning.

Maximum Power Extraction from a Standalone Photo Voltaic System via Neuro-Adaptive Arbitrary Order Sliding Mode Control Strategy with High Gain Differentiation (2022)
Journal Article
Anjum, M. B., Khan, Q., Ullah, S., Hafeez, G., Fida, A., Iqbal, J., & R. Albogamy, F. (2022). Maximum Power Extraction from a Standalone Photo Voltaic System via Neuro-Adaptive Arbitrary Order Sliding Mode Control Strategy with High Gain Differentiation. Applied Sciences, 12(6), Article 2773. https://doi.org/10.3390/app12062773

In this work, a photovoltaic (PV) system integrated with a non-inverting DC-DC buck-boost converter to extract maximum power under varying environmental conditions such as irradiance and temperature is considered. In order to extract maximum power (v... Read More about Maximum Power Extraction from a Standalone Photo Voltaic System via Neuro-Adaptive Arbitrary Order Sliding Mode Control Strategy with High Gain Differentiation.

Addressing Optimisation Challenges for Datasets with Many Variables, Using Genetic Algorithms to Implement Feature Selection (2022)
Journal Article
Gordon, N., Kambhampati, C., & Alabad, A. (2022). Addressing Optimisation Challenges for Datasets with Many Variables, Using Genetic Algorithms to Implement Feature Selection. AI, Computer Science and Robotics Technology, 1, 1-21. https://doi.org/10.5772/acrt.01

This article provides an optimisation method using a Genetic Algorithm approach to apply feature selection techniques for large data sets to improve accuracy. This is achieved through improved classification, a reduced number of features, and further... Read More about Addressing Optimisation Challenges for Datasets with Many Variables, Using Genetic Algorithms to Implement Feature Selection.