Browsing by Author "Guo, Weisi"

Adversarial reconfigurable intelligent surface against physical layer key generation

Wei, Zhuangkun; Li, Bin; Guo, Weisi (IEEE, 2023-04-12)

The development of reconfigurable intelligent surfaces (RIS) has recently advanced the research of physical layer security (PLS). Beneficial impacts of RIS include but are not limited to offering a new degree-of-freedom ...

Analysing region of attraction of load balancing on complex network

Zou, Mengbang; Guo, Weisi (Oxford Academic, 2022-06-29)

Many complex engineering systems network together functional elements to balance demand spikes but suffer from stability issues due to cascades. The research challenge is to prove the stability conditions for any arbitrarily ...

Ant-behavior inspired intelligent nanonet for targeted drug delivery in cancer therapy

Lin, Lin; Huang, Fupeng; Yan, Hao; Liu, Fuqiang; Guo, Weisi (IEEE, 2020-04-01)

Targeted drug delivery system is believed as one of the most promising solutions for cancer treatment due to its low-dose requirement and less side effects. However, both passive targeting and active targeting rely on ...

Assessing the impact of major historical events on urban landscapes via local entropy measures

Mazzamurro, Matteo; Guo, Weisi (IEEE, 2021-10-15)

In this paper we show how Shannon entropy, an intuitive and versatile measure of uniformity of a probability distribution, can be adapted to quantify the heterogeneity of land use and population density in and around human ...

Automatic quantification of settlement damage using deep learning of satellite images

Lu, Lili; Guo, Weisi (IEEE, 2021-10-15)

Humanitarian disasters and political violence cause significant damage to our living space. The reparation cost to homes, infrastructure, and the ecosystem is often difficult to quantify in real-time. Real-time quantification ...

A closed-loop output error approach for physics-informed trajectory inference using online data

Perrusquía, Adolfo; Guo, Weisi (IEEE, 2022-09-21)

While autonomous systems can be used for a variety of beneficial applications, they can also be used for malicious intentions and it is mandatory to disrupt them before they act. So, an accurate trajectory inference algorithm ...

Closed-loop output error approaches for drone’s physics informed trajectory inference

Perrusquía, Adolfo; Guo, Weisi (IEEE, 2023-02-22)

The design of adequate countermeasures against drone's threats needs accurate trajectory estimation to avoid economic damage to the aerospace industry and national infrastructure. As trajectory estimation algorithms need ...

Control layer security: a new security paradigm for cooperative autonomous systems

Guo, Weisi; Wei, Zhuangkun; Gonzalez, Oscar; Perrusquía, Adolfo; Tsourdos, Antonios (IEEE, 2023-07-21)

Autonomous systems often cooperate to ensure safe navigation. Embedded within the centralised or distributed coordination mechanisms are a set of observations, unobservable states, and control variables. Security of data ...

Control layer security: exploiting unobservable cooperative states of autonomous systems for secret key generation

Wei, Zhuangkun; Guo, Weisi (IEEE, 2024-02-26)

The rapid growth of autonomous systems (ASs) with data sharing means new cybersecurity methods have to be developed for them. Existing computational complexity-based cryptography does not have information-theoretical bounds ...

Cost inference of discrete-time linear quadratic control policies using human-behaviour learning

Perrusquía, Adolfo; Guo, Weisi (IEEE, 2022-06-30)

In this paper, a cost inference algorithm for discrete-time systems using human-behaviour learning is pro-posed. The approach is inspired in the complementary learning that exhibits the neocortex, hippocampus, and striatum ...

Deep learning methods for solving linear inverse problems: Research directions and paradigms

Bai, Yanna; Chen, Wei; Chen, Jie; Guo, Weisi (Elsevier, 2020-08-07)

The linear inverse problem is fundamental to the development of various scientific areas. Innumerable attempts have been carried out to solve different variants of the linear inverse problem in different applications. ...

A deep mixture of experts network for drone trajectory intent classification and prediction using non-cooperative radar data

Fraser, Benjamin; Perrusquía, Adolfo; Panagiotakopoulos, Dimitrios; Guo, Weisi (IEEE, 2024-01-01)

The intent prediction of unmanned aerial vehicles (UAVs) also known as drones is a challenging task due to the different mission profiles and tasks that the drone can perform. To alleviate this issue, this paper proposes ...

Deep reinforcement learning for optimal hydropower reservoir operation

Xu, Wei; Meng, Fanlin; Guo, Weisi; Li, Xia (American Society of Civil Engineers, 2021-05-21)

Optimal operation of hydropower reservoir systems is a classical optimization problem of high dimensionality and stochastic nature. A key challenge lies in improving the interpretability of operation strategies, i.e., the ...

Deep reinforcement learning of passenger behavior in multimodal journey planning with proportional fairness

Chu, Kai-Fung; Guo, Weisi (Springer, 2023-07-20)

Multimodal transportation systems require an effective journey planner to allocate multiple passengers to transport operators. One example is mobility-as-a-service, a new mobility service that integrates various transport ...

Design and hardware-in-the-loop evaluation of a time dissemination framework for drone operations in urban environments

Negru, Sorin Andrei; Petrunin, Ivan; Guo, Weisi; Tsourdos, Antonios (IEEE, 2023-11-10)

With the advent of UAVs (Unmanned Aerial Vehicles) several companies started to offer services, in urban, semi-urban, and rural regions. Although GNSS (Global Navigation Satellite System) can disseminate time information ...

Discovering latent spatial invariance of urban wireless data using compression and deep learning

Guo, Weisi (IEEE, 2020-07-27)

Increasingly available high resolution geospatial wireless demand data is available from high density base stations, wireless localisation, and geo-tagged social media posts. Mapping the evolving spatiotemporal demand is ...

Drone’s objective inference using policy error inverse reinforcement learning

Perrusquía, Adolfo; Guo, Weisi (IEEE, 2023-11-22)

Drones are set to penetrate society across transport and smart living sectors. While many are amateur drones that pose no malicious intentions, some may carry deadly capability. It is crucial to infer the drone’s objective ...

Dynamic complex network analysis of PM2.5 concentrations in the UK, using hierarchical directed graphs (V1.0.0)

Broomandi, Parya; Geng, Xueyu; Guo, Weisi; Pagani, Alessio; Topping, David; Kim, Jong Ryeol (MDPI, 2021-02-18)

The risk of a broad range of respiratory and heart diseases can be increased by widespread exposure to fine atmospheric particles on account of their capability to have a deep penetration into the blood streams and lung. ...

Error performance and mutual information for IoNT interface system

Li, Yu; Lin, Lin; Guo, Weisi; Zhang, Dingguo; Yang, Kun (IEEE, 2022-02-23)

Molecular communication and the internet of nanothings (IoNTs) are emerging research hotspots recently, which show great potential in biomedical applications inside the human body. However, how to transmit information from ...

Explainable artificial intelligence for 6G: improving trust between human and machine

Guo, Weisi (IEEE, 2020-07-15)

As 5G mobile networks are bringing about global societal benefits, the design phase for 6G has started. Evolved 5G and 6G will need sophisticated AI to automate information delivery simultaneously for mass autonomy, human ...

Browsing by Author "Guo, Weisi"

Browsing by Author "Guo, Weisi"

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