This study proposes a robust method for the face recognition from low-resolution red, green, and blue-depth (RGB-D) cameras acquired images which have a wide range of variations in head pose, illumination, facial expression, and occlusion in some cases. The local binary pattern (LBP) of the RGB-D images with the suitable feature dimension of Depth image is employed to extract the facial features. On the basis of error correcting output codes, they are fed to multiclass support vector machines (MSVMs) for the off-line training and validation, and then the online classification. The proposed method is called as the LBP-RGB-D-MSVM with the suitable feature dimension of the depth image. The effectiveness of the proposed method is evaluated by the four databases: Indraprastha Institute of Information Technology, Delhi (IIIT-D) RGB-D, visual analysis of people (VAP) RGB-D-T, EURECOM, and the authors. In addition, an extended database merged by the first three databases is employed to compare among the proposed method and some existing two-dimensional (2D) and 3D face recognition algorithms. The proposed method possesses satisfactory performance (as high as 99.10 ± 0.52% for Rank 5 recognition rate in their database) with low computation (62 ms for feature extraction) which is desirable for real-time applications.

Human-in-the-loop robotic system is an emerging technique in recent years. Human intelligence as well as machine intelligence are incorporated to accomplish tasks efficiently and effectively. However, grasp-and-lift (GAL) tasks through human–robot interactions are still a problem in an unstructured environment like urban search and rescue. Human assistive GAL tasks enable robots to complete search or rescue procedures quickly and accurately. Brain–machine interface (BMI) controlled robots have demonstrated promising applications in human–robot collaborative manipulations. In this study, an architecture of human–robot team is proposed for performing GAL tasks in BMI-based human–robot systems. The proposed architecture contains several workflows from both human and robot aspects to improve performance. In addition, human brain activities are generally considered as non-stationary signals with varying spatial and temporal distributions. To enhance robustness and stability of brain-controlled robot's GAL tasks, a new method via adaptive boosting mechanism is proposed. The proposed multiple subjects' adaptive boosting is able to suppress noisy data and outliers in multiple subjects’ electroencephalogram signals, and therefore enhance accuracy and robustness of intention and sensation signal classification in GAL tasks. Preliminary results show that the new architecture is feasible with ethical establishment and the proposed method can outperform traditional methods.

The authors investigated the effect of gaze tracking of humans by an agent. Psychological studies have shown that the presence of others facilitates task with implying partnership. This effect also occurs if the presence of others is replaced with a robot. Furthermore, the previous research showed that being touched by a robot motivates a person. However, direct contact such as the touch of a robot has a risk of disturbing human work. The authors used gaze tracking for social facilitation because gaze tracking can also facilitate human efforts and implemented a social facilitation robot agent by using gaze tracking. The agent projects its face on a surface to show quickly changing expressions, which is difficult to achieve with ordinary robots. The agent can also express gaze tracking by implementing eye trackers. The authors prepared three conditions with monotonous tasks to compare the effects of gaze tracking: the agent gazes at the instructed point moves its gaze randomly and traces the gaze point of a participant. The results showed that the participants’ motivation increased if the agent is tracking gazed point by a human, even though there are no differences between the achievement scores of the task and the continuation time.

With the development of information technology, designing urban experience faces an unprecedented challenge: the combination of cyber information and physical facilities. Cyber-Physical Social System (CPSS) forms the connection between virtual and physical objects, public and private, activeness and passiveness, leading an innovative way to explore human-centred design practice in the context of city and community. The challenges faced by urban communities and extend the design practice of SPSS in combination with public participation community design and Living Lab method. Through three practical cases and related evaluation feedbacks, this study presents a Cyber-Physical Public Design (CPPD) model of a human city. The CPPD model is constructed based on CPSS with the human-centred concept. By combining physical touch points with virtual information world, it is possible to collect data on residents’ lives and improve the city's public facilities and space design, rebuild the urban communities to better meet the needs of the public.

In this work, the authors have developed an integrated evaluation hierarchy for automotive human–machine interaction (HMI) software/hardware interfaces and a corresponding set of integrated evaluation carriers and decision modes, to improve the interactive experience and usability of HMI interfaces, evaluation node management in R&D processes, and the integral quality of hardware and software components. In addition, a case study where the integrated evaluation was performed on rapidly prototyped electric automotive user interfaces was utilised to demonstrate the evaluation of integral conceptual themes and system frameworks based on rapid prototypes. It was shown that the evaluation of integrated software/hardware electric automotive interfaces via rapid prototyping aids the communication and organisation of design concepts, thus enhancing the design quality.

The term cyber physical systems (CPS) refers to a new generation of systems with integrated computational and physical capabilities through computation, communication, and control. In the past decades, related techniques for CPS have been well studied and developed, and are widely applied in the fields such as industrial automation, smart transportation, aerospace, environment monitoring, and smart grids. However, with the expansion of CPS complexity and the enhancement of the system openness, most of CPS become not only safety-critical but also security-critical since deeply involving both physical objects and computer networks. In the last decade, it is no longer rare to see safety incidents and security attacks happening in industries. Safety and security issues are increasingly converging on CPS, leading to new situations in which these two closely interdependent issues should now be considered together, rather than separately or in sequence. This paper reviews the existing approaches of risk assessment and management from the perspective of safety, security, and their integration. The comparisons of these approaches are summarised with their pros and cons before the technical gaps between the demand and the current situation of safety and security issues in CPS are identified.

Power systems can be affected by unpredicted and unavoidable faults and failures, making security assessment an important challenge, which requires significant research works. An overview of this critical area, as presented here, shows that the security assessment has transformed from a deterministic to risk-based methods, with two broad categories, risk assessment and risk identification. First, a detailed discussion of risk assessment is given to summarise different methods to solve the problems of equipment failure probability model, scenarios formation, and severity assessment. Further, comprehensive survey and prospect for risk identification are provided as a roadmap to determine the risk source directly. Risk identification techniques such as tracking method, sensitivity analysis, and risk source identification help operators to take effectively preventive action and restore system security.

Extensive deployment of interoperable distributed energy resources (DER) is increasing the power system cyber security attack surface. National and jurisdictional interconnection standards require DER to include a range of autonomous and commanded grid-support functions, which can drastically influence power quality, voltage, and bulk system frequency. Here, the authors investigate the impact to the cyber-physical power system in scenarios where communications and operations of DER are controlled by an adversary. The findings show that each grid-support function exposes the power system to distinct types and magnitudes of risk. The physical impact from cyber actions was analysed in cases of DER providing distribution system voltage regulation and transmission system support. Finally, recommendations are presented for minimising the risk using engineered parameter limits and segmenting the control network to minimise common-mode vulnerabilities.

The authors present a simulation-based bounded-horizon verification framework for hybrid systems with Lipschitz continuity on the continuous dynamics. In this framework, the bounded initial set is covered by a finite set of representative states, whose forward simulations are used to generate an over-approximation of all the reachable states. A novel feature of the proposed approach is that the representative states are generated dynamically, on-the-fly, along with the forward simulations. This key innovation refines the current ‘reachability-face’ by a new partition only when needed. This approach works for hybrid systems with state-triggered discrete jumps and allows piecewise constant bounded inputs, extending the existing work applied to switched systems with neither state-triggered discrete jumps nor inputs. Additionally, when the continuous dynamics is incremental (input-to-state) stable, the algorithm uses a simple Lipschitz-based discrepancy function to provide a constant error bound of over-approximation. This is of practical significance since a Lipschitz-based discrepancy function is easily computable, while a more precise discrepancy function may not be available. Because of the constant error bound, the number of representative simulations also converges to a constant. A prototype verifier, HS ³ V, has been developed, implementing the proposed algorithms and providing verification results from several benchmarks for performance demonstration.

Further popularisation of electric vehicles (EVs) is hindered by their relatively short driving distance and long battery charging time. To overcome these shortcomings, the battery swapping station (BSS) has been proposed as a means of satisfying the increasing demands for fast EV battery recharging. At a BSS, (partially) depleted batteries from EVs can be replaced with partially or fully charged ones almost instantaneously. Recharging scheduling and maintenance of batteries are done by the operator of BSS, with the target of minimising electrical energy costs while satisfying customer demands. In this study, the authors consider a realistic BSS framework in which EVs can arrive at BSS with time of day dependent rates having different battery state-of-charges. They investigate the battery charging scheduling problem in the BSS under a dynamic energy pricing. They solve (i) an online optimal BSS control problem to minimise the energy cost with a quality-of-service (QoS) guarantee, and (ii) an offline optimal BSS design problem to determine the optimal number of stored batteries so as to achieve a desirable tradeoff between flexibility in charging and amortised battery costs. The experimental results show that the total charging energy cost can be reduced significantly under different traffic scenarios.

The cyber-physical nature of electric power systems has increased immensely over the past decades, with advanced communication infrastructure paving the way. It is now possible to design wide-area controllers, relying on remote monitor and control of devices that can tackle power system stability problems more effectively than local controllers. However, their performance and security relies extensively on the communication infrastructure and can make power systems vulnerable to disturbances emerging on the cyber side of the system. In this study, the authors investigate the effect of communication delays on the performance of wide-area damping controllers designed to stabilise oscillatory modes in a cyber-physical power system (CPPS). They propose a rule-based control strategy that combines wide-area and traditional local stabilising controllers to increase the performance and maintain the stable operation of CPPS. The proposed strategy is validated on a reduced CPPS equivalent model of Great Britain.

Parallelising transformations of Kahn process networks (KPNs) are important mechanisms for achieving speedup for deployment on heterogeneous multiprocessor systems particularly in the domain of signal processing applications. Correctness of such parallelising transformations is crucial for their reliable applications. In this study, verification frameworks for checking correctness of sequential to KPN behavioural transformation and KPN level transformations are presented. To the best of the authors’ knowledge, these are the first such approaches for verification problems. The sequential behaviour and the KPN behaviours are both modelled as array data dependence graphs (ADDGs) and the verification problem is posed as the problem of checking of equivalence between the two ADDGs. The key aspect of the proposed scheme is to model a KPN behaviour as an ADDG. Correctness of KPN to ADDG construction method is proved. Experimental results supporting usability of this scheme are also provided.