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This paper proposes a model of proton exchange membrane (PEM) fuel cells for real-time applications, with a 2-dimensional model of mass flow in the channel layer and a 1-dimensional model of electrochemical and mass diffusion in the diffusion layer and polymer membrane. It is also shown how an optimized program based on finite difference and finite volume methods may be developed for embedded applications, and how the error, convergence and hardware properties of this program may be analyzed to determine whether such a program can be uploaded to a real-time controller. New ideas for increasing the real-time simulation speed are given and discussed. An experimental validation of the model is done. Results from the 2-dimensional real-time mass flow model are presented and discussed, as well as performance results of the real-time simulation model. [ABSTRACT FROM AUTHOR]

Autonomous navigation of legged robots in complex environments poses a great deal of challenges compared with ground vehicles because of their different terrain traverse capabilities. An obstacle for vehicles may be traversable for legged robots. This paper proposes a real-time obstacle detection algorithm for legged robots using the Microsoft Kinect sensor. First, the elevation map of a reference grid is calculated. Then an obstacle definition for legged robots is proposed, which makes it possible for a legged robot to discriminate traversable areas from non-traversable areas. To reduce computational cost, sometimes, efficient judging rules are developed to identify obstacles. A spiral search strategy is proposed to find the most ground-like point as the starting point for graph-based traversal. Breadth-First-Traversal of the graph is used to label all traversable areas connecting to the starting point. Experimental results demonstrate that our algorithm is reliable and efficient. The proposed algorithm can be employed in real-time obstacle detection for legged robots in complex environments. [ABSTRACT FROM AUTHOR]

Saliency computation models aim to imitate the attention mechanism in the human visual system. The application of deep neural networks for saliency prediction has led to a drastic improvement over the last few years. However, deep models have a high number of parameters which makes them less suitable for real-time applications. Here we propose a compact yet fast model for real-time saliency prediction. Our proposed model consists of a modified U-net architecture, a location-dependent fully-connected layer, and central difference convolutional layers. The modification we made on U-Net architecture, promoted compactness and efficiency of the final model. Our location-dependent fully-connected layer facilitates implicit capturing of the location-dependent information. Using the central difference convolutional layers at different scales enables capturing more robust and biologically motivated features. We compare our model with state-of-the-art saliency models using traditional saliency scores as well as our newly devised scheme. Experimental results over four challenging saliency benchmark datasets demonstrate the effectiveness of our approach in striking a balance between accuracy and speed. Our model can be run in real-time which makes it appealing for edge devices and video processing. • Here we propose a compact yet fast model for real-time saliency prediction. • We employ a modified U-net architecture to reduce the number of model parameters. • We employ a location-dependent layer to capture location-dependent information. • We compare the structural capabilities of saliency models under unified assumptions. [ABSTRACT FROM AUTHOR]

Efficient scheduling is critical for achieving high performance in the multicore computing environment. This paper focuses on the scheduling problem for the real-time applications in the FPGA-based multicore structure with an objective to minimize the makespan under hardware resource constraints. To address this problem, we propose a priority-driven scheduling algorithm, called the Real-Time Priority-driven Algorithm (ReTPA). In this method, we first allocate the tasks into software and hardware computing units based on their hardware resource constraints. Then scheduling is performed to minimize the makespan. We further extend ReTPA with communication scheduling to improve the scheduling efficiency in the communication-intensive applications, which is called Communication-based Real-Time Priority-driven Algorithm (CReTPA). Our experimental results confirm the efficiency of the proposed algorithms in applications with different scales or different computation-communication ratios. Besides, we compare the two proposed algorithms with a classic priority-driven algorithm, HEFT, an advanced priority-driven algorithm, HETS, and two advanced genetic algorithms, GAA and MGAA, proposed by Abdallah et al. in 2019. The performance comparisons illustrate that our algorithms, ReTPA and CReTPA, both show the outstanding performance and CReTPA obtains the most reasonable solutions within the shortest scheduling time for communication-intensive applications. [ABSTRACT FROM AUTHOR]

SUMMARY In this contribution, a control strategy in phase coordinates abc is proposed as the reference current generator to be used by the shunt active power filter (APF) compensation device. The development of the proposed reference current generator is described in detail. Its control design is kept simple, and transformation between different frameworks is not needed, thus allowing the control strategy to be applicable for both three-phase and single-phase electric systems maintaining theoretical and practical advantages. The proposed control strategy for the reference current generator is tested using Matlab/Simulink® with the incorporation of the Real-Time Workshop® for the simulation of the shunt APF compensation in real time. Based on the reported real-time application, it is possible to obtain simulation conditions that are close to the true real-time environment under study using only a single computer, giving accurate results with relatively low-cost hardware and providing a more complete evaluation of the applied control strategy. The dynamic behavior and performance of the shunt APF, using the proposed reference current calculator, have shown remarkable results. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a non-invasive endogenous brain–machine interface (BMI) based on the correlation of EEG maps has been developed to work in real-time applications. The classifier is able to detect two mental tasks related to motor imagery with good success rates and stability. The BMI has been tested with four able-bodied volunteers. First, the users performed a training with visual feedback to adjust the classifier. Afterwards, the users carried out several trajectories in a visual interface controlling the cursor position with the BMI. In these tests, score and accuracy were measured. The results showed that the participants were able to follow the targets during the performed trajectory, proving that the EEG mapping correlation classifier is ready to work in more complex real-time applications aimed at helping people with a severe disability in their daily life. [Copyright &y& Elsevier]

ABSTRACT In this paper, we propose a method to achieve effective facial emotional expressivity for embodied conversational agents by considering two types of asymmetry when exploiting the valence-arousal-dominance representation of emotions. Indeed, the asymmetry of facial expressions helps to convey complex emotional feelings such as conflicting and/or hidden emotions due to social conventions. To achieve such a higher degree of facial expression in a generic way, we propose a new model for mapping the valence-arousal-dominance emotion model onto a set of 12 scalar facial part actions built mostly by combining pairs of antagonist action units from the Facial Action Coding System. The proposed linear model can automatically drive a large number of autonomous virtual humans or support the interactive design of complex facial expressions over time. By design, our approach produces symmetric facial expressions, as expected for most of the emotional spectrum. However, more complex ambivalent feelings can be produced when differing emotions are applied on the left and right sides of the face. We conducted an experiment on static images produced by our approach to compare the expressive power of symmetric and asymmetric facial expressions for a set of eight basic and complex emotions. Results confirm both the pertinence of our general mapping for expressing basic emotions and the significant improvement brought by asymmetry for expressing ambivalent feelings. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In cognitive radio (CR) networks, the channel sensing order is crucial for the CR users to find an available channel as fast as possible. In this paper, besides the primary user activities, the statistics of Signal-to-Noise Ratio for each channel are explored using pilot signals. Based on the fluctuating nature of heterogeneous channels as well as the QoS requirements of various applications, two channel sensing order methods are proposed. For real-time applications, a minimum delay-based channel sensing order is proposed to find an idle channel which meets the sustainable rate constraint as fast as possible. For best-effort applications, a maximum capacity-based channel sensing order is proposed to maximize the transmission rates for the CR users, and two different stopping rules are considered. One is that a CR user should stop and transmit at the first free channel, while for the other one, a q-stage look-ahead stopping problem is considered. The simulation results show that the opportunity-discovery delay is reduced for real-time applications. For best-effort applications, the second stopping method is better than the first one when the time cost of the pilot signal is small. [ABSTRACT FROM AUTHOR]

This paper presents a multiphysical proton exchange membrane fuel cell (PEMFC) stack model. The stack model is divided into three submodels describing the different physical domains, namely, electrical, fluidic, and thermal. The stacking method has been used to model the fuel cell stack from a single-cell model. The proposed model has been validated against a 1.2-kW commercial PEMFC stack with excellent agreement between simulation and experimentation. Based on the simulation results, a novel model reduction method is proposed. The reduced model is suitable for real-time simulation purpose. Moreover, a real-time-model-based fuel cell emulator is introduced. The emulator has three real-time computation cores with different rates. The three computation cores are interconnected with a digital communication bus. A dc/dc buck converter is designed in order to receive the model-predicted stack power conditions and emulate the real fuel cell stack power output. The experimental test results show that such an emulator is suitable for fuel cell system hardware-in-the-loop applications. [ABSTRACT FROM AUTHOR]

Abstract: A novel method for the identification of embedded piezoelectric stack actuator parameters in combination with a real-time capable hysteresis compensation measure is presented. The presented algorithms are based on the Maxwell resistive capacitor model and are particularly useful for the identification of piezoelectric actuators embedded in a high-precision micropositioning system where the disassembly of the complete system for separate actuator identification is not recommended or not possible. The parameter identification can be performed in a fully automated way and enables the adaptation of the compensation routine to the changed circumstances (temperature difference, wearing of actuators) as well. The hysteresis compensation method proposed here does not require significant CPU or memory resources. It can be implemented as an additional task on the already existing controller or a low-budget FPGA. As an example, the proposed method was validated experimentally by the parameter identification and hysteresis compensation of the piezoelectric actuators incorporated in a commercially available hybrid micropositioning system. The achieved experimental results are in very good agreement with the theoretical ones. [Copyright &y& Elsevier]

Abstract: In this paper, a concept to identify the adsorption isotherm of Simulated Moving Bed processes online during the operation is proposed. The influence of model parameters on the measurements is analyzed by a sensitivity analysis which enables to identify the set of parameters that can be estimated simultaneously. The parameters are estimated in real-time by a moving horizon state and parameter estimation scheme. Numerical simulations of validated models for separation problems with nonlinear isotherms of Langmuir type are presented. Furthermore, it is it shown that a structural plant/model mismatch in the void fraction can be compensated to a large extent by modifying the Henry coefficients of the adsorption isotherm such that the estimated model can be used in the context of online optimizing control. [ABSTRACT FROM AUTHOR]

Abstract: A novel algorithm is presented in this paper to extract the features of foreign fibers in lint cotton within a complex background. The 2D wavelet transform is used to implement the edge detection based on the gray contrast between foreign fibers and cotton background, while the color features are extracted in CrCgCb color cube to solve the problem of luminance fluctuation. Morphological analysis is a critical procedure of the algorithm and the discontinuity of object features and operation time must be considered. Therefore, the proposed approach integrates a two-level connected component labeling algorithm and a morphological identification algorithm based on equivalent length-width ratio. Tests on five typical kinds of foreign fibers were implemented, and the results show that the identification rate of the above-mentioned algorithm is about 95 %. The experimental results demonstrate that the feature extraction algorithm can identify foreign fibers effectively and can be used in real-time application. [Copyright &y& Elsevier]

In this paper, we propose and analyze a methodology for providing statistical guarantees within the diffserv model in a network, which uses static-priority schedulers. We extend the previous work on statistical delay analysis and develop a method that can be used to derive delay bounds without specific information on flow population. With this new method, we are able to successfully employ a utilization-based admission control approach for flow admission. This approach does not require explicit delay computation at admission time and hence is scalable to large systems. We systematically analyze the performance of our approaches in terms of system utilization. As expected, our experimental data show that statistical services can achieve much higher utilization than deterministic services. [ABSTRACT FROM AUTHOR]

Robust Model Predictive Control Theory (RMPC) which is firstly presented by Kothare et al.[1] is reviewed. In order to use this theory for set-point control of first-order systems with uncertain time delay and gain, the state-space model of the system is extended in order to transform this structural uncertainty to parametric uncertainty. Furthermore, to remove steady-state error, an integral action is added to the controller. The performance of proposed method, i.e., RMPC with Integral Action (RMPC+I) is investigated by simulations and the experimental results are obtained considering several uncertainty circumstances. RMPC+I design technique - proposed in this paper - have good robustness and good steady-state properties in real time application. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a moving horizon state and parameter estimation scheme for chromatographic simulated moving bed SMB processes is proposed. The simultaneous state and parameter estimation is based on a high-order nonlinear SMB model which incorporates rigorous models of the chromatographic columns and the discrete shiftings of the inlet and outlet ports. The estimation is performed using sparse measurement information: the concentrations of the components are only measured at the two outlet ports (which are periodically switched from one column to the next) and at one fixed location between two columns. The goal is to reconstruct the full state of the system, i.e. the concentration profiles along all columns, and to identify critical model parameters reliably such that the estimated model can be used in the context of online optimizing control. The state estimation scheme is based upon a deterministic model within the prediction horizon, state noise is only present in the state and the parameters prior to and at the beginning of the horizon. By solving the optimization problem with a multiple-shooting method and applying a real-time iteration scheme, the computation times are such that the scheme can be applied online. Numerical simulations of a validated model for a separation problem with nonlinear isotherms of the Langmuir type demonstrate the efficiency of the algorithm. [Copyright &y& Elsevier]

To achieve the real-time application of a dynamic programming (DP) control strategy, we propose a predictive energy management strategy (PEMS) based on full-factor trip information, including vehicle speed, slip ratio and slope. Firstly, the prediction model of the full-factor trip information is proposed, which provides an information basis for global optimization energy management. To improve the prediction's accuracy, the vehicle speed is predicted based on the state transition probability matrix generated in the same driving scene. The characteristic parameters are extracted by a feature selection method taken as the basis for the driving condition's identification. Similar to speed prediction, regarding the uncertain route at an intersection, the slope prediction is modelled as a Markov model. On the basis of the predicted speed and the identified maximum adhesion coefficient, the slip ratio is predicted based on a neural network. Then, a predictive energy management strategy is developed based on the predictive full-factor trip information. According to the statistical rules of DP results under multiple standard driving cycles, the reference SOC trajectory is generated to ensure global sub-optimality, which determines the feasible state domain at each prediction horizon. Simulations are performed under different types of driving conditions (Urban Dynamometer Driving Schedule, UDDS and World Light Vehicle Test Cycle, WLTC) to verify the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

Finite element methods (FEM) have been used extensively within the field of surgical simulation to describe physically realistic interactions with soft-tissue organs. However, FEMs require researchers to balance computational costs against approximation techniques to maintain adequate performance. We aim to extend previous work in nonlinear FEM implementation with extensions which improve the performance of accurate modelling of multiple organs undergoing deformations. [ABSTRACT FROM AUTHOR]

Abstract: Predicting transient behavior of lead-acid batteries during charge and discharge processes is an important factor in many applications including hybrid electric vehicles (HEVs). The conventional mathematical models, which are used to predict the battery dynamics, are either inaccurate or time-consuming. In this study, an improved and efficient mathematical model for simulation of flooded lead-acid batteries based on Computational Fluid Dynamics (CFD) and Equivalent Circuit Model (ECM) has been introduced which inherits the accuracy of CFD model and the physical understanding of ECM. This approach makes the numerical procedure very efficient and easy to implement. Moreover, because of simplification of boundary conditions (BC''s), it is very fast which makes it quite suitable for real-time simulations. The present approach is verified by previous CFD models and experimental data. [Copyright &y& Elsevier]

The adoption of wireless communication technologies in industrial environments for supporting (soft) real-time applications heavily depends on the ability to grant bounded response times for messages, at least from a probabilistic point of view. This aspect is particularly important in factory automation systems, where response times are considered much more significant than other performance indices, such as throughput, that are usually considered in different application areas. The ever-increasing availability on the market of products and solutions based on the IEEE 802.11 standard and the introduction of the 802.11e amendment for enhancing the quality of service (QoS) and prioritizing traffic make this kind of communication technology interesting also for adoption in (loosely coupled) distributed control systems. This paper reports on some experimental measures and the related analysis that have been carried out on real 802.11g/e networks for better understanding the statistical distribution of response times and can be of help in characterizing these solutions when used to support noncritical real-time traffic. [ABSTRACT FROM PUBLISHER]

Abstract: In this paper, an adaptive controller was applied to a 765MW large thermal power plant to decrease operating costs, increase quality of generated electricity and satisfy environmental concerns. Since power plants may present several operating problems such as disturbances and severe effects at operating points, design of their controllers needs to be carried out adequately. For these reasons, first, a reduced mathematical model was developed under Computer Aided Analysis and Design Package for Control, (CADACS), so that the results of the experimental model have briefly been discussed. Second, conventional PID and adaptive controllers were designed and implemented under the real-time environment of the CADACS software. Additionally, the design of the adaptive model-reference and conventional PID controllers used in the power plant for real-time control were theoretically presented. All processes were realized in real-time. Due to safety restrictions, a direct connection to the sensors and actuators of the plant was not allowed. Insted a coupling to the control system was realized. This offers, in addition, the usage of the supervisiory functions of an industrial process computer system. Application of the controllers indicated that the proposed adaptive controller has better performances for rise and settling times of electrical power, and enthalpy outputs than the conventional PID controller does. [Copyright &y& Elsevier]

This paper is concerned with flow control and resource allocation problems in computer networks in which real-time applications may have hard quality of service (QoS) requirements. Recent optimal flow control approaches are unable to deal with these problems since QoS utility functions generally do not satisfy the strict concavity condition in real-time applications. For elastic traffic, we show that bandwidth allocations using the existing optimal flow control strategy can be quite unfair. If we consider different QoS requirements among network users, it may be undesirable to allocate bandwidth simply according to the traditional max-min fairness or proportional fairness. Instead, a network should have the ability to allocate bandwidth resources to various users, addressing their real utility requirements. For these reasons, this paper proposes a new distributed flow control algorithm for multiservice networks, where the application's utility is only assumed to be continuously increasing over the available bandwidth. In this, we show that the algorithm converges, and that at convergence, the utility achieved by each application is well balanced in a proportionally (or max-mm) fair manner. [ABSTRACT FROM AUTHOR]

Multimedia systems must deal with multiple data streams. Each data stream usually contains significant volume of redundant noisy data. In many real-time applications, it is essential to focus the computing resources on a relevant subset of data streams at any given time instant and use it to build the model of the environment. We formulate this problem as an experiential sampling problem and propose an approach to utilize computing resources efficiently on the most informative subset of data streams. First, in this paper, we focus on theoretical background and develop a theoretical framework for a single data stream. We generalize the notion of static visual attention in a dynamical systems setting and propose a dynamical attention-orientated analysis method. This is achieved by a sampling representation that utilizes the current context and past experience for attention evolution. Hence, the multimedia analysis task at hand can select its data of interest while immediately discarding the irrelevant data to achieve efficiency and adaptability [ABSTRACT FROM PUBLISHER]

Multimedia systems must deal with multiple data streams. Each data stream usually contains significant volume of redundant noisy data. In many real-time applications, it is essential to focus the computing resources on a relevant subset of data streams at any given time instant and use it to build the model of the environment. We formulate this problem as an experiential sampling problem and propose an approach to utilize computing resources efficiently on the most informative subset of data streams. In this paper, we generalize our experiential sampling framework to multiple data streams and provide an evaluation measure for this technique. We have successfully applied this framework to the problems of traffic monitoring, face detection and monologue detection [ABSTRACT FROM PUBLISHER]

Real-time applications often stand to benefit from service guarantees, and in particular delay guarantees. However, most mechanisms that provide delay guarantees also hard-limit the amount of traffic the application can generate, i.e., to enforce to a traffic contract. This can be a significant constraint and interfere with the operation of many real-time applications. Our purpose in this paper is to propose and investigate solutions that overcome this limitation. We have four major goals: 1) guarantee a delay bound to a contracted amount of real-time traffic; 2) transmit with the same delay bound as many excess real-time packets as possible; 3) enforce a given link sharing ratio between excess real-time traffic and other service classes, e.g., best-effort; and 4) preserve the ordering of real-time packets, if required. Our approach is based on a combination of buffer management and scheduling mechanisms for both guaranteeing delay bounds, while allowing the transmission of excess traffic. We evaluate the "cost" of our scheme by measuring the processing overhead of an actual implementation, and we investigate its performance by means of simulations using video traffic traces. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a direct adaptive fuzzy controller for unknown monotonic nonlinear systems, thus not requiring the system model, but only a little information about it: the plant monotonicity and its delay. Without any off-line pre-training, the algorithm achieves very high control performance through a three-stage algorithm: (1) output scale factor, (2) adaptation of the fuzzy rule consequents and (3) optimization of the position of the membership functions. The design is simple, in the sense that both the membership functions and the rule-base can be initialized from arbitrary values. It can be applied to a large class of monotonic dynamic or static plants, due the fact that the system is able to modify its behaviour in real time, i.e., during the control process. [Copyright &y& Elsevier]

This paper presents a low-complexity multiuser decoding technique that can be implemented in real time for a convolutionally coded direct sequence code division multiple access (DS-CDMA) system. The main contribution, denoted here as the iterative prior update (IPU), consists of iterative interference cancellation and prior updates on sequences of coded bits combined with M-algorithm and list decoding. We illustrate performance gains over other low-complexity sequence detection and decoding strategies and argue that the algorithm converges within a few iterations and requires only a small size buffer for keeping track of the priors along iterations. The fact that the we can use existing available architectures for Viterbi decoding with slight modifications and can meet the real-time processing constraints makes the IPU algorithm an attractive alternative for cellular systems. [ABSTRACT FROM PUBLISHER]

Automatic video segmentation plays an important role in real-time MPEG-4 encoding systems. Several video segmentation algorithms have been proposed; however, most of them are not suitable for real-time applications because of high computation load and many parameters needed to be set in advance. This paper presents a fast video segmentation algorithm for MPEG-4 camera systems. With change detection and background registration techniques, this algorithm can give satisfying segmentation results with low computation load. The processing speed of 40 QCIF frames per second can be achieved on a personal computer with an 800 MHz Pentium-III processor. Besides, it has shadow cancellation mode, which can deal with light changing effect and shadow effect. A fast global motion compensation algorithm is also included in this algorithm to make it applicable in slight moving camera situations. Furthermore, the required parameters can be decided automatically, which can enhance the proposed algorithm to have adaptive threshold ability. It can be integrated into MPEG-4 videophone systems and digital cameras. [ABSTRACT FROM PUBLISHER]