Performance evaluation of the parallel processing producer–distributor–consumer network architecture

The CSMA/CD access method is no longer invoked in switched, full-duplex Ethernet, but the industrial protocols still take the presence of the method into account. The parallel processing producer–distributor–consumer network architecture (ppPDC) was designed specifically to actively utilize the frame queuing. The network nodes process frames in parallel, which shortens the time needed to perform a cycle of communication, especially in cases when frame processing times within the nodes are not uniform. The experiments show that the achievable cycle times of the ppPDC architecture are an order of magnitude shorter than in the well-known sequential PDC protocol.     

Orientationability analyses of a special class of the Stewart–Gough parallel manipulators using the unit quaternion representation

This paper addresses the orientation-singularity and orientationability analyses of a special class of the Stewart–Gough parallel manipulators whose moving and base platforms are two similar semi-symmetrical hexagons. Employing a unit quaternion to represent the orientation of the moving platform, an analytical expression representing the singularity locus of this class of parallel manipulators in a six-dimensional Cartesian space is obtained. It shows that for a given orientation, the position-singularity locus is a cubic polynomial expression in the moving platform position parameters, and for a given position, the orientation-singularity locus is an analytical expression but not a polynomial directly with respect to the mobile platform orientation parameters. Further inspection shows that for the special class of parallel manipulators, there must exist a nonsingular orientation void in the orientation space around the orientation origin for each position in the position-workspace. Therefore, a new performance index referred to as orientationability is introduced to describe the orientation capability of the special class of manipulators at a given position. A discretization algorithm is proposed for the computation of the orientationability of the special class of manipulators. Moreover, effects of the design parameters and position parameters on the orientationability are investigated in details. Based on the orientationability performance index, another novel performance index referred to as practical orientationability is presented which represents the practical orientation capability of the manipulator at a given position. The practical orientationability not only can satisfy all the kinematic demands and constraints of such class of manipulators, but also can guarantee that the manipulator is nonsingular.     

Modelling the scatter of E–N curves using a serial hybrid neural network

If structural reliability is estimated by following a strain-based approach, a material’s strength should be represented by the scatter of the ε–N (E–N) curves that link the strain amplitude with the corresponding statistical distribution of the number of cycles-to-failure. The basic shape of the ε–N curve is usually modelled by the Coffin–Manson relationship. If a loading mean level also needs to be considered, the original Coffin–Manson relationship is modified to account for the non-zero mean level of the loading, which can be achieved by using a Smith–Watson–Topper modification of the original Coffin–Manson relationship. In this paper, a methodology for estimating the dependence of the statistical distribution of the number of cycles-to-failure on the Smith–Watson–Topper modification is presented. The statistical distribution of the number of cycles-to-failure was modelled with a two-parametric Weibull probability density function. The core of the presented methodology is represented by a multilayer perceptron neural network combined with the Weibull probability density function using a size parameter that follows the Smith–Watson–Topper analytical model. The article presents the theoretical background of the methodology and its application in the case of experimental fatigue data. The results show that it is possible to model ε–N curves and their scatter for different influential parameters, such as the specimen’s diameter and the testing temperature.     

Performance–energy adaptation of parallel programs in pervasive computing

It is meaningful to use a little energy to obtain more performance improvement compared with the increased energy. It also makes sense to relax a small quantity of performance restriction to save an enormous amount of energy. Trading a small amount of energy for a considerable sum of performance or vice versa is possible if the relativities between performance and energy of parallel programs are exactly known. This work studies the relativities by recording the performance speedup and energy consumption of parallel programs when the number of cores on which programs run are changed. We demonstrate that the performance improvement and the increased energy consumption have a linear negative correlation.In addition, these relativities can guide us to do performance–energy adaptation under two assumptions. Our experiments show that the average correlation coefficients between performance and energy are higher than 97 %. Furthermore, it can be found that exchanging less than 6 % performance loss for more than 37 % energy consumption is feasible and vise versa.     

Method for improving the position precision of a hydraulic robot arm: dual virtual spring–damper controller

Recently, control approaches for a hydraulic robot in the field of robotics have attracted considerable attention owing to their high power-to-weight ratio. Many studies on behavior and control exploiting the advantages of hydraulic robots have been pursued. Application to hydraulically actuated systems, however, is not straightforward due to the nonlinear internal dynamics of the actuators. This paper presents a relatively simple method to improve the position precision of a hydraulic robot arm. We propose a simple control method concept based on a virtual spring–damper (VSD) controller, which enables the robot to realize a desired position. The main advantage of the VSD control is its simple calculation method, which eliminates the need to solve the Jacobian pseudo-inverse or ill-posed inverse kinematics. In this study, experiments were conducted to identify the problems in previous study results and evaluated the applicability of VSD control to the hydraulic robot arm. A relatively simple method was proposed to solve these problems and to verify improvements in the position precision. The proposed method is the dual VSD controller in which an additional VSD model is applied to the elbow, in addition to the conventional VSD model connected to the wrist. The effectiveness of the proposed control scheme is demonstrated in experimentation with the hydraulic robot arm.     

Shape recognition of laser beam trace for human–robot interface

A robot navigation system using the pattern recognition of figures drawn by a laser pointer has been proposed. Typical figures are registered and assigned to individual robot commands. Each figure is identified based on the feature of its edges. This system detects trace of laser beam and calculates its optical flow vectors. Each figure has its own characteristic distribution pattern of vector inclinations. By evaluating the optical flow pattern of displayed laser spot, the system distinguishes the shape of a laser beam trace and provides the command to a robot corresponding to the drawn figure. The proposed system has been applied to the mobile robot, and shows its effectiveness by steering successfully.     

Hyperspectral image classification using a spectral–spatial random walker method

This article proposes a spectral–spatial method for classification of hyperspectral images (HSIs) by modifying traditional random walker (RW). The proposed method consists of suggesting two main modifications. First, to construct a spatial edge weighting function, low-frequency edge weighting function is proposed. In this function, the detail weights are removed. Second, to enhance the classification accuracy, a fusion of spectral and spatial Laplacian matrix in RW is suggested. This fusion can improve the classification performances compared to traditional RW using only spatial Laplacian matrix. In comparison with some of the state-of-the-art RW and spectral–spatial classifier methods, the experimental results of the proposed method (spectral–spatial RW) show that the proposed method significantly increases the classification accuracy of HSI.     

Shape completion using orthogonal views through a multi-input–output network

Pattern Analysis and Applications - Knowing the shape of objects is essential to many robotics tasks. However, this is not always feasible. Recent approaches based on point clouds and voxel cubes...     

Assessment of composite beam performance using GWO–ELM metaheuristic algorithm

Composite beams (CBs) include concrete slabs jointed to the steel parts by the shear connectors, which highly popular in modern structures such as high rise buildings and bridges. This study has investigated the structural behavior of simply supported CBs in which a concrete slab is jointed to a steel beam by headed stud shear connector. Determining the behavior of CB through empirical study except its costly process can also lead to inaccurate results. In this case, AI models as metaheuristic algorithms could be effectively used for solving difficult optimization problems, such as Genetic algorithm, Differential evolution, Firefly algorithm, Cuckoo search algorithm, etc. This research has used hybrid Extreme machine learning (ELM)–Grey wolf optimizer (GWO) to determine the general behavior of CB. Two models (ELM and GWO) and a hybrid algorithm (GWO–ELM) were developed and the results were compared through the regression parameters of determination coefficient (R²) and root mean square (RMSE). In testing phase, GWO with the RMSE value of 2.5057 and R² value of 1.2510, ELM with the RMSE value of 4.52 and R² value of 1.927, and GWO–ELM with the RMSE value of 0.9340 and R² value of 0.9504 have demonstrated that the hybrid of GWO–ELM could indicate better performance compared to solo ELM and GWO models. In this case, GWO–ELM could determine the general behavior of CB faster, more accurate and with the least error percentages, so the hybrid of GWO–ELM is more reliable model than ELM and GWO in this study.

     

Transfer learning using the online Fuzzy Min–Max neural network

In this paper, we present an empirical analysis on transfer learning using the Fuzzy Min–Max (FMM) neural network with an online learning strategy. Three transfer learning benchmark data sets, i.e., 20 Newsgroups, WiFi Time, and Botswana, are used for evaluation. In addition, the data samples are corrupted with white Gaussian noise up to 50 %, in order to assess the robustness of the online FMM network in handling noisy transfer learning tasks. The results are analyzed and compared with those from other methods. The outcomes indicate that the online FMM network is effective for undertaking transfer learning tasks in noisy environments.     

Infinity-norm acceleration minimization of robotic redundant manipulators using the LVI-based primal–dual neural network

Kinematically redundant manipulators admit an infinite number of inverse kinematic solutions and hence the optimization of different performance measures corresponding to various task requirements must be considered. Joint accelerations of these mechanisms are usually computed by optimizing various criteria defined using the two-norm of acceleration vectors in the joint space. However, in formulating the optimization measures for computing the inverse kinematics of redundant arms, this paper investigates the use of the infinity norm of joint acceleration (INAM) (also known as the minimum-effort solution). The infinity norm of a vector is its maximum absolute value component and hence its minimization implies the determination of a minimum-effort solution as opposed to the minimum-energy criterion associated with the two-norm. Moreover, the new scheme reformulates the task as the online solution to a quadratic programming problem and incorporates three levels of joint physical limits, thus keeping the acceleration within a given range and avoiding the torque-instability problem. In addition, since the new scheme adopts the LVI-based primal–dual neural network, it does not entail any matrix inversion or matrix–matrix multiplication, which was embodied in other's researches with expensive O(n³)$O(n^3)$ operations. This new proposed QP-based dynamic system scheme is simulated based on the PUMA560 robot arm.     

Application of a Bayesian network for land-cover classification from a Landsat 7 ETM+ image

This article describes the use of a Bayesian network (BN) for the classification of land cover from satellite imagery in northern Swaziland. The main objective of this work was to apply and evaluate the efficacy of a BN for land-cover classification using gap-filled and terrain-corrected Landsat 7 Enhanced Thematic Mapper Plus (ETM+) imagery acquired on 15 May 2007. The posterior probabilities (parameters) were estimated using the expectation-maximization (EM) and conjugate gradient descent (CGD) algorithms. A comparison of the results obtained from the algorithms indicates similar and excellent overall classification accuracies of 93.01%, and kappa coefficient values of 0.9143. The main result obtained in this study is that both algorithms considered here provide relatively similar and accurate solutions for the classification of the multispectral image although the EM algorithm is marginally competitive relative to CGD algorithm when measured in terms of the Brier score and the logarithmic loss.     

An innovative piezoelectric energy harvester using clamped–clamped beam with proof mass for WSN applications

In this paper a miniature piezoelectric energy harvester (PEH) with clamped–clamped beam and mass loading at the center is introduced which has more consistency against off-axis accelerations and more efficiency in comparison to other cantilever PEH’s. The beams consist of different layers of Si, piezoelectric, and insulators based on MEMS technology that vibrates by applying an external force to the fixed frame. Due to beam vibration, variable stress is applied to the AlN piezoelectric and a potential difference is created at the output terminals. AlN is deposited on clamped–clamped beams in such a way that produce more stress points which cause more power to be generated in comparison to other cantilever beam PEH’s with about same dimensions. A partial differential equations (PDE) describing the flexural wave propagating in the multi-morph clamped–clamped beam are solved as theoretical calculations for inherent frequency estimation and is confirmed by simulation results. The obtained inherent frequency is 42 Hz which with 1 g (g = 9.81 m/s²) acceleration produces 4 V and 80 µW maximum electrical peak power that can be used in the node of low-power consumption wireless sensor node for wireless sensor network (WSN) applications.

     

Modelling and analysis of a rigid–compliant parallel mechanism

This paper presents a two-staged parallel mechanism composed by a rigid platform in a serial connection with a compliant platform, and concentrates on its configuration and interrelation. The analysis starts with the operator of a 3UPU configuration with a central strut being derived. Configuration and displacement formulas of the compliant platform are demonstrated, leading to the analytic equations of the relationship between the actuated angles of the operator and the position parameters of the end-effector. The numerical evaluation of workspace of the two-staged parallel mechanism is then followed.     

Hardware-in-the-loop simulation for the design and verification of the control system of a series–parallel hybrid electric city-bus

Hybrid electric buses have been a promising technology to dramatically lower fuel consumption and carbon dioxide (CO₂) emission, while energy management strategy (EMS) is a critical technology to the improvements in fuel economy for hybrid electric vehicles (HEVs). In this paper, a suboptimal EMS is developed for the real-time control of a series–parallel hybrid electric bus. It is then investigated and verified in a hardware-in-the-loop (HIL) simulation system constructed on PT-LABCAR, a commercial real-time simulator. First, an optimal EMS is obtained via iterative dynamic programming (IDP) by defining a cost function over a specific drive cycle to minimize fuel consumption, as well as to achieve zero battery state-of-charge (SOC) change and to avoid frequent clutch operation. The IDP method can lower the computational burden and improve the accuracy. Second, the suboptimal EMS for real-time control is developed by constructing an Elman neural network (NN) based on the aforementioned optimal EMS, so the real-time suboptimal EMS can be used in the vehicle control unit (VCU) of the hybrid bus. The real VCU is investigated and verified utilizing a HIL simulator in a virtual forward-facing HEV environment consisting of vehicle, driver and driving environment. The simulation results demonstrate that the proposed real-time suboptimal EMS by the neural network can coordinate the overall hybrid powertrain of the hybrid bus to optimize fuel economy over different drive cycles, and the given drive cycles can be tracked while sustaining the battery SOC level.     

Application of genetic algorithm in crack detection of beam-like structures using a new cracked Euler–Bernoulli beam element

In this paper, a crack identification approach is presented for detecting crack depth and location in beam-like structures. For this purpose, a new beam element with a single transverse edge crack, in arbitrary position of beam element with any depth, is developed. The crack is not physically modeled within the element, but its effect on the local flexibility of the element is considered by the modification of the element stiffness as a function of crack's depth and position. The development is based on a simplified model, where each crack is substituted by a corresponding linear rotational spring, connecting two adjacent elastic parts. The localized spring may be represented based on linear fracture mechanics theory. The components of the stiffness matrix for the cracked element are derived using the conjugate beam concept and Betti's theorem, and finally represented in closed-form expressions. The proposed beam element is efficiently employed for solving forward problem (i.e., to gain accurate natural frequencies of beam-like structures knowing the cracks’ characteristics). To validate the proposed element, results obtained by new element are compared with two-dimensional (2D) finite element results as well as available experimental measurements. Moreover, by knowing the natural frequencies, an inverse problem is established in which the cracks location and depth are identified. In the inverse approach, an optimization problem based on the new beam element and genetic algorithms (GAs) is solved to search the solution. The proposed approach is verified through various examples on cracked beams with different damage scenarios. It is shown that the present algorithm is able to identify various crack configurations in a cracked beam.