Expert system application for the loading capability assessment oftransmission lines

This paper describes the application of an expert system for the evaluation of the short-term thermal rating and temperature rise of overhead conductors. The expert system has been developed using a database and Leonardo expert system shell which is gaining popularity among commercial tools for developing expert system applications. The expert system has been found to compare well when evaluated against site tests. A practical application is given to demonstrate the usefulness of the expert system developed     

Development and control of a new AUV platform

This paper presents an architecture of a newly developed autonomous underwater vehicle (AUV) platform, named KAUV-1, which is designed as a torpedo with very light weight and small size, suitable for use in marine exploration and monitoring. The KAUV-1 has a unique ducted propeller located at the aft end with yawing actuation acting as a rudder. For depth motion, the KAUV-1 is designed to have a mass shifter mechanism inside to change the vehicle center of gravity and to control its pitch angle and depth motion. The paper also presents an analysis on the equations of motion of the KAUV-1 with mass shifter mechanism and a new depth control strategy for the KAUV-1. The feasibility of the proposed control strategy is validated through simulation and experiment of performance of the vehicle.     

Room-Temperature-Processable Highly Reliable Resistive Switching Memory with Reconfigurability for Neuromorphic Computing and Ultrasonic Tissue Classification

Reversible metal-filamentary mechanism has been widely investigated to design an analog resistive switching memory (RSM) for neuromorphic hardware-implementation. However, uncontrollable filament-formation, inducing its reliability issues, has been a fundamental challenge. Here, an analog RSM with 3D ion transport channels that can provide unprecedentedly high reliability and robustness is demonstrated. This architecture is realized by a laser-assisted photo-thermochemical process, compatible with the back-end-of-line process and even applicable to a flexible format. These superior characteristics also lead to the proposal of a practical adaptive learning rule for hardware neural networks that can significantly simplify the voltage pulse application methodology even with high computing accuracy. A neural network, which can perform the biological tissue classification task using the ultrasound signals, is designed, and the simulation results confirm that this practical adaptive learning rule is efficient enough to classify these weak and complicated signals with high accuracy (97%). Furthermore, the proposed RSM can work as a diffusive-memristor at the opposite voltage polarity, exhibiting extremely stable threshold switching characteristics. In this mode, several crucial operations in biological nervous systems, such as Ca²⁺ dynamics and nonlinear integrate-and-fire functions of neurons, are successfully emulated. This reconfigurability is also exceedingly beneficial for decreasing the complexity of systems—requiring both drift- and diffusive-memristors.     

Improving traversability of quadruped walking robots using body movement in 3D rough terrains

This paper presents a study on improving the traversability of a quadruped walking robot in 3D rough terrains. The key idea is to exploit body movement of the robot. The position and orientation of the robot are systematically adjusted and the possibility of finding a valid foothold for the next swing is maximized, which makes the robot have more chances to overcome the rough terrains. In addition, a foothold search algorithm that provides the valid foothold while maintaining a high traversability of the robot, is investigated and a gait selection algorithm is developed to help the robot avoid deadlock situations. To explain the algorithms, new concepts such as reachable area, stable area, potential search direction, and complementary kinematic margin are introduced, and the effectiveness of the algorithms is validated via simulations and experiments.     

Low temperature synthesis and characterisation of lecontite, (NH4)Na(SO4)·2H20

Lecontite, (NH₄)Na(SO₄).2H₂O, was synthesised at room temperature in high purity compared to earlier work with a minor impurity of mascagnite, (NH₄)₂SO₄. Rietveld refinement of the XRD results confirmed the crystal structure and unit cell dimensions as published earlier. Raman and Infrared spectroscopy, in conjunction with factor group analysis, resulted in a complex pattern of overlapping sulphate, NH and OH modes. The NH modes υ₁ was observed around 2880 cm⁻¹, υ₂ around 1700 cm⁻¹ overlapping with water OH-bending modes, υ₃ around 3300 cm⁻¹ overlapping with water OH-stretching modes around 3023, 3185 and 3422 cm⁻¹, and υ₄ around 1432, 1447 and 1462 cm⁻¹. The sulphate group in the crystal structure displays a decrease in symmetry from T_d as evidenced by the activation of the ν₁ mode at 982 cm⁻¹ and the ν₂ mode around 452 cm⁻¹ in the Infrared spectrum. The υ₃ mode shows clear splitting in the infrared spectra with a strong band at 1064 cm⁻¹ accompanied by two shoulders at 1107 and 1139 cm⁻¹. The Raman spectra show three weak bands at 1068, 1109 and 1135 cm⁻¹ with a shoulder at 1155 cm⁻¹. Similar splitting was observed for the υ₄ mode around 611 and 632 cm⁻¹ in the Infrared and Raman spectra, respectively.     

High-dimensional MRI data analysis using a large-scale manifold learning approach

A novel manifold learning approach is presented to efficiently identify low-dimensional structures embedded in high-dimensional MRI data sets. These low-dimensional structures, known as manifolds, are used in this study for predicting brain tumor progression. The data sets consist of a series of high-dimensional MRI scans for four patients with tumor and progressed regions identified. We attempt to classify tumor, progressed and normal tissues in low-dimensional space. We also attempt to verify if a progression manifold exists—the bridge between tumor and normal manifolds. By identifying and mapping the bridge manifold back to MRI image space, this method has the potential to predict tumor progression. This could be greatly beneficial for patient management. Preliminary results have supported our hypothesis: normal and tumor manifolds are well separated in a low-dimensional space. Also, the progressed manifold is found to lie roughly between the normal and tumor manifolds.     

Dynamics of geometrically exact sandwich structures

A finite element formulation of a recent theory for geometrically exact multilayer beams, applicable to one-dimensional plates, is presented here. The beam can take any arbitrary initial position in the two-dimensional space. Each layer of the beam can have different material properties with no restriction on the stiffness, mass distribution and layer thickness, thus allowing for the modeling of ideals sandwich structures. Finite rotation and shear deformation are accommodated for in each layer. The continuity of the displacements across the layer interfaces is exactly enforced; the deformed cross section is thus continuous, piecewise-linear. Extensive numerical examples including harmonic response of sandwich structures with three identical layers, with comparison to single-layer beams, and the response of ideal sandwich beams to impact forces are presented to illustrate the applicability and versatility of the proposed formulation.     

Sensing and gait planning of quadruped walking and climbing robot for traversing in complex environment

In this paper, a general study on improving adaptability of quadruped walking and climbing robot in complex environment is presented. First, a sensing system composed of range and gyroscope sensors in a novel arrangement is developed. By combining the sensing signals and the internal state of the robot, the surface geometry of the environment is sufficiently reconstructed in real-time. Secondly, a planning algorithm for the robot to overcome the reconstructed environment is conducted. Based on the reshaped surface, the planning algorithm not only provides the exact body trajectory and foot positions but also the adaptability of the robot in a specific environment. A method to improve the adaptability of the walking and climbing robot is also introduced. Thanks to the adherent ability of the robot, the center of gravity of the robot is allowed to move outside the support polygon to increase the reach-ability of the next swing leg. Finally, the effectiveness of the proposed approach is verified by the performances of the experiments in complex environments using a quadruped walking and climbing robot named MRWALLSPECT IV.     

New predictor/corrector algorithms with improved energy balance for a recent formulation of dynamic vehicle/structure interaction

A new class of predictor/corrector algorithms is proposed to solve the complex system of differential equations that arises from a Galerkin spatial discretization of the equations of motion in a recent formulation of dynamic vehicle/structure interaction. The applicability of the concept of a building-block vehicle/structure interaction model developed in our previous work—where the vehicle nominal motion is not prescribed a priori, but is part of the unknown motion of the system—is demonstrated through the construction of a simple vehicle model. In the new algorithms, the presence of the accelerations of the vehicle component is eliminated in the predictor structural equations, making these equations different from the corrector structural equations. The special treatment of the predicted axial motion that provides an artificial damping to eliminate unstable oscillations in the numerical results as proposed in the old algorithms is avoided. Accurate results from numerical simulations using the new algorithms are obtained, and there are no unstable oscillations that were observed in some other predictor/corrector schemes. The system energy balance is also better preserved compared with the old algorithms.