A new range-free localisation in wireless sensor networks using support vector machine

Location information of sensor nodes is of vital importance for most applications in wireless sensor networks (WSNs). This paper proposes a new range-free localisation algorithm using support vector machine (SVM) and polar coordinate system (PCS), LSVM-PCS. In LSVM-PCS, two sets of classes are first constructed based on sensor nodes’ polar coordinates. Using the boundaries of the defined classes, the operation region of WSN field is partitioned into a finite number of polar grids. Each sensor node can be localised into one of the polar grids by executing two localisation algorithms that are developed on the basis of SVM classification. The centre of the resident polar grid is then estimated as the location of the sensor node. In addition, a two-hop mass-spring optimisation (THMSO) is also proposed to further improve the localisation accuracy of LSVM-PCS. In THMSO, both neighbourhood information and non-neighbourhood information are used to refine the sensor node location. The results obtained verify that the proposed algorithm provides a significant improvement over existing localisation methods.     

Active carbody roll control in railway vehicles using hydraulic actuation

Carbody tilting is used in railway vehicles to reduce the exposure of passengers to lateral acceleration in curves, allowing these to be negotiated at higher speeds with the same level of comfort. This, however, requires a rather complex actuation system that increases vehicle weight and reduces space for passengers.This paper introduces a new concept that provides a limited amount of carbody tilt using hydraulic actuation. The device consists of interconnected hydraulic actuators attached to the carbody and bogies, replacing the passive anti-roll bar used in railway vehicles and in addition permitting active tilt control.Three control strategies for the active hydraulic suspension are proposed, and the regulator gains are defined using Genetic Algorithm optimisation, based on numerical simulation of the running behaviour of the actuated railway vehicle in a high-speed curve. Finally, the performance of the actuated vehicle is assessed on the basis of numerical simulations, showing it is possible to increase significantly the vehicle׳s running speed in fast curves compared with a vehicle equipped with passive suspension.     

Transverse contraction criteria for existence,stability, and robustness of a limit cycle

This paper derives a differential contraction condition for the existence of an orbitally-stable limit cycle in an autonomous system. This transverse contraction condition can be represented as a pointwise linear matrix inequality (LMI), thus allowing convex optimisation tools such as sum-of-squares programming to be used to search for certificates of the existence of a stable limit cycle. Many desirable properties of contracting dynamics are extended to this context, including the preservation of contraction under a broad class of interconnections. In addition, by introducing the concepts of differential dissipativity and transverse differential dissipativity, contraction and transverse contraction can be established for interconnected systems via LMI conditions on component subsystems.     

A unified theory for optimal feedforward torque control of anisotropic synchronous machines

A unified theory for optimal feedforward torque control of anisotropic synchronous machines with non-negligible stator resistance and mutual inductance is presented which allows to analytically compute (1) the optimal direct and quadrature reference currents for all operating strategies, such as maximum torque per current (MTPC), maximum current, field weakening, maximum torque per voltage (MTPV) or maximum torque per flux (MTPF), and (2) the transition points indicating when to switch between the operating strategies due to speed, voltage or current constraints. The analytical solutions allow for an (almost) instantaneous selection and computation of actual operation strategy and corresponding reference currents. Numerical methods (approximating these solutions only) are no longer required. The unified theory is based on one simple idea: all optimisation problems, their respective constraints and the computation of the intersection point(s) of voltage ellipse, current circle or torque, MTPC, MTPV, MTPF hyperbolas are reformulated implicitly as quadrics which allows to invoke the Lagrangian formalism and to find the roots of fourth-order polynomials analytically. The proposed theory is suitable for any anisotropic synchronous machine. Implementation and measurement results illustrate effectiveness and applicability of the theoretical findings in real world.     

Failure analysis of novel microhollow cathode discharge microplasma reactors

Compact fuel cells are one logical progression for portable power in comparison to batteries since fuel cells have much higher energy densities. However, fuel cells have not fully entered the portable power market as they require a readily available hydrogen feed. Microplasmas offer a way to produce hydrogen portably. Microplasma reactors developed from standard semiconductor fabrication techniques, specifically microhollow cathode discharge (MHCD) devices, have been tested by our group in reforming various hydrocarbons.     

Automation and optimisation of Family Mould Cavity and Runner Layout Design (FMCRLD) using genetic algorithms and mould layout design grammars

Family Mould Cavity Runner Layout Design (FMCRLD) is the most demanding and critical task in the early Conceptual Mould Layout Design (CMLD) phase. Traditional experience-dependent manual FCMRLD workflow causes long design lead time, non-optimum designs and human errors. However, no previous research can support FMCRLD automation and optimisation. The nature of FMCRLD is non-repetitive and generative. The complexity of FMCRLD optimisation involves solving a complex two-level combinatorial layout design optimisation problem. Inspired by the theory of evolutionary design in nature “Survival of the Fittest” and the biological genotype–phenotype mapping process of the generation of form in living systems, this research first proposes an innovative evolutionary FMCRLD approach using Genetic Algorithms (GA) and Mould Layout Design Grammars (MLDG) that can automate and optimise such generative and complex FMCRLD with its explorative and generative design process embodied in a stochastic evolutionary search. Based on this approach, an Intelligent Conceptual Mould Layout Design System (ICMLDS) prototype has been developed. The ICMLDS is a powerful intelligent design system as well as an interactive design-training system that can encourage and accelerate mould designers’ design alternative exploration, exploitation and optimisation for better design in less time. This research innovates the traditional manual FMCRLD workflow to eliminate costly human errors and boost the less-experienced mould designer’s ability and productivity in performing FCMRLD during the CMLD phase.     

A novel hybrid cellular automata–linear programming approach for the optimal sizing of planar truss structures

This paper presents a novel hybrid cellular automata (CA) linear programming (LP) methodology for the size optimisation of planar truss structures. The method uses the nodal displacements and internal forces of the truss as the design variables of the optimisation problem. The objective function is the volume of the structure and the constraints of the original optimisation problem are recast in terms of the new decision variables in the two-phase step. Starting with an arbitrary set of nodal displacements and internal forces, these are updated in turn in an iterative two-phase process. In the first phase, the internal forces are kept fixed and the nodal displacements are found using a CA approach. In the second phase, a LP is used to find the set of internal forces of truss elements which minimises the total volume of the structure. The effectiveness and efficiency of the methodology is also examined with its application to some benchmark truss structures.     

Optimum aqueous extraction conditions for preparation of a phenolic‐enriched Davidson's plum (Davidsonia pruriens F. Muell) extract

This study aimed to optimise aqueous extraction conditions for total phenolic compounds (TPC) from Davidson's plum (Davidsonia pruriens F. Muell) and to assess the physicochemical and antioxidant properties of the phenolic‐enriched extract. The results showed that temperature, time and ratio significantly affected the extraction of TPC. Optimization of extraction conditions was performed using response surface methodology (RSM) utilising a Box–Behnken design. Optimal extraction conditions were determined to be temperature: 90 °C, extraction time: 30 min and solvent to mass ratio: 20:1 mL g^?1. The extracted solid obtained under these conditions had low‐moisture content, high water solubility and contained 45 mg GAE g^?1 of TPC, 22 mg RUE g^?1 of flavonoids, 3.2 mg CAE g^?1 of proanthocyanidins, 2 mg CGE g^?1 of anthocyanidins and 56 mg ACE g^?1 vitamin C. The extract possessed potent antioxidant capacity, but was comparatively lower than those of vitamin E and BHT. Thus, Davidson's plum should be further investigated for its potential health promoting benefits and utilisation in the nutraceutical and food industries.     

A multivariate approach to optimise the synergistic blend of oleoresin rosemary (Rosmarinus officinalis L.) and ascorbyl palmitate added into sunflower oil

The simultaneous optimisation of a synergistic blend of oleoresin rosemary (ROS) and ascorbyl palmitate (AP) in sunflower oil (SO) was performed using central composite and rotatable design coupled with principal component analysis (PCA) and response surface methodology (RSM). The physicochemical parameters, viz. peroxide value, anisidine value, induction period, total polar matter, UV absorbances (232 and 270 nm) and antioxidant capacity were considered as response variables. PCA reduced the original set of correlated responses to few uncorrelated principal components (PC). The PC1 (eigenvalue, 6.08; data variance explained, 86.97%) was selected for optimisation using RSM. The quadratic model described the data (R² = 0. 93, P < 0.05), and lack of fit was insignificant (P > 0.05). The contour plot of PC 1 score indicated the optimal synergistic combination of 1309.62 and 129.29 ppm for ROS and AP, respectively. In conclusion, the versatility of PCA–RSM approach has resulted in an easy interpretation in multiple response optimisations.     

Towards sustainable production and consumption: A novel DEcision-Support Framework IntegRating Economic,Environmental and Social Sustainability (DESIRES)

The idea of sustainable production and consumption is becoming a widely-accepted societal goal worldwide. However, its implementation is slow and the world continues to speed down an unsustainable path. One of the difficulties is the sheer complexity of production and consumption systems that would need to be re-engineered in a more sustainable way as well as the number of sustainability constraints that have to be considered and satisfied simultaneously. This paper argues that bringing about sustainable production and consumption requires a systems approach underpinned by life cycle thinking as well as an integration of economic, environmental and social aspects. In an attempt to aid this process, a novel decision-support framework DESIRES has been developed comprising a suite of tools, including scenario analysis, life cycle costing, life cycle assessment, social sustainability assessment, system optimisation and multi-attribute decision analysis. An application of the framework is illustrated by a case study related to energy.