Adaptive fast finite-time multiple-surface sliding control for a class of uncertain non-linear systems

This paper concerns the adaptive fast finite-time multiple-surface sliding control (AFFTMSSC) problem for a class of high-order uncertain non-linear systems of which the upper bounds of the system uncertainties are unknown. By using the fast control Lyapunov function and the method of so-called adding a power integrator merging with adaptive technique, a recursive design procedure is provided, which guarantees the fast finite-time stability of the closed-loop system. Further, it is proved that the control input is bounded.

Challenges to consumers travelling with multiple medicines

Objectives: The need to maintain medicine adherence when travelling is irrefutable, yet how people achieve this goal and the challenges they encounter in doing so have seldom been explored in previous research. This study examined how consumers residing in Australia experience and manage their multiple medicines while travelling. Methods: Face-to-face, narrative interviews were conducted in participants' homes or workplaces and were audio and video-recorded. The coding schema was devised with the input of an Advisory Panel with expertise in multiple medicines. Data were analysed using the constant comparative method. Key findings: Participants who had experienced medicines mishaps when travelling had learnt to take greater care when planning and preparing for future trips. Prior to travelling, they rarely sought advice regarding their regular medicines from health professionals. Organising and packing their medicines could be extremely time-consuming and confusing; younger participants especially lamented the reduced spontaneity this imposed on their lives. Replicating their usual routines was a successful strategy for many; however, this was challenged by unforeseen events and the lack of privacy. Conclusions: Travel comprised inherent risks to the users of multiple medicines and often required intensive and complicated preparation. Community pharmacists and other health professionals are well placed to advise and assist consumers with complex regimens who are planning to travel, as well as raise general awareness concerning the need for utmost care with multiple medicines.

Multiple days of heat exposure on firefighters' work performance and physiology

This study assessed the accumulated effect of ambient heat on the performance of, and physiological and perceptual responses to, intermittent, simulated wildfire fighting tasks over three consecutive days. Firefighters (n = 36) were matched and allocated to either the CON (19°C) or HOT (33°C) condition. They performed three days of intermittent, self-paced simulated firefighting work, interspersed with physiological testing. Task repetitions were counted (and converted to distance or area) to determine work performance. Participants were asked to rate their perceived exertion and thermal sensation after each task. Heart rate, core temperature (Tc), and skin temperature (Tsk) were recorded continuously throughout the simulation. Fluids were consumed ad libitum. Urine volume was measured throughout, and urine specific gravity (USG) analysed, to estimate hydration. All food and fluid consumption was recorded. There was no difference in work output between experimental conditions. However, significant variation in performance responses between individuals was observed. All measures of thermal stress were elevated in the HOT, with core and skin temperature reaching, on average, 0.24 ± 0.08°C and 2.81 ± 0.20°C higher than the CON group. Participants' doubled their fluid intake in the HOT condition, and this was reflected in the USG scores, where the HOT participants reported significantly lower values. Heart rate was comparable between conditions at nearly all time points, however the peak heart rate reached each circuit was 7 ± 3% higher in the CON trial. Likewise, RPE was slightly elevated in the CON trial for the majority of tasks. Participants' work output was comparable between the CON and HOT conditions, however the performance change over time varied significantly between individuals. It is likely that the increased fluid replacement in the heat, in concert with frequent rest breaks and task rotation, assisted with the regulation of physiological responses (e.g., heart rate, core temperature).

Using Multi-Objective Optimization To Maximize Multiple Benefits For Sustainable Drainage Design

For many years, drainage design was mainly about providing sufficient network capacity. This traditional approach had been successful with the aid of computer software and technical guidance. However, the drainage design criteria had been evolving due to rapid population growth, urbanisation, climate change and increasing sustainability awareness. Sustainable drainage systems that bring benefits in addition to water management have been recommended as better alternatives to conventional pipes and storages. Although the concepts and good practice guidance had already been communicated to decision makers and public for years, network capacity still remains a key design focus in many circumstances while the additional benefits are generally considered secondary only. Yet, the picture is changing. The industry begins to realise that delivering multiple benefits should be given the top priority while the drainage service can be considered a secondary benefit instead. The shift in focus means the industry has to adapt to new design challenges. New guidance and computer software are needed to assist decision makers. For this purpose, we developed a new decision support system. The system consists of two main components – a multi-criteria evaluation framework for drainage systems and a multi-objective optimisation tool. Users can systematically quantify the performance, life-cycle costs and benefits of different drainage systems using the evaluation framework. The optimisation tool can assist users to determine combinations of design parameters such as the sizes, order and type of drainage components that maximise multiple benefits. In this paper, we will focus on the optimisation component of the decision support framework. The optimisation problem formation, parameters and general configuration will be discussed. We will also look at the sensitivity of individual variables and the benchmark results obtained using common multi-objective optimisation algorithms. The work described here is the output of an EngD project funded by EPSRC and XP Solutions.

Evaluating And Optimizing Sustainable Drainage Design To Maximize Multiple Benefits: Case Studies In China

In the past, the focus of drainage design was on sizing pipes and storages in order to provide sufficient network capacity. This traditional approach, together with computer software and technical guidance, had been successful for many years. However, due to rapid population growth and urbanisation, the requirements of a “good” drainage design have also changed significantly. In addition to water management, other aspects such as environmental impacts, amenity values and carbon footprint have to be considered during the design process. Going forward, we need to address the key sustainability issues carefully and practically. The key challenge of moving from simple objectives (e.g. capacity and costs) to complicated objectives (e.g. capacity, flood risk, environment, amenity etc) is the difficulty to strike a balance between various objectives and to justify potential benefits and compromises. In order to assist decision makers, we developed a new decision support system for drainage design. The system consists of two main components – a multi-criteria evaluation framework for drainage systems and a multi-objective optimisation tool. The evaluation framework is used for the quantification of performance, life-cycle costs and benefits of different drainage systems. The optimisation tool can search for feasible combinations of design parameters such as the sizes, order and type of drainage components that maximise multiple benefits. In this paper, we will discuss real-world application of the decision support system. A number of case studies have been developed based on recent drainage projects in China. We will use the case studies to illustrate how the evaluation framework highlights and compares the pros and cons of various design options. We will also discuss how the design parameters can be optimised based on the preferences of decision makers. The work described here is the output of an EngD project funded by EPSRC and XP Solutions.

High power factor dimmable electronic ballast for multiple tubular fluorescent lamps

This paper presents a dimmable electronic ballast designed for multiple fluorescent lamps applications. A ZCS-PWM Boost rectifier and a classical resonant Full-Bridge inverter compose this new electronic ballast, providing conditions for the obtaining of high input power-factor, and soft-switching processes for all semiconductor devices employed in the structure. The instantaneous average input current control technique is employed in the Boost rectifier. Concerning the Full-Bridge inverter, it is controlled by the imposition of phase-shift in the current processed through the sets of resonant filters + lamps, according to an adaptation in a specially designed control IC, called IR2159. Experimental results are presented in order to validate the analyses developed in this paper.

Electronic ballast for multiple fluorescent lamp systems

An electronic ballast for multiple tubular fluorescent lamp systems is presented. The proposed structure has a high value for the power factor, a dimming capability, and soft switching of the semiconductor devices operated at high frequencies. A zero-current switching pulse width modulated SEPIC converter is used as the rectifying stage and it is controlled using the instantaneous average input current technique. The inverting stage consists of classical resonant half-bridge converter with series-resonant parallel-loaded filters. The dimming control technique is based on varying the switching frequency and monitoring the phase shift of the current drained by the filters and lamps in order to establish a closed loop control. Experimental results are presented that validate the theoretical analysis.

The STATFLUX code: a statistical method for calculation of flow and set of parameters, based on the Multiple-Compartment Biokinetical Model

The code STATFLUX, implementing a new and simple statistical procedure for the calculation of transfer coefficients in radionuclide transport to animals and plants, is proposed. The method is based on the general multiple-compartment model, which uses a system of linear equations involving geometrical volume considerations. Flow parameters were estimated by employing two different least-squares procedures: Derivative and Gauss-Marquardt methods, with the available experimental data of radionuclide concentrations as the input functions of time. The solution of the inverse problem, which relates a given set of flow parameter with the time evolution of concentration functions, is achieved via a Monte Carlo Simulation procedure.Program summaryTitle of program: STATFLUXCatalogue identifier: ADYS_v1_0Program summary URL: http://cpc.cs.qub.ac.uk/summaries/ADYS_v1_0Program obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandLicensing provisions: noneComputer for which the program is designed and others on which it has been tested: Micro-computer with Intel Pentium III, 3.0 GHzInstallation: Laboratory of Linear Accelerator, Department of Experimental Physics, University of São Paulo, BrazilOperating system: Windows 2000 and Windows XPProgramming language used: Fortran-77 as implemented in Microsoft Fortran 4.0. NOTE: Microsoft Fortran includes non-standard features which are used in this program. Standard Fortran compilers such as, g77, f77, ifort and NAG95, are not able to compile the code and therefore it has not been possible for the CPC Program Library to test the program.Memory, required to execute with typical data: 8 Mbytes of RAM memory and 100 MB of Hard disk memoryNo. of bits in a word: 16No. of lines in distributed program, including test data, etc.: 6912No. of bytes in distributed Program, including test data, etc.: 229 541Distribution format: tar.gzNature of the physical problem: the investigation of transport mechanisms for radioactive substances, through environmental pathways, is very important for radiological protection of populations. One such pathway, associated with the food chain, is the grass-animal-man sequence. The distribution of trace elements in humans and laboratory animals has been intensively studied over the past 60 years [R.C. Pendlenton, C.W. Mays, R.D. Lloyd, A.L. Brooks, Differential accumulation of iodine-131 from local fallout in people and milk, Health Phys. 9 (1963) 1253-1262]. In addition, investigations on the incidence of cancer in humans, and a possible causal relationship to radioactive fallout, have been undertaken [E.S. Weiss, M.L. Rallison, W.T. London, W.T. Carlyle Thompson, Thyroid nodularity in southwestern Utah school children exposed to fallout radiation, Amer. J. Public Health 61 (1971) 241-249; M.L. Rallison, B.M. Dobyns, F.R. Keating, J.E. Rall, F.H. Tyler, Thyroid diseases in children, Amer. J. Med. 56 (1974) 457-463; J.L. Lyon, M.R. Klauber, J.W. Gardner, K.S. Udall, Childhood leukemia associated with fallout from nuclear testing, N. Engl. J. Med. 300 (1979) 397-402]. From the pathways of entry of radionuclides in the human (or animal) body, ingestion is the most important because it is closely related to life-long alimentary (or dietary) habits. Those radionuclides which are able to enter the living cells by either metabolic or other processes give rise to localized doses which can be very high. The evaluation of these internally localized doses is of paramount importance for the assessment of radiobiological risks and radiological protection. The time behavior of trace concentration in organs is the principal input for prediction of internal doses after acute or chronic exposure. The General Multiple-Compartment Model (GMCM) is the powerful and more accepted method for biokinetical studies, which allows the calculation of concentration of trace elements in organs as a function of time, when the flow parameters of the model are known. However, few biokinetics data exist in the literature, and the determination of flow and transfer parameters by statistical fitting for each system is an open problem.Restriction on the complexity of the problem: This version of the code works with the constant volume approximation, which is valid for many situations where the biological half-live of a trace is lower than the volume rise time. Another restriction is related to the central flux model. The model considered in the code assumes that exist one central compartment (e.g., blood), that connect the flow with all compartments, and the flow between other compartments is not included.Typical running time: Depends on the choice for calculations. Using the Derivative Method the time is very short (a few minutes) for any number of compartments considered. When the Gauss-Marquardt iterative method is used the calculation time can be approximately 5-6 hours when similar to 15 compartments are considered. (C) 2006 Elsevier B.V. All rights reserved.

Multiple active levels in Bi12TiO20 crystals

The existence of multiple active levels in a photorefractive Bi12TiO20 crystal is here investigated at 514.5nm wavelength. We carry out two-wave mixing experiments using symmetrically incident beams of equal intensities. A large amplitude fast phase modulation in one of the beams reduces the fringes visibility and improves the detection of the generated frequency modulated signals in both (R and S) output directions. Diffraction efficiencies of the phase (photorefractive) and the absorption (photochromic) gratings are quantitatively computed as functions of the grating period. Results show that the absorption grating has two distinct components: one associated to the photorefractive trap density modulation and another related to local light-induced effects between different levels. The photorefractive grating was also investigated at 633nm and 594nm (besides 514.5nm) and a significant quenching of the photorefractive effect was observed at these wavelengths.

Challenges of modeling depth-integrated marine primary productivity over multiple decades: A case study at BATS and HOT

The performance of 36 models (22 ocean color models and 14 biogeochemical ocean circulation models (BOGCMs)) that estimate depth-integrated marine net primary productivity (NPP) was assessed by comparing their output to in situ (14)C data at the Bermuda Atlantic Time series Study (BATS) and the Hawaii Ocean Time series (HOT) over nearly two decades. Specifically, skill was assessed based on the models' ability to estimate the observed mean, variability, and trends of NPP. At both sites, more than 90% of the models underestimated mean NPP, with the average bias of the BOGCMs being nearly twice that of the ocean color models. However, the difference in overall skill between the best BOGCM and the best ocean color model at each site was not significant. Between 1989 and 2007, in situ NPP at BATS and HOT increased by an average of nearly 2% per year and was positively correlated to the North Pacific Gyre Oscillation index. The majority of ocean color models produced in situ NPP trends that were closer to the observed trends when chlorophyll-alpha was derived from high-performance liquid chromatography (HPLC), rather than fluorometric or SeaWiFS data. However, this was a function of time such that average trend magnitude was more accurately estimated over longer time periods. Among BOGCMs, only two individual models successfully produced an increasing NPP trend (one model at each site). We caution against the use of models to assess multiannual changes in NPP over short time periods. Ocean color model estimates of NPP trends could improve if more high quality HPLC chlorophyll-alpha time series were available.

A unity power factor multiple isolated outputs switching mode power supply using a single switch

The authors present an offline switching power supply with multiple isolated outputs and unity power factor with the use of only one power processing stage, based on the DC-DC SEPIC (single ended primary inductance converter) modulated by variable hysteresis current control. The principle of operation, the theoretical analysis, the design procedure, an example, and simulation results are presented. A laboratory prototype, rated at 160 W, operating at a maximum switching frequency of 100 kHz, with isolated outputs rated at +5 V/15 A -5 V/1 A, +12 V/6 A and -12 V/1 A, has been built given an input power factor near unity.

Dimmable electronic ballast with high power-factor SEPIC preregulator, for multiple tubular fluorescent lamps

An electronic ballast for multiple tubular fluorescent lamps is presented in this paper. The proposed structure features high power-factor, dimming capability, and soft-switching to the semiconductor devices operated in high frequencies. A Zero-Current-Switching - Pulse-Width-Modulated (ZCS-PWM) SEPIC converter composes the rectifying stage, controlled by the instantaneous average input current technique, performing soft-commutations and high input power factor. Regarding the inverting stage, it is composed by a classical resonant Half-Bridge converter, associated to Series Parallel-Loaded Resonant (SPLR) filters. The dimming control technique employed in this Half-Bridge inverter is based on the phase-shift in the current processed through the sets of filter + lamp. In addition, experimental results are shown in order to validate the developed analysis.

Machine vision and planning applied on assembby line of multiple products

This article describes the use of Artificial Intelligence (IA) techniques applied in cells of a manufacturing system. Machine Vision was used to identify pieces and their positions of two different products to be assembled in the same productive line. This information is given as input for an IA planner embedded in the manufacturing system. Therefore, initial and final states are sent automatically to the planner capable to generate assembly plans for a robotic cell, in real time.

A multiple time scale survival model with a cure fraction

Many recent survival studies propose modeling data with a cure fraction, i.e., data in which part of the population is not susceptible to the event of interest. This event may occur more than once for the same individual (recurrent event). We then have a scenario of recurrent event data in the presence of a cure fraction, which may appear in various areas such as oncology, finance, industries, among others. This paper proposes a multiple time scale survival model to analyze recurrent events using a cure fraction. The objective is analyzing the efficiency of certain interventions so that the studied event will not happen again in terms of covariates and censoring. All estimates were obtained using a sampling-based approach, which allows information to be input beforehand with lower computational effort. Simulations were done based on a clinical scenario in order to observe some frequentist properties of the estimation procedure in the presence of small and moderate sample sizes. An application of a well-known set of real mammary tumor data is provided.

Advantages and Applications of Transforming Empirical Model Input Space with Dimensional Models

Model-based calibration of steady-state engine operation is commonly performed with highly parameterized empirical models that are accurate but not very robust, particularly when predicting highly nonlinear responses such as diesel smoke emissions. To address this problem, and to boost the accuracy of more robust non-parametric methods to the same level, GT-Power was used to transform the empirical model input space into multiple input spaces that simplified the input-output relationship and improved the accuracy and robustness of smoke predictions made by three commonly used empirical modeling methods: Multivariate Regression, Neural Networks and the k-Nearest Neighbor method. The availability of multiple input spaces allowed the development of two committee techniques: a 'Simple Committee' technique that used averaged predictions from a set of 10 pre-selected input spaces chosen by the training data and the "Minimum Variance Committee" technique where the input spaces for each prediction were chosen on the basis of disagreement between the three modeling methods. This latter technique equalized the performance of the three modeling methods. The successively increasing improvements resulting from the use of a single best transformed input space (Best Combination Technique), Simple Committee Technique and Minimum Variance Committee Technique were verified with hypothesis testing. The transformed input spaces were also shown to improve outlier detection and to improve k-Nearest Neighbor performance when predicting dynamic emissions with steady-state training data. An unexpected finding was that the benefits of input space transformation were unaffected by changes in the hardware or the calibration of the underlying GT-Power model.