Efficient tool path computation using multi-core GPUs

Tool path generation is one of the most complex problems in Computer Aided Manufacturing. Although some efficient strategies have been developed, most of them are only useful for standard machining. However, the algorithms used for tool path computation demand a higher computation performance, which makes the implementation on many existing systems very slow or even impractical. Hardware acceleration is an incremental solution that can be cleanly added to these systems while keeping everything else intact. It is completely transparent to the user. The cost is much lower and the development time is much shorter than replacing the computers by faster ones. This paper presents an optimisation that uses a specific graphic hardware approach using the power of multi-core Graphic Processing Units (GPUs) in order to improve the tool path computation. This improvement is applied on a highly accurate and robust tool path generation algorithm. The paper presents, as a case of study, a fully implemented algorithm used for turning lathe machining of shoe lasts. A comparative study will show the gain achieved in terms of total computing time. The execution time is almost two orders of magnitude faster than modern PCs.

Fault tolerant embedded systems design by multi-objective optimization

The design of fault tolerant systems is gaining importance in large domains of embedded applications where design constrains are as important as reliability. New software techniques, based on selective application of redundancy, have shown remarkable fault coverage with reduced costs and overheads. However, the large number of different solutions provided by these techniques, and the costly process to assess their reliability, make the design space exploration a very difficult and time-consuming task. This paper proposes the integration of a multi-objective optimization tool with a software hardening environment to perform an automatic design space exploration in the search for the best trade-offs between reliability, cost, and performance. The first tool is commanded by a genetic algorithm which can simultaneously fulfill many design goals thanks to the use of the NSGA-II multi-objective algorithm. The second is a compiler-based infrastructure that automatically produces selective protected (hardened) versions of the software and generates accurate overhead reports and fault coverage estimations. The advantages of our proposal are illustrated by means of a complex and detailed case study involving a typical embedded application, the AES (Advanced Encryption Standard).

Dynamic multi-resolution spatial object derivation for mobile and WWW applications

Online geographic information systems provide the means to extract a subset of desired spatial information from a larger remote repository. Data retrieved representing real-world geographic phenomena are then manipulated to suit the specific needs of an end-user. Often this extraction requires the derivation of representations of objects specific to a particular resolution or scale from a single original stored version. Currently standard spatial data handling techniques cannot support the multi-resolution representation of such features in a database. In this paper a methodology to store and retrieve versions of spatial objects at, different resolutions with respect to scale using standard database primitives and SQL is presented. The technique involves heavy fragmentation of spatial features that allows dynamic simplification into scale-specific object representations customised to the display resolution of the end-user's device. Experimental results comparing the new approach to traditional R-Tree indexing and external object simplification reveal the former performs notably better for mobile and WWW applications where client-side resources are limited and retrieved data loads are kept relatively small.

Multi-level zero-inflated Poisson regression modelling of correlated count data with excess zeros

Count data with excess zeros relative to a Poisson distribution are common in many biomedical applications. A popular approach to the analysis of such data is to use a zero-inflated Poisson (ZIP) regression model. Often, because of the hierarchical Study design or the data collection procedure, zero-inflation and lack of independence may occur simultaneously, which tender the standard ZIP model inadequate. To account for the preponderance of zero counts and the inherent correlation of observations, a class of multi-level ZIP regression model with random effects is presented. Model fitting is facilitated using an expectation-maximization algorithm, whereas variance components are estimated via residual maximum likelihood estimating equations. A score test for zero-inflation is also presented. The multi-level ZIP model is then generalized to cope with a more complex correlation structure. Application to the analysis of correlated count data from a longitudinal infant feeding study illustrates the usefulness of the approach.

The appraisal and management of multi-storey dwelling blocks using large concrete panel systems

This exploratory study is concerned with the integrated appraisal of multi-storey dwelling blocks which incorporate large concrete panel systems (LPS). The first step was to look at U.K. multi-storey dwelling stock in general, and under the management of Birmingham City Council in particular. The information has been taken from the databases of three departments in the City of Birmingham, and rearranged in a new database using a suite of PC software called `PROXIMA' for clarity and analysis. One hundred of their stock were built large concrete panel system. Thirteen LPS blocks were chosen for the purpose of this study as case-studies depending mainly on the height and age factors of the block. A new integrated appraisal technique has been created for the LPS dwelling blocks, which takes into account the most physical and social factors affecting the condition and acceptability of these blocks. This appraisal technique is built up in a hierarchical form moving from the general approach to particular elements (a tree model). It comprises two main approaches; physical and social. In the physical approach, the building is viewed as a series of manageable elements and sub-elements to cover every single physical or environmental factor of the block, in which the condition of the block is analysed. A quality score system has been developed which depends mainly on the qualitative and quantitative conditions of each category in the appraisal tree model, and leads to physical ranking order of the study blocks. In the social appraisal approach, the residents' satisfaction and attitude toward their multi-storey dwelling block was analysed in relation to: a. biographical and housing related characteristics; and b. social, physical and environmental factors associated with this sort of dwelling, block and estate in general.The random sample consisted of 268 residents living in the 13 case study blocks. Data collected was analysed using frequency counts, percentages, means, standard deviations, Kendall's tue, r-correlation coefficients, t-test, analysis of variance (ANOVA) and multiple regression analysis. The analysis showed a marginally positive satisfaction and attitude towards living in the block. The five most significant factors associated with the residents' satisfaction and attitude in descending order were: the estate, in general; the service categories in the block, including heating system and lift services; vandalism; the neighbours; and the security system of the block. An important attribute of this method, is that it is relatively inexpensive to implement, especially when compared to alternatives adopted by some local authorities and the BRE. It is designed to save time, money and effort, to aid decision making, and to provide ranked priority to the multi-storey dwelling stock, in addition to many other advantages. A series of solution options to the problems of the block was sought for selection and testing before implementation. The traditional solutions have usually resulted in either demolition or costly physical maintenance and social improvement of the blocks. However, a new solution has now emerged, which is particularly suited to structurally sound units. The solution of `re-cycling' might incorporate the reuse of an entire block or part of it, by removing panels, slabs and so forth from the upper floors in order to reconstruct them as low-rise accommodations.

Design of a novel solar thermal collector using a multi-criteria decision-making methodology

Three novel solar thermal collector concepts derived from the Linear Fresnel Reflector (LFR) are developed and evaluated through a multi-criteria decision-making methodology, comprising the following techniques: Quality Function Deployment (QFD), the Analytical Hierarchy Process (AHP) and the Pugh selection matrix. Criteria are specified by technical and customer requirements gathered from Gujarat, India. The concepts are compared to a standard LFR for reference, and as a result, a novel 'Elevation Linear Fresnel Reflector' (ELFR) concept using elevating mirrors is selected. A detailed version of this concept is proposed and compared against two standard LFR configurations, one using constant and the other using variable horizontal mirror spacing. Annual performance is analysed for a typical meteorological year. Financial assessment is made through the construction of a prototype. The novel LFR has an annual optical efficiency of 49% and increases exergy by 13-23%. Operational hours above a target temperature of 300 C are increased by 9-24%. A 17% reduction in land usage is also achievable. However, the ELFR suffers from additional complexity and a 16-28% increase in capital cost. It is concluded that this novel design is particularly promising for industrial applications and locations with restricted land availability or high land costs. The decision analysis methodology adopted is considered to have a wider potential for applications in the fields of renewable energy and sustainable design. © 2013 Elsevier Ltd. All rights reserved.

A modular holistic approach to prosody modelling for Standard Yorùbá speech synthesis

This paper presents a novel prosody model in the context of computer text-to-speech synthesis applications for tone languages. We have demonstrated its applicability using the Standard Yorùbá (SY) language. Our approach is motivated by the theory that abstract and realised forms of various prosody dimensions should be modelled within a modular and unified framework [Coleman, J.S., 1994. Polysyllabic words in the YorkTalk synthesis system. In: Keating, P.A. (Ed.), Phonological Structure and Forms: Papers in Laboratory Phonology III, Cambridge University Press, Cambridge, pp. 293–324]. We have implemented this framework using the Relational Tree (R-Tree) technique. R-Tree is a sophisticated data structure for representing a multi-dimensional waveform in the form of a tree. The underlying assumption of this research is that it is possible to develop a practical prosody model by using appropriate computational tools and techniques which combine acoustic data with an encoding of the phonological and phonetic knowledge provided by experts. To implement the intonation dimension, fuzzy logic based rules were developed using speech data from native speakers of Yorùbá. The Fuzzy Decision Tree (FDT) and the Classification and Regression Tree (CART) techniques were tested in modelling the duration dimension. For practical reasons, we have selected the FDT for implementing the duration dimension of our prosody model. To establish the effectiveness of our prosody model, we have also developed a Stem-ML prosody model for SY. We have performed both quantitative and qualitative evaluations on our implemented prosody models. The results suggest that, although the R-Tree model does not predict the numerical speech prosody data as accurately as the Stem-ML model, it produces synthetic speech prosody with better intelligibility and naturalness. The R-Tree model is particularly suitable for speech prosody modelling for languages with limited language resources and expertise, e.g. African languages. Furthermore, the R-Tree model is easy to implement, interpret and analyse.

Nonlinear speech analysis algorithms mapped to a standard metric achieve clinically useful quantification of average Parkinson's disease symptom severity

The standard reference clinical score quantifying average Parkinson's disease (PD) symptom severity is the Unified Parkinson's Disease Rating Scale (UPDRS). At present, UPDRS is determined by the subjective clinical evaluation of the patient's ability to adequately cope with a range of tasks. In this study, we extend recent findings that UPDRS can be objectively assessed to clinically useful accuracy using simple, self-administered speech tests, without requiring the patient's physical presence in the clinic. We apply a wide range of known speech signal processing algorithms to a large database (approx. 6000 recordings from 42 PD patients, recruited to a six-month, multi-centre trial) and propose a number of novel, nonlinear signal processing algorithms which reveal pathological characteristics in PD more accurately than existing approaches. Robust feature selection algorithms select the optimal subset of these algorithms, which is fed into non-parametric regression and classification algorithms, mapping the signal processing algorithm outputs to UPDRS. We demonstrate rapid, accurate replication of the UPDRS assessment with clinically useful accuracy (about 2 UPDRS points difference from the clinicians' estimates, p < 0.001). This study supports the viability of frequent, remote, cost-effective, objective, accurate UPDRS telemonitoring based on self-administered speech tests. This technology could facilitate large-scale clinical trials into novel PD treatments.

The measurement properties of the menorrhagia multi-attribute quality-of-life scale:a psychometric analysis

Menorrhagia, or heavy menstrual bleeding (HMB), is a common gynaecological condition. As the aim of treatment is to improve women's wellbeing and quality of life (QoL), it is necessary to have effective ways to measure this. This study investigated the reliability and validity of the menorrhagia multi-attribute scale (MMAS), a menorrhagia-specific QoL instrument. Participants (n = 431) completed the MMAS and a battery of other tests as part of the baseline assessment of the ECLIPSE (Effectiveness and Cost-effectiveness of Levonorgestrel-containing Intrauterine system in Primary care against Standard trEatment for menorrhagia) trial. Analyses of their responses suggest that the MMAS has good measurement properties and is therefore an appropriate condition-specific instrument to measure the outcome of treatment for HMB. © 2011 The Authors BJOG An International Journal of Obstetrics and Gynaecology © 2011 RCOG.

Intonation contour realisation for Standard Yorùbá text-to-speech synthesis:a fuzzy computational approach

This paper presents a novel intonation modelling approach and demonstrates its applicability using the Standard Yorùbá language. Our approach is motivated by the theory that abstract and realised forms of intonation and other dimensions of prosody should be modelled within a modular and unified framework. In our model, this framework is implemented using the Relational Tree (R-Tree) technique. The R-Tree is a sophisticated data structure for representing a multi-dimensional waveform in the form of a tree. Our R-Tree for an utterance is generated in two steps. First, the abstract structure of the waveform, called the Skeletal Tree (S-Tree), is generated using tone phonological rules for the target language. Second, the numerical values of the perceptually significant peaks and valleys on the S-Tree are computed using a fuzzy logic based model. The resulting points are then joined by applying interpolation techniques. The actual intonation contour is synthesised by Pitch Synchronous Overlap Technique (PSOLA) using the Praat software. We performed both quantitative and qualitative evaluations of our model. The preliminary results suggest that, although the model does not predict the numerical speech data as accurately as contemporary data-driven approaches, it produces synthetic speech with comparable intelligibility and naturalness. Furthermore, our model is easy to implement, interpret and adapt to other tone languages.

Multi-frequency segmental bio-impedance device:design, development and applications

Bio-impedance analysis (BIA) provides a rapid, non-invasive technique for body composition estimation. BIA offers a convenient alternative to standard techniques such as MRI, CT scan or DEXA scan for selected types of body composition analysis. The accuracy of BIA is limited because it is an indirect method of composition analysis. It relies on linear relationships between measured impedance and morphological parameters such as height and weight to derive estimates. To overcome these underlying limitations of BIA, a multi-frequency segmental bio-impedance device was constructed through a series of iterative enhancements and improvements of existing BIA instrumentation. Key features of the design included an easy to construct current-source and compact PCB design. The final device was trialled with 22 human volunteers and measured impedance was compared against body composition estimates obtained by DEXA scan. This enabled the development of newer techniques to make BIA predictions. To add a ‘visual aspect’ to BIA, volunteers were scanned in 3D using an inexpensive scattered light gadget (Xbox Kinect controller) and 3D volumes of their limbs were compared with BIA measurements to further improve BIA predictions. A three-stage digital filtering scheme was also implemented to enable extraction of heart-rate data from recorded bio-electrical signals. Additionally modifications have been introduced to measure change in bio-impedance with motion, this could be adapted to further improve accuracy and veracity for limb composition analysis. The findings in this thesis aim to give new direction to the prediction of body composition using BIA. The design development and refinement applied to BIA in this research programme suggest new opportunities to enhance the accuracy and clinical utility of BIA for the prediction of body composition analysis. In particular, the use of bio-impedance to predict limb volumes which would provide an additional metric for body composition measurement and help distinguish between fat and muscle content.

Application of the Artificial Intelligence Algorithms for System Analysis of Multi Dimension Physiological Data for Developing Polyparametric Information System of Public Health Diagnostics

The polyparametric intelligence information system for diagnostics human functional state in medicine and public health is developed. The essence of the system consists in polyparametric describing of human functional state with the unified set of physiological parameters and using the polyparametric cognitive model developed as the tool for a system analysis of multitude data and diagnostics of a human functional state. The model is developed on the basis of general principles geometry and symmetry by algorithms of artificial intelligence systems. The architecture of the system is represented. The model allows analyzing traditional signs - absolute values of electrophysiological parameters and new signs generated by the model – relationships of ones. The classification of physiological multidimensional data is made with a transformer of the model. The results are presented to a physician in a form of visual graph – a pattern individual functional state. This graph allows performing clinical syndrome analysis. A level of human functional state is defined in the case of the developed standard (“ideal”) functional state. The complete formalization of results makes it possible to accumulate physiological data and to analyze them by mathematics methods.

A randomised controlled trial of the clinical effectiveness and cost-effectiveness of the levonorgestrel-releasing intrauterine system in primary care against standard treatment for menorrhagia:the ECLIPSE trial

BACKGROUND: Heavy menstrual bleeding (HMB) is a common problem, yet evidence to inform decisions about initial medical treatment is limited. OBJECTIVES: To assess the clinical effectiveness and cost-effectiveness of the levonorgestrel-releasing intrauterine system (LNG-IUS) (Mirena(®), Bayer) compared with usual medical treatment, with exploration of women's perspectives on treatment. DESIGN: A pragmatic, multicentre randomised trial with an economic evaluation and a longitudinal qualitative study. SETTING: Women who presented in primary care. PARTICIPANTS: A total of 571 women with HMB. A purposeful sample of 27 women who were randomised or ineligible owing to treatment preference participated in semistructured face-to-face interviews around 2 and 12 months after commencing treatment. INTERVENTIONS: LNG-IUS or usual medical treatment (tranexamic acid, mefenamic acid, combined oestrogen-progestogen or progesterone alone). Women could subsequently swap or cease their allocated treatment. OUTCOME MEASURES: The primary outcome was the patient-reported score on the Menorrhagia Multi-Attribute Scale (MMAS) assessed over a 2-year period and then again at 5 years. Secondary outcomes included general quality of life (QoL), sexual activity, surgical intervention and safety. Data were analysed using iterative constant comparison. A state transition model-based cost-utility analysis was undertaken alongside the randomised trial. Quality-adjusted life-years (QALYs) were derived from the European Quality of Life-5 Dimensions (EQ-5D) and the Short Form questionnaire-6 Dimensions (SF-6D). The intention-to-treat analyses were reported as cost per QALY gained. Uncertainty was explored by conducting both deterministic and probabilistic sensitivity analyses. RESULTS: The MMAS total scores improved significantly in both groups at all time points, but were significantly greater for the LNG-IUS than for usual treatment [mean difference over 2 years was 13.4 points, 95% confidence interval (CI) 9.9 to 16.9 points; p < 0.001]. However, this difference between groups was reduced and no longer significant by 5 years (mean difference in scores 3.9 points, 95% CI -0.6 to 8.3 points; p = 0.09). By 5 years, only 47% of women had a LNG-IUS in place and 15% were still taking usual medical treatment. Five-year surgery rates were low, at 20%, and were similar, irrespective of initial treatments. There were no significant differences in serious adverse events between groups. Using the EQ-5D, at 2 years, the relative cost-effectiveness of the LNG-IUS compared with usual medical treatment was £1600 per QALY, which by 5 years was reduced to £114 per QALY. Using the SF-6D, usual medical treatment dominates the LNG-IUS. The qualitative findings show that women's experiences and expectations of medical treatments for HMB vary considerably and change over time. Women had high expectations of a prompt effect from medical treatments. CONCLUSIONS: The LNG-IUS, compared with usual medical therapies, resulted in greater improvement over 2 years in women's assessments of the effect of HMB on their daily routine, including work, social and family life, and psychological and physical well-being. At 5 years, the differences were no longer significant. A similar low proportion of women required surgical intervention in both groups. The LNG-IUS is cost-effective in both the short and medium term, using the method generally recommended by the National Institute for Health and Care Excellence. Using the alternative measures to value QoL will have a considerable impact on cost-effectiveness decisions. It will be important to explore the clinical and health-care trajectories of the ECLIPSE (clinical effectiveness and cost-effectiveness of levonorgestrel-releasing intrauterine system in primary care against standard treatment for menorrhagia) trial participants to 10 years, by which time half of the cohort will have reached menopause. TRIAL REGISTRATION: Current Controlled Trials ISRCTN86566246. FUNDING: This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 19, No. 88. See the NIHR Journals Library website for further project information.

Corporate cash-pool valuation in a multi-firm context: a closed formula

Following our earlier paper on the subject, we present a general closed formula to value the interest savings due to a multi-firm cash-pool system. Assuming normal distribution of the accounts the total savings can be expressed as the product of three independent factors representing the interest spread, the number and the correlation of the firms, and the time-dependent distribution of the cash accounts. We derive analytic results for two special processes one characterizing the initial build-up period and the other describing the mature period. The value gained in the stationary system can be thought of as the interest, paid at the net interest spread rate on the standard deviation of the account. We show that pooling has substantial value already in the transient period. In order to increase the practical relevance of our analysis we discuss possible extensions of our model and we show how real option pricing technics can be applied here.