A novel method for quantifying the criticality and vulnerability of the components of railway bridges

Conditions of bridges deteriorate with age, due to different critical factors including, changes in loading, fatigue, environmental effects and natural events. In order to rate a network of bridges, based on their structural condition, the condition of the components of a bridge and their effects on behaviour of the bridge should be reliably estimated. In this paper, a new method for quantifying the criticality and vulnerability of the components of the railway bridges in a network will be introduced. The type of structural analyses for identifying the criticality of the components for carrying train loads will be determined. In addition to that, the analytical methods for identifying the vulnerability of the components to natural events whose probability of occurrence is important, such as, flood, wind, earthquake and collision will be determined. In order to maintain the practicality of this method to be applied to a network of thousands of railway bridges, the simplicity of structural analysis has been taken into account. Demand by capacity ratios of the components at both safety and serviceability condition states as well as weighting factors used in current bridge management systems (BMS) are taken into consideration. It will be explained what types of information related to the structural condition of a bridge is required to be obtained, recorded and analysed. The authors of this paper will use this method in a new rating system introduced previously. Enhancing accuracy and reliability of evaluating and predicting the vulnerability of railway bridges to environmental effects and natural events will be the significant achievement of this research.

Robust Reentry Guidance of a Reusable Launch Vehicle Using Model Predictive Static Programming

A robust suboptimal reentry guidance scheme is presented for a reusable launch vehicle using the recently developed, computationally efficient model predictive static programming. The formulation uses the nonlinear vehicle dynamics with a spherical and rotating Earth, hard constraints for desired terminal conditions, and an innovative cost function having several components with associated weighting factors that can account for path and control constraints in a soft constraint manner, thereby leading to smooth solutions of the guidance parameters. The proposed guidance essentially shapes the trajectory of the vehicle by computing the necessary angle of attack and bank angle that the vehicle should execute. The path constraints are the structural load constraint, thermal load constraint, bounds on the angle of attack, and bounds on the bank angle. In addition, the terminal constraints include the three-dimensional position and velocity vector components at the end of the reentry. Whereas the angle-of-attack command is generated directly, the bank angle command is generated by first generating the required heading angle history and then using it in a dynamic inversion loop considering the heading angle dynamics. Such a two-loop synthesis of bank angle leads to better management of the vehicle trajectory and avoids mathematical complexity as well. Moreover, all bank angle maneuvers have been confined to the middle of the trajectory and the vehicle ends the reentry segment with near-zero bank angle, which is quite desirable. It has also been demonstrated that the proposed guidance has sufficient robustness for state perturbations as well as parametric uncertainties in the model.

基于多特征模糊聚类的图像融合方法

首先利用模糊C-均值聚类算法在多特征形成的特征空间上对图像进行区域分割,并在此基础上对区域进行多尺度小波分解;然后利用柯西函数构造区域的模糊相似度,应用模糊相似度及区域信息量构造加权因子,从而得到融合图像的小波系数;最后利用小波逆变换得到融合图像·采用均方根误差、峰值信噪比、熵、交叉熵和互信息5种准则评价融合算法的性能·实验结果表明,文中方法具有良好的融合特性·

3D die shape optimisation for net-shape forging of aerofoil blades

This paper reports on work in developing a finite element (FE) based die shape optimisation for net-shape forging of 3D aerofoil blades for aeroengine applications. Quantitative representations of aerofoil forging tolerances were established to provide a correlation between conventional dimensional and shape specifications in forging production and those quantified in FE simulation. A new direct compensation method was proposed, employing variable weighting factors to minimise the total forging tolerances in forging optimisation computations. A surface approximation using a B-spline surface was also developed to ensure improved die surface quality for die shape representation and design. For a Ni-alloy blade test case, substantial reduction in dimensional and shape tolerances was achieved using the developed die shape optimisation system.

Zero attracting recursive least squares algorithms

The l1-norm sparsity constraint is a widely used technique for constructing sparse models. In this contribution, two zero-attracting recursive least squares algorithms, referred to as ZA-RLS-I and ZA-RLS-II, are derived by employing the l1-norm of parameter vector constraint to facilitate the model sparsity. In order to achieve a closed-form solution, the l1-norm of the parameter vector is approximated by an adaptively weighted l2-norm, in which the weighting factors are set as the inversion of the associated l1-norm of parameter estimates that are readily available in the adaptive learning environment. ZA-RLS-II is computationally more efficient than ZA-RLS-I by exploiting the known results from linear algebra as well as the sparsity of the system. The proposed algorithms are proven to converge, and adaptive sparse channel estimation is used to demonstrate the effectiveness of the proposed approach.

Design method for solar heating systems in combination with pellet boilers/stoves

In this study an optimization method for the design of combined solar and pellet heating systems is presented and evaluated. The paper describes the steps of the method by applying it for an example of system. The objective of the optimization was to find the design parameters that give the lowest auxiliary energy (pellet fuel + auxiliary electricity) and carbon monoxide (CO) emissions for a system with a typical load, a single family house in Sweden. Weighting factors have been used for the auxiliary energy use and CO emissions to give a combined target function. Different weighting factors were tested. The results show that extreme weighting factors lead to their own minima. However, it was possible to find factors that ensure low values for both auxiliary energy and CO emissions.

Using an IDMI methodology to make multi-criteria decisions

Multi-criteria decisions usually require measurement or evaluation of performance in different units and their mix by application of weighting factors. This approach leads to potential manipulation of the results as a direct consequence of the applied weightings. In this paper a mechanism has been proposed to overcome this problem. It is known as the : Interlink Decision Making Index (IDMI) and has all the desired features: simple, interlink (all criteria) and automatically and quantified influence of critical criteria (i.e. no human weighting needed). The IDMI is capable of reflecting the total merits of a particular option once the normal decision making criteria and (up to two) critical criteria (CC) have been chosen. Then, without arbitrarily weighting criteria, comparison and selection of the best possible option can be made. Simple software has been developed to do this numerical transfer and graphic presentation. Two hypothetical examples are presented in the paper to demonstrate the application of the IDMI concept and its advantages over the traditional "tabular and weighting method" in the decision making process.

Assessment of wilderness quality using the analytic hierarchy process

Wilderness is a unique environmental resource that provides a multitude of use and non-use benefits. The use and management of wilderness depend on the assessment of wilderness quality. Current wilderness assessment in Australia is based on two broad criteria, the remoteness and naturalness of the wilderness, determined using geographic information systems. This paper discusses a complementary assessment method using the Analytic Hierarchy Process (AHP). The AHP can be used to incorporate additional criteria, such as social and cultural criteria, to improve the quality of wilderness assessment. It provides a flexible and compatible method for large-scale wilderness assessments with multiple criteria. The weighting factors for the different criteria can be obtained from expert panels and focus groups.

Image fusion metrics : evolution in a nutshell

Image fusion process merges two images into a single more informative image. Objective image fusion per- formance metrics rely primarily on measuring the amount of information transferred from each source image into the fused image. Objective image fusion metrics have evolved from image processing dissimilarity metrics. Additionally, researchers have developed many additions to image dissimilarity metrics in order to better value the local fusion worthy features in source images. This paper studies the evolution of objective image fusion performance metrics and their subjective and objective validation. It describes how a fusion performance metric evolves starting with image dissimilarity metrics, its realization into image fusion contexts, its localized weighting factors and the validation process.

Convergent validity of a novel method for quantifying rowing training loads

Elite rowers complete rowing-specific and non-specific training, incorporating continuous and interval-like efforts spanning the intensity spectrum. However, established training load measures are unsuitable for use in some modes and intensities. Consequently, a new measure known as the T2minute method was created. The method quantifies load as the time spent in a range of training zones (time-in-zone), multiplied by intensity- and mode-specific weighting factors that scale the relative stress of different intensities and modes to the demands of on-water rowing. The purpose of this study was to examine the convergent validity of the T2minute method with Banister's training impulse (TRIMP), Lucia's TRIMP and Session-RPE when quantifying elite rowing training. Fourteen elite rowers (12 males, 2 females) were monitored during four weeks of routine training. Unadjusted T2minute loads (using coaches' estimates of time-in-zone) demonstrated moderate-to-strong correlations with Banister's TRIMP, Lucia's TRIMP and Session-RPE (rho: 0.58, 0.55 and 0.42, respectively). Adjusting T2minute loads by using actual time-in-zone data resulted in stronger correlations between the T2minute method and Banister's TRIMP and Lucia's TRIMP (rho: 0.85 and 0.81, respectively). The T2minute method is an appropriate in-field measure of elite rowing training loads, particularly when actual time-in-zone values are used to quantify load.

Dosimetry and cost of imaging osseointegrated implants with film-based and computed tomography

Thermoluminescent dosimeters were used to measure radiation doses at craniofacial sites in a tissue-equivalent phantom during film-based multidirectional tomography with the Tomax Ultrascan (Incubation Industries, Ivyland, Pa.) and during computed tomography with the Elscint Excel 2400 (Elscint Corp., Tel Aviv, Israel). Mean absorbed doses for presurgical mandibular and maxillary canine and molar implant assessments were converted to equivalent doses, which were then multipied by published weighting factors and summed to give effective doses. The computed tomgraphy device consistently delivered higher doses than the Tomax Ultrascan to all anatomic locations; the differences were most pronounced when only one or two implant sites were evaluated. The reasons for the dose disparities are considered both anatomically and procedurally. A survey of examination cost revealed film-based multidirectional tomography to be less expensive than computed tomography.

An unproblematic method to solve economic and emission dispatch

This paper proposes a method to determine the output of all online units with minimum total cost when the amount of emission is reasonable. A joint economic and emission dispatch is proposed in order to get a significant compromise between costs and emission such that real power supply-demand equilibrium is satisfied. In order to have a meaningful compromise between costs and emission in the problem formulation, two variables are used, weighting factor and price penalty factor. A case study comprising of a 3-unit power system is employed, where various demand is used. Results for the test system indicate the fastness and effectiveness of proposed method. © 2011 IEEE.

Community managed rural water supply systems in the Dominican Republic : assessment of sustainability of systems built by the National Institute of Potable Water and Peace Corps, Dominican Republic

In the Dominican Republic economic growth in the past twenty years has not yielded sufficient improvement in access to drinking water services, especially in rural areas where 1.5 million people do not have access to an improved water source (WHO, 2006). Worldwide, strategic development planning in the rural water sector has focused on participatory processes and the use of demand filters to ensure that service levels match community commitment to post-project operation and maintenance. However studies have concluded that an alarmingly high percentage of drinking water systems (20-50%) do not provide service at the design levels and/or fail altogether (up to 90%): BNWP (2009), Annis (2006), and Reents (2003). World Bank, USAID, NGOs, and private consultants have invested significant resources in an effort to determine what components make up an “enabling environment” for sustainable community management of rural water systems (RWS). Research has identified an array of critical factors, internal and external to the community, which affect long term sustainability of water services. Different frameworks have been proposed in order to better understand the linkages between individual factors and sustainability of service. This research proposes a Sustainability Analysis Tool to evaluate the sustainability of RWS, adapted from previous relevant work in the field to reflect the realities in the Dominican Republic. It can be used as a diagnostic tool for government entities and development organizations to characterize the needs of specific communities and identify weaknesses in existing training regimes or support mechanisms. The framework utilizes eight indicators in three categories (Organization/Management, Financial Administration, and Technical Service). Nineteen independent variables are measured resulting in a score of sustainability likely (SL), possible (SP), or unlikely (SU) for each of the eight indicators. Thresholds are based upon benchmarks from the DR and around the world, primary data collected during the research, and the author’s 32 months of field experience. A final sustainability score is calculated using weighting factors for each indicator, derived from Lockwood (2003). The framework was tested using a statistically representative geographically stratified random sample of 61 water systems built in the DR by initiatives of the National Institute of Potable Water (INAPA) and Peace Corps. The results concluded that 23% of sample systems are likely to be sustainable in the long term, 59% are possibly sustainable, and for 18% it is unlikely that the community will be able to overcome any significant challenge. Communities that were scored as unlikely sustainable perform poorly in participation, financial durability, and governance while the highest scores were for system function and repair service. The Sustainability Analysis Tool results are verified by INAPA and PC reports, evaluations, and database information, as well as, field observations and primary data collected during the surveys. Future research will analyze the nature and magnitude of relationships between key factors and the sustainability score defined by the tool. Factors include: gender participation, legal status of water committees, plumber/operator remuneration, demand responsiveness, post construction support methodologies, and project design criteria.

A novel clinical scoring system for outcome prediction in dogs with acute kidney injury managed by hemodialysis.

BACKGROUND No reliable tool to predict outcome of acute kidney injury (AKI) exists. HYPOTHESIS A statistically derived scoring system can accurately predict outcome in dogs with AKI managed with hemodialysis. ANIMALS One hundred and eighty-two client-owned dogs with AKI. METHODS Logistic regression analyses were performed initially on clinical variables available on the 1st day of hospitalization for relevance to outcome. Variables with P< or = .1 were considered for further analyses. Continuous variables outside the reference range were divided into quartiles to yield quartile-specific odds ratios (ORs) for survival. Models were developed by incorporating weighting factors assigned to each quartile based on the OR, using either the integer value of the OR (Model A) or the exact OR (Models B or C, when the etiology was known). A predictive score for each model was calculated for each dog by summing all weighting factors. In Model D, actual values for continuous variables were used in a logistic regression model. Receiver-operating curve analyses were performed to assess sensitivities, specificities, and optimal cutoff points for all models. RESULTS Higher scores were associated with decreased probability of survival (P < .001). Models A, B, C, and D correctly classified outcomes in 81, 83, 87, and 76% of cases, respectively, and optimal sensitivities/specificities were 77/85, 81/85, 83/90 and 92/61%, respectively. CONCLUSIONS AND CLINICAL RELEVANCE The models allowed outcome prediction that corresponded with actual outcome in our cohort. However, each model should be validated further in independent cohorts. The models may also be useful to assess AKI severity.

Sustainable materials: The business case for green chemistry design practices

Product manufacturers face increasing environmental and human health regulations with certain regulations targeting specific chemicals of concern that must be removed from the supply chain. This study examines a green chemistry approach to choosing between flame retardant alternatives in electronic products during the design phase of product development. An aggregated score based on five criteria was generated for each flame retardant. To address subjectivity and cognitive bias concerns probabilistic sensitivity analysis was applied to the weighting factors used to generate the scores to examine the reliability of the results. The highest scoring flame retardants based on the comprehensive green chemistry approach were different from the flame retardants chosen using cost as the primary selection criteria.