Search

Wireless Sensor Networks (WSNs) are becoming ubiquitous in everyday life due to their applications in weather forecasting, surveillance, implantable sensors for health monitoring and other plethora of applications. WSN is equipped with hundreds and thousands of small sensor nodes. As the size of a sensor node decreases, critical issues such as limited energy, computation time and limited memory become even more highlighted. In such a case, network lifetime mainly depends on efficient use of available resources. Organizing nearby nodes into clusters make it convenient to efficiently manage each cluster as well as the overall network. In this paper, we extend our previous work of grid-based hybrid network deployment approach, in which merge and split technique has been proposed to construct network topology. Constructing topology through our proposed technique, in this paper we have used analytical network process (ANP) model for cluster head selection in WSN. Five distinct parameters: distance from nodes (DistNode), residual energy level (REL), distance from centroid (DistCent), number of times the node has been selected as cluster head (TCH) and merged node (MN) are considered for CH selection. The problem of CH selection based on these parameters is tackled as a multi criteria decision system, for which ANP method is used for optimum cluster head selection. Main contribution of this work is to check the applicability of ANP model for cluster head selection in WSN. In addition, sensitivity analysis is carried out to check the stability of alternatives (available candidate nodes) and their ranking for different scenarios. The simulation results show that the proposed method outperforms existing energy efficient clustering protocols in terms of optimum CH selection and minimizing CH reselection process that results in extending overall network lifetime. This paper analyzes that ANP method used for CH selection with better understanding of the dependencies of different components involved in the evaluation process. [ABSTRACT FROM AUTHOR]

This paper proposes a new approach to study the sensitivity analysis in the network flow problems, in particular, the minimum spanning tree and shortest path problems. In a sensitivity analysis, one looks for the amount of changes in the edges' weights, number of edges or number of vertices such that the optimal solution, i.e., the minimum spanning tree or shortest path does not change. We introduce a novel approach, and develop associated equations and mathematics. We discuss two illustrative examples to show the applicability of the proposed approach. [ABSTRACT FROM AUTHOR]

Pallet is a very important innovation in logistics industry. Pallets are so widely used that we can find them in nearly every logistical operation scenario. In order to manage pallets efficiently, researchers have developed several pallet management strategies (PMS). The most common and widely accepted PMS includes extensive management of pallets (EMP), transfer of pallet's ownership (TPO), and pallet rent (PR). This paper addresses mainly on how to help pallet managers choose a certain kind of PMS from the perspective of supply chain cost. Firstly, cost models of three kinds of PMS are presented. Secondly, all parameters involved in the models are valued based on data that is collected from industry survey. The results show that the cost of PR is constantly lower than EMP, and also lower than TPO when the operation period is no more than 37 months. Finally, the effect of several important parameters on the cost is studied by sensitivity analysis. The selection strategies of PMS are proposed based on the results. [ABSTRACT FROM AUTHOR]

Systems biology models are used to understand complex biological and physiological systems. Interpretation of these models is an important part of developing this understanding. These models are often fit to experimental data in order to understand how the system has produced various phenomena or behaviour that are seen in the data. In this paper, we have outlined a framework that can be used to perform Bayesian analysis of complex systems biology models. In particular, we have focussed on analysing a systems biology of the brain using both simulated and measured data. By using a combination of sensitivity analysis and approximate Bayesian computation, we have shown that it is possible to obtain distributions of parameters that can better guard against misinterpretation of results, as compared to a maximum likelihood estimate based approach. This is done through analysis of simulated and experimental data. NIRS measurements were simulated using the same simulated systemic input data for the model in a ‘healthy’ and ‘impaired’ state. By analysing both of these datasets, we show that different parameter spaces can be distinguished and compared between different physiological states or conditions. Finally, we analyse experimental data using the new Bayesian framework and the previous maximum likelihood estimate approach, showing that the Bayesian approach provides a more complete understanding of the parameter space. [ABSTRACT FROM AUTHOR]

An important segment of the reliability-based optimization problems is to get access to the sensitivity derivatives. However, since the failure probability is not a closed-form function of the input variables, the derivatives are not explicitly computable and rather require a full reliability analysis which is computationally expensive. In this paper, a step-by-step algorithm has been presented to calculate the derivatives of the probability of failure and safety index with respect to the input parameters based on the advanced first-order second-moment (AFOSM) reliability method. The proposed algorithm is then implemented in a spreadsheet using Visual Basic for Application (VBA) programming language. Two geotechnical and structural examples are then presented to examine the program and describe the modeling procedure. The robustness of the proposed method is examined using a Gaussian random perturbation. The capability of the proposed method in the calculation of the sensitivity derivatives of the model uncertainty is explained in a separate section. Finally, the proposed model has been compared to the forward finite difference (FFD) method and the results are validated. [ABSTRACT FROM AUTHOR]

Abstract The sensitivity conjecture proposed by Nisan and Szegedy in 1994, which asserts that for any Boolean function, its sensitivity complexity is polynomially related to the block sensitivity complexity, is one of the most important and challenging problems in the study of decision tree complexity. Despite a lot of efforts, the best known upper bound of block sensitivity, as well as the certificate complexity, is still exponential in terms of sensitivity. In this paper, we give a better upper bound for certificate complexity and block sensitivity, b s (f) ≤ C (f) ≤ (8 9 + o (1)) s (f) 2 s (f) − 1 , where b s (f) , C (f) and s (f) are the block sensitivity, certificate complexity and sensitivity, respectively. The proof is based on a deep investigation on the structure of the sensitivity graph. We also provide a tighter relationship between the 0-certificate complexity C 0 (f) and 0-sensitivity s 0 (f) for functions with small 1-sensitivity s 1 (f). [ABSTRACT FROM AUTHOR]

Abstract With the increasing use of composite material and external energy dissipation device in civil structures, the classical Rayleigh damping becomes an inappropriate assumption in structural damage identification. In this paper, a parametric sensitivity-based approach is developed to identify the structural damage and damping defect of non-classically damped shear-type building simultaneously. As the preliminary step, the complex eigenvalues and eigenvectors of damaged structure are obtained by a novel identification technique, which decouples the first-order modal analysis equation under physical coordinate so that the complex modal parameters of each mode can be identified independently. Thereafter, by analysing the sensitivities of complex eigenparameter, non-linear least square method is applied to identify the locations and magnitudes of damage with respect to stiffness reduction and damping defect. The proposed identification approach is illustrated by identifying the damage in a numerical five-storey shear building. The identification results show that the proposed approach can locate and quantify the stiffness reductions satisfactorily even when measurement noise is taken into account. However, in order to quantify the damping defects consistently, their locations need to be known as a priori. Highlights • A novel complex eigenparameter identification approach under state-space coordinate. • Damage identification on non-proportionally damped shear-type building. • Identify the stiffness reduction and damping defect simultaneously. • Identify the design parameters which locate and quantify the damages. • Numerical validation on a five-storey shear building by considering measurement noise. [ABSTRACT FROM AUTHOR]

Background: Well-constructed systematic reviews and meta-analyses are key tools in evidenced-based healthcare. However, a common problem with performing a meta-analysis is missing data, such as standard deviations (SD). An increasing number of methods are utilised to calculate or impute missing SDs, allowing these studies to be included in analyses. The aim of this review was to investigate the methods reported and utilised for handling missing change SDs in meta-analyses, using the topic of exercise therapy in heart failure patients as a model. Methods: A systematic search of PubMed, EMBASE and Cochrane Library from 1 January 2014 to 31st March 2018 was conducted for meta-analyses of exercise based trials in heart failure. Studies were eligible to be included if they performed a meta-analysis of change in exercise capacity in heart failure patients after a training intervention. Results: Twenty two publications performed a meta-analysis on the effect of exercise therapy on exercise capacity in heart failure patients. Eleven (50%) publications did not directly report the approach for dealing with missing change SDs. Approaches reported and utilised to deal with missing change SDs included imputation, actual and approximate algebraic recalculation using study level summary statistics and exclusion of studies. Conclusion: Change SDs are often not reported in trial papers and while in the first instance meta-analysts should attempt to obtain missing data from trial authors, this information is frequently not forthcoming. Meta-analysts are then forced to make a decision on how these trials and missing data are to be handled. Whilst not one approach is favoured for dealing with this matter, authors need to clearly report the approach to be utilised for missing change SDs. Where change SDs are imputed meta-analyst are encouraged to explore several options and have a sound rationale as to the choice, and where data is imputed, sensitivity analysis should be conducted. [ABSTRACT FROM AUTHOR]

New rapid diagnostic tests (RDTs) for screening human African trypanosomiasis (HAT) have been introduced as alternatives to the card agglutination test for trypanosomiasis (CATT). One brand of RDT, the SD BIOLINE HAT RDT has been shown to have lower specificity but higher sensitivity than CATT, so to make a rational choice between screening strategies, a cost-effectiveness analysis is a key element. In this paper we estimate the relative cost-effectiveness of CATT and the RDT when implemented in the Democratic Republic of the Congo (DRC). Data on the epidemiological parameters and costs were collected as part of a larger study. These data were used to model three different diagnostic algorithms in mobile teams and fixed health facilities, and the relative cost-effectiveness was measured as the average cost per case diagnosed. In both fixed facilities and mobile teams, screening of participants using the SD BIOLINE HAT RDT followed by parasitological confirmation had a lower cost-effectiveness ratio than in algorithms using CATT. Algorithms using the RDT were cheaper by 112.54 (33.2%) and 88.54 (32.92%) US dollars per case diagnosed in mobile teams and fixed health facilities respectively, when compared with algorithms using CATT. Sensitivity analysis demonstrated that these conclusions were robust to a number of assumptions, and that the results can be scaled to smaller or larger facilities, and a range of prevalences. The RDT was the most cost-effective screening test in all realistic scenarios and detected more cases than CATT. Thus, on this basis, the SD BIOLINE HAT RDT could be considered as the most cost-effective option for use in routine screening for HAT in the DRC. [ABSTRACT FROM AUTHOR]

In this paper, a support vector machine (SVM) model which can be used to predict the compressive strength of mortars exposed to sulfate attack was established. An accelerated corrosion test was applied to collect compressive strength data. For predicting the compressive strength of mortars, a total of 638 data samples obtained from experiment was chosen as a dataset to establish a SVM model. The values of the coefficient of determination, the mean absolute error, the mean absolute percentage error and the root mean square error were used for evaluating the predictive accuracy. The main factors affecting the predicted compressive strength were obtained by sensitivity analysis. A SVM model was calibrated, validated, and finally established. Moreover, the performance of the SVM model was compared to an artificial neural network (ANN) model. Results show that the prediction values from the SVM model were close to the experimental values; the main factors sensitive to concrete compressive strength were exposure time, water-cement ratio and sulfate ions; the performance of the SVM model was better than the ANN model. The SVM model developed in this study can be potentially used for predicting the compressive strength of cement-based materials servicing in harsh environments. [ABSTRACT FROM AUTHOR]

This paper focuses on the development of a method for road network vulnerability analysis, from the perspective of capacity degradation, which seeks to identify the critical infrastructures in the road network and the operational performance of the whole traffic system. This research involves defining the traffic utility index and modeling vulnerability of road segment, route, OD (Origin Destination) pair and road network. Meanwhile, sensitivity analysis method is utilized to calculate the change of traffic utility index due to capacity degradation. This method, compared to traditional traffic assignment, can improve calculation efficiency and make the application of vulnerability analysis to large actual road network possible. Finally, all the above models and calculation method is applied to actual road network evaluation to verify its efficiency and utility. This approach can be used as a decision-supporting tool for evaluating the performance of road network and identifying critical infrastructures in transportation planning and management, especially in the resource allocation for mitigation and recovery. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a linear photometer circuit based on robust feedback compensation is presented. Here, the photodiode was modelled as a dynamic system and its mathematical model was obtained from the well-known equivalent circuit for a photodiode reported in scientific literature. Next, in order to make the output of the system robust against uncertainties and the inevitable disturbances that corrupt the response of the photometer circuit, a robust feedback controller was designed. Finally, the robust photometer circuit presented in this paper was compared against a conventional photometer circuit based on a transimpedance amplifier. The results of comparing the aforementioned photometers showed that the photometer based on robust control techniques is superior to the one based on the conventional design. The linear robust photometer circuit presented in this paper was used for making measurements of light at 670nm, its temperature coefficient was very low, and very high sensitivity and linearity characteristics were achieved. [Copyright &y& Elsevier]

Abstract: In this paper, using proximal-point mapping technique of P-η-accretive mapping and the property of the fixed-point set of set-valued contractive mappings, we study the behavior and sensitivity analysis of the solution set of a parametric generalized implicit quasi-variational-like inclusion involving P-η-accretive mapping in real uniformly smooth Banach space. Further, under suitable conditions, we discuss the Lipschitz continuity of the solution set with respect to the parameter. The technique and results presented in this paper can be viewed as extension of the techniques and corresponding results given in [R.P. Agarwal, Y.-J. Cho, N.-J. Huang, Sensitivity analysis for strongly nonlinear quasi-variational inclusions, Appl. Math. Lett. 13 (2002) 19–24; S. Dafermos, Sensitivity analysis in variational inequalities, Math. Oper. Res. 13 (1988) 421–434; X.-P. Ding, Sensitivity analysis for generalized nonlinear implicit quasi-variational inclusions, Appl. Math. Lett. 17 (2) (2004) 225–235; X.-P. Ding, Parametric completely generalized mixed implicit quasi-variational inclusions involving h-maximal monotone mappings, J. Comput. Appl. Math. 182 (2) (2005) 252–269; X.-P. Ding, C.L. Luo, On parametric generalized quasi-variational inequalities, J. Optim. Theory Appl. 100 (1999) 195–205; Z. Liu, L. Debnath, S.M. Kang, J.S. Ume, Sensitivity analysis for parametric completely generalized nonlinear implicit quasi-variational inclusions, J. Math. Anal. Appl. 277 (1) (2003) 142–154; R.N. Mukherjee, H.L. Verma, Sensitivity analysis of generalized variational inequalities, J. Math. Anal. Appl. 167 (1992) 299–304; M.A. Noor, Sensitivity analysis framework for general quasi-variational inclusions, Comput. Math. Appl. 44 (2002) 1175–1181; M.A. Noor, Sensitivity analysis for quasivariational inclusions, J. Math. Anal. Appl. 236 (1999) 290–299; J.Y. Park, J.U. Jeong, Parametric generalized mixed variational inequalities, Appl. Math. Lett. 17 (2004) 43–48]. [Copyright &y& Elsevier]

A sufficient optimality criterion for linearly-constrained concave minimization problems is given in this paper. Our optimally criterion is based on the sensitivity analysis of the relaxed linear programming Problem. The main result is similar to that of Phillips and Rosen (Ref. 1); however, our proofs are simpler and constructive. In the Phillip and Rosen paper (Ref.1), they derived a sufficient optimality criterion for a slightly different linearly-constrained concave minimization problem using exponentially many linear programming problems. We introduce special test points and, using these for several cases, we are able to show optimally of the current basic solution. The sufficient optimality criterion described in this paper can be used as a stopping criterion for branch-and-bound algorithm developed for linearly-constrained concave minimization problems. [ABSTRACT FROM AUTHOR]

Methods for choosing an appropriate sample size in animal experiments have received much attention in the statistical and biological literature. Due to ethical constraints the number of animals used is always reduced where possible. However, as the number of animals decreases so the risk of obtaining inconclusive results increases. By using a more efficient experimental design we can, for a given number of animals, reduce this risk. In this paper two popular cases are considered, where planned comparisons are made to compare treatments back to control and when researchers plan to make all pairwise comparisons. By using theoretical and empirical techniques we show that for studies where all pairwise comparisons are made the traditional balanced design, as suggested in the literature, maximises sensitivity. For studies that involve planned comparisons of the treatment groups back to the control group, which are inherently more sensitive due to the reduced multiple testing burden, the sensitivity is maximised by increasing the number of animals in the control group while decreasing the number in the treated groups. [ABSTRACT FROM AUTHOR]

The zero propellant maneuver (ZPM) is an advanced space station, large angle attitude maneuver technique, using only control momentum gyroscopes (CMGs). Path planning is the key to success, and this paper studies the associated multi-objective optimization problem. Three types of maneuver optimal control problem are formulated: (i) momentum-optimal, (ii) time-optimal, and (iii) energy-optimal. A sensitivity analysis approach is used to study the Pareto optimal front and allows the tradeoffs between the performance indices to be investigated. For example, it is proved that the minimum peak momentum decreases as the maneuver time increases, and the minimum maneuver energy decreases if a larger momentum is available from the CMGs. The analysis is verified and complemented by the numerical computations. Among the three types of ZPM paths, the momentum-optimal solution and the time-optimal solution generally possess the same structure, and they are singular. The energy-optimal solution saves significant energy, while generally maintaining a smooth control profile. [ABSTRACT FROM AUTHOR]

Heart rate variability (HRV) analysis has quantified the functioning of the autonomic regulation of the heart and heart's ability to respond. However, majority of studies on HRV report several differences between patients with congestive heart failure (CHF) and healthy subjects, such as time-domain, frequency domain and nonlinear HRV measures. In the paper, we mainly presented a new approach to detect congestive heart failure (CHF) based on combination support vector machine (SVM) and three nonstandard heart rate variability (HRV) measures (e.g. SUM_TD, SUM_FD and SUM_IE). The CHF classification model was presented by using SVM classifier with the combination SUM_TD and SUM_FD. In the analysis performed, we found that the CHF classification algorithm could obtain the best performance with the CHF classification accuracy, sensitivity and specificity of 100%, 100%, 100%, respectively. [ABSTRACT FROM AUTHOR]

As a performance measure for a prediction model, the area under the receiver operating characteristic curve (AUC) is insensitive to the addition of strong markers. A number of measures sensitive to performance change have recently been proposed; however, these relative-performance measures may lead to self-contradictory conclusions. This paper examines alternative performance measures for prediction models: the Lorenz curve-based Gini and Pietra indices, and a standardized version of the Brier score, the scaled Brier. Computer simulations are performed in order to study the sensitivity of these measures to performance change when a new marker is added to a baseline model. When the discrimination power of the added marker is concentrated in the gray zone of the baseline model, the AUC and the Gini show minimal performance improvements. The Pietra and the scaled Brier show more significant improvements in the same situation, comparatively. The Pietra and the scaled Brier indices are therefore recommended for prediction model performance measurement, in light of their ease of interpretation, clinical relevance and sensitivity to gray-zone resolving markers. [ABSTRACT FROM AUTHOR]

Pedestrian movements are the consequence of several complex and stochastic facts. The modelling of pedestrian movements and the ability to predict the travel time are useful for evaluating the performance of a pedestrian facility. However, only a few studies can be found that incorporate the design of the facility, local pedestrian body dimensions, the delay experienced by the pedestrians, and level of service to the pedestrian movements. In this paper, a queuing based analytical model is developed as a function of relevant determinants and functional factors to predict the travel time on pedestrian facilities. The model can be used to assess the overall serving rate or performance of a facility layout and correlate it to the level of service that is possible to provide the pedestrians. It has also the ability to provide a clear suggestion on the designing and sizing of pedestrian facilities. The model is empirically validated and is found to be a robust tool to understand how well a particular walking facility makes possible comfort and convenient pedestrian movements. The sensitivity analysis is also performed to see the impact of some crucial parameters of the developed model on the performance of pedestrian facilities. [ABSTRACT FROM AUTHOR]

Consider the surjective, continuous map ƒ : X → X and the continuous map f of K(X) induced by ƒ, where ƒ is a compact metric space and K(X) is the space of all nonempty compact subsets of ƒ endowed with the Hausdorff metric. In this paper, we give a short proof that if ƒ is Li-Yoke sensitive, then ƒ is Li-Yorke sensitive. Furthermore, we give an example showing that Li-Yorke sensitivity of ƒ does not imply Li-Yorke sensitivity of ƒ. [ABSTRACT FROM AUTHOR]

Sensitivity analysis plays a key role in structural optimization, but traditional methods of sensitivity analysis in strength and stiffness are time consuming and of high cost. In order to effectively carry out structural optimization of hydraulic press, this paper presents a novel sensitivity analysis method in structural performance of hydraulic press, which saves a great deal of time and design costs. The key dimension parameters of the optimization of design variables, which remarkably impact on the structural performance of hydraulic press, are efficiently selected. The impact order of various sensitivity parameters in strength and stiffness of machine tools is consistent with the sensitivity ranking of regression analysis. The research results provide the basis for the hydraulic machine design and references in research of machine tools and equipment. [ABSTRACT FROM AUTHOR]

Abstract: The shape optimization problem consists in looking for the geometry that minimizes an objective function, like mass or compliance, subject to mechanical constraints. The boundary element method (BEM) is used for the structural analysis. For linear elasticity problems, it needs only a mesh on the boundary of the structure. This characteristic makes the BEM a natural method for shape optimization, since only the boundary is needed to define the optimization problem and to carry out the structural analysis. The simultaneous analysis and design formulation (SAND) for structural optimization considers the state variables as unknowns of the optimization problem and includes the equilibrium equations as equality constraints. In this way, it is not necessary to solve the equilibrium equation per iteration; the equilibrium is only obtained at the end of the optimization process. In this paper, the shape optimization problem is dealt with using the BEM formulation to define a SAND optimization problem that is solved using an interior point algorithm. Numerical results for two-dimensional linear elasticity problems are presented to illustrate the efficacy of the proposed technique. [Copyright &y& Elsevier]

We investigate the sensitivity of the problem of nonorthogonal (matrix) joint diagonalization (NOJD). First, we consider the uniqueness conditions for the problem of exact joint diagonalization (EJD), which is closely related to the issue of uniqueness in tensor decompositions. As a byproduct, we derive the well-known identifiability conditions for independent component analysis (ICA) based on an EJD formulation of ICA. We next introduce some known cost functions for NOJD and derive flows based on these cost functions for NOJD. Then we define and investigate the noise sensitivity of the stationary points of these flows. We show that the condition number of the joint diagonalizer and uniqueness of the joint diagonalizer as measured by modulus of uniqueness (as defined in this paper) affect the sensitivity. We also investigate the effect of the number of matrices on the sensitivity. Our numerical experiments confirm the theoretical results. [ABSTRACT FROM AUTHOR]

Abstract: This paper addresses a new optimization scheme designed for a continuous network design problem with respect to link capacity expansions. The network design problem can be formulated as a mathematical program with equilibrium constraints (MPEC) where the user equilibrium with variable demand is expressed as a variational inequality problem. Due to the non-differentiability of the perturbed solutions in equilibrium constraints, a non-smooth optimization model is established. A generalized bundle subgradient projection is presented to effectively solve the network design problem. Global convergence analysis for the proposed method is also delivered. Numerical calculations are conducted and promising results have shown potential of the proposed method in solving network design problem when compared to earlier studies. [Copyright &y& Elsevier]

Accelerated life tests are extensively used to provide quickly the information about the life distributions of products. Test units are subjected to elevated stresses which yield shorter lives. For some products whose life is defined by usage, e.g., mileage and cycles, test units are also run at higher usage rates (UR) to compress the test time. This paper presents a method for testing products at both higher stress levels, and UR. Censoring time is pre-determined and fixed, while censoring usage is a function of UR. A UR effect model is proposed to describe the dependence of usage to failure (UTF) on UR. The relationship between UTF, and stress and UR is established, and used to estimate the UTF distribution at design stresses and usual UR. The mode! parameters are estimated by maximum likelihood method. The best compromise test plans, which choose the UR, stress levels, and sample sizes, are devised by minimizing the asymptotic variance of the estimator of a life percentile at design stresses and usual UR. The efficiency, and sensitivity of the test plans are evaluated. The results show that the test plans are efficient, and robust. [ABSTRACT FROM AUTHOR]

It is well known that the implicit resolvent equations are equivalent to the quasivariational inclusions. We use this alternative equivalent formulation to study the sensitivity of the quasivariational inclusions without assuming the differentiability of the given data. Since the quasi-variational inclusions include classical variational inequalities, quasi (mixed) variational inequalities, and complementarity problems as special cases, results obtained in this paper continue to hold for these problems. In fact, our results can be considered as a significant extension of previously known results. [Copyright &y& Elsevier]