This paper is concerned with automated classification of Combinatorial Optimization Problem instances for instance-specific parameter tuning purpose. We propose the CluPaTra Framework, a generic approach to CLUster instances based on similar PAtterns according to search TRAjectories and apply it on parameter tuning. The key idea is to use the search trajectory as a generic feature for clusterin...

The standard F test for linear restrictions in regression is relevant as a criterion but fails to capture the notion of tradeoff between bias and variance. Average squared distance criteria yield operational tests that are more appropriate, depending upon objectives. In the present paper two alternative criteria are developed. The first allows testing of the hypothesis that the average squared ...

A Poisson-type equation arising in a commonly used numerical weather forecasting model is solved using an alternating direction implicit (ADI) method with Wachpress optimum parameters on a trapezoidal domain which coincides with the operational forecast domain. Various optimum parameter sequences were obtained for the corresponding squares which enclose the region under consideration, computati...

Though Blind Source Separation (BSS) techniques have typically been applied within Operational Modal Analysis (OMA) framework, there joint diagonalization property can also be utilized within traditional input-output Experimental Modal Analysis (EMA) for the purpose of modal parameter estimation. This paper explores this possibility and suggests an approach to achieve the same. The paper presen...

In this work, a lipase-catalyzed selective enzymatic hydrolysis of the borage oil was carried out using commercial enzymes and native crude enzymatic extract from Brazil as biocatalysts for the reaction. Two crude enzymatic extracts home-produced and three commercial lipases were screened for concentrating γlinolenic acid of the triacylglycerols in unhydrolyzed acylglycerols. The kinetics of en...

Soil moisture memory is a key component of seasonal predictability. However, uncertainty in current memory estimates is not clear and it is not obvious to what extent these are dependent on model uncertainties. To address this question, we perform a global sensitivity analysis of memory to key hydraulic parameters, using an uncoupled version of the H-TESSEL land surface model. Results show sign...

Multi-objective optimization algorithms are widely used for the calibration of conceptual hydrological models. Such algorithms yield a set of Pareto-optimal solutions, reflecting the model structure uncertainty. In this study, a multi-objective optimization strategy is suggested, which aims at reducing the model structure uncertainty by considering parameter interaction within Pareto-optimal so...

Data collected from the supervisory control and data acquisition (SCADA) system, used widely in wind farms to obtain operational and condition information about wind turbines (WTs), is of important significance for anomaly detection in wind turbines. The paper presents a novel model for wind turbine anomaly detection mainly based on SCADA data and a back-propagation neural network (BPNN) for au...

Technology plays the major role in healthcare system, not only for recording parameters through sensory devices but also in communicating, recording and displaying the measured parameter. It is very important to monitor various medical parameters and post operational data. To access the patient’s medical parameters in local and remote area, healthcare communication using Internet of Things (IoT...

A confidence interval is an interval (i.e., a range of values) estimate of a parameter of a population (e.g., a mean) calculated from a sample drawn from the population. A confidence interval has an associated confidence level, which is frequency with which a calculated confidence interval is expected to contain the population parameter. Confidence intervals are of interest in modeling and simu...