Resource discovery approaches in cloudIoT: a systematic review

The Journal of Supercomputing - The cloud of things (CloudIoT) represents a general system of supporting infrastructure for storing and processing information gathered from smart objects and their...     

Stochastic collocation-based nonlinear analysis of concrete bridges with uncertain parameters

This paper focuses on the stochastic response of concrete bridges considering uncertainty in bearing and abutment stiffness. A multi-span simply supported bridge with concrete girders is selected. A 3D-dimensional model is prepared, and nonlinear response history analyses are performed. For the numerical dynamic simulation, the non-sampling stochastic method based on generalized polynomial chaos (gPC) expansion is utilised. The uncertain parameters include the vertical and shear stiffness of bearings and the lateral stiffness of abutments are presented by the truncated gPC expansions. Furthermore, the system response such as base shear, acceleration, velocity and displacement in different columns is presented by gPC expansion with unknown deterministic coefficients. The stochastic Galerkin projection is employed to calculate a set of deterministic equations. A non-intrusive solution, as a set of collocation points, determines the unknown gPC coefficients of the system response and the results are compared with Monte Carlo simulations. The key advantage of spectral discretization is the combination of the mentioned method with the spatial discretization, e.g. finite element model. This study also emphasises the accuracy in results and time efficiency of the proposed non-sampling method for uncertainty quantification of stochastic systems comparing to sampling procedure (e.g. Monte Carlo simulation).     

Audio watermarking based on synergy between Lucas regular sequence and Fast Fourier Transform

Multimedia Tools and Applications - The growth of digital technology over the recent years has led to increased sending and saving of electronic media. Taking advantage of digital works without...     

Audio Steganalysis based on collaboration of fractal dimensions and convolutional neural networks

Multimedia Tools and Applications - Steganography is the art of concealing a message within a cover media with the least understandable changes. On the other hand, steganalysis algorithms try to...     

Zeolite filled polyimide membranes for dehydration of isopropanol through pervaporation process

Six mixed matrix membranes (MMMs) were prepared using zeolites of 4A and ZSM-5 incorporated in polyimide of Matrimid 5218. Effects of filler type on membrane morphology and pervaporation performance of MMMs were investigated using isopropanol dehydration. In addition, effects of operating temperature (30, 40, 50, and 60 °C), feed water concentration (10, 20, 30, and 40 wt.%) and permeate side pressure (0 and 15 torr) on pervaporation performance were studied. Scanning electron microscopy (SEM) analysis showed there were good adhesion between the fillers and the polymer matrix. Zeolite 4A has a better contact with the polymer phase and thereby nearly no void is formed in the MMM structure. Pervaporation were performed based on L16 array of Taguchi method for design of experiments. The results showed that the best separation condition is achieved at temperature, feed water concentration, and permeate pressure of 30 °C, 10 wt.% water and 0 torr, respectively. Selectivities of zeolites 4A and ZSM-5 filled MMMs were calculated as 8991 and 3904 compared with 1276 measured for the neat Matrimid 5218 membrane. Permeation rates of the zeolite 4A and ZSM-5 filled MMMs and the neat polymeric membrane were found to be 0.018, 0.016, and 0.013 kg/m² h, respectively.     

Cognitive modeling and dynamic probabilistic simulation of operating crew response to complex system accidents: Part 5: Dynamic probabilistic simulation of the IDAC model

This is the last in a series of five papers that discuss the Information Decision and Action in Crew (IDAC) context for human reliability analysis (HRA) and example application. The model is developed to probabilistically predict the responses of the control room operating crew in nuclear power plants during an accident, for use in probabilistic risk assessments (PRA). The operator response spectrum includes cognitive, emotional, and physical activities during the course of an accident. This paper describes a dynamic PRA computer simulation program, accident dynamics simulator (ADS), developed in part to implement the IDAC model. This paper also provides a detailed example of implementing a simpler version of IDAC, compared with the IDAC model discussed in the first four papers of this series, to demonstrate the practicality of integrating a detailed cognitive HRA model within a dynamic PRA framework.     

A procedure for the analysis of errors of commission in a Probabilistic Safety Assessment of a nuclear power plant at full power

This paper describes an analytical procedure that has been developed to facilitate the identification of errors of commission for inclusion in a Probabilistic Safety Assessment (PSA) of a nuclear power plant operating at full power. The procedure first identifies the opportunities for error by determining when operators are required to intervene to bring the plant to a safe condition following a transient, and then identifying under what conditions this is likely to occur using a model of the causes of error. In order to make the analysis practicable, a successive screening approach is used to identify those errors with the highest potential of occurrence. The procedure has been applied as part of a PSA study, and the results of that application are summarized. For the particular plant to which the procedure was applied, the conclusion was that, because of the nature of the procedures, the high degree of redundancy in the instrumentation, the operating practices, and the control board layouts, the potential for significant errors of commission is low.     

A framework to integrate software behavior into dynamic probabilistic risk assessment

Software plays an increasingly important role in modern safety-critical systems. Although, research has been done to integrate software into the classical probabilistic risk assessment (PRA) framework, current PRA practice overwhelmingly neglects the contribution of software to system risk. Dynamic probabilistic risk assessment (DPRA) is considered to be the next generation of PRA techniques. DPRA is a set of methods and techniques in which simulation models that represent the behavior of the elements of a system are exercised in order to identify risks and vulnerabilities of the system. The fact remains, however, that modeling software for use in the DPRA framework is also quite complex and very little has been done to address the question directly and comprehensively. This paper develops a methodology to integrate software contributions in the DPRA environment. The framework includes a software representation, and an approach to incorporate the software representation into the DPRA environment SimPRA. The software representation is based on multi-level objects and the paper also proposes a framework to simulate the multi-level objects in the simulation-based DPRA environment. This is a new methodology to address the state explosion problem in the DPRA environment. This study is the first systematic effort to integrate software risk contributions into DPRA environments.