A novel optimized approach for resource reservation in cloud computing using producer–consumer theory of microeconomics

The Journal of Supercomputing - Designing economic pricing mechanisms have recently attracted a great deal of attention in the context of cloud computing. We believe that microeconomics theory is a...     

A perception-based model for EDI adoption in small businesses using a technology–organization–environment framework

The wide adoption of electronic data interchange (EDI) has been argued to be important for the success of the technology. Past studies on EDI have focused mainly on large firms, as they were the major users at the time. With the advance of technology, however, EDI applications that used to require mainframe computers can be used on PCs at a much lower cost. At a result, small businesses are now able to enjoy the benefits of EDI. Using a technology–organization–environment framework, this study proposes a perception-based small business EDI adoption model that is tested against data collected from 575 small firms in Hong Kong. Six factors are tested using logistic regression and five are found to be significant in distinguishing adopter firms from non-adopter firms. The results suggest the perception-based model using a technology–organization–environment framework is a useful approach for examining factors affecting the adoption decision. For small businesses, while direct benefits are perceived to be higher by adopter firms than by non-adopter firms, indirect benefits are not perceived differently by either adopter firms or non-adopter firms, contrary to the findings in studies on large business. In addition, adopter firms perceive lower financial costs and higher technical competence than non-adopter firms do. Also, adopter firms perceive higher government pressure but lower industry pressure than non-adopter firms do. Implications of the findings and future research areas are discussed.     

Towards efficient human–machine interaction for home energy management with seasonal scheduling using deep fuzzy neural optimizer

Cognition, Technology & Work - Maintaining the records of domestic consumers’ electricity consumption patterns is very complex task for the utilities, especially for extracting the...     

A framework for exploring numerical solutions of advection–reaction–diffusion equations using a GPU-based approach

In this paper we describe a general purpose, graphics processing unit (GP-GPU)-based approach for solving partial differential equations (PDEs) within advection–reaction–diffusion models. The GP-GPU-based approach provides a platform for solving PDEs in parallel and can thus significantly reduce solution times over traditional CPU implementations. This allows for a more efficient exploration of various advection–reaction–diffusion models, as well as, the parameters that govern them. Although the GPU does impose limitations on the size and accuracy of computations, the PDEs describing the advection–reaction–diffusion models of interest to us fit comfortably within these constraints. Furthermore, the GPU technology continues to rapidly increase in speed, memory, and precision, thus applying these techniques to larger systems should be possible in the future. We chose to solve the PDEs using two numerical approaches: for the diffusion, a first-order explicit forward Euler solution and a semi-implicit second order Crank–Nicholson solution; and, for the advection and reaction, a first-order explicit solution. The goal of this work is to provide motivation and guidance to the application scientist interested in exploring the use of the GP-GPU computational framework in the course of their research. In this paper, we present a rigorous comparison of our GPU-based advection–reaction–diffusion code model with a CPU-based analog, finding that the GPU model out-performs the CPU implementation in one-to-one comparisons.     

Cryptanalysis of a remote user authentication scheme for mobile client–server environment based on ECC

Understanding security failures of cryptographic protocols is the key to both patching existing protocols and designing future schemes. The design of secure remote user authentication schemes based on elliptic curve crypto-graphy (ECC) for mobile applications is still quite a challenging problem, though many schemes have been published lately. In this paper, we analyze an efficient ID-based scheme for mobile client–server environment without the MapToPoint function introduced by He et al. in 2012. This proposal attempts to overcome many of the well known security and efficiency shortcomings of previous schemes, and it also carries a claimed proof of security in the random oracle model. However, notwithstanding its formal security arguments, we show that He et al.’s protocol even cannot attain the basic goal of mutual authentication by demonstrating its vulnerabilities to reflection attack and parallel session attack. Besides these two security vulnerabilities, their scheme also suffers from some practical pitfalls such as user anonymity violation and clock synchronization problem. In addition, we carry out an investigation into their security proof and propose some changes to the scheme so that it can achieve at least its basic security goal, in the hope that similar mistakes are no longer made in the future.     

Modelling stress–strain and volume change behaviour of unsaturated soils using an evolutionary based data mining technique,an incremental approach

Modelling of unsaturated soils has been the subject of many research works in the past few decades. A number of constitutive models have been developed to describe the complex behaviour of unsaturated soils. However, many have proven to be unable to predict all aspects of the behaviour of unsaturated soils in a unified manner. In this paper an alternative new approach is presented, based on the Evolutionary Polynomial Regression (EPR) technique. EPR is a data mining technique that generates a transparent and structured representation of the behaviour of a system directly from input test data. The capabilities of the proposed EPR-based framework in modelling of behaviour of unsaturated soils are illustrated using results from a comprehensive set of triaxial tests on samples of compacted unsaturated soils from literature. The main parameters used for modelling of the behaviour of unsaturated soils during shearing are initial water content, initial dry density, mean net stress, axial strain, suction, volumetric strain, and deviator stress. The model developed is used to predict different aspects of the behaviour of unsaturated soils for conditions not used in the model building process. The results show that the proposed approach provides a useful framework for modelling of unsaturated soils. The merits and advantages of the proposed approach are highlighted.     

Play segmentation for the play–break based sports video using a local adaptive model

This paper proposes a new play segmentation algorithm using a local adaptive model for each sports game, in which the play start shots (PSS) that represent the start of each play segment are detected by comparing all of keyframes with the PSS model. The PSS model is calculated on the fly using generic clustering algorithm and a repetitive characteristic of the PSS. The end of each play segment (the play end shot (PES)) is determined by detecting close up shots using the field color extracted from the play start shots since the camera will focus on the players or the audience with close up view. Experimental results with 28 baseball videos show that good performance can be obtained with the proposed algorithm compared to other algorithms.

The design and implementation of an individual-based predator–prey model for a distributed computing environment

A distributed implementation of the Spatially-Explicit Individual-Based Simulation Model of Florida Panther and White-Tailed Deer in the Everglades and Big Cypress Landscapes (SIMPDEL) model is presented. SIMPDEL models the impact of different water management strategies in the South Florida region on the white-tailed deer and the Florida panther populations. SIMPDEL models the interaction of the four interrelated components – vegetation, hydrology, white-tailed deer and Florida panther, over a time span up to several decades. Very similar outputs of bioenergetic and survival statistics were obtained from the serial and distributed models. A performance evaluation of the two models revealed moderate speed improvements for the distributed model (referred to as DSIMPDEL). The 4-processor configuration attained a speed improvement of 3.83 with small deer populations on an ATM-based network of SUN Ultra 2 workstations over the serial model executing on a single SUN Ultra 2 workstation.     

A novel TODIM-VIKOR approach based on entropy and Jensen–Tsalli divergence measure for picture fuzzy sets in a decision-making problem

The picture fuzzy set (PFS) has grown huge attention in the research area of uncertain information from the last few years. Information measures have been widely studied in various fuzzy environments. Therefore, in this paper, we study the entropy and divergence measures under the picture fuzzy environment. First, the paper introduced a new entropy measure to measure the fuzziness degree associated with a PFS. An example is established to show the capabilities of the proposed entropy measure. Second, the paper defines a new Jensen–Tsalli divergence measure for PFS to evaluate the information of discrimination between two PFS. We also discuss several properties of entropy and divergence measures in detail. Then we present a new method, based on proposed entropy and divergence measure, to determine the objective weights of experts for multicriteria group decision making with picture fuzzy information. The final criteria weights are obtained by combining subjective and objective weights for more reliable weightage of evaluation criteria. By using this comprehensive weight-determination technique, the proposed method can effectively reduce the unreasonable impact of the extreme evaluation data on the evaluation results. Further, a new multi-criteria decision-making approach is developed based on the combining concepts of the TODIM and VIKOR method under the picture fuzzy environment. We used TODIM to obtain the overall dominance degree which considers the bounded rationality of decision makers and VIKOR is used to obtain the compromise ranking of alternatives. Lastly, an application of the proposed integrated model is demonstrated to verify the feasibility and usefulness and the outcomes of the proposed model are compared with the outcomes of the existing approaches to indicate its validity. This integrated method can effectively reduce the distortion of decision information and provide extraordinary evaluation results. The proposed approach is used in detecting the major issues due to which a company is facing such breakdowns.     

New optimal controller tuning method for an AVR system using a simplified Ant Colony Optimization with a new constrained Nelder–Mead algorithm

In this paper, an optimal gain tuning method for PID controllers is proposed using a novel combination of a simplified Ant Colony Optimization algorithm and Nelder–Mead method (ACO-NM) including a new procedure to constrain NM. To address Proportional-Integral-Derivative (PID) controller tuning for the Automatic Voltage Regulator (AVR) system, this paper presents a meta-analysis of the literature on PID parameter sets solving the AVR problem. The investigation confirms that the proposed ACO-NM obtains better or equivalent PID solutions and exhibits higher computational efficiency than previously published methods. The proposed ACO-NM application is extended to realistic conditions by considering robustness to AVR process parameters, control signal saturation and noisy measurements as well as tuning a two-degree-of-freedom PID controller (2DOF-PID). For this type of PID, a new objective function is also proposed to manage control signal constraints. Finally, real time control experiments confirm the performance of the proposed 2DOF-PIDs in quasi-real conditions. Furthermore, the efficiency of the algorithm is confirmed by comparing its results to other optimization algorithms and NM combinations using benchmark functions.     

Classification of radar echoes with a textural–fuzzy approach: an application for the removal of ground clutter observed in Sétif (Algeria) and Bordeaux (France) sites

This work deals with the classification of radar echoes and the removal of clutter caused by the Earth’s surface. Two incoherent radar sites are considered, which are the regions of Sétif (Algeria) and Bordeaux (France) where different climates and landforms prevail. To perform this task, we used a combination of textural and fuzzy approaches. For the textural technique, we applied grey-level co-occurrence matrices that are widely used in the analysis of texture images. We have shown that among nine parameters, only energy and local homogeneity are considered to be effective in discriminating between precipitation echoes and clutter. Then, these parameters are used as inputs for the fuzzy system, while the two radar echo types are its output classes. Image processing done by using this approach has reduced ground echoes by more than 93.5% for Sétif and 92.3% for Bordeaux sites, while more than 97.6% of precipitation echoes are stored at both sites. In addition, over 96% of the anomalous propagations observed only in Bordeaux site are removed. The proposed approach gives a filtering average rate that is 94.5% higher than that obtained for the textural technique alone, which is 91.5%.