Resource discovery in the Internet of Things integrated with fog computing using Markov learning model

The Journal of Supercomputing - Due to high and unpredictable connection delays, privacy gaps, and traffic load of networks connecting cloud computing to end users in many of the Internet of Things...     

Transmission pricing and recovery of investment costs in the deregulated power system based on optimal circuit prices

Transmission pricing has become a major issue in the discussions about the deregulated electricity markets.Consequently,open access to the transmission system is one of the basic topics to allow competition among participants in the energy market.Transmission costs have an important impact on relative competition among participants in the energy market as well as on short-and long-term economic efficiencies of the whole electricity industry,although they represent only close to 10% of the energy market price.This paper deals with the design and tests of a transmission pricing method based on the optimal circuit prices derived from the economically adapted network(EAN).Prices derived from the EAN have the advantage of being in tune with the maximum revenue allowed to the owner of transmission assets and simplifying the optimal allocation of transmission costs among participants.Beginning from the conceptual design,the proposed method is tested on a three-bus network and on the IEEE 24-bus reliability test system.     

A multiobjective integrated multiproject scheduling and multiskilled workforce assignment model considering learning effect under uncertainty

Today, organizations try to decline academically expenses using humans and resources in addition to rising managers and operators' satisfaction. Meantime, a very important step in the process of decision is the assignment of human resources, particularly in connection with research and development (R&D) projects in which the system is highly dependent on the capabilities of human resources. In this study, we tried all the assumptions that come true in the real world, considered a model for applied R&D projects to reduce costs and increase the efficiency of projects. Therefore, an integrated multiproject scheduling and multiskill human resource assignment model under uncertainty has developed for R&D projects. Furthermore, it is assumed that the activity processing time is related to human resources assignment that means the learning effect is considered. To demonstrate the proposed model efficiency, the various dimensions instance problem was solved accurately and efficiently in GAMS software, and the results have been reported. In addition, the proposed model is validated through the input parameter sensitivity analysis. The results indicate a suitable performance of the proposed fuzzy mathematical programming model is due to the complexity of the problem.     

A skewed unscented Kalman filter

State estimation of nonlinear systems is a challenging task, especially when the Gaussian approximation fails. The unscented Kalman filter was proposed to deal with state estimation of nonlinear systems. We modify the traditional unscented Kalman filter to capture the third-order moment (skewness) of the state vector. Methods are also proposed to reduce the computation time of the suggested approach, and showing that the proposed algorithm is as fast as the unscented Kalman filter. Simulation results confirm that the method is better than, or at least as good as, the unscented Kalman filter.     

Adaptive robust control of uncertain systems with state and input delay

In this paper, adaptive robust control of uncertain systems with multiple time delays in states and input is considered. It is assumed that the parameter uncertainties are time varying norm-bounded whose bounds are unknown but their functional properties are known. To overcome the effect of input delay on the closed loop system stability, new Lyapunov Krasovskii functional will be introduced. It is shown that the proposed adaptive robust controller guarantees globally uniformly exponentially convergence of all system solutions to a ball with any certain convergence rate. Moreover, if there is no disturbance in the system, asymptotic stability of the closed loop system will be established. The proposed design condition is formulated in terms of linear matrix inequality (LMI) which can be easily solved by LMI Toolbox in Matlab. Finally, an illustrative example is included to show the effectiveness of results developed in this paper.     

High strain electromechanical actuators based on electrodeposited polypyrrole doped with di-(2-ethylhexyl)sulfosuccinate

The low-voltage electromechanical actuation of polypyrrole (PPy) doped with di-(2-ethylhexyl)sulfosuccinate (DEHS) has been investigated. The PPy-DEHS has been prepared both chemically (cast as films from solution) and by more conventional electrochemical polymerization. Very large strains of ∼30% were obtained during slow-scan redox cycling of the electrochemically prepared PPy-DEHS films. In constrast, PPy-DEHS films cast from solutions of the chemically polymerized polymer gave actuation strains of ∼2.5%. The polymerization method was also found to have a significant effect on the structure, conductivity and mechanical properties of the PPy-DEHS materials. The conductivity of the electrochemically polymerized PPy-DEHS was 75 S cm⁻¹, considerably higher than that found for the chemically derived polymer (7 S cm⁻¹). The structure of the PPy-DEHS was further elucidated from UV-vis, Raman and FT-IR spectral studies which indicated that the conjugation length of the PPy could be increased significantly by varying the polymerization method. Films obtained by casting chemically prepared PPy-DEHS showed higher modulus (2.3 GPa) than electropolymerized PPy-DEHS (0.6 GPa), but were more brittle. Both materials were electroactive in acetonitrile/water electrolyte. The higher actuation strain observed in the electrochemically prepared films was attributed to a more open molecular structure (as indicated by the lower modulus) allowing for easier ion diffusion and a higher conductivity allowing easier charge transfer.     

Incremental one-class classifier based on convex–concave hull

Pattern Analysis and Applications - One subject that has been considered less is a binary classification on data streams with concept drifting in which only information of one class (target class)...     

Violence detection in videos using interest frame extraction and 3D convolutional neural network

Multimedia Tools and Applications - With the rapid development of detecting violent behaviors in surveillance cameras, requests on systems that automatically recognize violent events are expanded....     

RACER: accurate and efficient classification based on rule aggregation approach

Neural Computing and Applications - Rule-based classification is one of the most important topics in the field of data mining due to its wide applications. This article presents a novel rule-based...     

A NEW DISTRIBUTED JOB SCHEDULING ALGORITHM FOR GRID SYSTEMS

Job scheduling is one of the key issues in the design of grid environments. The performance of the grid system severely degrades if a method does not exist to efficiently schedule the user jobs. In this article, a fully distributed, learning automata–based job scheduling algorithm is proposed for grid environments. The proposed method is composed of two types of procedures: in the first, a procedure is run at the grid nodes and in the second, the procedure is run at the schedulers. The proposed algorithm synchronizes the performance of the schedulers by the learning automata that select their actions using the pseudo-random number generators with the same seed. In this method, the grid computational capacity that is allocated to each scheduler is proportional to its workload. To show the efficiency of the proposed method, several simulation experiments were conducted under different grid scenarios. The obtained results show that the proposed algorithm outperforms several well-known methods in terms of makespan, flow time, and load balancing.