A multi-agent based approach for change management in manufacturing enterprises

Change management becomes an unavoidable necessity for manufacturing enterprises. Since change in business processes carries significant impact on the performance of manufacturing companies, a change management model is definitely required to remain competitive. Moreover, utilizing agent based systems will provide computational provision and integrity to manage and measure the capabilities to follow the change in a progressive approach by employing the cooperation and collaboration properties of various agents helping for retrieval of the required information in a rapid way. Therefore, in this paper, a multi-agent based change management model is proposed to handle the changes in manufacturing enterprises. The model is validated through a case study done to measure the performance of change management capabilities in a manufacturing company. A sensitivity analysis on the results of this case study is also conducted to reveal the system reactivity to various parameters.     

Investigation of microwave power limiter for Industrial Scientific Medical band (ISM) applications

In this paper, a new design of microstrip power limiter which is based on microstrip technology and zero bias Schottky diode is introduced. In this context, the FR‐4 substrate that was characterized by dielectric permittivity (4.4), dielectric thickness (1.6 mm), and the HSMS 286k Schottky diode is used to design the proposed power limiter. The planar resonators are designed, optimized, and simulated with the shunting of the HSMS 286k diodes by using Schematic solver integrated in ADS from Agilent Technologies. The simulation results are significant in terms of high impedance matching, strong insertion of the low power, and good limitation ratio of the high power. The proposed power limiter is fabricated and tested in the measurement part. It is observed that the results are in agreement with the numerical analysis in terms of matching, isolation, and power limitation. The achieved microwave power limiter offers simple construction, small size (44 × 40 mm²), wide bandwidth, and good limitation ratio less than 10 dBm when the input power reaches 30 dBm.     

Wide band fractal‐based perfect energy absorber and power harvester

In this article, a novel wide band polarization and incident angle independent metamaterial absorber (MA) and energy harvesting applications which operates at C (4GHz‐8 GHz) and X (8GHz‐12 GHz) is proposed. The unit‐cell of the proposed structure based on fractal circle loop. Four lumped resistors are mounted the structure to obtain a broad band absorption characteristics. Resistors increase the absorption characteristic of proposed MA significantly at mentioned frequency ranges. In addition, under favor of the resistors proposed MA can convert absorbed energy from incident wave to appearing power.     

Unbalanced states violates RFID privacy

Designing privacy preserving authentication protocols for massively deployed Radio Frequency IDentification (RFID) systems is a real world challenge that have drawn significant attention from RFID community. This interest yields considerable amount of proposals targeting to overcome the main bottleneck (i.e. the exhaustive search over the list of all tag entries) which appears in the back-end database for large-scale RFID tag deployments. A class of these proposals contains RFID protocols where the server authenticates the tag in a negligible constant/sub-linear time for a more frequent normal state and needs a linear search in a rare abnormal states. In this study, however, we show that such protocols having unbalanced states are subject to side-channel attacks and do not preserve the RFID privacy. To illustrate this brutal security flaw, we conduct our analysis on different RFID protocols.     

Improving DBSCAN’s execution time by using a pruning technique on bit vectors

Clustering is the process of assigning a set of physical or abstract objects into previously unknown groups. The goal of clustering is to group similar objects into the same clusters and dissimilar objects into different clusters. Similarities between objects are evaluated by using the attribute values of objects. There are many clustering algorithms in the literature; among them, DBSCAN is a well known density-based clustering algorithm. We improve DBSCAN’s execution time performance for binary data sets and Hamming distances. We achieve considerable speed gains by using a novel pruning technique, as well as bit vectors, and binary operations. Our novel method effectively discards distant neighbors of an object and computes only the distances between an object and its possible neighbors. By discarding distant neighbors, we avoid unnecessary distance computations and use less CPU time when compared with the conventional DBSCAN algorithm. However, the accuracy of our method is identical to that of the original DBSCAN. Experimental test results on real and synthetic data sets demonstrate that, by using our pruning technique, we obtain considerably faster execution time results compared to DBSCAN.     

A new approach for estimation of obstructive sleep apnea syndrome

Obstructive sleep apnea syndrome (OSAS) is a situation where repeatedly upper airway stops off while the respiratory effort continues during sleep at least for 10 s. Apart from polysomnography, many researchers have concentrated on exploring alternative methods for OSAS detection. However, not much work has been done on using non-Gaussian and nonlinear behavior of the electroencephalogram (EEG) signals. Bispectral analysis is an advanced signal processing technique particularly used for exhibiting quadratic phase-coupling that may arise between signal components with different frequencies. From this perspective, in this study, a new technique for recognizing patients with OSAS was introduced using bispectral characteristics of EEG signal and an artificial neural network (ANN). The amount of Quadratic phase coupling (QPC) in each subband of EEG (namely; delta, theta, alpha, beta and gamma) was calculated over bispectral density of EEG. Then, these QPCs were fed to the input of the designed ANN. The neural network was configured with two outputs: one for OSAS and one for estimation of normal situation. With this technique a global accuracy of 96.15% was achieved. The proposed technique could be used in designing automatic OSAS identification systems which will improve medical service.     

Coalescence of oil droplets in plasticized starch matrix in simple shear flow

The formation of oil droplets in plasticized starch matrices is studied by using well-defined conditions similar to extrusion. A method based on double staining and confocal scanning microscopy was developed to investigate the role of coalescence during droplet formation. The results indicate that coalescence takes place at all process conditions studied. The apparent critical capillary number was used to quantify the coalescence intensity and to separate the influence of interdependent process parameters on the coalescence. The intensity of coalescence increased with shear rate and oil content whereas an increase in blend viscosity reduced the extent of coalescence. Besides, the results showed that the critical dispersed phase concentration (Φ_c), below which no coalescence takes place, depends on applied shear rate and decreases with increasing shear rate.     

Effect of ultrasound on separation selectivity and efficiency of flotation

The effect of the use of ultrasound in the froth phase on the flotation performance has been investigated in relation to the flotation rate of a complex sulphide ore. A series of kinetic flotation tests with and without ultrasound were conducted in a flotation machine with a 2-L cell, in which an ultrasonic probe is located in the froth zone. The results indicate that there is a considerable effect of ultrasound on separation selectivity and efficiency in the flotation of a complex sulphide ore at intermediate and high level airflow rates whereas, no significant differences in the separation performance were obtained from the flotation with and without ultrasound at low airflow rates. In addition, the results of the size-by-size analysis show that a much better cleaning action in the froth was promoted for coarse particles rather than fine particles as a result of the use of ultrasound. As a result of increase in the bubble coalescence, it was found that the use of ultrasound in the froth is more effective at shallow froths. Therefore, either effective pulp volume can be increased with a negligible loss of flotation performance or the pulp density can be decreased to obtain better product quality with the use of ultrasound in shallow froths.     

Three-Dimensional Surface Texture Characterization of Portland Cement Concrete Pavements

Abstract:   This article investigates the effectiveness of different mathematical methods in describing the three-dimensional surface texture of Portland cement concrete (PCC) pavements. Ten PCC field cores of varying surface textures were included in the analysis. X-ray Computed Tomography (CT) was used to scan the upper portion of these cores, resulting in a stack of two-dimensional grayscale images. Image processing techniques were utilized to isolate the void pixels from the solid pixels and reconstruct the three-dimensional surface topography. The resulting three-dimensional surfaces were reduced to two-dimensional "map of heights" images, whereby the grayscale intensity of each pixel within the image represented the vertical location of the surface at that point with respect to the lowest point on the surface. The "map of heights" images were analyzed using four mathematical methods, namely the Hessian model, the Fast Fourier transform (FFT), the wavelet analysis, and the power spectral density (PSD). Results obtained using these methods were compared to the mean profile depth (MPD) computed in accordance with ASTM E1845 .