Color object segmentation and tracking using flexible statistical model and level-set

Multimedia Tools and Applications - This study presents an unsupervised novel algorithm for color image segmentation, object detection and tracking based on unsupervised learning step followed with...     

Cryptanalysis of an embedded systems’ image encryption

Multimedia Tools and Applications - Recently, a new image encryption-scheme for embedded systems based on continuous third-order hyperbolic sine chaotic system, has been proposed. The...     

Iris-based human identity recognition with machine learning methods and discrete fast Fourier transform

Innovations in Systems and Software Engineering - One of the most important modules of computer systems is the one that is responsible for user safety. It was proven that simple passwords and...     

Progress and challenges in sustainability,compatibility, and production of eco-composites: A state-of-art review

Owing to economic and environmental benefits, new generations of materials/commodities follow “from waste to wealth” strategy. Recently, there has been a huge upsurge in research on the development of eco-composites using recycled plastic polymers and agro-residues because the eco-composites satisfy the stringent environment regulations and are cost-effective. Herein, we present a detailed review on the potential use of several types of natural fillers as an efficient reinforcement for recycled plastic polymers. In particular, the characterization of different categories of eco-composites according to their morphological, physical, thermal, and mechanical properties is extensively reviewed and their results are analyzed, compared, and highlighted. Furthermore, a framework to produce functional eco-composites, which includes functionalization of ingredients, critical issues on microstructural parameters, processing, and fabrication methods, is outlined and supported with sufficient data from the literature. Finally, the review outlines the emerging challenges and future prospects of eco-composites to be addressed by interested researchers to bridge the gap between research and commercialization of such a class of material. Overall, the acquired knowledge will guide researchers, scientists, and manufacturers to plan, select, and develop various forms of eco-composites with enhanced properties and optimized production processes.     

Corrosion behavior of HVOF coated sheets

High velocity oxygen-fuel (HVOF) thermal spray coating finds application in industry due to its superior resistance to corrosion and thermal loading. In the HVOF process, the metallic powders at elevated temperature are sprayed at supersonic speed onto a substrate material. The powder granules sprayed impact onto each other, forming a mechanical bonding across the coating layer. In most of the cases, the distances among the particles (powder granules sprayed) are not the same, which in turn results in inhomogeneous structure across the coating layer. Moreover, the rate of oxidation of the powder granules during the spraying process varies. Consequently, the electrochemical response of the coating layer surfaces next to the base material and free to atmosphere differs. In the current study, the electrochemical response of a coating sheet formed during HVOF thermal spraying was investigated. NiCrMoNb alloy (similar to Inconel 625) wass used for the powder granules. Thermal spraying was carried out onto a smooth surface of stainless steel workpiece (without grid blasting), and later the coating layer was removed from the surface to obtain the coating sheet for the electrochemical tests. It was found that the corrosion rate of the smooth surface (surface next to the stainless steel surface before its removal) is considerably larger than that corresponding to the rough surface (free surface) of the coating sheet, and no specific patterns were observed for the pit sites.     

The isoxazolidines: the effects of steric factor and hydrophobic chain length on the corrosion inhibition of mild steel in acidic medium

Several new isoxazolidines having varying degree of steric environment and hydrophobic chain length, prepared efficiently using single-step nitrone cycloaddition reactions, are tested for corrosion inhibition of mild steel in 1 M and 5 M HCl at 50-70 °C range by gravimetric and electrochemical methods. All compounds have shown very good corrosion inhibition efficiency (IE%) in acidic solution. Steric crowding around the nitrogen centres and hydrophobic chain lengths as well as increase in temperature (in the presence of the inhibitor in the higher concentration range 100-400 ppm) are found to increase the inhibition efficiency of the isoxazolidines. Thermodynamic parameters (ΔG°_ads, ΔH°_ads, ΔS°_ads) for the adsorption process and kinetic parameters for the metal dissolution (or hydrogen evolution) reaction in the presence of one of the isoxazolidines were determined. Experimental results agree with the Temkin adsorption isotherm. The inhibition of corrosion in 1 M HCl, influenced by both physi- and chemi-sorption, was found to be under mixed control, but predominantly under cathodic control.     

Swarm Intelligent Compressive Routing in Wireless Sensor Networks

This article proposes a novel algorithm to improve the lifetime of a wireless sensor network. This algorithm employs swarm intelligence algorithms in conjunction with compressive sensing theory to build up the routing trees and to decrease the communication rate. The main contribution of this article is to extend swarm intelligence algorithms to build a routing tree in such a way that it can be utilized to maximize efficiency, thereby rectifying the delay problem of compressive sensing theory and improving the network lifetime. In addition, our approach offers accurate data recovery from small amounts of compressed data. Simulation results show that our approach can effectively extend the network lifetime of a large‐scale wireless sensor network.     

A Model for Incident Tickets Correlation in Network Management

In Information Technology Service Management (ITSM), network management teams typically use an Incident Ticket System (ITS) as a tool to track, troubleshoot, and coordinate the resolution of network incidents that occur during the daily operation of the network. A well organized ITS may positively impact on the efficiency of the incident management process. Nevertheless, in many cases the handling of tickets by the management team is not completely systematic and may be incoherent and inefficient. This way, irrelevant or redundant tickets for the same incident may be issued, thus creating a redundancy in the system that leads to inefficiencies. In this paper, we suggest a model aimed to correlate redundant tickets in order to reduce the information to a single ticket per incident. We validate the proposed correlation model by evaluating it with two datasets taken from a real ticketing system of a telecommunications network company. Using this model as a basis, we also develop and evaluate a methodology that assesses the efficiency of the management team during the process of tickets creation and management. Based on it, we also get some insights on the performance of the different management groups involved in the ticket creation process. These analyses can be leveraged for improving both the management groups functioning and the policies for the tickets’ creation.     

Siamese multi-layer perceptrons for dimensionality reduction and face identification

This paper presents a framework using siamese Multi-layer Perceptrons (MLP) for supervised dimensionality reduction and face identification. Compared with the classical MLP that trains on fully labeled data, the siamese MLP learns on side information only, i.e., how similar of data examples are to each other. In this study, we compare it with the classical MLP on the problem of face identification. Experimental results on the Extended Yale B database demonstrate that the siamese MLP training with side information achieves comparable classification performance with the classical MLP training on fully labeled data. Besides, while the classical MLP fixes the dimension of the output space, the siamese MLP allows flexible output dimension, hence we also apply the siamese MLP for visualization of the dimensionality reduction to the 2-d and 3-d spaces.