Enhanced Multi-attribute Combinative Double Auction (EMCDA) for Resource Allocation in Cloud Computing

Wireless Personal Communications - Cloud computing is a growing technology where lot of heterogeneous resources are available and large amount of requests are submitted by the customers...     

Sybil Attack with RSU Detection and Location Privacy in Urban VANETs: An Efficient EPORP Technique

In recent years, Vehicular ad hoc networks (VANETs) could facilitate the decision-making progress of the drivers for example trip planning with the consideration of traffic. In the VANET, the Sybil attack is a very serious attack that collapses the security. In literature, some of the methods are reviewed to detect Sybil attacks in VANETs, but it fails to achieve Sybil attack detection. Hence, in this paper, Emperor Penguin Optimization-based Routing protocol (EPORP) is developed for detecting the Sybil attack which enhances the VANETs security. The main motive of the research is detecting the Sybil attack in VANETs for enhancing the secure operation. In the proposed approach, the Sybil attack will be detected with the help of the Rumour riding technique. To enhance the security of the VANETs, the Split XOR (SXOR) operation is utilized. In the SXOR operation, the optimal key is selected with the help of Emperor Penguin Optimization (EPO). The proposed method is implemented in the NS2 platform and performances are evaluated by metrics such as delay, throughput, delay, encryption time, and decryption time. The proposed method is compared with existing methods such as Whale Optimization Algorithm (WOA), Particle Swarm Optimization (PSO), and Firefly Algorithm (FA) respectively. While analyzing the delivery ratio, the proposed method has 0.96 s, and the WOA, PSO, and FA are 0.94, 0.92, and 0.90 respectively. From the analysis, the proposed method has a high delivery ratio value compared with the WOA, PSO, and FA methods. Similarly, the other parameters are analyzed and compared with the existing methods.

     

Epitomic Location Recognition

This paper presents a novel method for location recognition, which exploits an epitomic representation to achieve both high efficiency and good generalization. A generative model based on epitomic image analysis captures the appearance and geometric structure of an environment while allowing for variations due to motion, occlusions, and non-Lambertian effects. The ability to model translation and scale invariance together with the fusion of diverse visual features yields enhanced generalization with economical training. Experiments on both existing and new labeled image databases result in recognition accuracy superior to state of the art with real-time computational performance.     

Influence ofβ-cyclodextrin as an encapsule and as an inclusion complex dopant on conducting polyaniline

An investigation on the effect ofβ-cyclodextrin (CD) in both free and inclusion-complexed forms with a guest anionic metal complex, dioxalatodiaquochromate(III) (DDC), on the characteristics of conducting polyaniline (PANI) is carried out. Four materials, PANI (i.e. PANI-SO ₄ ²⁻ ), PANI-DDC, PANI-CD and PANI-CD + DDC were prepared byin situ chemical oxidative polymerization in aqueous H ₂SO₄ at pH 1 and subjected to electrical conductivity and spectral (IR and UV-vis bd measurements. DDC and CD when separately incorporated, reduce the conductivity of PANI by about half whilst their inclusion complex CD + DDC enhances it. Spectral characterization reveals that DDC as a dopant and CD as an encapsule exhibit their effects through adverse interaction with imine-amine N centres and benzenoid moiety of PANI. The inclusion complex CD + DDC, on the contrary, functions as a dopant by lying in between the chains and seems to promote the extended conformation of PANI chain and hence theπ -electron delocalization. Exposure of the material to methanol vapour causes a decrease in conductivity in PANI and PANI-CD while an increase in PANI-CD + DDC. This study makes explicit the distinct role of CD as an encapsule and CD + DDC inclusion complex as a dopant in altering the electrical property of PANI.     

Tumor detection in T1, T2, FLAIR and MPR brain images using a combination of optimization and fuzzy clustering improved by seed‐based region growing algorithm

Tumor and Edema region present in Magnetic Resonance (MR) brain image can be segmented using Optimization and Clustering merged with seed‐based region growing algorithm. The proposed algorithm shows effectiveness in tumor detection in T1 ‐ w, T2 – w, Fluid Attenuated Inversion Recovery and Multiplanar Reconstruction type MR brain images. After an initial level segmentation exhibited by Modified Particle Swarm Optimization (MPSO) and Fuzzy C – Means (FCM) algorithm, the seed points are initialized using the region growing algorithm and based on these seed points; tumor detection in MR brain images is done. The parameters taken for comparison with the conventional techniques are Mean Square Error, Peak Signal to Noise Ratio, Jaccard (Tanimoto) index, Dice Overlap indices and Computational Time. These parameters prove the efficacy of the proposed algorithm. Heterogeneous type tumor regions present in the input MR brain images are segmented using the proposed algorithm. Furthermore, the algorithm shows augmentation in the process of brain tumor identification. Availability of gold standard images has led to the comparison of the suggested algorithm with MPSO‐based FCM and conventional Region Growing algorithm. Also, the algorithm recommended through this research is capable of producing Similarity Index value of 0.96, Overlap Fraction value of 0.97 and Extra Fraction value of 0.05, which are far better than the values articulated by MPSO‐based FCM and Region Growing algorithm. The proposed algorithm favors the segmentation of contrast enhanced images. © 2017 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 27, 33–45, 2017     

Workload Mining in Cloud Computing using Extended Cloud Dempster–Shafer Theory (ECDST)

Wireless Personal Communications - Cloud computing is a growing technology where the resources are provided as a service on demand basis. The services offered are Infrastructure as a Service,...     

Topological design of channels for squeeze flow optimization of thermal interface materials

Performance of thermal interface materials (TIMs) used between a microelectronic device and its associated heat spreader is largely dependent on the bulk thermal conductivity of the TIM, but the bond-line thickness (BLT) of the applied material as well as the interfacial contact resistances are also significant contributors to overall performance. Hierarchically Nested Channels (HNCs), created by modifying the surface topology of the chip or the heatsink with hierarchical arrangements of microchannels in order to improve flow, have been proposed to reduce both the required squeezing force and the final BLT at the interfaces. In the present work, a topological optimization framework that enables the design of channel arrangements is developed. The framework is based on a resistance network approximation to Newtonian squeeze flow. The approximation, validated against finite element (FE) solutions, allows efficient, design-oriented solutions for squeeze flow in complex geometries. A comprehensive design sensitivity analysis exploiting the resistance network approximation is also developed and implemented. The resistance approximation and the sensitivity analysis is used to build an automated optimal channel design framework. A Pareto optimal problem formulation for the design of channels is posed and the optimal solution is demonstrated using the framework.     

Bio-oil extraction and physicochemical characterization of Caesalpinia pulcherrima plant seed oil

Dwarf Poinciana (Caesalpinia pulcherrima) seeds are studied for first time for the extraction of bio-oil. The dried and crushed seeds are optimized for maximum yield of bio-oil with a series of polar and nonpolar solvents and recovered by a simple distillation process. Methanol is found to yield the maximum bio-oil. The fatty acid analysis of bio-oil reveals the prevalence of linoleic acid (54.67%), followed by palmitic acid (16.9%), stearic acid (12.5%), and oleic acid (10.32%). Basic fuel properties like specific gravity, viscosity, refractive index, iodine value, saponification value, fire point, flash point, pour point, and calorific value are studied.     

Biomass carbon & its prospects in electrochemical energy systems

Activated carbon has now become a vital active material in multifarious applications such as catalytic supports, removal of pollutants, battery electrodes, capacitors, gas storage etc., and these applications require carbon powders with desirable functionalities like surface area, chemical constituents and pore structure. Hence the production of activated carbon materials, especially from cheap and natural bio-precursors (biomass) is a highly attractive research theme in today's science of advanced materials. Though abundant and detailed reports on activated carbons for these applications are available in the literature, creating a consolidated account on the biomass derived activated carbon would serve as a database for the researchers and thus appears justified. Hence an overview on activated carbons (preparation, physical and electrochemical properties) derived especially from biomass for the specific application as electrodes in electrochemical energy devices has been presented to stress the importance of biomass, bioenergy and conversion of wastes into energy concept further. It is certain from the survey of around 100 recent published articles that the biomass carbons have outstanding capability of being applied as electrodes in the energy devices. Particularly, carbon (unactivated) derived from pyrolized peanut shells exhibited a maximum specific capacity of 4765 mAhg⁻¹ in the case of lithium-ion batteries and coconut shell derived carbon in KOH electrolyte gave capacitance of 368 Fg⁻¹ and ZnCl₂ activated carbon from waste coffee grounds exhibited 368 Fg⁻¹ in H₂SO₄. Undoubtedly the study indicates that the biomass derived carbons have economic and commercial promise in the near future.