B-GWO based multi-UAV deployment and power allocation in NOMA assisted wireless networks

Wireless Networks - Unmanned Aerial Vehicles (UAVs) deployed as flying base stations is a promising technology for enhancing the quality of service (QoS) and quick recovery from unexpected damages...     

Deployment of a cloud pipeline for real-time visual inspection using fast streaming high-definition images

We investigate the challenges of building an end-to-end cloud pipeline for real-time intelligent visual inspection system for use in automotive manufacturing. Current methods of visual detection in automotive assembly are highly labor intensive, and thus prone to errors. An automated process is sought that can operate within the real-time constraints of the assembly line and can reduce errors. Components of the cloud pipeline include capture of a large set of high-definition images from a camera setup at the assembly location, transfer and storage of the images as needed, execution of object detection, and notification to a human operator when a fault is detected. The end-to-end execution must complete within a fixed time frame before the next car arrives in the assembly line. In this article, we report the design, development, and experimental evaluation of the tradeoffs of performance, accuracy, and scalability for a cloud system.     

Keyword-based private searching on cloud data along with keyword association and dissociation using cuckoo filter

International Journal of Information Security - Outsourcing of data is a very common scenario in the present-day world and quite often we need to outsource confidential data whose privacy is of...     

Surface functionalization of silver nanoparticles: novel applications for insect vector control

Every day, people and animals contract debilitating and life threatening diseases due to bites from infected flies, ticks, and mosquitoes. The current methods utilized to fight against these diseases are only partially effective or safe for humans and animals. When it comes to insect vector control, a conceptual paradigm shift is urgently needed. This work proposes a novel synthetic scheme to produce a nanoparticle-pesticide core-shell conjugate to be used as an active agent against arthropod vectors, such as mosquitoes. As a proof of concept, we conjugated nanosilver to the pyrethroid pesticide deltamethrin. First, electron microscopy and Fourier transform infrared spectroscopy verified the presence of a 15 nm nanosilver core surrounded by deltamethrin. Second, when the conjugate was exposed to mosquitoes for a 24 h bioassay, mortality was observed at 9 × 10(-4) M. Silver was detected in the hemolymph of mosquitoes exposed to the conjugate. We concluded that the newly developed nanoconjugate did not inactivate the primary function of the pesticide and was effective in killing mosquitoes at low concentrations. These results demonstrate the potential to use nanoparticle surfaces to kill insects, specifically vectors of human pathogens.     

Preparation and performance evaluation of poly (ether-imide) incorporated polysulfone hemodialysis membranes

Biocompatible Polysulfone (PSf) hemodialysis membranes were prepared by phase inversion technique using poly (ether-imide) (PEI) as the modification agent and Polyethylene glycol (PEG-200) as the pore former. The effect of PSf/PEI blend ratio on the morphology, hydrophilicity, water content, porosity, glass transition temperature, mechanical strength, biocompatibility and permeation rate of the prepared membranes were studied and were found to be improved significantly by the incorporation of PEI in the dope solution. The scanning electron microscopy (SEM) studies revealed that, incorporation of PEI resulted in the formation of spongy sub-layer and increased the connectivity of pores between sub-layer and bottom layer. The water content and permeation rate of the membranes of PSf/PEI blend membranes were increased considerably indicating the enhancement of hydrophilicity and it was supported by lower contact angle values of the blend membranes. The existence of single well defined Tg over entire composition established the compatibility between the components in blend membranes. The biocompatibility of membranes was investigated through protein adsorption, platelet adhesion and thrombus formation on the membrane surface. Anticoagulant activity of PSf/PEI blend membranes was evaluated by measuring the activated partial thrombin time (APTT), prothrombin time (PT), thrombin time (TT) and fibrinogen time (FT). The results revealed that antithrombogenicity of PSf/PEI blend membranes was increased significantly. The efficiency of these membranes in removal of urea, creatinine and vitamin B₁₂ were studied and found to be improved for blend membranes. Thus, it is worth mentioning to note that, the biocompatible PSf/PEI blend membranes prepared in this study would offer immense potential in hemodialysis.     

A novel multimodal medical image fusion using sparse representation and modified spatial frequency

Fusion of multimodal imaging data supports medical experts with ample information for better disease diagnosis and further clinical investigations. Recently, sparse representation (SR)‐based fusion algorithms has been gaining importance for their high performance. Building a compact, discriminative dictionary with reduced computational effort is a major challenge to these algorithms. Addressing this key issue, we propose an adaptive dictionary learning approach for fusion of multimodal medical images. The proposed approach consists of three steps. First, zero informative patches of source images are discarded by variance computation. Second, the structural information of remaining image patches is evaluated using modified spatial frequency (MSF). Finally, a selection rule is employed to separate the useful informative patches of source images for dictionary learning. At the fusion step, batch‐OMP algorithm is utilized to estimate the sparse coefficients. A novel fusion rule which measures the activity level in both spatial domain and transform domain is adopted to reconstruct the fused image with the sparse vectors and trained dictionary. Experimental results of various medical image pairs and clinical data sets reveal that the proposed fusion algorithm gives better visual quality and competes with existing methodologies both visually and quantitatively.     

An image fusion framework using novel dictionary based sparse representation

Image fusion is an important technique which aims to produce a synthetic result by leveraging the cross information available in the existing data. Sparse Representation (SR) is a powerful signal processing theory used in wide variety of applications like image denoising, compression and fusion. Construction of a proper dictionary with reduced computational efficiency is a major challenge in these applications. Owing to the above criterion, we propose a supervised dictionary learning approach for the fusion algorithm. Initially, gradient information is obtained for each patch of the training data set. Then, the edge strength and information content are measured for the gradient patches. A selection rule is finally employed to select the patches with better focus features for training the over complete dictionary. By the above process, the number of input patches for dictionary training is reduced to a greater extent. At the fusion step, the globally learned dictionary is used to represent the given set of source image patches. Experimental results with various source image pairs demonstrate that the proposed fusion framework gives better visual quality and competes with the existing methodologies quantitatively.     

Mechanical,morphological, and thermal properties of chemically treated pine needles reinforced thermosetting composites

Natural fibers are widely used as reinforcement in composites. Pine needles are one of the major biowaste generated by Pinus roxburgii plant. This species is found abundantly in the forests of Himachal Pradesh. In this work, composites of urea–resorcinol–formaldehyde resin‐reinforced with Pine needles fibers were prepared. Fibers were chemically modified to improve their compatibility with matrix. These fibers were mercerized with NaOH solution and acetylated to increase their hydrophobic character. The chemically modified fibers were characterized with Fourier transform infrared spectra, ¹³C‐nuclear magnetic resonance (NMR) spectroscopy, and scanning electron microscopy. The composites were prepared with treated and untreated fibers containing 30% fibers by weight using compression molding technique. The morphology of the materials thus obtained was evaluated by scanning electron microscopy. The chemical modifications of fibers improve fiber–matrix adhesion and also have markedly effect on mechanical properties of composites. Moreover, the thermal resistance of these composites was improved on chemical modification. These results indicate that chemically modified fibers exhibit better compatibility with the polymer matrix than that of untreated fiber. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci, 2013