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...     

Learning to hash: a comprehensive survey of deep learning-based hashing methods

Explosive growth of big data demands efficient and fast algorithms for nearest neighbor search. Deep learning-based hashing methods have proved their efficacy to learn advanced hash functions that suit the desired goal of nearest neighbor search in large image-based data-sets. In this work, we present a comprehensive review of different deep learning-based supervised hashing methods particularly for image data-sets suggested by various researchers till date to generate advanced hash functions. We categorize prior works into a five-tier taxonomy based on: (i) the design of network architecture, (ii) training strategy based on nature of data-set, (iii) the type of loss function, (iv) the similarity measure and, (v) the nature of quantization. Further, different data-sets used in prior works are reported and compared based on various challenges in the characteristics of images that are part of the data-sets. Lastly, different future directions such as incremental hashing, cross-modality hashing and guidelines to improve design of hash functions are discussed. Based on our comparative review, it has been observed that generative adversarial networks-based hashing models outperform other methods. This is due to the fact that they leverage more data in the form of both real world and synthetically generated data. Furthermore, it has been perceived that triplet-loss-based loss functions learn better discriminative representations by pushing similar patterns together and dis-similar patterns away from each other. This study and its observations shall be useful for the researchers and practitioners working in this emerging research field.

     

Annealing temperature-dependent structural and electrical properties of (Ta2O5)1-x - (TiO2)x thin films,x ≤ 0.11

(Ta₂O₅)_1-x- (TiO₂)_x (TTO_x) thin films, with x = 0, 0.03, 0.06, 0.08, and 0.11, were deposited using magnetron direct current (DC) sputtering method onto the P/boron-silicon (1 0 0) substrates by varying areas of Tantalum and Titanium metallic targets, in oxygen environment at ambient temperature. The as-deposited thin films were annealed at temperatures ranging from 500 to 800 °C. Generally, the formation of the Ta₂O₅ structure was observed from the X-ray diffraction measurements of the annealed films. The capacitance of prepared metal– oxide– semiconductor (MOS) structures of Ag/TTO_x/p-Si was measured at 1 MHz. The dielectric constant of the deposited films was observed altering with varying composition and annealing temperature, showing the highest value 71, at 1 MHz, for the TTO_x films, x = 0.06, annealed at 700 °C. With increasing annealing temperature, from 700 to 800 °C, the leakage current density was observed, generally decreasing, from 10^?5 to 10^?8 A cm^?2, for the prepared compositions. Among the prepared compositions, films with x = 0.06, annealed at 800 °C, having the observed value of dielectric constant 48, at 1 MHz; and the leakage current density 2.7 × 10^?8 A cm^?2, at the electric field of 3.5 × 10⁵ V cm^?1, show preferred potential as a dielectric for high-density silicon memory devices.     

Performance Investigations and PAPR Reduction Analysis Using Very Efficient and Optimized Amended SLM Algorithm for Wireless Communication OFDM System

Wireless Personal Communications - The orthogonal frequency division multiplexing (OFDM) is the most encouraging multi-carrier modulation system chosen for the high data rates but the objective is...     

A QoS Aware Resource Placement Approach Inspired on the Behavior of the Social Spider Mating Strategy in the Cloud Environment

Wireless Personal Communications - The efficient management of resource sharing plays a crucial role in the cloud execution environment. The constraints such as heterogeneity and dynamic nature of...     

A Survey of Various Schedulers Used for Fair Bandwidth Allocation in WiMAX: IEEE 802.16

ABSTRACT

Wireless Interoperability for Multiple Access (WiMAX) is one of the emerging fields of high-speed wireless communication that has enormous capabilities due to its range and the connection speed. Like wireless local area networks (LANs), WiMAX networks implement multiple quality of service (QoS) frameworks at the Media Access Control (MAC) level for assured data, voice, and video services. The question of ensuring QoS is basically how to distribute available resources to users in order to satisfy QoS parameters such as latency, jitter and throughput requirements. IEEE 802.16 standard does not have any particular guidelines on scheduling of incoming and outgoing data. This has caught the attention of researchers working on WiMAX. This article discusses the various issues in WiMAX along with a classification of various scheduling approaches based upon the type of scheduler for the sake of better understanding the scheduling problem and analyzing various available theories.     

An MRI brain disease classification system using PDFB-CT and GLCM with kernel-SVM for medical decision support

Multimedia Tools and Applications - The automatic binary classification of normal and abnormal subjects using magnetic resonance (MR) brain images has made remarkable progress in recent years. This...     

Study of Corrosion Behavior and In Vitro Bioactivity of Single NbSi2 and Duplex NbSi2/Nb5Si3 Coatings on Nb Substrates for Biomedical Applications

Protection of Metals and Physical Chemistry of Surfaces - Single NbSi2 and duplex NbSi2/Nb5Si3 coatings were successfully applied on Nb substrates using halide activated pack cementation (HAPC)...