A hybrid model for spelling error detection and correction for Urdu language

Neural Computing and Applications - Detecting and correcting misspelled words in a written text are of great importance in many natural language processing applications. Errors can be broadly...     

Context-dependent software solutions to handle video synchronization and delay in collaborative live mobile video production

The advent of modern mobile phones, 3G networks, and live video streaming has made it possible to broadcast live video from mobile devices. This is now giving rise to a new class of applications which enable mobile collaborative live video production, in which groups of amateurs work together to provide a rich broadcast of events. We focus on new and expected synchronization problems that arise in these more complex systems when broadcasting live events because of the delays that often occur in streaming over internet and mobile networks. The problem has been investigated by acquiring initial user feedback, as well as conducting technical delay measurements of two examples of such systems and relating them to existing literature. We identified two types of technical problems which affect the mixing of the streams, namely the difference in delay in multiple streams, a.k.a. asynchrony among streams, and the delay between the event itself and its presentation in the mixer. These problems affect the mixing in various ways depending on whether or not the director has visual access to the unmediated event. This knowledge has then been used to inform the conceptualization of identifiable ways of handling delays and synchronization. We suggest the introduction of a software feature providing context-dependent delay, in which these requirements can be balanced differently to fit specific contexts of use. We specifically address the different types of mixing which occurs when the director, or mixer, only has access to the topic through the mobile media (“out of view”), as well as mixing in a context in which the topic also is physically present (“in-view”) in front of the mixer.     

BSLPSDN: Base station location privacy via software-defined networking (SDN) in wireless sensor networks

Base station's location privacy in a wireless sensor network (WSN) is critical for information security and operational availability of the network. A key part of securing the base station from potential compromise is to secure the information about its physical location. This paper proposes a technique called base station location privacy via software-defined networking (SDN) in wireless sensor networks (BSLPSDN). The inspiration comes from the architecture of SDN, where the control plane is separated from the data plane, and where control plane decides the policy for the data plane. BSLPSDN uses three categories of nodes, namely, a main controller to instruct the overall operations, a dedicated node to buffer and forward data, and lastly, a common node to sense and forward the packet. We employ three kinds of nodes to collaborate and achieve stealth for the base station and thus protecting it against the traffic-analysis attacks. Different traits of the WSN including energy status and traffic density can actively be monitored by BSLPSDN, which positively affects the energy goals, expected life of the network, load on common nodes, and the possibility of creating diversion in the wake of an attack on the base station. We incorporated multiple experiments to analyze and evaluate the performance of our proposed algorithm. We use single controller with multiple sensor nodes and multiple controllers with multiple sensor nodes to show the level of anonymity of BS. Experiments show that providing BS anonymity via multiple controllers is the best method both in terms of energy and privacy.     

Power Control for Cognitive Radio Networks: A Game Theoretic Approach

In communication industry one of the most rapidly growing area is wireless technology and its applications. The efficient access to radio spectrum is a requirement to make this communication feasible for the users that are running multimedia applications and establishing real-time connections on an already overcrowded spectrum. In recent times cognitive radios (CR) are becoming the prime candidates for improved utilization of available spectrum. The unlicensed secondary users share the spectrum with primary licensed user in such manners that the interference at the primary user does not increase from a predefined threshold. In this paper, we propose an algorithm to address the power control problem for CR networks. The proposed solution models the wireless system with a non-cooperative game, in which each player maximize its utility in a competitive environment. The simulation results shows that the proposed algorithm improves the performance of the network in terms of high SINR and low power consumption.

     

Intrusion Detection Based on Bidirectional Long Short-Term Memory with Attention Mechanism

With the recent developments in the Internet of Things (IoT), the amount of data collected has expanded tremendously, resulting in a higher demand for data storage, computational capacity, and real-time processing capabilities. Cloud computing has traditionally played an important role in establishing IoT. However, fog computing has recently emerged as a new field complementing cloud computing due to its enhanced mobility, location awareness, heterogeneity, scalability, low latency, and geographic distribution. However, IoT networks are vulnerable to unwanted assaults because of their open and shared nature. As a result, various fog computing-based security models that protect IoT networks have been developed. A distributed architecture based on an intrusion detection system (IDS) ensures that a dynamic, scalable IoT environment with the ability to disperse centralized tasks to local fog nodes and which successfully detects advanced malicious threats is available. In this study, we examined the time-related aspects of network traffic data. We presented an intrusion detection model based on a two-layered bidirectional long short-term memory (Bi-LSTM) with an attention mechanism for traffic data classification verified on the UNSW-NB15 benchmark dataset. We showed that the suggested model outperformed numerous leading-edge Network IDS that used machine learning models in terms of accuracy, precision, recall and F1 score.     

Nanograin Mn-Zn ferrite smart cores to miniaturize electronic devices

Conventional ceramic and sol-gel auto combustion routes were adopted to develop Mn-Zn ferrite cores. To control high frequency (>500 kHz) losses, zirconia (0.2 wt%) and calcia (0.04 wt%) were added in Mn_0.57Zn_0.35Fe_2.08O₄. The results revealed that Mn-Zn ferrite smart cores synthesized by auto combustion process have superior properties than conventionally prepared cores. It is believed that the presence of unique properties such as nanograin microstructure, light weight and short height (thickness) dimensions have played their role to enhance the magnetic impedance of smart core to manifold. Fabricated smart core excellently performed in a test frequency band of 3-15 MHz.     

Influence of metal‐oxide‐supported bentonites on the pyrolysis behavior of polypropylene and high‐density polyethylene

In this article, we report on the pyrolysis of polypropylene (PP) and high‐density polyethylene (HDPE) in the absence and presence of plain and metal‐oxide‐impregnated bentonite clays [BCs; acid‐washed bentonite clay (AWBC), Zn/AWBC, Ni/AWBC, Co/AWBC, Fe/AWBC, and Mn/AWBC] into useful products. Thermal and catalytic runs were performed at 300°C in the case of PP and at 350°C in the case of HDPE for a contact time of 30 min. The effects of different catalysts and their concentrations on the overall yields and the yields of liquid, gas, and residue were studied. The efficacy of each catalyst is reported on the basis of the highest liquid yields (in weight percentage). The derived liquid products were analyzed by Fourier transform infrared spectroscopy and gas chromatography–mass spectroscopy; this confirmed the presence of paraffins, olefins, and naphthenes. The results indicate the catalytic role of impregnated BCs compared to plain BC with the optimum efficiency shown by Co/AWBC in the case of PP and Zn/AWBC in the case of HDPE toward the formation of liquid products in a desirable C range with the enrichment of olefins and naphthenes in the case of PP and paraffins and olefins in the case of HDPE compared to the thermal run. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41221.     

Improving properties of silicone rubber composites using macromolecular silane coupling agent (MMSCA)

Two types of vinyl silicone oil (VSO), allyl‐capped hyperbranched polycarbosilane (HBP), and triethoxysilane (TES) were employed to synthesize macromolecular silane coupling agent (MMSCA) by hydrosilylation. VSOs, HBP, and the hydrosilylated products were used as crosslinker, respectively, to improve weak mechanical properties of silicone rubber (SR). Structures of the crosslinkers were studied by gel permeation chromatography (GPC), Fourier transform infrared spectroscopy (FTIR), and nuclear magnetic resonance (NMR). Crosslinking density test and scanning electron microscope (SEM) observation showed an increased interaction between silicone rubber and fumed silica by the use of MMSCA. Mechanical properties of the resulted composites using MMSCAs were increased to varying degrees compared with those possessing crosslinkers without ethoxy group. MMSCAs were effective for further property enhancements of composites. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43415.     

Bio-cellular processes modeling on silicon substrate: receptor–ligand binding and Michaelis Menten reaction

Reducing transmit power is the most straightforward way towards more energy-efficient communications, but it results in lower SNRs at the receiver which can add a performance and/or complexity cost. At low SNRs, synchronization and channel estimation errors erode much of the gains achieved through powerful turbo and LDPC codes. Further expanding the turbo concept through an iterative receiver—which brings synchronization and equalization modules inside the loop—can help, but this solution is prohibitively complex and it is not clear what can and what cannot be a part of the iterative structure. This paper fills two important gaps in this field: (1) as compared to previous research which either focuses on a subset of the problem assuming perfect remaining parameters or is computationally too complex, we propose a proper partitioning of algorithm blocks in the iterative receiver for manageable delay and complexity, and (2) to the best of our knowledge, this is the first physical demonstration of an iterative receiver based on experimental radio hardware. We have found that for such a receiver to work, (1) iterative timing synchronization is impractical, iterative carrier synchronization can be avoided by using our proposed approach, while iterative channel estimation is essential, and (2) the SNR gains claimed in previous publications are validated in indoor channels. Finally, we propose a heuristic algorithm for simplifying the carrier phase synchronization in an iterative receiver such that computations of the log likelihood ratios of the parity bits can be avoided to strike a tradeoff between complexity and performance.     

Cognitive Radio as the Facilitator for Advanced Communications Electronic Warfare Solutions

Throughout the 1990s, Software Defined Radio (SDR) technology was viewed almost exclusively as a solution for interoperability problems between various military standards, waveforms and devices. In the meantime, Cognitive Radio (CR) – a novel communication paradigm which embodies SDR with intelligence and self-reconfigurability properties – has emerged. Intelligence and on-the-fly self-reconfiguration abilities of CRs constitute an important next step in the Communications Electronic Warfare, as they may enable the jamming entities with the capabilities of devising and deploying advanced jamming tactics. Similarly, they may also aid the development of the advanced intelligent self-reconfigurable systems for jamming mitigation. This work outlines the development and implementation of the Spectrum Intelligence algorithm for Radio Frequency (RF) interference mitigation. The developed system is built upon the ideas of obtaining relevant spectrum-related data by using wideband energy detectors, performing narrowband waveform identification, extracting the waveforms’ parameters and properly classifying the waveforms. All relevant spectrum activities are continuously monitored and stored. Coupled with the self-reconfigurability of various transmission-related parameters, Spectrum Intelligence is the facilitator for the advanced interference mitigation strategies. The implementation is done on the Cognitive Radio test bed architecture which consists of two military Software Defined Radio terminals, each interconnected with the computationally powerful System-on-Module.