Full-state neural network observer-based hybrid quantum diagonal recurrent neural network adaptive tracking control

Neural Computing and Applications - This study introduces a neural network (NN) adaptive tracking controller-based reinforcement learning (RL) scheme for unknown nonlinear systems. First, an...     

Speech enhancement with an adaptive Wiener filter

This paper proposes an adaptive Wiener filtering method for speech enhancement. This method depends on the adaptation of the filter transfer function from sample to sample based on the speech signal statistics; the local mean and the local variance. It is implemented in the time domain rather than in the frequency domain to accommodate for the time-varying nature of the speech signals. The proposed method is compared to the traditional frequency-domain Wiener filtering, spectral subtraction and wavelet denoising methods using different speech quality metrics. The simulation results reveal the superiority of the proposed Wiener filtering method in the case of Additive White Gaussian Noise (AWGN) as well as colored noise.     

Proactive discovery protocol with security enhancement for D2D communication system

With the increase in mobile traffic and the band-width demand, Device-to-Device (D2D) communication has gained tremendous interest by the researchers, cellular operators and equipment manufacturers. However, D2D communication has been limited to study the converge services at cell edge. D2D users that located outside the cellular network coverage haven’t received enough attention. Some of the problems faced in this case are discovering process of neighbor user equipment (UE) and services, as well as designing suitable and secure protocols for D2D communication. Toward these problems, in this paper, we propose security enhancement for D2D communication based on modified elliptic curve cryptography (MECC), which provides greater efficiency in computational overhead, key sizes and bandwidths for user’s authentication applied on proactive routing protocol for neighbor and service discovery. We study Diffie–Hellman, ElGamal and MECC techniques to improve service of D2D users at cell edge. Results show that the proposed scheme can strength the secrecy with less control overhead and can increase the robustness in a wide range of scenarios for service discovery in D2D networks.

     

Detection of Abnormal Activities from Various Signals Based on Statistical Analysis

We perceive big data with massive datasets of complex and variegated structures in the modern era. Such attributes formulate hindrances while analyzing and storing the data to generate apt aftermaths. Privacy and security are the colossal perturb in the domain space of extensive data analysis. In this paper, our foremost priority is the computing technologies that focus on big data, IoT (Internet of Things), Cloud Computing, Blockchain, and fog computing. Among these, Cloud Computing follows the role of providing on-demand services to their customers by optimizing the cost factor. AWS, Azure, Google Cloud are the major cloud providers today. Fog computing offers new insights into the extension of cloud computing systems by procuring services to the edges of the network. In collaboration with multiple technologies, the Internet of Things takes this into effect, which solves the labyrinth of dealing with advanced services considering its significance in varied application domains. The Blockchain is a dataset that entertains many applications ranging from the fields of crypto-currency to smart contracts. The prospect of this research paper is to present the critical analysis and review it under the umbrella of existing extensive data systems. In this paper, we attend to critics' reviews and address the existing threats to the security of extensive data systems. Moreover, we scrutinize the security attacks on computing systems based upon Cloud, Blockchain, IoT, and fog. This paper lucidly illustrates the different threat behaviour and their impacts on complementary computational technologies. The authors have mooted a precise analysis of cloud-based technologies and discussed their defense mechanism and the security issues of mobile healthcare.

     

Ultra-High bit rate all-optical AND/OR logic gates based on photonic crystal with multi-wavelength simultaneous operation

In this paper, a novel two-dimensional photonic crystal based all-optical AND/OR logic gates are designed, simulated and optimized. The structure is built on a linear square lattice photonic crystal platform. A multi-wavelength operation, together with a simultaneous operation, is achieved at ultra-high bit rates. The concurrent operation is attained without altering the proposed design continuously, as stated in the literature. It provides simplicity because there is no auxiliary input required along with the absence of externally attached phase shift units. The enhancement process has been done to the rod radius. A magnificent representation tool is developed. The benefit of the mentioned tool lies in the data combination of different operating wavelengths, contrast ratio, and bit rate; which will establish an efficient optimization process. Each gate is enhanced independently, then an overall improvement has been done. As a result, the operation at 1.52?µm will provide a successful multi logic gate operation with ultra-high bit rates of 6.76 and 4.74 Tbit/s for AND and OR logic gates, respectively. The design has an acceptable size of (19.8?×?12.6 µm) and a contrast ratio of 9.74?dB and 17.95?dB for the designed AND and OR gate, respectively. The design is highly sensitive to the waveguide length to verify the gates on demand.     

Encoder-independent decoder-dependent depth-assisted error concealment algorithm for wireless 3D video communication

Three-Dimensional Multi-View Video (3D MVV) contains diverse video streams taken by different cameras around an object. Thence, it is an imperative assignment to fulfill efficient compression to attain future resource bonds whilst preserving a decisive reception MVV quality. The extensive 3D MVV encoding and transmission over mobile or Internet are vulnerable to packet losses on account of the existence of severe channel faults and restricted bandwidth. In this work, we propose a new Encoder-Independent Decoder-Dependent Depth-Assisted Error Concealment (EIDD-DAEC) algorithm. It invests the depth correlations between the temporally, spatially, and inter-view adjoining Macro-Blocks (MBs) to conceal the erroneous streams. At the encoder, the existing inter-view, temporal, and spatial matching are exploited to efficiently compress the 3D MVV streams and to estimate the Disparity Vectors (DVs) and Motion Vectors (MVs). At the decoder, the gathered MVs and DVs from the received coded streams are used to calculate additional depth-assisted MVs and DVs, which are afterwards combined with the collected candidate texture color MVs and DVs groups for concealing the lost MBs of inter- and intra-encoded frames. Finally, the optimum DVs and MVs concealment candidates are selected by the Directional Interpolation Error Concealment Algorithm (DIECA) and Decoder Motion Vector Estimation Algorithm (DMVEA), respectively. Experimental results on several standardized 3D MVV sequences verified the efficacy of the proposed EIDD-DAEC algorithm by achieving ameliorated efficacious objective and subjective results without generating and transporting depth maps at the encoder. The proposed work achieves high 3D MVV quality performance with an improved average Peak Signal-to-Noise Ratio (PSNR) gain by up to 0.95 ~ 2.70 dBs compared to the state-of-the-art error concealment algorithms, which do not employ depth-assisted correlations at different Quantization Parameters (QPs) and Packet Loss Rates (PLRs) of 40%.     

Hilbert Transform and Statistical Analysis for Channel Selection and Epileptic Seizure Prediction

This paper is concerned with Electroencephalography (EEG) seizure prediction, which means the detection of the pre-ictal state prior to ictal activity occurrence. The basic idea of the proposed approach for EEG seizure prediction is to work on the signals in the Hilbert domain. The operation in the Hilbert domain guarantees working on the low-pass spectra of EEG signal segments to avoid artifacts. Signal attributes in the Hilbert domain including amplitude, derivative, local mean, local variance, and median are analyzed statistically to perform the channel selection and seizure prediction tasks. Pre-defined prediction and false-alarm probabilities are set to select the channels, the attributes, and bins of probability density functions (PDFs) that can be useful for seizure prediction. Due to the multi-channel nature of this process, there is a need for a majority voting strategy to take a decision for each signal segment. Simulation results reveal an average prediction rate of 96.46%, an average false-alarm rate of 0.028077/h and an average prediction time of 60.1595 min for a 90-min prediction horizon.

     

Multiple access interference cancelation technique in optical CDMA systems

This paper presents a simple and efficient multiple access interference (MAI) cancelation technique in optical code division multiple access (OCDMA) system. The proposed technique is based on hybrid frequency shift keying (FSK) with an enhanced modified prime code as a signature sequence for coding techniques. Coherent FSK modulation along with incoherent demodulation using Arrayed-Waveguide Grating has been examined in the transceiver structure. In the proposed technique, a reference signal is constructed by using one of the addressed spreading sequences, and MAI cancelation is performed by subtracting the reference signal from the received signal of the desired user. The performance of the proposed FSK-OCDMA system is compared with the performance of the existing pulse position modulation (PPM)–OCDMA system. The simulation results reveal that the bit-error rate performance of the proposed technique is superior to the performance of the pulse position modulation (PPM) technique. Also, the results indicate that the proposed technique is very power efficient, and when the bit rate is constant, the network capacity can be expanded to accommodate a large number of simultaneous active users with low error rate. Moreover, the proposed technique simplifies the hardware of the receiver design.     

Efficient hybrid framework for transmission enhancement of composite 3D H.264 and H.265 compressed video frames

Multimedia Tools and Applications - Three-Dimensional Multi-View Video (3D-MVV) transmission over wireless networks suffers from losses. Therefore, the robust performance of 3D-MVV transmission...