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Table Of Integrals Series And Products

In this letter, we derive the probability density function (PDF) and cumulative distribution function (CDF) of the minimum of two non-central Chi-square random variables with two degrees of freedom in terms of power series. With the help of the derived PDF and CDF, we obtain the exact ergodic capacity of the following adaptive protocols in a decode-and-forward (DF) cooperative system over dissimilar Rician fading channels: (i) constant power with optimal rate adaptation; (ii) optimal simultaneous power and rate adaptation; (iii) channel inversion with fixed rate. By using the analytical expressions of the capacity, it is observed that the optimal power and rate adaptation provides better capacity than the optimal rate adaptation with constant power from low to moderate signal-to-noise ratio values over dissimilar Rician fading channels. Despite low complexity, the channel inversion based adaptive transmission is shown to suffer from significant loss in capacity as compared to the other adaptive transmission based techniques over DF Rician channels.

On the Capacity of Decode-and-Forward Relaying over Rician Fading Channels

Nowadays, filament wound composite pipes (GRP) are used as a structural element in many applications such as natural gas and oil transmission lines, and portable bridge constructions for military purposes. GRP pipes can expose to impact loading from various causes. This loading can cause an invisible level of damage. Thus, the detection and evaluation of such damages are of great importance. In this study, the low velocity impact response of (±55°)3 filament wound E-glass/epoxy composite pipes has been studied. The pipes have been subjected to drop weight impact loading with various impact energies. The force-time and force-displacement relations have been examined. The impact damage formation was also evaluated. It is concluded that the damage development in the pipes is controlled by displacement trough radial direction. The obtained results were evaluated statistically by means of Weibull approach. Microscopy analysis of impacted region revealed that debonding, radial cracks, transfer cracks and delamination damage modes are the main observed damage modes.

Experimental and statistical analysis of low velocity impact response of filament wound composite pipes

Fast and automated recognizing of abnormal behaviors in crowded scenes is significantly effective in increasing public security. The traditional procedure of recognizing abnormalities in the Web of Thing (WoT) platform comprises monitoring the activities and describing the crowd properties such as density, trajectory, and motion pattern from the visual frames. Accordingly, incorporating real-time security monitoring based on the WoT platform and machine learning algorithms would significantly enhance the influential detection of abnormal behaviors in the crowds. This paper addresses various automatic and real-time surveillance methods for abnormal event detection to recognize the dynamic crowd behavior in security applications. The critical aspect of security and protection of public places is that we cannot manually monitor the unpredictable and complex crowded environments. The abnormal behavior algorithms have attempted to improve efficiency, robustness against pixel occlusion, generalizability, computational complexity, and execution time. Similar to the state-of-the-art abnormal behavior detection of crowded scenes, we broadly classified methods into different categories such as tracking, classification based on handcrafted extracted features, classification based on deep learning, and hybrid approaches. Hybrid and deep learning methods have been found to have more satisfactory results in the classification stage. A set of video frames called Motion Emotion Dataset (MED) is employed in this study to examine the various conditions governing these methods. Incorporating an appropriate real-time approach with considering WoT platform can facilitate the analysis of crowd and individuals’ behavior for security screening of abnormal events.

A survey on deep learning-based real-time crowd anomaly detection for secure distributed video surveillance

The mobile demands and future business context are anticipated to be resolved by the fifth-generation (5G) of mobile communication systems. It is expected to provide an utterly mobile device, connected society, and support the demanding services of various use cases (UCs). This is intended to meet the demand requirement by providing services at tens of Gbps in terms of data rates, higher mobility range, lower latencies, and massive connectivity density devices per square kilometer. A comprehensive and up-to-date survey of the different developed and proposed use cases is presented in this paper. The first part of the paper presents the overview of the new 5G Architecture by introducing new features such as the new radio interface (New Radio), an overview of the 5G Core Network, minimum requirements, and the Radio Access Network, 5G spectrum requirements and other fundamentals of the network. Secondly, a detailed review of the developed and proposed use cases for 5G communications by the standards development organizations (SDO) and other key players in mobile communication is provided. Thirdly, we went ahead to propose spectrum bands for the deployment of the various use cases based on the low-, mid-, and high-band spectrum and further classified the use cases with respect to their relevance and family, identifying the IMT-2020 test environments and the usage scenarios derived by the 3GPP, fourthly, the channel capacity and the bandwidth of the spectrum was studied, simulated and compared to ascertain the spectrum proposed in this paper for each UC family. Hence, this paper serves as a guideline for understanding the future 5G deployment scenarios in various environments. This would allow system developers to design and implement 5G channel characterization models specific to the usage scenarios to meet the system requirements.

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5G Mobile Communication Applications: A Survey and Comparison of Use Cases

Crowd anomaly detection using Aggregation of Ensembles of fine-tuned ConvNets

In 5G communication, spectrum sensing is a viable technology to use the available spectrum efficiently. Energy detection based spectrum sensing is known to be very simple as far as the implementation of hardware circuitry is concerned. The performance of Energy Detector (ED) over α–η–μ/gamma and α–κ–μ/gamma composite fading channels is obtained using numerical approximation. Unified analytic expressions for the average probability of detection and average area under the receiver operating characteristic curves (AUC) are derived for both the channels using Gaussian-Laguerre method. The produced results are very generic in the sense that the performance already derived for generalized distributions such as α–η–μ, α– κ–μ, η–μ/gamma, α–μ/gamma, κ–μ/gamma and their inclusive ones can be easily evaluated using the these results. The impact of the system parameters on the performance of ED is studied in terms of complimentary receiver operating characteristics (CROC) and AUC.

Energy detection based spectrum sensing for gamma shadowed α–η–μ and α–κ–μ fading channels

This study investigates the unified performance analysis of an energy detector (ED) over α - η - μ /IG and α - κ - μ /IG generalized fading channels. The probability density functions (PDF) of the received signal-to-noise ratio (SNR) for the composite fading channels are derived using Gauss-Laguerre method. Novel analytical expressions for the average probability of detection (PD) for a single user and cooperative spectrum sensing (SS) are derived. The effects of diversity and noise uncertainty on the average PD are also presented. Rapidly convergent infinite series representations for the average PD are derived in terms of the upper bound of the truncation error. These expressions are used to analyze the behavior of ED-based SS over moderate, severe and extreme fading conditions, and to investigate the use of cooperation and diversity as a means of mitigating the fading effects. The accuracy of the derived expressions is validated through comparison of results obtained by Monte-Carlo simulations.

ED performance over α-η-μ/IG and α-κ-μ/IG generalized fading channels with diversity reception and cooperative sensing: A unified approach

With the expansion of IoT and device-to-device communication applications, the security and privacy of the information have been kept at the forefront. The existence of a secondary eavesdropper, which attempts to access the confidential information of the legitimate partners, makes the data communication insecure. In this regard, we study the effect of randomness caused by the Beaulieu-Xie fading channel on the performance of physical layer security. To this end, the analysis for the secrecy outage probability (SOP) and average secrecy capacity (ASC) is carried out. Further, we derived the closed-form expressions for lower-bound of secrecy outage probability and strictly positive secrecy capacity (SPSC) for the said channel. To get more insight into the system, the high-power and low-power analysis of the ASC are also provided. Besides, the impact of different fading parameters on the system matrices is also investigated. Finally, the theoretical results are verified via extensive Monte Carlo simulations.

On the physical layer security over Beaulieu-Xie fading channel

Internet of things contains the hefty number of devices communicating with each other; give rise to the problem of spectrum scarcity. Cognitive radio has emerged as the promising solution to this problem. Spectrum sensing is the important function of cognitive radio and energy detector is the most popular technique used for spectrum sensing. In this paper, the performance of energy detector (ED) over α–η–μ fading channel has been analyzed. The analytical expressions for average probability of detection and average area under the receiver operating characteristics curve (AUC) are derived for the generalized fading channel in terms of the bivariate Fox H-function. The closed-form mathematical expressions for the average probability of detection for cooperative spectrum sensing as well as square law selection diversity reception are derived. The implication of the system parameters on the performance of ED is studied in terms of complimentary receiver operating characteristics and AUC. It is shown that the performance of ED can be improved when cooperation and diversity are employed. The derived results are generic and can be directly used for the performance analysis of η–μ and α–μ fading channels and their special cases. Monte-Carlo simulations are incorporated for validating the accuracy of the derived results.

Sandeep Kumar

Papers

Crowd anomaly detection using Aggregation of Ensembles of fine-tuned ConvNets

Energy detection based spectrum sensing for gamma shadowed α–η–μ and α–κ–μ fading channels

ED performance over α-η-μ/IG and α-κ-μ/IG generalized fading channels with diversity reception and cooperative sensing: A unified approach

On the physical layer security over Beaulieu-Xie fading channel

Performance of ED Based Spectrum Sensing Over α–η–μ Fading Channel