Defence Science Journal
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Robust, Efficient and Low Profile Fractal Enabled EBG Incorporated Wearable Antenna for WLAN Standards
Get PDFA compact, robust Koch fractal combined triangular monopole antenna incorporated with a Sierpinski fractal EBG unit cell array is proposed for integral solutions of wearable devices in WLAN standards. The fractal enabled EBG-Antenna has a modified triangular microstrip that acts as a radiator and a 2X2 array of Sierpinski square EBG unit cells as a reflective surface to enhance the performance also as a shield linking the antenna and human body. The proposed antenna demonstrations and impedance match bandwidth of 32 MHz, a gain of 7.86 dBi, Front to back ratio of 13 dB, Radiation Efficiency of 90.35 % at 2.45 GHz in free space. The EBG-Antenna performs well under different bending conditions and human tissue loading as verified by measurements. The specific absorption rate (SAR) is also evaluated and found within limits as per standards. The computed results accomplished the SAR of 0.302 W/Kg, 0.1423 W/Kg for 1 g, 10 g of tissue, respectively, which demonstrates about a 95 % drop associated with the antenna without EBG. Furthermore, the fractal loading makes the antenna compact; EBG introduced at the underside of the monopole antenna gives a high gain-bandwidth product and disengages the human body and the antenna, making the realized antenna a potential candidate with possible seamless incorporation of specified wearable applications in WLAN standards
Congestion Prediction in Internet of Things Network using Temporal Convolutional Network A Centralized Approach
Get PDFThe unprecedented ballooning of network traffic flow, specifically, Internet of Things (IoT) network traffic, has big stressed of congestion on todays Internet. Non-recurring network traffic flow may be caused by temporary disruptions, such as packet drop, poor quality of services, delay, etc. Hence, the network traffic flow estimation is important in IoT networks to predict congestion. As the data in IoT networks is collected from a large number of diversified devices which have unlike format of data and also manifest complex correlations, so the generated data is heterogeneous and nonlinear in nature. Conventional machine learning approaches unable to deal with nonlinear datasets and suffer from misclassification of real network traffic due to overfitting. Therefore, it also becomes really hard for conventional machine learning tools like shallow neural networks to predict the congestion accurately. Accuracy of congestion prediction algorithms play an important role to control the congestion by regulating the send rate of the source. Various deeplearning methods (LSTM, CNN, GRU, etc.) are considered in designing network traffic flow predictors, which have shown promising results. In this work, we propose a novel congestion predictor for IoT, that uses Temporal Convolutional Network (TCN). Furthermore, we use Taguchi method to optimize the TCN model that reduces the number of runs of the experiments. We compare TCN with other four deep learning-based models concerning Mean Absolute Error (MAE) and Mean Relative Error (MRE). The experimental results show that TCN based deep learning framework achieves improved performance with 95.52% accuracy in predicting network congestion. Further, we design the Home IoT network testbed to capture the real network traffic flows as no standard dataset is available
Solution of Large Sparse System of Linear Equations over GF(2) on a Multi Node Multi GPU Platform
Get PDFWe provide an efficient multi-node, multi-GPU implementation of the Block Wiedemann Algorithm (BWA)to find the solution of a large sparse system of linear equations over GF(2). One of the important applications ofsolving such systems arises in most integer factorization algorithms like Number Field Sieve. In this paper, wedescribe how hybrid parallelization can be adapted to speed up the most time-consuming sequence generation stage of BWA. This stage involves generating a sequence of matrix-matrix products and matrix transpose-matrix products where the matrices are very large, highly sparse, and have entries over GF(2). We describe a GPU-accelerated parallel method for the computation of these matrix-matrix products using techniques like row-wise parallel distribution of the first matrix over multi-node multi-GPU platform using MPI and CUDA and word-wise XORing of rows of the second matrix. We also describe the hybrid parallelization of matrix transpose-matrix product computation, where we divide both the matrices row-wise into equal-sized blocks using MPI. Then after a GPU-accelerated matrix transpose-matrix product generation, we combine all those blocks using MPI_BXOR operation in MPI_Reduce to obtain the result. The performance of hybrid parallelization of the sequence generation step on a hybrid cluster using multiple GPUs has been compared with parallelization on only multiple MPI processors. We have used this hybrid parallel sequence generation tool for the benchmarking of an HPC cluster. Detailed timings of the complete solution of number field sieve matrices of RSA-130, RSA-140, and RSA-170 are also compared in this paper using up to 4 NVidia V100 GPUs of a DGX station. We got a speedup of 2.8 after parallelization on 4 V100 GPUs compared to that over 1 GPU
Application of a D Number based LBWA Model and an Interval MABAC Model in Selection of an Automatic Cannon for Integration into Combat Vehicles
Get PDFA decision making procedure for selection of a weapon system involves different, often contradictory criteriaand reaching decisions under conditions of uncertainty. This paper proposes a novel multi-criteria methodology based on D numbers which enables efficient analysis of the information used for decision making. The proposed methodology has been developed in order to enable selection of an efficient weapon system under conditions when a large number of hierarchically structured evaluation criteria has to be processed. A novel D number based Level Based Weight Assessment – Multi Attributive Border Approximation area Comparison (D LBWA-MABAC) model is used for selection of an automatic cannon for integration into combat vehicles. Criteria weights are determined based on the improved LBWA-D model. The traditional MABAC method has been further developed by integration of interval numbers. A hybrid D LBWA-MABAC framework is used for evaluation of an automatic cannon for integration into combat vehicles. Nine weapon systems used worldwide have been ranked in this paper. This multicriteria approach allows decision makers to assess options objectively and reach a rational decision regarding the selection of an optimal weapon system. Validation of the proposed methodology is performed through sensitivity analysis which studies how changes in the weights of the best criterion and the elasticity coefficient affect the ranking results
Optimisation of Flight and Maintenance Planning for Defence Aviation with Modified Artificial Bee Colony Algorithm
Get PDFThe planning of flight operations and maintenance is a crucial activity for both commercial and military aircraft. Military aircraft have to be always mission-ready. The task of ensuring this can become quite challenging when several operational requirements and maintenance constraints are to be fulfilled simultaneously. This paper, therefore, addresses the optimisation of flight and maintenance planning (FMP) when several diverse factors such as aircraft flying hours (AFH), flight cycles (FC), calendar life, annual flying requirement (AFR), etc. are to be factored in. Such a problem has not been considered previously. Because the problem can become unwieldy to solve by other methods, two schemes, that is, the genetic algorithm (GA) and modified artificial bee colony (ABC) algorithm for constrained optimisation have been utilised. The objective is to maximise the utilisation rate (UR) of aircraft, while also satisfying other operational and maintenance constraints. The algorithm is tested on a fleet of eight aircraft. In addition to a one-year planning period, a planning horizon of ten years has also been simulated. The results show that both the GA and modified ABC algorithm can be effectively used to solve the FMP problem
Aeroload Simulation of Interceptor Missile using Fin Load Simulator
Get PDFInterceptor missiles are designed to destroy enemy targets in air. Targets can be destroyed either in atmosphere or out of atmosphere. So for Air Defence scenario, a two layer protection system is required with one taking care of exo atmosphere and another endo atmosphere. In this Air Defence scenario, irrespective of target trajectory interceptor should neutralise it. So the control, guidance are to be designed and validated thoroughly with various scenarios of interceptor and target. These interceptors sense the rates from rate gyroscopes and accelerations from accelerometers which are fitted on board the interceptor. The navigation algorithm calculates the interceptor’s position and velocity from these rates and accelerations from time to time. Using these interceptor data and target information received from ground RADAR or on board seeker, guidance calculates accelerations demand and subsequently rate demand. The control algorithm runs in on board mission computer along with guidance. The control algorithm calculates the commanded rate and eventually commanded deflections to the control fins to move towards the target. The fins have to move as per commanded deflections to meet the mission objective of hitting the target. But the load known as aeroload which comes on the control fins during mission, causes control fins not to move as per command. Due to the difference between control command and physical movement of fin, the expected path towards target deviates. This increases the miss distance and also misses the target hit. This aeroload scenario is to be simulated on ground and some feature is to be designed to take care of it during mission. By studying the control system behaviour due to load, the control autopilot is to be automatically tuned to compensate for the loss in commanded deflections. This scenario can be carried out in Hardware-in-Loop simulation (HILS) setup. Mission load conditions can be applied on hardware actuation system in HILS setup and mission performance can be seen and also with different loads and different autopilot tunings
Relook at Aileron to Rudder Interconnect
Get PDFThe implementation of interconnect gain from aileron to rudder surface on the majority of the aircraftis to decrease sideslip which is generated because of adverse yaw with the movement of control stick in lateral axis and also enhances the turning rate performance.The Aileron to Rudder Interconnect (ARI)involves significant part to decouple the Dutch roll oscillations from roll rate response to aileron command. ARI is feed-forward gain whichis susceptible to aircraft system uncertainty. Incorrect ARI gain can lead to side slip buildup which can cause aircraft to depart in case of fault scenarios. Four systematic ARI design methods are proposed. One of the proposed methods which use the norm of ARI transfer function at roll damping frequency is suitable for online reconfiguration of control law. The reconfiguration of ARI gain is illustratedwith the simulation responses of fault scenario case of aileron surface damage
Analysis Design and Simulation of an Axially partitioned Dielectric loaded Bi frequency MILO
Get PDFIn this paper, a bi-frequency magnetically insulated line oscillator (MILO) was proposed and designed. The bi-frequency MILO proposed has two axially partitioned slow-wave interaction structures (SWS) and the second SWS is dielectric-loaded to create the frequency shift in the resonant frequency. The conventional MILO device design methodology was followed along with two SWSs separated by a segregation cavity. The dispersion relation of the dielectric-loaded SWS was calculated using an equivalent circuit approach. Furthermore, the cold analysis was carried out to find the energy stored in the different SWSs to validate the device oscillation frequency. The beam wave interaction behaviour and device RF output performance were investigated through 3D PIC (Particle-in-cell) simulation for typical diode voltage of 550 kV, and current 48 kA, respectively. Simulation results illustrate that the proposed MILO generates RF peak power of ~3.5 GW at frequencies 3.62 GHz and 3.72 GHz. The conversion efficiency of the device was ~13.25%
Design and Simulation of Extended Interaction Cavities for a Ka band Multi beam Klystron
Get PDFThis article reports about the design approach, electromagnetic simulation and analysis results of high-frequency ladder-type input, output, and intermediate RF cavaties for Ka-band multi-beam extended interaction klystron. Several parameters of the cavity, such as quality factor, shunt impedance, etc., have been investigated by the assistance of electromagnetic software CST microwave studio
Secret Key Generation Schemes for Physical Layer Security
Get PDFPhysical layer security (PLS) has evolved to be a pivotal technique in ensuring secure wireless communication. This paper presents a comprehensive analysis of the recent developments in physical layer secret key generation (PLSKG). The principle, procedure, techniques and performance metricesare investigated for PLSKG between a pair of users (PSKG) and for a group of users (GSKG). In this paper, a detailed comparison of the various parameters and techniques employed in different stages of key generation such as, channel probing, quantisation, encoding, information reconciliation (IR) and privacy amplification (PA) are provided. Apart from this, a comparison of bit disagreement rate, bit generation rate and approximate entropy is also presented. The work identifies PSKG and GSKG schemes which are practically realizable and also provides a discussion on the test bed employed for realising various PLSKG schemes. Moreover, a discussion on the research challenges in the area of PLSKG is also provided for future research