The current research work proposed a novel optimization-based 2D-SIMM(Two-Dimensional Sine Iterative chaotic map with infinite collapse Mod-ulation Map)model for image *** proposed 2D-SIMM model is derived out of sine ...
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The current research work proposed a novel optimization-based 2D-SIMM(Two-Dimensional Sine Iterative chaotic map with infinite collapse Mod-ulation Map)model for image *** proposed 2D-SIMM model is derived out of sine map and Iterative Chaotic Map with Infinite Collapse(ICMIC).In this technique,scrambling effect is achieved with the help of Chaotic Shift Transform(CST).Chaotic Shift Transform is used to change the value of pixels in the input image while the substituted value is cyclically shifted according to the chaotic sequence generated by 2D-SIMM *** chaotic sequences,generated using 2D-SIMM model,are sensitive to initial *** the proposed algorithm,these initial conditions are optimized using JAYA optimization *** coefficient and entropy are considered asfitness functions in this study to evaluate the best solution for initial *** simulation results clearly shows that the proposed algorithm achieved a better performance over existing *** addition,the VLSI implementation of the proposed algorithm was also carried out using Xilinx system *** optimization,the correlation coefficient was-0.014096 and without optimization,it was 0.002585.
In the field of automation, precise control and modelling of robotic gripping are essential for efficient and reliable product utilization. This paper presents an overview of robotics modelling and simulation utilizin...
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The silicon drift detector, known for its high resolution and low noise as a semiconductor detector, is extensively utilized in fields like X-ray spectroscopy analysis and particle energy detection. The performance of...
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A transparent and flexible wideband metasurface featuring a reflective cross-polarization converter is proposed in this paper. The metasurface is designed with a single-layered rectangular and circular-shaped resonato...
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—A multi-resonating coplanar waveguide (CPW) fed flexible antenna using metamaterial unit cell is designed for various UWB wireless communication systems. The designed unit cell has the total dimension of 14.8 mm ...
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Beam-hopping technology has become one of the major research hotspots for satellite communication in order to enhance their communication capacity and ***,beam hopping causes the traditional continuous time-division m...
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Beam-hopping technology has become one of the major research hotspots for satellite communication in order to enhance their communication capacity and ***,beam hopping causes the traditional continuous time-division multiplexing signal in the forward downlink to become a burst signal,satellite terminal receivers need to solve multiple key issues such as burst signal rapid synchronization and high-per-formance ***,this paper analyzes the key issues of burst communication for traffic signals in beam hopping sys-tems,and then compares and studies typical carrier synchro-nization algorithms for burst ***,combining the requirements of beam-hopping communication systems for effi-cient burst and low signal-to-noise ratio reception of downlink signals in forward links,a decoding assisted bidirectional vari-able parameter iterative carrier synchronization technique is pro-posed,which introduces the idea of iterative processing into car-rier *** at the technical characteristics of communication signal carrier synchronization,a new technical approach of bidirectional variable parameter iteration is adopted,breaking through the traditional understanding that loop struc-tures cannot adapt to low signal-to-noise ratio burst ***,combining the DVB-S2X standard physical layer frame format used in high throughput satellite communication systems,the research and performance simulation are *** results show that the new technology proposed in this paper can significantly shorten the carrier synchronization time of burst signals,achieve fast synchronization of low signal-to-noise ratio burst signals,and have the unique advantage of flexible and adjustable parameters.
Image interpolation is the process of transforming a low-resolution image into a higher-resolution image of a different size. The current study analyzes several picture interpolation algorithms, concentrating on their...
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This paper focuses on the Energy-Efficient Hybrid Clustering Technique (EEHCT) and Bandwidth-Efficient Cluster-Based Data Aggregation to address energy consumption, bandwidth utilization, and network lifetime in wirel...
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Because of the numerous benefits, unmanned aerial vehicles (UAVs) assist ground users in maintaining a satisfactory quality of service (QoS) even when they are far from terrestrial base stations (BSs) or outside the c...
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Because of the numerous benefits, unmanned aerial vehicles (UAVs) assist ground users in maintaining a satisfactory quality of service (QoS) even when they are far from terrestrial base stations (BSs) or outside the cellular coverage area. However, the limited energy capacity of UAVs restricts their operational duration. This study, therefore, investigates how to maximize energy efficiency (EE) in a UAV-enabled data collection system to prolong the network's lifespan, taking into account variations in UAV propulsion and data reception energy. The study focuses on optimizing user associations, their instantaneous transmit power allocation (PA), and UAV's trajectory while meeting users' minimum data rate requirements. This optimization problem is challenging due to its non-convex and combinatorial nature, making analytical solutions difficult. To address this, the study uses the Markov decision process (MDP) to split the problem into two sub-problems: user association with PA and UAV's optimal successive locations. These sub-problems are then solved alternately, first deriving optimal instantaneous transmit powers for each user analytically and then employing a deep reinforcement learning (DRL) framework based on the soft actor-critic (SAC) algorithm to acquire the UAV's optimal flying path. The proposed adaptive SAC algorithm allows the UAV to adjust its speed, heading direction, and altitude while efficiently shaping rewards to adhere to practical constraints. Numerical results validate the analysis and demonstrate significant improvements in total EE compared to benchmark deep deterministic policy gradient (DDPG), twin-delayed DDPG, and particle swarm optimization techniques, with increases of $19.29\%$, $7.53\%$, and $53.96\%$, respectively. IEEE
The categorization of brain tumors is a significant issue for healthcare *** and timely identification of brain tumors is important for employing an effective treatment of this *** tumors possess high changes in terms...
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The categorization of brain tumors is a significant issue for healthcare *** and timely identification of brain tumors is important for employing an effective treatment of this *** tumors possess high changes in terms of size,shape,and amount,and hence the classification process acts as a more difficult research *** paper suggests a deep learning model using the magnetic resonance imaging technique that overcomes the limitations associated with the existing classification *** effectiveness of the suggested method depends on the coyote optimization algorithm,also known as the LOBO algorithm,which optimizes the weights of the deep-convolutional neural network *** accuracy,sensitivity,and specificity indices,which are obtained to be 92.40%,94.15%,and 91.92%,respectively,are used to validate the effectiveness of the suggested *** result suggests that the suggested strategy is superior for effectively classifying brain tumors.
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