Systems-on-chips need numerous predesigned cores to advance. NoC enables Multi-Core SoCs (MC_SoCs). Conventional NoC cores use power and latency on multi-hop wired connections. An effective Wireless Network-on-Chip (WiNoC) architecture can overcome NoC difficulties. On-chip antennas, transceivers, and routers replace multi-hop cable connections with high-bandwidth single-hop wireless networks using WiNoC. Nanotechnology development demands fast data transfer to overcome performance bottlenecks from sharing memory modules and connecting fabrics. This research offers a new Proactive Flow control using Adaptive Beam formation for Smart Intra-layer Data Communication technique(PF_SDC) to optimally use network resources and assure QoS in Wireless Network-on-Chip for next-generation nano-domain technology. Hybrid NoC architecture optimises application admission for data transfer over wired and wireless interconnects. Data traffic is managed by a fuzzy inference-based Intelligent Head Agent (IHA). Queue load predicts router status for the fittest path selection. IHA initiates beams at angles to admit data flow towards the target while utilising the least amount of network power and resources. A simulation model shows that the proposed system may be applied in real-world applications and consumes little power with good throughput.

The current work aims to propose an adequate thermodynamic model, in addition to proposing and evaluating two composite models for the thermal decomposition of insulating mineral oil (IMO), considering that the models based on classical diagnostic methods do not have the ability to satisfactorily reproduce empirical data. The simulation results obtained using the proposed model showed better agreement with the presented data than the results obtained using classical models. The proposed model was also used in the development of a phenomenological based diagnostic method. The characteristics of this new phenomenological proposal and the classical diagnostic methods of dissolved gas analysis are compared and discussed; the proposed method showed better performance when compared to Rogers, Doernenburg, or IEC and equivalent performance to Duval triangle method commonly used in this field of knowledge. The general procedure for applying the new diagnostic method is also described. In order to account for the event's dynamics, the suggested model in particular made it feasible to replicate intermediate scenes of equilibrium C(s). Compared to the findings from the classical models found in the literature, the two-dimensional simulation results generated with this model demonstrated a better agreement with the actual data.

Several antennas are used for sending and receiving in large MIMO (Multiple-Input-Multiple-Output) devices and assist in enhanced performances of wireless communication systems. One important component of Large MIMO systems is that MIMO detectors are placed at receiver ends, whose functions are to regain symbols broadcasts from multiple antennas. In this paper, novelAMLCD (Alternating Minimizationbased Low Complexity Detections) method is proposed in which AMs (Alternating Minimizations) are applied in initial stages to detect signals. Soft value generation is used for the second stage to estimate the signals. Finally, the more optimal estimated signal value will be chosen by applying the MPSOs (Modified Particle Swarm Optimizations). The system's functions are evaluated using CPMs (Continuous Phase Modulations) and channel’s AWGNs (Additive White Gaussian Noises). According to the results obtained, the suggested AMLCD method with modulations of CPMs outperform known methods using QAMs (Quadrature Amplitude Modulations) under multiple antennas in terms of BERs (Bit Error Rates). The AMLCD method also reduces the time complexity and computational complexity compared to the existing methods.

Information technology (IT) providers should use cloud-based services due to their flexibility, reliability, and scalability to handle the rising requirement for processing capacity. The maintenance of dependable services between cloud providers and their customers in a cloud environment, on the other hand, depends on Quality of Service (QoS) assurance. Virtual machine (VM) consolidation is nondeterministic polynomial time (NP) hard issue, and numerous heuristic techniques have been suggested to solve it. In this work, the suggested VM consolidation technique takes into account both current and future uniform distribution elephant herding optimization (UDEHO) based VM consolidation approaches for resource utilization via host overload detection (utilization prediction based potential overload detection (UP-POD)) and host underload detection (UP-PUD). A UDEHO method efficiently predicts resource use in the future. Depending on the power utilization and the number of migrations, a power-saving value is advised for identifying under-loaded hosts. Furthermore, the CloudSim toolkit is used to construct and test these techniques using the same experimental parameters. Lastly, the findings demonstrate that the suggested methodologies considerably decrease the number of VM migrations by about 0.073%, the energy usage of about 11%, and SLA violations by 6.15% while retaining QoS guarantees when compared to conventional techniques.

ABSTRACT In this paper, we propose an adaptive sliding mode-based fault tolerant control for mobile robots. While a mobile robot is tracking a given trajectory, several fault cases may occur, such as sensor model and controller faults, changes in the dynamic equation due to robot body shape or weight changes, and loss of actuator effectiveness. Disturbance signals are caused by the actuator faults and, for various reasons, can be considered the primary issue for the robots. In real-time applications, the Sliding Mode Controller (SMC) is insufficient if the robot parameters are unknown, the robot model is non-linear, and the overall system is subject to disturbances. An adaptive law is used to support the SMC to maintain the sliding surface and solve the problems of unknown system parameters, actuator faults, and disturbances. Besides SMC, the kinematic controller is also used, and its gain values are optimized using a neural network and a kinematic controller. The stability of the overall system is proven by using the Lyapunov theory. Besides actuator faults, the system is disturbed by defining a disturbance signal, which is added to the control signals. To show the effectiveness of the proposed controller, it is compared with traditional SMC and PID.

This paper presents the design, analysis and comparative study of three different configurations of Switched Reluctance Motor (SRM) suitable for In-wheel application in Electric Vehicles. C-core stator with dual rotor SRM, C-core stator with disk-type segmented rotor SRM and Dual gap inner segmented rotor SRM are designed and compared for the same stator/rotor pole, supply current, current density and outer diameter. The significant performance indices of an electric motor for an in-wheel application, such as torque ripple, torque per unit active weight and torque per unit active volume, are considered for analysis. 3D Finite Element Analysis (FEA) of the machines is performed using the software MagNet 7.5 due to the axial field distribution of the configurations. The best among the three configurations is fabricated and experimental results are presented.

Renewable energy sources, widely considered as distribution generation units, will be essential parts of the future electrical network. They will be integrated into the network at all voltage levels and act as the main controlling elements in the microgrid to stabilize the network. However, the objective of determining the suitable busbar to integrate the renewable generation source and its maximum capacity is still an indecisive problem. This article presents a methodology to select suitable busbars to integrate the renewable generation unit. A bus selection index is proposed based on three criteria, i.e. voltage deviation, active power loss, and grid energy infeed. The developed algorithm considers network busbar voltage limit and branch loading as constraints and the solution is determined using analytical technique. Algorithm is implemented in MATLAB, and MATPOWER is used for the power flow analysis. Furthermore, the proposed methodology is analysed on CIGRE and IEEE medium voltage benchmark network.

Nodes are deployed randomly in the network area of the WSN. data transmission from source to destination via intermediate nodes should be done in a secure fashion. Due to the large size of packet loss and energy consumption of sensor nodes, a secure and energy-efficient path must be required. The main objective of this research is to provide secure data transmission among node-to-node for efficient delivery of data packets to the destination. The system uses a novel hybrid firefly and BAT algorithm for path selection, an innovative trust value generation, and optimal neighborhood selection using fuzzy logic. The research employs Elliptic Curve Cryptography (ECC) combined with Diffie-Hellman exchange for key generation and key exchange. Path selection is done by fuzzy logic and optimization of selection has been carried out by hybrid BAT and Firefly algorithms. Key generation includes a time-based randomness factor that increases the complexity of cryptanalysis, thereby providing the most security. The performance of the simulation is analyzed and depicted in terms of delay, throughput, energy, and processing time. The research has been carried out using a network simulator with nodes deployed randomly in the network area with mobility as the primary concern that requires dynamic path selection.

ABSTRACT A solar-powered drive for the separately excited DC (SEDC) motor drive system has been proposed and validated. The proposed system uses a set of two cascaded series compensated buck boost converters (SCBBCs) and a push pull DC to DC converter. The maximum power point tracking (MPPT) for the solar PV energy harvesting system is based on a sliding mode controller (SMC) and the SCBBC next to the solar PV source is used for this purpose. The armature winding of the SEDC motor receives the required isolated DC voltage from a push pull converter that is powered from a common DC link that carries a battery. The field winding of the SEDC motor is fed by the second SCBBC. The speed of the SEDC motor is regulated by a separate sliding mode controller implemented in the second SCBBC. A detailed state space analysis of the SCBBC and related mathematical modelling of the complete system are presented. The simulations were carried out in the MATLAB SIMULINK environment, and an experimental prototype was developed utilizing a 200 W 110 V SEDC motor.

ABSTRACT In the existing pieces of literature about the three-coil wireless power transfer (WPT) system, a three-coil structure is proposed to increase the efficiency compared to the two-coil WPT system. The cross-coupling among three coils, compensation capacitor of the repeating coil (RPC) and the rectified load are considered incompletely. The circuit model of a three-coil WPT system with rectified load is developed by taking the cross-coupling of all coils and the compensation capacitor of RPC into consideration in this paper. The relationship among system efficiency, compensation level, and rectifier load is deduced. The detailed mathematical analysis and compensation capacitor selection of RPC are investigated to improve the system efficiency. An experimental study demonstrates that the selected compensation capacitor of RPC achieves a higher efficiency than resonant compensation in a three-coil WPT system with different cross-coupling conditions and rectifier load conditions. System efficiency is promoted from 73.9% (resonant compensation capacitor for RPC) to 84.2% (selected compensation capacitor for RPC).