Aerial image-based target object detection has several glitches such as low accuracy in multi-scale target detection locations, slow detection, missed targets, and misprediction of targets. To solve this problem, this paper proposes an improved You Only Look Once (YOLO) algorithm from the viewpoint of model efficiency using target box dimension clustering, classification of the pre-trained network, multi-scale detection training, and changing the screening rules of the candidate box. This modified approach has the potential to be better adapted to the positioning task. The aerial image of the unmanned aerial vehicle (UAV) can be positioned to the target area in real-time, and the projection relation can convert the latitude and longitude of the UAV. The results proved to be more effective; notably, the average accuracy of the detection network in the aerial image of the target area detection tasks increased to 79.5%. The aerial images containing the target area are considered to experiment with the flight simulation to verify its network positioning accuracy rate and were found to be greater than 84%. This proposed model can be effectively used for real-time target detection for multi-scale targets with reduced misprediction rate due to its superior accuracy.

In wireless personal area networks (WPANs), devices can communicate with each other without relying on a central router or access point. They can improve performance and efficiency by allowing devices to share resources directly; however, managing resource allocation and optimizing communication between devices can be challenging. This paper proposes an intelligent load-based resource optimization model to enhance the performance of device-to-device communication in 5G-WPAN. Intelligent load-based resource optimization in device-to-device communication is a strategy used to maximize the efficiency and effectiveness of resource usage in device-to-device (D2D) communications. This optimization strategy is based on optimizing the network’s resource load by managing resource utilization and ensuring that the network is not overloaded. It is achieved by monitoring the current load on the network and then adjusting the usage of resources, such as bandwidth and power, to optimize the overall performance. This type of optimization is essential in D2D communication since it can help reduce costs and improve the system’s performance. The proposed model has achieved 86.00% network efficiency, 93.74% throughput, 91.94% reduced latency, and 92.85% scalability.

Multilevel inverter had been paid a lot of attention from the academia and research community in recent times due to its role in high and medium power applications. In this paper, a detailed survey is made on the recently designed multilevel inverter to find the suitability of the inverters for particular applications. Research is performed on various types of multilevel inverters such as: Symmetric, asymmetric, hybrid and modularized multilevel inverter in order to identify the issues in generating more levels at the output. A summary of various issues in multilevel inverter with reduced switch count is provided, so that a novel topology of multilevel inverter can be designed in future. Further, an 81-level switched ladder multilevel inverter using unidirectional and bidirectional switches is designed. Simulation work is carried out using Matlab/Simulink in order to validate the performance of the inverter with change in resistive load and impedance load. The output of the 81-level inverter is fed to a 110 V, 186.5 W single phase induction motor in order to study the characteristics, further speed control of motor is performed by varying the input voltage of the motor and the results are presented.

In recent years, human action recognition is modeled as a spatial-temporal video volume. Such aspects have recently expanded greatly due to their explosively evolving real-world uses, such as visual surveillance, autonomous driving, and entertainment. Specifically, the spatio-temporal interest points (STIPs) approach has been widely and efficiently used in action representation for recognition. In this work, a novel approach based on the STIPs is proposed for action descriptors i.e., Two Dimensional-Difference Intensity Distance Group Pattern (2D-DIDGP) and Three Dimensional-Difference Intensity Distance Group Pattern (3D-DIDGP) for representing and recognizing the human actions in video sequences. Initially, this approach captures the local motion in a video that is invariant to size and shape changes. This approach extends further to build unique and discriminative feature description methods to enhance the action recognition rate. The transformation methods, such as DCT (Discrete cosine transform), DWT (Discrete wavelet transforms), and hybrid DWT+DCT, are utilized. The proposed approach is validated on the UT-Interaction dataset that has been extensively studied by past researchers. Then, the classification methods, such as Support Vector Machines (SVM) and Random Forest (RF) classifiers, are exploited. From the observed results, it is perceived that the proposed descriptors especially the DIDGP based descriptor yield promising results on action recognition. Notably, the 3D-DIDGP outperforms the state-of-the-art algorithm predominantly.

Multilevel inverters have made another surge of enthusiasm for industry and investigation. While the set up topologies have wound up being an achievable choice in a broad assortment of high-power medium-voltage applications, there has been a dynamic energy for the advancement of fresher topologies. Decrease in general part considers contrasted with the traditional topologies has been a vital objective in the as of late presented topologies. In this paper, a segment of the starting late proposed multilevel inverter topologies with decreased power switch number are studied and evaluated. This paper will serve as an associate and a redesign with these topologies, both to the extent of subjective and quantitative parameters.

Now a day the photovoltaic (PV) age is continuously notable, while regular burdens require significantly more high-control quality. One PV generator providing to nonlinear burdens is wanted to be consolidated with a limit as an Active Power Filter (APF). In our errand, a three-arrange three-wire system, including a bare essential PV generator, modified single completed fundamental inductor converter (M-SEPIC) for high voltage change is sketched out. Furthermore, to separate greatest radiation control a most extreme power point following, calculation is utilized. Here a dc/air conditioning molding voltage source converter to go about as an Active power channel (APF), is proposed. The incite control speculation is utilized to design the PV-APF controller, which shows tried and true displays. Space vector direction (SVM) control system is used as a piece of the PV-APF controller for better execution.