Wireless networking is now central to modern life, and is anticipated to become ever more pervasive. Therefore, there may be several possible uses for combining lightweight fabric antennas. A flexible fabric is used to increase convenience, and the inclusion of antennas in garments ensures they do not have to be hand-held. Wireless deployment, a single-feed and a dual-frequency H-shaped antenna is presented. The transmitting model is used to build the H-shaped antenna. Varying the dual frequency is achieved with the aid of a capacitive range between 3.85 and 1.88 pF and a Zener diode. The operating frequencies for the cellular implementations of the H-shaped antenna are 2.5–4.5 GHz. The configuration of the antenna is built on an 80 mm × 60 mm dielectric by using FR4 epoxy substrate; the scale of the switch dimension is 0.7 mm × 1.4 mm with relative permittivity of 3.68 and the height of the substratum is 1.6 mm. The patch of the planned structure is supplied by a 50 ohm matching impedance co-axial cable. In this research work the proposed antenna structure gain is 8.2 dBi (86%) for wireless devices. Under the current structure, the high and minimal return losses are from –39.05 to –18.68 dB. The highest and lowest Voltage Standing Wave Ratio values of the proposed structure are 1.78 and 1.02, respectively.
Internet of things (IoT) will be the main part in upcoming generation devices that would not simply sense and report, also will have the controlling capability. It may be a connected vehicle, connected devices, robot, a building automation system, a door lock or a thermostat, these connected machines or devices will provide greater impact on our daily lives. Control data and the operating instructions could be protected to ensure control and autonomy for our safety and security, this could be a critical task. Privacy and security are important consideration in designing the system. With the intense growth of devices or devices with facilities such as computing and communication are carried out using a profound technology known as machine to machine (M2M) communication, which is specially designed for cross‐platform integration. In many industries, smart homes, smart cities, smart agriculture, government, connected devices, security, healthcare, education, public safety, and supply chain management. Internet of things (IoT) and machine to machine communication have to be implemented in near future. Also, this paper gives an in depth view about the different M2M techniques with interconnected IoT for truly connected, smart, and sustainable world.
The clinical indication of arrhythmia identifies specific aberrant circumstances in heart pumping that may be detected using electrical impulses during conduction or by allowing a little amount of current to travel through the electrodes, disrupting the cardiac muscle's resistance. The electrocardiogram (ECG) is one of the most important instruments for detecting cardiac arrhythmia since it is the most least intrusive and effective procedure. Physically or visually inspecting the heart is time-consuming and difficult, hence the development of computer aided diagnosis (CAD) is being developed to aid clinical decision-making. In this suggested research, a convolutional neural network (CNN)-based approach is used to automate the heartbeat classification process in order to identify cardiac arrhythmia. The improved enhancement of CNN structure has been implemented in this suggested research. The feature maps are then subjected to the max pooling process. Finally, feature maps are generated by concatenating kernels of different sizes and delivering them as an input to the fully linked layers. The MIT BIH arrhythmia database is used to implement this approach, and the total average accuracy is 99.21%. The proof of the suggested study's efficiency and efficacy in identifying cardiac arrhythmia has also been done via an experimental comparison
The problem of denoising iris pictures for iris identification systems will be discussed, as well as a novel solution based on wavelet and median filters. Different salt and pepper extraction algorithms, as well as Gaussian and speckle noises, were used. Because diverse sounds decrease picture quality during image collection, noise reduction is even more important. To reduce sounds like salt and pepper, Gaussian, and speckle, filtering (median, wiener, bilateral, and Gaussian) and wavelet transform are utilised. Provide better results as compared to other ways. A study of several efficiency indicators such as peak signal-to-noise ratio (PSNR) and mean squared error will be used to demonstrate the superiority of the proposed technique (MSE).
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