Energy harvesting materials and systems have become a popular study topic that is rapidly expanding. The harvesters will be used for a variety of applications, including distributed wireless sensor nodes for structural health monitoring, embedded and implanted sensor nodes for medical applications, recharging large system batteries, monitoring pressure in automobiles, powering unmanned vehicles, and running security systems in domestic settings. Components and devices at micro-macro sizes, spanning materials, electronics, and integration, have recently been developed. Energy harvesting has

Static random-access memory (SRAM) is a cornerstone in modern microprocessors architecture, as it has high power consumption, large area, and high complexity. Also, the stability of the data in the SRAM against the noise and the performance under the radian exposure are main concern issues. To overcome these limitations in the quest for higher information density by memory element, the ternary logic system has been investigated, showing promising potential compared with the conventional binary base. Moreover, carbon nanotube field effect transistor (CNTFET) is a new alternative device with

Countries are collaborating to make agriculture more efficient by combining new technologies to improve its procedure. Improving irrigation efficiency in agriculture is thus critical for the survival of sustainable agricultural production. Smart irrigation methods can enhance irrigation efficiency, specially with the introduction of wireless communication systems, monitoring devices, and enhanced control techniques for efficient irrigation scheduling. The study compared on a wide range of study subjects to investigate scientific approaches for smart irrigation. As a result, this project

This chapter presents results on the most suitable bio-impedance circuits for modeling woody plants. The modified double-shell, the modified triple Cole-Cole, and the traditional wood circuit models are compared for fitting experimentally measured data. Consequently, a modified circuit model is proposed. This model gives the best results for all interelectrode spacing distances when compared to the other circuits. All impedance data have been measured using the research-grade SP150 electrochemical station in the frequency range 0.1 Hz to 200 kHz. The fitting is done using the Zfit of the

Impedance spectroscopy has became an essential non-invasive tool for quality assessment measurements of the biochemical and biophysical changes in plant tissues. The electrical behaviour of biological tissues can be captured by fitting its bio-impedance data to a suitable circuit model. This paper investigates the use of power-law filters in circuit modelling of bio-impedance. The proposed models are fitted to experimental data obtained from eight different fruit types using a meta-heuristic optimization method (the Water Cycle Algorithm (WCA)). Impedance measurements are obtained using a

We introduce a new chaotic system with nonhyperbolic equilibrium and study its sensitivity to different numerical integration techniques prior to implementing it on an FPGA. We show that the discretization method used in numerically integrating the set of differential equations in MATLAB and Mathematica does not yield chaotic behavior except when a low accuracy Euler method is used. More accurate higher-order numerical algorithms (such as midpoint and fourth-order Runge-Kutta) result in divergence in both MATLAB and Mathematica (but not Python), which agrees with the divergence observed in an

Wireless power transfer (WPT) is highly desirable for applications with battery restrictions, such as biomedical applications. For example, in the case of implantable devices, power is transmitted through the human body, which has dielectric characteristics that must be considered during the design of the WPT system. This paper examines capacitive power transfer through the human body and formulates the complete WPT system, including the human body model. The power delivered to the implantable device is also analyzed. Finally, the system efficiency is discussed under different body and load

Air quality assessment has been discussed for urban environments with a high degree of industrialization, as they are infested with hazardous chemicals and airborne pollutants. The assessment is carried out by monitoring stations, that basically support limited areas while leaving large geographical areas uncovered. The expansion in the agriculture sector directed us towards air quality assessment on the farms. This is because research has shown that crops can be injured when exposed to high concentrations of various air pollutants, while also affecting farmers' health states. But those air

The applications of Federated Learning are many, and they can be used to predict electricity consumption and, at the same time, enable smart meters to collaboratively learn a shared model while keeping all their data locally in their own private database. With this approach, the central model will see more data and will work better to predict electricity consumption more accurately than the models trained on only one local Dataset. The planning of infrastructure, grid operation, and budgeting all depend on accurate load forecasting. As a result, this paper suggests federated learning for load

Optogenetic-based neuroprosthetic therapies are increasingly being considered for human trials. However, the optoelectronic design of clinical-grade optogenetic-based neuroprosthetic probes still requires some thought. Design constraints include light penetration into the brain, stimulation efficacy, and probe/tissue heating. Optimisation can be achieved through experimental iteration. However, this is costly, time-consuming and ethically problematic. Hence it is highly desirable to have an alternative to excessive animal trials. Thus, a simulation tool for optimising probe design can be an