Plasmonic Photovoltaics (PVs) are an effective method for increasing optical absorption by adding metallic nanoparticles to the photovoltaic active layer. The role of these nanoparticles is confining the incident light near them in the PV cell, resulting in thin film PVs of enhanced efficiency. Therefore, different materials and new NPs shapes are used for this purpose. In this research, a step pyramid is introduced as a novel structure for nanoparticles for enhancing plasmonic PVs by embedding an array of the proposed step pyramid nanoparticles within the PV cell. Therefore, the extinction

This chapter introduces optimization algorithms for parameter extractions of three fractional-order circuits that model bioimpedance. The Cole-impedance model is investigated; it is considered one of the most commonly used models providing the best fit with the measured data. Two new models are introduced: the fractional Hayden model and the fractional-order double-shell model. Both models are the generalization of their integer-order counterpart. These fractional-order models provide an improved description of observed bioimpedance behavior. New metaheuristic optimization algorithms for

The full-wave rectifier is an essential step for extracting energy from a piezoelectric source. Yet, the inherent capacitance of the piezoelement significantly is considered a limitation of the efficiency of extraction. To address this issue, the bias-flip rectifier can be used. However, this rectifier needs large inductor and precise tuning. The large inductor increases the overall volume of the system which is inefficient. This paper address the problems with the traditional bias-flip rectifier by introducing an enhanced multi-step bias-flip rectifier to achieve a high voltage-flip

The Internet of Things (IoT) is a global network of interconnected computing, sensing, and networking devices that can exchange data and information via various network protocols. It can connect numerous smart devices thanks to recent advances in wired, wireless, and hybrid technologies. Lightweight IoT protocols can compensate for IoT devices with restricted hardware characteristics in terms of storage, Central Processing Unit (CPU), energy, etc. Hence, it is critical to identify the optimal communication protocol for system architects. This necessitates an evaluation of next-generation

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that is characterized by abnormalities in the brain, leading to difficulties in social interaction and communication, as well as learning and attention. Early diagnosis of ASD is challenging as it mainly relies on detecting abnormalities in brain function, which may not be evident in the early stages of the disorder. Facial expression analysis has shown promise as an alternative and efficient solution for early diagnosis of ASD, as children with ASD often exhibit distinctive patterns that differentiate them from typically

Image security becomes important topic because of increasing image usage in communication besides assures information security which is unseen in these images such as military and medical images. Blowfish is a superb symmetric cryptography that ensures a high degree of resistance to attacks. The proposed system modifies Blowfish algorithm by substituting the function in blowfish round with light weight function to save memory and resources of the platforms and Using 3-D chaotic system (Improved Lorenz) that work as a key timetable for creating Blowfish sub keys in order to increasing

There is an increasing interest in energy harvesting for wearable biomedical devices. This requires power conservation and management to ensure long-term and steady operation. Hence, task scheduling algorithms will be used throughout this work to provide a reliable solution to minimize energy consumption while considering the system operation constraints. This study proposes a novel power-aware task scheduler to manage system operations. For example, we used the scheduler to handle system operations, including heart rate and temperature sensors. Two optimization techniques have been used to

Water contamination with colours and heavy metals from textile effluents has harmed the ecology and food chain, with mutagenic and carcinogenic effects on human health. As a result, removing these harmful chemicals is critical for the environment and human health. Various standard physicochemical and biological treatment technologies are used; however, there are still some difficulties. Adsorption is described as a highly successful technology for removing contaminants from textile-effluents wastewater compared to other methods. Several adsorbent materials, including nanomaterials, natural

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

This research paper presents the wireless data and power transfer system for optogenetics visual cortical prosthesis. The system uses the inductive coupling power transfer and 2.4GHz Bluetooth 4.0 data transfer. This system contains two hardware parts: the external headset consists of power and data transmitters, image capture, and image processing units; the subcutaneous implant PCB consists of power and data receiver and the control unit. We also present the relative image processing method for this system. The whole system could power and control the optogenetic neural stimulus of the