Securing optical transmission has become a critical concern in high-speed and data-intensive communication. Although optical networks offer high speed and large capacity, they are also vulnerable to cyberattacks, such as eavesdropping and signal manipulation. Traditional encryption methods are commonly used but often struggle to keep up with changing network conditions and can be broken using powerful attack techniques. To address these issues, this research proposes a novel chaotic signal generation with moth-flame optimization (CSG-MFO) approach, which integrates Chaotic Signal Generation (CSG) with the Moth Flame Optimization (MFO) algorithm. Chaotic signals are unpredictable and sensitive to small changes, making them great for hiding information. The MFO algorithm, inspired by the way moths move toward light in nature, is used to fine-tune the chaotic signal settings in real-time, thereby improving security and flexibility. Tests and simulations demonstrate that the CSG-MFO method outperforms traditional encryption in several key areas. It reduces errors during data transmission, making it more difficult for attackers to guess or reconstruct the signal, and adapts well to various network conditions with minimal computing power. In summary, chaos theory and the MFO algorithm provide a robust and efficient method for protecting data in modern optical networks. This method is especially useful for secure, high-speed communication in sensitive areas like national infrastructure and advanced data centers.

The need for more bandwidth in wireless communication has led to the utilization of the millimeter wave spectrum at higher frequencies. Millimeter waves will have a frequency range of 30 to 300 GHz, which corresponds to the wavelength of 10 to 1mm. Though mobile service providers are working to provide enough bandwidth at fast speeds to achieve reduced latency for improved streaming, the limited frequency range accessible is a big roadblock. This can be avoided by using mm-wave to reduce the size of various components, particularly antennas, by employing steerable antennas. The data rate limit is greatly increased by increasing the RF channel transmission capacity for portable radio channels. The propagation of millimeter wave signals was analyzed using the method of ray tracing & examining its effects and losses in the outdoor environment. The attenuation due to path loss and weather loss is significant, hence the signal cannot be propagated over long distances. The main challenges are addressed and the suggested solution is proposed for minimizing such losses incurred during the transmission of signals.

Time-domain metrics on a continuous glucose monitoring (CGM) miss hidden dynamics, but frequency-domain features detect up on oscillating patterns, which makes it easier to measure glucose variability and gain clinical understanding. This study aimed to analyze the time and frequency domain features of CGM data for three patients (PtID 65, PtID 109, and PtID 134) to assess glucose variability and control. CGM data were collected over a specified period, with key metrics such as mean glucose, standard deviation (SD), time in range (TIR), and spectral features being computed. The analysis included both time domain and frequency domain features. PtID 109 exhibited the highest mean glucose (207.86 mg/dL) and greatest variability, reflected in the highest SD (85.57 mg/dL) and the lowest TIR (38.24%). PtID 134 showed the most stable glucose levels with the highest TIR (73.60%) and the lowest SD (59.81 mg/dL). Frequency domain analysis revealed that PtID:134 had the highest spectral flatness, indicating more variability in the glucose signal’s frequency content. PtID 109 had the lowest TIR at 38.24%, whereas PtID 134 achieved 73.60%, indicating a 24% enhancement and demonstrating superior glucose stability. Dual-domain analysis offers thorough framework for comprehending glucose variability, facilitating individualized treatment and enhanced metabolic health care.