Resonance frequency analysis of laser optical fiber based on microcantilever

The normal frequency of smart beams was originated utilizing FEM [Ansys and Comsol] code for first five modes by varying the position of actuator from the fixed end of the structure, and it has a suitable arrangement with analytically found the standard frequency. This paper includes learning a resonance frequency analysis of laser optical fiber based on microcantilever of designing magnetic actuator using Ansys and Comsol simulation. The design of optical fiber includes Nickel cantilever, two magnets and one coil that apply to force on the cantilever. After the current flows in the coil domain, the shape of microcantilever will be deformed. It will move to z- direction that depends on the force direction. Two methods including, Comsol Multiphysics, Ansys and analytical equations have been utilized to calculate the resonance frequency, current and force values. The simulation results include calculating the current (magnetic current density) and effects of the magnetic field of the coil on the cantilever (force calculation). Utilizing this method is to limit faults(errors) of optical fiber laser between transmitter and receiver system (detection system) for any time of cutting coil when the signal of a laser passes through the coil. In conculsions, resonant frequency (f_n) tuning using cantilivier presented in the resrach have larger variable range by using simulations. However,the adjusting of the system and changing the deminsions.Resolutions to this problematic contain tuning the modes of resonant frequency to produce by cantilivier with  2-magnets and coil when the signal  pass from  laser source. Based on these simulations and characterization results, the proposed assembly can be a good applicant for evolving a low price, high material platform for many biological, laser optical fiber, communication, machine learning, biosensors and biomedical applications.

Analysis and simulations of optimal geometry shapes of the 4 and 9 nano hole arrays (NHAs) with surface plasmonics and optical properties of biosensors systems

The possibility to limit and manipulate photons at nanometer scales attracted a lot of interest for exciting applications from subwavelength in laser, biosensors, biomedical and optoelectronics devices, the sensor optical properties, however; are complex due to two resonances through propagating and localized surface plasmons. The optical properties of surface plasmons (SPs) at the resonant wavelength is depending on the geometrical nanostructure of materials. In this article, we used different geometry of nanoholes array, 4 and 9 nanoholes array in a metallic film gold nanoparticle with different thickness (20,50,100) nm on SiO2 substrate with refractive index 1.46, we designed two different geometries; 4- holes: hole radius r1=200 nm, period p1=600 nm; and 9- holes: r2=100 nm, period p2=300 nm. Transmission and reflection spectrum have been calculated and simulated by FDTD Lumerical program. From results are observed the effect of thickness is interesting, transmission is increased at (t=20nm) for two arrays. Furthermore, the number of hole and its area has an influence on optical transmission and other parameters (E, H, Ref) which are characteristics of design of metallic nanostructure. We can see that there is a peak value of the wavelength at 519 nm approximately to 73% strong light transmission with 4-NHA in the other hand wavelength of 519 nm transmission is 45% with 9-NHA. strong light transmission is hopeful for many applications (biomedical devices, nanoantennas and laser optical fiber)

An efficient of estimation stages for segmentation skin lesions based optimization algorithm

Modern dermatology distinguishes premature diagnosis for example an important part in reducing the death percentage and promising less aggressive treatment for patients. The classifications comprise various stages that must be selected suitably using the characteristics of the filter pointing to get a dependable analysis. The dermoscopic images hold challenges to be faced and overcome to enhance the automatic diagnosis of hazardous lesions. It is calculated to survey a different metaheuristic and evolutionary computing working for filter design systems. Approximately general computing techniques are observed to improve features of infect design method. Nevertheless, the median filter (MF) is normally multimodal with respect to the filter factors and so, reliable approaches that can provide optimal solutions are required. The design of MF depends on modern artificial swarm intelligence technique (MASIT) optimization algorithm which has proven to be more effective than other population-based algorithms to improve of estimation stages for segmentation skin lesions. A controlled artificial bee colony (ABC) algorithm is advanced for solving factors optimization problems and, also the physical-programming-depend on ABC way is applied to proposal median filter, and the outcomes are compared to another approaches

Effect of nanocopper additives on the physical properties of porous alumina ceramics using graphite waste as a pore-forming agent

Solid state and sacrificial techniques were used to prepare the porous alumina ceramics. The target of the present research is to investigate the effect of Cu metal addition of nanoscale particle size on the physical properties of porous alumina ceramics using graphite waste as a pore-forming agent. X-Ray Diffraction (XRD), a Field Emission Scanning Electron Microscope (FESEM) and a Transmission and Electron Microscope (TEM) were used to analyse the microstructure and ceramic phases. Different ratios of Cu metal were added (3, 6, 9 and 12 wt.%) at different ratios of graphite waste. The results of this investigation show that with increasing ratios of Cu metal, the porosity decreased while the shrinkage and densities increased. Increases in the density and decreases in the porosity of porous alumina ceramics and the formation of the tenorite (CuO) phase due to sintering at high temperature (1600°C) may lead to improving the strength of porous alumina ceramics. Some potential applications include gas filtration components and as thermal insulation materials

Decision-making in Cybersecurity: A Bibliometric analysis

This bibliometric analysis explores research trends and patterns in the intersection of decision-making and cybersecurity. Using Scopus data, we conducted a systematic search and identified 4,637 relevant documents published between 2018-2024. Quantitative analysis reveals rising annual publications with a peak in 2023, the predominance of journal articles, and robust international collaboration networks. China and the USA lead global scientific production. Key topics include risk assessment, network security, decision support systems, and emerging technologies like machine learning and artificial intelligence. Core journals with high citation impact such as IEEE Access and Expert Systems with Applications highlight significant sources of literature. The study provides a holistic overview of the landscape, evolution, contributors, and themes within decision-making and cybersecurity research

Implementing an Automated Inventory Management System for Small and Medium-sized Enterprises

Alfa Company is a medium-sized Iraqi distributor of laboratory equipment and supplies; in this study, we analyze their experience with implementing an automated inventory management system. This research explains the potential benefits and implementation challenges of such a system for small and medium-sized businesses. Improved inventory tracking, less storage fees, and happier consumers resulted from adopting this system. However, implementation was complex and time-consuming, requiring the expertise of outside IT consultants as well as the training of internal staff. This case study shows how beneficial it can be for small and medium-sized enterprises to work with external IT consultants and vendors to help them evaluate the costs and benefits of installing an automated inventory management system. In sum, the case study is instructive for other SMEs thinking about investing in automated inventory management systems to boost efficiency and cut costs

SVD-based adaptive fuzzy for generalized transportation

This research stems from the urgent need to address the complex challenges faced in multimodal transportation within the cargo sector, particularly concerning the reduction of transportation costs and CO2 emissions. Existing transportation systems often struggle to efficiently balance economic and environmental concerns, necessitating innovative solutions. In this paper, we have introduced a novel mathematical model that integrates Singular Value Decomposition (SVD), Genetic Algorithms (GA), and the Adaptive Neural Fuzzy Inference System (ANFIS). The synergy of GA and the ANFIS forms a dynamic learning system that continually refines solutions by adapting to historical decisions and aligning with supply-demand dynamics. This integrated approach aims to optimize cost allocation and resource utilization while simultaneously minimizing CO2 emissions. Deploying the ANFIS+GA+SVD model in multimodal scenarios yields impressive results, with a minimal average percentage error (MAPE) of 0.28% for transportation costs and a remarkable coefficient of determination R2 of 0.992 for the Truck + Ship scenario. Similarly, a MAPE of 0.11% for CO2 emissions, supported by an impressive R2 of 0.989, underscores the model's accuracy. Observations of people's transportation choices in response to emission price changes reveal a significant decrease in truck usage, plummeting from 84% to below 50%. Alternative transportation methods, especially in the 3S-3 M-3 C scenario, show a substantial surge, with railways leading at a remarkable 30% increase in utilization. The combined quantity and cost comparison, utilizing the ANFIS+GA+SVD model, emphasizes the suitability of the Truck + Ship scenario for Iraq's transportation network, reinforcing the case for sustainable and efficient multimodal transportation systems