International Journal of Innovation in Engineering
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Theoretical Modeling of Electromagnetic Field Exposure from High-Voltage Power Lines and Potential Health Implications
Get PDFThis study aimed to investigate potential health concerns linked to electromagnetic field (EMF) exposure from high-voltage power lines and develop a thorough knowledge of the underlying mechanisms causing these effects. The study looks into how Specific Absorption Rate (SAR) varies, how temperatures are distributed, and how these things affect people's health when they are close to electricity grid lines. The discretization finite difference approach was employed in this study to describe the electromagnetic waves, absorption rate, and temperature. The findings show a considerable variation in SAR values, from 0.0000 to 0.0072 W/kg, and SAR decreases from 1.0 to 0.0 W/kg as distance from the grid increases. The study also shows that stronger electric fields cause temperatures to rise along the grid lines. These results highlight the significance of comprehending and reducing possible health concerns related to electromagnetic field exposure close to electricity infrastructure. To diminish exposure and safeguard public health, it is advised that regulatory rules, public awareness campaigns, and urban planning efforts be implemented in light of the observed variability of surface radiation and temperature swings. Effective solutions to safeguard the safety of people living and working near electrical grid lines must be implemented through consultation with government agencies, utility companies, healthcare providers, and community groups. Stakeholders can create knowledgeable policies and practices to encourage safer living conditions and lessen the possible negative impacts of electromagnetic field exposure on human health
Characterization of Numerical Radius Preserving Isomorphisms in Norm-Attainable Classes
Get PDFIn functional analysis, understanding when an isomorphism preserves numerical radius in norm-attainable classes remains interesting. This paper examines conditions under which isomorphisms preserve the numerical radius in norm-attainable classes. We develop and prove conditions that provide insights into the behavior of isomorphisms concerning numerical radius preservation. The results show that if an isomorphism Φ preserves the numerical radius for all self-adjoint operators, then Φ is either a unitary operator or the negative of a unitary operator. Moreover, if Φ is an isomorphism in NA(H), then Φ is an orthogonal isomorphism
The Numerical Solution of Hammerstein-Fredholm Second Kind - Integral Equations by using the Block Method
No full textThe Fredholm–Hammerstein integral equations appear in a variety of applications in many fields including continuum mechanics, potential theory, geophysics, electromagnetic fluid dynamics, antenna synthesis problem, communication theory, mathematical economics, population genetics, radiation, the particle transport problems of astrophysics and reactor theory, fluid mechanics. The purpose of this research is to extend a numerical method for solving a special type of integral equations, which is known as the block method. In this work, a new algorithm has been developed for the first time to treat the Hammerstein Fredholm-second kind integral equation (HFSKIE), and that method consists of three blocks. The resulting nonlinear equations from this method are solved by the Newton-Raphson method.
ASSESSING PROLIFERATION OF CONTAMINANTS AND PUBLIC HEALTH RISKS IN RURAL WATER RESOURCES OF OGBOMOSO, SOUTHWESTERN, NIGERIA
No full textAnthropogenic activities pose a significant threat to water resources in rural communities of developing countries, where access to protected sources is limited. This study provides a critical assessment of water quality in rural Ogbomoso, Southwestern Nigeria, by evaluating physicochemical and microbiological parameters across different water source types. Duplicate samples were collected from 15 sites, categorized as surface streams (n=5), unprotected shallow wells (n=7), and protected boreholes (n=3). Analyses were conducted for colour, turbidity, Total Dissolved Solids (TDS), pH, chloride, nitrate, sulphate, and Escherichia coli. Results revealed severe contamination across all source types. Surface streams were most degraded, exhibiting excessively high turbidity (35.45–129.00 NTU) and colour (190–550 TCU). While most physicochemical parameters (TDS, pH, chloride, sulphate) in groundwater were within permissible limits, nitrate contamination was prevalent, with stream concentrations (up to 133 mg/L) far exceeding the WHO guideline of 50 mg/L. The most critical finding was the presence of E. coli in most sampled sources, providing conclusive evidence of widespread faecal contamination and rendering the water unfit for human consumption without treatment. The study concludes that water sources in these communities are heavily compromised by anthropogenic activities, posing grave public health risks. The findings underscore the urgent need for targeted interventions, including source protection, improved sanitation infrastructure, and community-led water safety plans, to safeguard public health and achieve the Sustainable Development Goals
Effects of Intermolecular Distance on the Absorption Spectra of Organic Semiconductors
Get PDFOrganic semiconductors have several advantages over conventional inorganic semiconductors. The optical properties of π-conjugated organic molecules are important in determining the performance efficiencies of photovoltaic cells, optoelectronic devices and organic thin-film transistors and lasers.
This work examined the variation of absorption spectra of three organic semiconductors (perylene, pentacene, and sexithienyl) with their geometries and intermolecular distances between the dimer molecules. Quantum mechanical calculations using the PM3 semi-empirical approximation were used to obtain the optimal geometry of the semiconductors, and ZINDO/S was used to determine absorption spectra. The study revealed distinct absorption spectra for each molecule, with specific absorption edges of 499.295 nm (2.49 eV), 506 nm (2.41 eV), and 12449.90 nm (0.1 eV) identified for pentacene, perylene, and sexithienyl momomers, respectively. The significance of intermolecular distance in influencing the absorption spectra of the materials investigated was revealed, indicating a systematic blue shift at certain distances and a red shift at others. For Perylene, a red shift in the absorption edge was observed between the intermolecular distances of 1.5 Å - 3 Å. A blue shift occurred as the separation distance increased to 3.5 Å and 4 Å. A similar trend was observed for Pentacene in which a read shift was noticed between 1.5 Å – 2.5 Å. A blue shift occurred as the intermolecular (separation distance) was raised to 3 Å and 3.5 Å. A different trend was observed for Sexithienyl, where a blue shift in the absorption edge was seen between 1.5 Å and 2.5 Å. A read shift was observed between 3 Å and 4 Å. It was observed that the peak absorptions occur at an intermolecular distance of 1.5 Å for both perylene and pentacene and at 2.5 Å for sexithienyl. The minimum absorptions occur at an intermolecular distance of 2.5 Å for both perylene and pentacene and at 4.0 Å for sexithienyl
Optimizing User Experience in Digital Payments: The Case of Finpay Money
Get PDFThis paper explores strategies for optimizing the user experience (UX) of Finpay Money, a digital payment application in Indonesia. Despite the growing adoption of digital wallets, Finpay Money has struggled with lower user ratings on the Google Play Store, indicating usability challenges that hinder its competitiveness. User reviews and preliminary interviews reveal pain points such as complex onboarding, limited engagement features, and authentication inefficiencies. This study aims to identify key UX enhancements to improve user satisfaction and drive adoption. To achieve this, the research applies the design thinking framework, consisting of seven stages: understand, observe, define the point of view (PoV), ideate, prototype, test, and reflect. A descriptive qualitative approach involves in-depth interviews with Finpay Money users to uncover pain points and opportunities. The PoV stage formulates a "How Might We" (HMW) question to refine user problems, followed by brainstorming and dot-voting in the ideation phase to generate solutions.
Findings suggest optimizing onboarding, introducing a loyalty points system, and implementing biometric authentication to significantly enhance the UX. A prototype integrating these features was tested, achieving a high usability score of 91.5. Positive user feedback emphasized the value of an improved loyalty program, with recommendations to expand redemption options at major merchants. This research contributes to the practical understanding of UX optimization in digital payment services, demonstrating the impact of design thinking as a structured problem-solving approach. The insights from this study offer actionable recommendations for financial technology providers and serve as a reference for improving digital payment applications globally
AI and Machine Learning in Breast Cancer: Advancing Precision Medicine Through Data-Driven Models
Get PDFArtificial Intelligence (AI) and Machine Learning (ML) advancements have revolutionized precision medicine, offering transformative breast cancer diagnosis and treatment solutions. By leveraging vast datasets, AI-powered models provide enhanced accuracy in tumor detection, classification, and prognosis, surpassing traditional diagnostic methods. Machine learning algorithms, including deep learning networks, uncover intricate patterns within imaging, genomic, and clinical data, enabling personalized treatment strategies. This paper highlights the integration of AI in breast cancer care, discussing state-of-the-art techniques, challenges in clinical implementation, and future opportunities. Through a comparative analysis of data-driven models, we demonstrate their potential to optimize early detection, improve patient outcomes, and support oncologists in decision-making processes
Proposed Architecture and Mathematical Model to Enhance Interference Management in 5G-Enabled M2M Networks
Get PDFThe growing number of connected devices has led to a significant shift in cellular standards, particularly with the Long-Term Evolution (LTE) framework. The fifth-generation (5G) standard supports several innovative mobile technologies, including Machine-to-Machine (M2M) communication and Device-to-Device (D2D) communication, enabling a vast network of interconnected intelligent devices. In Nigeria's power system, the deployment of M2M devices within the smart grid has introduced new challenges in resource allocation and interference management. The interference caused by reduced inter-cell distances and the seamless integration of heterogeneous devices into the 5G cellular network leads to a decline in Quality of Service (QoS) and overall network performance. In this paper, we propose an interference-aware architecture for Machine-to-Machine (M2M) communication within a smart grid. This architecture aims to mitigate the interference caused by the localization of M2M devices on the grid. Additionally, we will mathematically model the proposed interference mitigation scheme as a multi-objective particle swarm optimization problem, taking into account the complexity of the fitness function and the trade-offs between different particles. As a result of this approach, the interference generated by M2M devices will decrease significantly. Consequently, we expect to achieve a balance between the optimal separation distance of M2M devices and improved network performance
Assessment of the Efficiency of Decision-Making Units by Combining Artificial Neural Networks and Data Envelopment Analysis
Get PDFEvaluating the performance and efficiency of similar units within an organization using the DEA (Data Envelopment Analysis) model has been a topic of debate among researchers in recent decades. In this research, for evaluation of the performance and efficiency of Provincial Gas Companies in Iran, first CCR (Charnes, Cooper, and Rhodes) Input-Oriented Multiple Model and AP (Andersen-Petersen) Model were analyzed for ranking efficient units in the format of DEA; however, the weakness of models was determined in terms of separating efficiency of companies. In the DEA model, units with an efficiency score of "1" are not ranked using classical DEA methods; in other words, DEA does not differentiate between such units. To solve this problem, the AP approach is proposed to classify efficient units. This problem is generalizable due to the lower quantity of units compared to the input and output quantities of the model. In the continuation of this study, to address this problem and analyze the efficiency of companies, attitudes including Performance Calculator Neural Networks were employed, utilizing units clustering and attitude in the format of synthetic models of DEA and ANNs (Artificial Neural Networks), referred to as Neuro-DEA. Analytical results of calculating the efficiency of these models indicated the higher power of calculation and separability of the model for companies in terms of efficiency. The superiority of the neural data envelopment analysis model (Neuro-DEA) lies in its ability to minimize inputs to achieve the desired output level. To measure the efficiency of the companies with the research model, first, a suitable neural network model is simulated, and then, based on the initial data, the network is trained using the desired output (calculated by DEA) until it can learn the reference patterns and calculate the efficiency of the units based on it
Effect of Annealing Temperature on the Optical Properties of Bismuth Sulfide (Bi2S3)
Get PDFThe effect of annealing temperature on the optical properties of Bismuth Sulfide was studied. A chemical bath deposition technique was employed in the synthesis, and UV-Vis spectroscopy (Spectrum lab 752s) was used to measure the optical properties. The measurement was carried out at a wavelength range between 200 nm and 500 nm. The transmittance increased with an increase in wavelength, and lower values were observed at higher annealing temperatures. The absorbance is high at higher annealing temperatures, and its value decreases with increased wavelength. The reflectance also has high values at high annealing temperatures, and its value increases with an increase in wavelength. The band gap was found to decrease with an increase in annealing temperature. It is clearly shown that the annealing temperature greatly affects the optical properties of Bismuth Sulfide semiconductors