International Journal of Advances in Scientific Research and Engineering (IJASRE), ISSN:2454-8006, DOI: 10.31695/IJASRE
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Study and Analysis of Credit Life Insurance Premiums for Loans with Flat and Effective Interest Rate
Get PDFCredit life insurance is a type of life insurance designed to pay off a borrower's remaining debt in the event of their death. It is a collaborative product between a bank and an insurance company, offering the benefit of loan repayment to the bank in the event of the death of the borrower (debtor). The repayment includes the outstanding debt and accrued interest. This study aims to analyze credit life insurance premiums for loans with flat and effective interest rates, and explore how the borrower's age and loan term affect these premiums. The bank offers loans with a fixed interest rate of 1.25% per month (15% per annum). The effective interest rate is 2.4% per month (28.8% per annum) for a loan term of 24 months. The method used is a quantitative approach, and uses the principle of equality so that the company's obligations are equal to the rights received by participants. The results show that credit life insurance premiums for flat and effective interest rates are almost the same. However, the premium increases significantly as the participant's age increases and further increases as the loan term progresses
The Relation Study between Geochemical and Geomechanical Properties of Shale Formation: A comprehensive review
Get PDFUnderstanding the effects of geochemistry and mineral composition on geomechanical characteristics is critical in the design and optimization of hydraulic fracturing necessary for shale gas reservoir production. Fundamental information is still missing in experimental methodologies used to evaluate the influence of geochemical parameters and mineral composition on geomechanical properties of shale gas reserves. This paper provided an in-depth assessment of the various experimental methodologies and their applications in the relationship between the geomechanical and geochemical features of the Longmaxi shale formation. The limits of these methodologies were recognized, comparative analyses on experimental data and geomechanical parameters were performed, and recommendations for improved geomechanical assessments were provided. This review will contribute to fundamental understanding and will guide future experimentally-based geochemical and geomechanical investigations on shale gas reserves
Lightweight Residual CNN with Four Skip Connections for Grayscale Metal Casting Defect Classification
Get PDFIn industrial quality control, accurate and efficient defect detection in metal casting processes remains a critical challenge, particularly in high-throughput environments. This study investigates a lightweight convolutional neural network (CNN) architecture enhanced with residual connections for classifying grayscale images of casting products into defective and non-defective categories. Using a dataset of 7,348 grayscale images sourced from Pilot Technocast, the proposed model was evaluated against standard lightweight pretrained architectures, including MobileNet, MobileNetV2, and EfficientNetV2.
The residual CNN was trained from scratch using binary cross-entropy loss and the Adam optimizer, with additional image augmentation techniques applied to improve generalization. Results show that the residual CNN achieved the highest accuracy of 99.58%, F1-score of 0.99669, and demonstrated superior precision and recall compared to all other models. Despite having only 57,665 parameters, the model outperformed more complex architectures in both performance and deployment efficiency.
These findings underscore the potential of domain-specific, residual-enhanced CNNs for real-time defect classification tasks, particularly in resource-constrained industrial settings. The model’s balance between accuracy and lightweight design makes it suitable for integration into embedded quality control systems
Design and Development of an Electronic Prescribing System
Get PDFThe increasing adoption of digital healthcare solutions has accelerated the implementation of electronic prescribing (e-prescribing) systems to enhance patient safety, reduce prescription errors, and improve workflow efficiency. This study presents the design, development, and pilot implementation of an e-prescribing system in Chipata, Zambia, involving two healthcare facilities and two pharmacies. A baseline study identified persistent issues with handwritten prescriptions, including illegibility, delays in medication access, and low patient adherence. Using the Waterfall System Development Life Cycle (SDLC), the developed system integrated real-time drug interaction alerts, role-based access control, and compatibility with existing Electronic Health Records (EHRs). Pilot results demonstrated a 40% reduction in prescription errors, a 50% decrease in prescription fulfillment time, and a 20% improvement in medication adherence. Challenges such as limited technical infrastructure and user resistance were noted. Key recommendations include infrastructure enhancements, offline functionality, expanded training, and national scalability. This study highlights the transformative potential of e-prescribing systems in resource-limited healthcare settings
Analysis of the Influence of Certified Wastewater Treatment Personnel Competence on Meeting Industrial Wastewater Quality Standards in Semarang City
Get PDFThis research examines the effect of certified personnel competence in industrial wastewater treatment on the fulfillment of industrial wastewater quality standards in Semarang City, Indonesia. Amid rapid industrial expansion, ensuring environmental sustainability has become increasingly challenging, prompting regulatory requirements for operator certification. The study adopts a quantitative descriptive approach, gathering data from 26 key wastewater treatment operators (POPAL) in major manufacturing sectors through structured questionnaires, interviews, and direct field observation. Findings demonstrate that the majority of industries in Semarang have already appointed certified wastewater treatment personnel, with most respondents possessing a strong educational background and extensive experience. Results indicate that certified operators significantly improve industrial compliance with wastewater quality standards, particularly regarding key parameters such as Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), and Total Suspended Solids (TSS). Certified personnel exhibit enhanced ability in identifying risks, operating and maintaining wastewater facilities, and implementing standard procedures, which directly translates into higher rates of regulatory compliance. However, the research also finds that certification alone is not a panacea; certain industries still face challenges due to outdated technology, insufficient management support, or a lack of continuous training. These factors may hinder optimal wastewater treatment, even when certified personnel are present. The study’s implications are twofold. Theoretically, it affirms the critical role of human resource competence in effective industrial environmental management. Practically, it encourages policymakers and industry leaders to prioritize ongoing professional development, technological upgrades, and supportive management systems, in addition to certification. Such efforts will further strengthen the effectiveness of certified operators and improve overall environmental compliance. In conclusion, certified personnel competence, when supported by proper institutional and technological resources, is a key driver for successful and sustainable industrial wastewater management in Semarang
Evaluating the Performance and Resistance of Dynamic AES Image Encryption to Noise and Key Sensitivity
Get PDFIn an era of digital information abundance, securing visual content against potential cybersecurity breaches is crucial, given that sensitive visual data can be transmitted or stored and are often susceptible to malicious attacks. This article proposes a new novel and robust framework with AES algorithm combined with dynamically developed keys and IVs in order to provide a stronger cryptographic framework for image encryption. The most widely known framework is a collection of AES modes (ECB, CBC, CTR, etc.) with their effectiveness evaluated through a comprehensive suite of security and performance metrics. This covers traits like randomness assessment through entropy analysis, the Number of Pixel Change Rate (NPCR) and Unified Average Changing Intensity (UACI), and key sensitivity measurements between slight modifications in the encryption key and system robustness.
Real-world challenges are rigorously tested against this system through experiments, which involved introducing common disturbances such as Gaussian and salt-and-pepper noise to the encrypted data, simulating tampering and data corruption scenarios. Further, encryption and decryption efficiency are analyzed comprehensively over images with varying resolutions. obtains significant entropy values close to the theoretical maximum (≈8), high robustness factors with NPCR ≥ 99% and UACI > 33% indicating a very intensive change of pixels at the two moment sides of the reluctant encrypt BIOUNET. A third chapter delves into specific comparisons with other implementations, including ChaCha20) and RSA, demonstrating the various advantages of the new method in terms of randomness, speed, and minimum key length required for a given level of security. The proposed dynamic AES-based encryption system offers secure protection of sensitive images against unauthorized access for various applications in the real-world, as demonstrated by these results, which also prove the system to be a practical, robust, and scalable solution
Classification of People’s Opinions on Fuel Subsidy Removal in Nigeria: An Enhancement of Unsupervised Learning Algorithm-Opinion Lexicon algorithm
Get PDFThis research aims to collect Nigerians’ opinions on subsidy removal in Nigeria and classify them using an unsupervised learning algorithm, specifically corpus-based lexicon algorithm in order to enhance it prediction accuracy. The data was extracted from an online survey via social media platforms: Facebook and WhatsApp. A comprehensive literature review has been conducted on fuel subsidy removal, sentiment analysis, and unsupervised machine learning approach. The methodology involved are: data collection, preprocessing, feature extraction, model training, and evaluation. The result of this study shows that Nigerians are not happy with fuel subsidy removal, because of the highest number of negative comments over positive ones. This implies that there exist in socio-economic and security issues in Nigeria. The unsupervised learning algorithm for sentiment analysis, the Lexicon was improved with an accuracy of 84.5%. thus, enhanced by 15.27%. These results can potentially inform policymakers and stakeholders about the public's sentiments, the social and security consequences of subsidy removal in Nigeria
Computational Linguistics
Get PDFLinguistics is concerned with rules that are followed by languages as a system. Computational linguistics (CL) combines the power of machine learning and human language. As a subfield of linguistics, CL is concerned with the computational description of rules that languages follow. It is what powers anything in a machine or device that has to do with language—speaking, writing, reading, and listening. It is often linked with natural language processing (NLP), which is the use of computers to identify structures in natural language. The boundary between NLP and CL is not so clear-cut. This paper is a primer on computational linguistics
The Feasibility of Installing a Small-Scale PV System in a Carport in Kuwait
Get PDFThe need to obtain sustainable energy sources is one of the most important challenges in this century. Several alternatives have been sought, but attention has been focused on Wind turbines and solar energy PV or CSP. The state of Kuwait is one of the countries that is working to Attain a Target of Achieving 15% of its power production in 2030 from clean energy. Since Kuwait is in a hot and sunny region, it was worthwhile to have solar energy as one of the solutions. The state of Kuwait has established the Al-Shagaya clean energy plant, which produces 70 MW moreover, the Consumers and small businesses have established several private ancillary power generation small-scale projects with the encouragement of the Kuwait government that set Laws in 2022 to Allow the Ministry of Elect the city and Water and Renewable Energy MEW to buy Power from citizens and consumers. This research aims to determine the feasibility of small-scale photovoltaic P.V. solar projects
Appraising the Effect of Biochar in Groundnuts(Arachis hypogaea L) Growth Parameters and Yield Under Screen House Conditions
Get PDFBiochar soil amendment is known to suppress the effect of pathogenic fungi and favour plant resistance against soil‐borne pathogen effects. This study appraises the impact of biochar on groundnut yield planted in the slightly acidic sandy loam soil. The study was done at the Nelson Mandela African Institution of Science and Technology (NM-AIST) screen house, where groundnuts were planted in the 2L pots filled with soil mixed with biochar at different rates (2.5%, 5% and 7.5%) in April 2022. Groundnut’s growth parameters were managed by measuring shoot length and root length, counting the number of leaves and taking leaf area once every week from the second week after planting to harvesting, where its yield was also measured. Analysis of variance showed a significant (P < 0.05) increase in groundnut growth parameters and yield when 5% Biochar was used. There was a strong positive correlation between biochar and some groundnut growth parameters. No significant (P < 0.05) difference was observed between Biochar and groundnut growth parameters and yield when 2.5% biochar was used. A slightly weak negative correlation was observed when a 7.5% Biochar rate was used. Biochar-amended soils indicated a dramatic increase in soil pH, CEC, Mn, P, K, Ca, B, Zn, and Si. The current study demonstrates that using 5% maize cob biochar, pyrolyzed at 500°C, in acidic sandy loam soil, can lead to maximum enhancement in soil physical and chemical properties, as well as groundnut growth and yield parameters