7 research outputs found
Fraud Detection in Health Insurance Claims using Machine Learning
No full textThis project focuses on detecting fraudulent health insurance claims using machine learning techniques. The dataset includes various patient attributes, claim amounts, and medical details, which were preprocessed by handling missing values, encoding categorical features, and standardizing numerical data. Fraud detection was formulated as a classification problem, where claims in the top 5% of the cost distribution were labeled as potentially fraudulent. Several models, including Logistic Regression, Random Forest, and XG Boost, were trained and evaluated, with Random Forest providing the best performance after tuning.
To gain deeper insights, multiple visualizations were created to analyze fraud patterns based on age, region, smoking habits, blood pressure levels, and feature correlations. While initial models exhibited overfitting, techniques such as feature selection, SMOTE balancing, and adjusting fraud detection thresholds improved generalization. The final optimized model achieved a balance between high precision and recall, making it suitable for real-world applications. Though deployment was initially considered, the project concluded with a locally usable model for fraud prediction, ensuring robust, data-driven decision-making for healthcare fraud detection.
Keywords: Insurance Claims Classification Predictive Analytics Fraud Detection Machine Learning Models Random Forest Classifier Claim Amount Prediction Data Preprocessing Feature Importance Analysis Logistic Regression XG Boos
Anti-lock braking system (ABS) and regenerative braking system (RBS) in hybrid electric vehicle for smart transportation system
No full textInternational Journal of Mathematical Combinatorics, Vol.6
No full textThe International J.Mathematical Combinatorics (ISSN 1937-1055) is a fully refereed international journal, sponsored by the MADIS of Chinese Academy of Sciences and published in USA quarterly comprising 460 pages approx. per volume, which publishes original research papers and survey articles in all aspects of Smarandache multi-spaces, Smarandache geometries, mathematical combinatorics, non-euclidean geometry and topology and their applications to other sciences
The role of nongovernmental organizations in primary education - a study of six NGOs in India
No full textNongovernmental organizations (NGOs) extend education to underprivileged children in India, and develop innovations that improve the quality of primary education. In this study of six NGOs working with school-age children in India, the author shows the potential benefits of a government-NGO alliance to achieve universal primary education. The author emphasizes several areas in which collaboration can be particularly fruitful. 1) Targeting under-served children: The Government could support the efforts of NGOs to bring out-of-school children into schools, through timely supply of teachers, classroom space, and other resources. Targeted action is needed to reach different types of out-of-school children - those who work, those who live in slums, those on the street, those who are members of tribes, or of migrant families, and those who live in places without schools. To encourage young, first-generation learners to stay in school, requires a supportive, and nurturing environment. To help make learning interesting, and worthwhile for such children, teachers in government schools could receive special training in new methods developed by NGOs. 2) Enhancing quality: Improving the quality of education requires working closely with key agents of change, such as teachers, school heads, school management committees, and village education committees. To develop a cadre of trainers for primary school teachers, teacher training institutes would do well to evaluate, and learn from NGO models for teacher training. Teachers need a range of knowledge, and skills to teach underprivileged children effectively. Here again, NGO models would be a useful tool for teacher training institutes. NGOs, and the government could collaborate in developing appropriate, and flexible learning assessment tools, in line with innovative teaching, and learning methods. But without safeguards, large-scale replication by the government of such NGO innovations as the"alternative school"and the"voluntary teacher"could lower the quality of education. 3) Government-NGO links: The Government and NGOs will need to share a common vision on how to achieve universal primary education if India is to reach this goal. NGOs can be credible partners with the government in shaping policies for primary education. This entails collaboration, rather than parallel initiatives by NGOs. To stay at the cutting edge in education, NGOs should continually evaluate, and refine their models. If NGOs are to play a policy role in education, two areas that have been neglected will need to be addressed - NGO capacity building, and organizational development.Primary Education,Teaching and Learning,Health Monitoring&Evaluation,Gender and Education,Curriculum&Instruction
Mixture Morphology of the ZnO Catalyst Synthesized by a Hydrothermal Method for an Outstanding Photocatalytic Decolourization on Organic Dyes
No full textThe special mixture morphology of the spherical and rod like the ZnO catalyst was successfully synthesized by a simple approach hydrothermal method. As the synthesized catalyst carried out by different conditions such as the ZnO dried, 250 °C and 500 °C calcination. Here, to investigated the calcination temperacture effect on crystal structure, phase, morphology and photocatalytic dye degraration with various dyes an including methylene blue (MB), methyl orange (MO), congo red (CR), and rhodamine b (RhB) under the direct Sunlight, was examined as manufactured ZnO catalysts. According to the results, all temperature conditions the ZnO have same crystal structure, phase, morphology and different performnce of the photocatalytic degradation with various dyes. Among these, the dried ZnO catalyst shown outstanding decolorization of the MB, MO, CR, and RhB dyes within 45 min followed by order percentages is about 100%, 93.89%, 98.18% and 96.98% respectively.The author thanks to RUSA facility lab for providing the UV-vis spectra instrument in Yogi Vemana University, Vemanapuram, Y.S.R. Kadapa, Andhrapradesh, INDIA. This work was funded by the Researchers Supporting Project Number (RSPD2023R441), King Saud University, Riyadh, Saudi Arabia.Scopu
Author Correction: Water-efficient genotypes along with conservation measures significantly reduce the green and blue water footprints in sugarcane (Saccharum spp.)
No full textLarge eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions
No full text© 2020, The Author(s). The availability of high-quality RNA-sequencing and genotyping data of post-mortem brain collections from consortia such as CommonMind Consortium (CMC) and the Accelerating Medicines Partnership for Alzheimer’s Disease (AMP-AD) Consortium enable the generation of a large-scale brain cis-eQTL meta-analysis. Here we generate cerebral cortical eQTL from 1433 samples available from four cohorts (identifying >4.1 million significant eQTL for >18,000 genes), as well as cerebellar eQTL from 261 samples (identifying 874,836 significant eQTL for >10,000 genes). We find substantially improved power in the meta-analysis over individual cohort analyses, particularly in comparison to the Genotype-Tissue Expression (GTEx) Project eQTL. Additionally, we observed differences in eQTL patterns between cerebral and cerebellar brain regions. We provide these brain eQTL as a resource for use by the research community. As a proof of principle for their utility, we apply a colocalization analysis to identify genes underlying the GWAS association peaks for schizophrenia and identify a potentially novel gene colocalization with lncRNA RP11-677M14.2 (posterior probability of colocalization 0.975)
