International Journal of Science, Engineering and TechnologyAn Inversion Algorithm for Subsurface Sensing Problem
Authors: 11Yijun Yu, 2Nailong Guo
Affiliation:
1Department of Mathematics, Tuskegee University, AL, USA
22Department of Mathematics and Computer Science, Benedict College, SC, USA
Abstract:
An inversion algorithm with Bayesian Formulation is considered for subsurface Sensing problem. The algorithm inverts the parameters of a heterogeneity profile based on measured scattering data. The Algorithm is developed based on assumption that there is a mismatch between the measured data and the model employed, with the error represented as a random process. The mean of the distribution may be used as a point estimate of the heterogeneity profile. Here the basic Bayesian inversion framework is presented, with example results presented for subsurface-sensing problems.
Work-Related Stressors and Coping Strategies of Elementary Sped Teachers in Metro Manila
Authors – Dr. John Mark Distor
Abstract- – IThis study aspires to identify the work-related stressors and coping strategies of Elementary SPED (Special Education) Teachers around Metro Manila. It aims to determine the work-related stressors of SPED teachers, methods that they utilize to cope with given stressors, and if there is any significance between work-related stressors and coping strategies being experienced and utilized by the said demographics. The researchers used a self-constructed questionnaire that is validated by 2 Psychology experts, 1 Education expert, and 1 SPED teacher. Purposive sampling method was utilized, and the researchers have used survey methods to gather data, along with a semi-structured supporting interview. Weighted mean was used to identify which stressors among the given specifies had been the most stressful, and which coping strategies were the most effective. Chi Square Test of Independence or Fisher’s exact test was utilized to determine if there are any relationships between the demographic profile and work-related stressors and coping strategies, and work-related stressors and coping strategies. The study would raise awareness on the stressors that possibly affects the performance of SPED teachers. The findings could possibly reflect the needs and complaints of the SPED teachers, and the supervising officials could make adjustments in order to be effective and efficient leaders.
Advanced Data Modeling In Power Bi: Best Practices For Performance Optimization And Data Integrity_360
Authors: Imran Saif
Abstract: Advanced data modeling in Power BI is critical for enabling high-performance, scalable, and accurate business intelligence. This review explores best practices for designing efficient data models, optimizing query performance, and maintaining data integrity across complex datasets. Key strategies include schema optimization using star and snowflake models, managing relationships and cardinality, leveraging calculation groups, hierarchies, and incremental refresh, and integrating with SQL databases and cloud platforms. The review also highlights techniques for query folding, VertiPaq optimization, and hybrid architectures that combine batch and real-time data. Case studies from finance, retail, healthcare, and logistics demonstrate practical applications and lessons learned in enterprise deployments. Challenges such as high-cardinality columns, complex DAX calculations, and organizational skill gaps are discussed alongside emerging trends in AI-driven modeling, automated optimization, and self-service governance. By following these best practices, organizations can build Power BI models that deliver actionable insights, ensure data accuracy, and support timely decision-making in enterprise environments.
DOI: http://doi.org/
The Power Bi Ecosystem: Integrating SQL And SSIS For Seamless, End-To-End Business Intelligence Solutions
Authors: Madhavi Rao
Abstract: The integration of SQL databases and SQL Server Integration Services (SSIS) with Power BI forms a robust ecosystem for end-to-end business intelligence (BI) solutions. Modern enterprises require seamless access to accurate, timely, and actionable insights to drive operational efficiency and strategic decision-making. SQL databases provide structured, high-performance data storage, while SSIS enables automated, scalable ETL (Extract, Transform, Load) pipelines that consolidate, clean, and enrich data from multiple sources. Power BI complements these capabilities by offering interactive dashboards, real-time reporting, and advanced visualization tools. This review explores the architectural design, data modeling strategies, and integration techniques necessary to build effective BI pipelines, emphasizing performance optimization, governance, and scalability. It also highlights industry applications, practical lessons from enterprise deployments, and challenges related to large datasets, organizational alignment, and hybrid cloud setups. By leveraging SQL, SSIS, and Power BI in concert, organizations can transform raw data into meaningful insights, support self-service analytics, and maintain compliance in complex business environments. The review further discusses advanced integration strategies, including Power Query enhancements and cloud-based ETL solutions, providing a comprehensive framework for building resilient, scalable, and actionable BI ecosystems.
DOI: http://doi.org/