Authors: Dave A. Camuta, Bryan B. Ortouste, Jen Rose A. Limentang, Krisha Nicole G. Bacolod, Jesson H. Cinto

Abstract: This study focused on developing a biodegradable food wrapper CalaSSAG, made from bio-based materials such as calamansi peel powder, starch, sodium alginate, and glycerol. The research aimed on making an alternative to plastic packaging that causes pollution. Calamansi is responsible for antimicrobial and antifungal properties. An experimental design was used to test how durable and thick the CalaSSAG bioplastic wrapper was, using three different concentrations of calamansi peel powder, 50%, 75%, and 100%. Testing its thickness and tensile strength. The results showed that the 100% calamansi mixture made the wrapper (1.26 mm), while the 50% mixture had the highest tensile strength (0.165 MPa). However, the control group was stronger than the alternative experimental group in terms of tensile strength with a tensile strength of 3.33 MPa. Statistical analysis using ANOVA confirmed that there is a significant difference in mean tensive strength among CalaSSAG bioplastic wrapper containing varying proportions of calamansi powder and commercially produced plastic wrapper. CalaSSAG was not as strong as the traditional control group, it showed to be flexible, biodegradable, and made from natural materials. It offers a safer, eco-friendly choice for food packaging. Future research is advised to test the antifungal properties of calamansi in the wrapper and its real-time application. CalaSSAG shows potential in reducing plastic pollution and waste.

DOI: https://doi.org/10.5281/zenodo.18781357

 

Published by: vikaspatanker

Authors: Divya Ravindra kshirsagar, Dr. Ansari U.S

Abstract: Eanhquakes pose a significant threat to the safety and stability of built structures. making seismic performance evaluation an essential aspect of modern structural engineering. Steel buildings, known for their high ductility, strength-to-weight ratio, and superior energy dissipation capacity, have emerged as a preferred solution in seismic regions. This study investigates the seismic behavior of a multi-storey steel building using advanced analytical tools and codal provisions, with the objective of understanding its dynamic response under earthquake loading. A derailed 3D structural model was developed using ETABS/STAAD Pro, and seismic forces were evaluated in accordance with IS 1893:2016, while member design considerations followed IS 800:2007. Response Spectrum Analysis (RSA) and Time—History Analysis (THA) were performed to assess critical parameters such as base shear, storey drift, lateral displacement, and structural stability. The results highlight the significance of structural configuration, bracing system selection, and stiffness distribution in determining overall seismic performance. Observed trends indicate that proper detailing and optimized member design substantially improve ductility and reduce seismic demand. The study provides valuable insights into the dynamic characteristics of steel buildings and offers recommendations for enhancing seismic resilience through performance-based design. The findings contribute to safer, more efficient, and code-compliant steel construction in earthquake-prone areas.

 

 

Published by: vikaspatanker

Authors: Nagender Yamsani

Abstract: This study examines the growing need to embed intelligence directly into master data platforms to improve regulatory compliance, operational transparency, and data quality monitoring in complex enterprise environments. Organizations increasingly struggle to maintain consistent governance and audit readiness as data volumes expand across distributed systems, creating a research problem centered on how artificial intelligence and structured evidence mapping can enhance visibility and decision support. The purpose of this research is to develop and evaluate a framework that integrates AI enabled dashboards with master data governance workflows to support continuous compliance and quality assurance. A mixed methodological approach was applied, combining evidence mapping of prior governance and analytics models with architectural synthesis and scenario based evaluation in enterprise data management contexts. The findings demonstrate that intelligent dashboards, when supported by automated metadata analysis, anomaly detection, and lineage driven monitoring, significantly improve detection of data quality risks, accelerate audit preparation, and enhance stewardship effectiveness. The study introduces an architectural model that aligns monitoring, policy enforcement, and predictive analytics within a unified governance layer. These contributions extend existing research in data governance and enterprise analytics by providing a practical and scalable design framework. The results highlight the strategic importance of integrating intelligence into master data platforms, offering guidance for industry practitioners and establishing a foundation for further academic research on autonomous governance and continuous data assurance.

DOI: https://doi.org/10.5281/zenodo.18770933

 

Published by: vikaspatanker

Authors: Tanvi Ramkumar Sunewad, Shahin Tanvir Shaikh, Divya Hemant Dhende, Diksha Datta Jethe

Abstract: Paralysis is a debilitating condition that significantly impairs a patient’s ability to move and communicate, often resulting from neurological disorders, spinal cord injuries, or diseases such as stroke. According to the World Health Organization, stroke and related neurological conditions are among the leading causes of long-term disability worldwide, emphasizing the need for continuous and reliable patient monitoring systems. The Paralysis Patient Health Care Monitoring System is an advanced, technology-driven solution designed to continuously monitor the vital parameters and safety of paralyzed patients in hospitals or home environments. The system integrates biomedical sensors to track essential health indicators such as heart rate, body temperature, blood pressure, oxygen saturation (SpO₂), and movement detection. These parameters are processed through a microcontroller-based unit and transmitted via wireless communication modules to caregivers or medical professionals in real time. The proposed system also incorporates emergency alert mechanisms, enabling patients to communicate distress signals through minimal physical input, such as eye blink detection or slight finger movement sensors. In critical situations, automated notifications are sent to caregivers or healthcare providers to ensure immediate medical intervention. Data collected by the system can be stored in a cloud-based database for continuous analysis, enabling long-term health trend monitoring and improved clinical decision-making. The system enhances patient safety, reduces the burden on caregivers, and supports timely medical response, ultimately improving the quality of life for paralysis patients. In conclusion, the Paralysis Patient Health Care Monitoring System provides an efficient, reliable, and cost-effective approach to continuous health monitoring, promoting better patient outcomes through real-time data tracking, remote accessibility, and intelligent alert mechanisms.

DOI: https://doi.org/10.5281/zenodo.18769831

 

Published by: vikaspatanker

Authors: Ketaki Nanaware, Vedant Dhopate, Atharv Hapse

Abstract: This research paper details the creation of a versatile smart IoT device using the ESP32 microcontroller, MIT App Inventor, and Google Firebase. The device integrates multiple interfaces for real-time data collection, processing, and control, making it ideal for applications in smart homes, industrial automation, and environmental monitoring. The ESP32 handles sensor data (e.g., temperature and humidity) and communicates with Google Firebase for real-time data storage. Users interact through a mobile app developed with MIT App Inventor, which allows monitoring, configuration, and control of connected devices, such as motors. The system also employs MDNS and HTTP servers for efficient local network communication. Key features include dynamic data collection, real-time visualization on the mobile app, and remote device control. The integration with Firebase ensures scalability and secure data handling. This IoT solution demonstrates flexibility and potential for diverse applications, with future enhancements possible through additional sensors and advanced analytics.

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Published by: vikaspatanker

Authors: Khodke Pawan Rajendra, Prof. Dr.U.S.Ansari

Abstract: Offshore steel fixed jacket platforms are essential structural systems that support exploration and production operations in harsh marine environments. These platforms are subjected to complex and fluctuating environmental loads, including wind, waves, currents, and seismic forces, which significantly influence their stability and long-term performance. Bracing systems play a crucial role in enhancing lateral stiffness, improving load distribution, and reducing structural deformations in offshore jackets. This study investigates the structural behaviour of offshore steel fixed jacket platforms equipped with different bracing configurations using SAP 2000. A detailed finite element model was developed, incorporating realistic material properties, geometric parameters, and environmental load combinations based on standard design codes. Static and dynamic analyses were performed to evaluate displacement, base shear, stress distribution, natural frequency, and overall stiffness under combined environmental loading. The comparative assessment revealed notable differences in performance among various bracing layouts, with some configurations demonstrating superior resistance to deformation and improved stability. The study emphasizes the importance of selecting an optimal bracing system to enhance the safety, reliability, and efficiency of jacket platforms. The findings provide valuable insights for design optimization and contribute to the advancement of offshore structural engineering practices.

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Published by: vikaspatanker

Authors: Dr. Priyanka B. Shingade

Abstract: Positivity questions occupy a central place in algebraic combinatory: given a naturally occurring symmetric or quasisymmetric, or polynomial function, when does it expand with nonnegative coefficients in a preferred basis monomial, elementary, Schurz, etc. This survey/research-style paper organizes classical and recent positivity problems, summarizes principal techniques, records key breakthroughs, and lists open conjectures and directions. We emphasize (i) classical positivity phenomena Littlewoods–Richardson, Schurz- and e- positivity, (ii) structural conjectures such as the Stanley–Stem bridge and Macdonald positivity problems and their recent status, (iii) positivity for representation-theoretic multiplicities Kroenke, platysma, and (iv) modern tools that have proved or advanced these questions. We close with a curated bibliography of key references and suggested research directions.

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Published by: vikaspatanker

Authors: Gowri A, Mohamed Sathik Z, Moses Saveriyar A, Sanjay P

Abstract: Construction sites are among the most hazardous work environments due to unsafe practices and the improper use of Personal Protective Equipment (PPE). To address these safety challenges, this project proposes an AI-based Construction Site Safety Violation Detection System that automatically identifies unsafe behaviors and PPE violations in real-time video streams. The system utilizes computer vision and deep learning techniques to detect workers, safety gear such as helmets and vests, and hazardous actions including entry into restricted zones and working at heights without protection. A tracking-by-detection approach is employed to monitor individuals across video frames, while pose estimation and action recognition models analyze human posture and movements to classify unsafe activities. When a safety violation persists beyond a predefined duration, the system generates instant alerts to enable timely intervention. This automated approach enhances workplace safety, reduces human supervision effort, and helps construction organizations proactively prevent accidents and injuries.

DOI: https://doi.org/10.5281/zenodo.18766472

Published by: vikaspatanker

Authors: Dr. Amudha G, Porselvi B, Radha A, Usha Mahi Pon

Abstract: Rising electricity demand and the need for sustainable energy solutions have encouraged exploration of alternative micro-generation technologies. This study investigates the use of piezoelectric powered flooring systems to harvest mechanical energy from human footsteps in high-footfall areas such as railway stations, commercial buildings, and educational institutions in India. By converting mechanical stress into electrical energy, piezoelectric materials offer a method of generating supplementary power without requiring additional land or fuel resources. The proposed work presents the system design framework, working principle, and feasibility of large-scale implementation within public infrastructure. Performance estimations indicate that although piezoelectric flooring cannot replace conventional energy sources, it can contribute to localized power needs and support smart, energy-efficient urban environments. The study highlights the potential of integrating energy harvesting technologies into everyday infrastructure to promote sustainable development.

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Published by: vikaspatanker

Authors: Pranabesh Ghosh, Abhishek Konar, Tahsina Tabia

Abstract: The microbial ecosystem within a wastewater treatment facility serves multiple functions-removal of contaminants, recycling nutrients, and recovering resources. However, conventional process monitoring focuses on bulk physicochemical data, limiting information on the microbial processes driving system function. Recent advancements in multi-omics technologies—metagenomics, metatranscriptomics, metaproteomics, and other omics domains—have significantly advanced the study of the microbial communities in wastewater treatment by allowing researchers to comprehensively describe a microbial community's composition, functional capacity, and metabolic activity. Omics technologies have improved knowledge of the biological processes governing the nitrogen, phosphorus, and carbon cycles in wastewater, and the technologies can identify new contaminants and antibiotic resistance genes. When paired with predictive bioprocess modelling, multi-omic data enhances operational control and system stability and promotes energy-efficient process design. Omics data have revealed opportunities for the modernized wastewater treatment plant (WWTP) to transition to a water resource recovery facility (WRRF), wherein the plant can produce methane, recover nutrients, generate biopolymers, and contribute to the carbon economy. Despite advancements utilizing multi-omics technologies, there remain obstacles. Ongoing and emerging challenges include the high cost of sequencing, data integration difficulties, limited applicability to real-time processes, and a lack of infrastructure in developing regions. Closing the gap on process-scale implementation of multi-omics technologies will require standardized testing, multi-disciplinary collaboration, and the use of artificial intelligence control systems. Multi-omics techniques signify a changing of the guard in precision ecological engineering and the development of sustainable, climate-resilient, and resource-efficient bioprocess systems for wastewater treatment. Sustained technological advancement and integration at the systems level will be essential for the future of energy-positive and carbon-neutral wastewater treatment.

DOI: https://doi.org/10.5281/zenodo.18755909

 

Published by: vikaspatanker