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FESTIVAL BLACK EYES BEANS ou Niébé À PORT-BERGE et MAMPIKONY DANS LA REGION SOFIA, MADAGASCAR

The Black Eyes Beans (BEB) or cowpea festival is a cultural festival in the Sofia region in the northwestern part of Madagascar, during which the organizers aim to promote the agricultural and cultural development of the region. This region is known as the Malagasy capital of BEB, whose farmers represent 80% of the region's inhabitants. The production area is mainly located in two districts: Port-Bergé and Mampikony. This work therefore aims to present the importance of black eyes culture but also to demonstrate the cultural richness in artistic music through the BEB festival in the Sofia region. To this end, many beneficiaries benefit from the organization of the festival. Mainly BEB producers for sale. It is a great opportunity for farmers and even for those who are not involved in the cultivation of said product to exhibit their productions. It is also a highlight for artistic festivities. Artists actively participate during the event by providing entertainment and making the days more festive. Thus, compared to other festivals in Madagascar, the BEB festival is typical of the Sofia region in view of the agricultural and artistic potential presented there. Behind this festival event lies an exploitation of enormous economic potential. Thus, recommendations are then proposed to all stakeholders, both farmers or producers, the organizer, and decentralized local authorities for the improvement and sustainability of the BEB festival.

Published by: Cyprien Zaralahy

Author: Cyprien Zaralahy

Paper ID: V10I6-1367

Paper Status: published

Published: April 7, 2025

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Analysis of Mental Health Economics

Over the past few decades, the economics of mental health has drawn more attention, changing from a neglected area to a crucial one for healthcare policy and resource distribution. The economic aspects of mental health, such as resource allocation, intervention cost-effectiveness, and the financial toll that mental health illnesses have on both individuals and societies, are examined in this study. It examines how funding for mental and physical health care differs, emphasising the problems of stigma, geographical imbalances, and a lack of qualified personnel. The research paper assesses the cost-effectiveness of preventive, treatment, and rehabilitation programs using data from international studies. It also looks into how economic assessments, like quality-adjusted life years (QALYs) and cost-benefit analyses, are used to make policy. The study emphasises the value of allocating resources in an equal and evidence-based manner, encouraging openness, accessibility, and effectiveness in the provision of mental health services. This paper seeks to support policy changes that improve the availability and caliber of mental health services globally by addressing economic inefficiencies and arguing for more financing.

Published by: Parii Jain

Author: Parii Jain

Paper ID: V11I1-1528

Paper Status: published

Published: April 5, 2025

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CBIR: Enhancing Image Retrieval through AutoEncoders and Metric-Based Search

The exponential growth of visual data demands robust Content-Based Image Retrieval (CBIR) systems that ac- curately and efficiently retrieve relevant images. In this paper, we present a novel CBIR framework that integrates AutoEncoders for latent feature extraction with hashing and Vantage-Point Trees (VP-Trees) for efficient similarity search. Experimental results on a publicly available dataset demonstrate significant improvements in retrieval precision and computational efficiency.

Published by: Ayush Anand, Shreyansh Narayan, Vinayak Gupta

Author: Ayush Anand

Paper ID: V11I1-1496

Paper Status: published

Published: April 5, 2025

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A Patient-Specific Computational Framework Utilizing CFD and Bio-Numerical Modelling to Predict Growth of Abdominal Aneurysms for Therapeutical Aid

This research aims at devising a framework between a CFD model and a derived biomechanical model that effectively makes AAA (abdominal aortic aneurysms) therapeutics more accurate. The input data required is patient abdominal CT-imaging scans using CAD software's and features we can extract out of the vessel geometry in which, after meshing, we can simulate the blood flow using CFD in Ansys Fluent. This blood flow CFD simulation helps us identify the high-pressure or stressed regions of the vessel wall. Using the biomechanical factors affecting aneurysmal expansion, a model to quantify expansion per unit time was derived. This model took into consideration factors like compliance, elastic modulus, and other mechanical properties. Using the geometrical parameters that can be acquired from VMTK processing on the CAD vessel geometry and variable parameters like pressure and velocity from the CFD simulation, the date of rupture can be approximated, thus precisifying aneurysmal therapeutics.

Published by: Aadittya Deouskar

Author: Aadittya Deouskar

Paper ID: V11I1-1504

Paper Status: published

Published: April 5, 2025

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Federated Learning in Data Warehousing: A Privacy-Preserving Approach for Distributed Analytics

With the explosion of data generated across distributed environments, organizations face challenges in extracting insights while maintaining data privacy and regulatory compliance. Federated Learning (FL), a machine learning paradigm where models are trained across decentralized data sources without moving the data, has emerged as a promising solution. This paper explores the integration of FL with modern data warehousing architectures to enable secure, scalable, and privacy-preserving distributed analytics. We outline a federated data warehousing framework, highlight real-world use cases, evaluate system performance, and discuss future research directions.

Published by: Akash Vijayrao Chaudhari, Pallavi Ashokrao Charate

Author: Akash Vijayrao Chaudhari

Paper ID: V11I1-1513

Paper Status: published

Published: April 4, 2025

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Enhanced Recovery After Surgery (ERAS) vs. Conventional Protocols in Open Abdominal Hysterectomy: A Comparative Study

Objective: This study evaluates and compares postoperative recovery outcomes in women undergoing open abdominal hysterectomy using either the conventional recovery protocol (CRP) or the early recovery after surgery (ERAS) protocol. The objective is to assess the impact of ERAS on hospital stay duration, pain management, ambulation, and complications. Methods: A prospective comparative study was conducted on 100 women undergoing open abdominal hysterectomy for benign gynecological conditions. Patients were divided into two groups: 50 managed with CRP and 50 with ERAS. The primary outcome measures were postoperative pain scores, time to ambulation, length of hospital stay, postoperative nausea and vomiting (PONV), and surgical site infection (SSI). Results: Patients in the ERAS group had significantly improved recovery outcomes. Their hospital stay was shorter (3.2 ± 1.1 days vs. 5.8 ± 1.4 days for CRP), ambulation was achieved earlier (8 ± 3 hours vs. 24 ± 6 hours), and postoperative pain scores were lower (VAS score: 4.8 ± 1.1 vs. 7.2 ± 1.3). Additionally, ERAS patients experienced fewer complications, with lower rates of PONV (16% vs. 30%) and SSI (4% vs. 12%). Conclusion: The ERAS protocol enhances postoperative recovery after open abdominal hysterectomy by reducing hospital stay, improving pain control, and decreasing complications. These findings support the implementation of ERAS as a standard approach to improve patient outcomes and reduce healthcare burdens.

Published by: Dr. Surabhi Sharma, Dr. Ravikant Bhardwaj

Author: Dr. Surabhi Sharma

Paper ID: V11I1-1533

Paper Status: published

Published: April 4, 2025

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