Manuscripts

Recent Papers

Research Paper

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

Full Details
Research Paper

Rural India’s FMCG Consumer: A Review

This review paper synthesizes existing research to provide a comprehensive understanding of the Indian rural FMCG consumer. It examines the unique demographic, psychographic, and behavioral characteristics that influence purchasing decisions in this significant market segment. By analyzing various marketing insights, the paper identifies key challenges and opportunities for FMCG companies seeking to penetrate rural India. Specifically, it explores the impact of socio-cultural factors, economic conditions, and evolving digital literacy on consumer behavior, emphasizing the importance of localized marketing strategies, innovative distribution models, and community engagement. This review contributes to the existing literature by providing a consolidated perspective on the multifaceted nature of the Indian rural FMCG consumer, offering actionable insights for effective market penetration and sustainable growth.

Published by: Thilakk MB, S. Swetha Shree, Dr. A.S. Princy

Author: Thilakk MB

Paper ID: V11I1-1509

Paper Status: published

Published: April 2, 2025

Full Details
Research Paper

History of Music: How History Shaped Music, and Music Shaped History

Music is not merely a reflection of history—it is a force that has shaped it. This paper explores the symbiotic relationship between music and historical events, illustrating how melodies, rhythms, and lyrics have influenced societies, driven political movements, and preserved cultural identities. Music has acted as a catalyst for social change, fueling revolutions, advocating for justice, and even altering the course of global diplomacy. Genre hybridization and technological advancements have further expanded music’s impact, allowing for cross-cultural fusion and worldwide accessibility. By analyzing key moments in history where music played a pivotal role—whether through protest anthems, nationalistic compositions, or groundbreaking innovations—this study highlights music's enduring power as both a historical artifact and an agent of transformation.

Published by: Jiya Doshi

Author: Jiya Doshi

Paper ID: V11I1-1515

Paper Status: published

Published: April 2, 2025

Full Details
Research Paper

Dairy Farming

The Dairy Farming App enhances traditional livestock trading by offering a secure, transparent, and user-friendly digital platform. Built with Android Studio for the frontend and Java for backend integration, the app facilitates direct interaction between farmers, veterinarians, and buyers, reducing reliance on intermediaries. Its core functionalities include real-time messaging, location-based listings, livestock health record management, and IoT-driven herd monitoring. Comprehensive testing ensured the app meets functional, UI/UX, and security standards, achieving a 95% success rate in transaction completion. This paper explores the app’s development, implementation, and its transformative impact on modernizing livestock management through innovative technology.

Published by: Purvank Chauhan, Shubham Upadhyay

Author: Purvank Chauhan

Paper ID: V11I1-1475

Paper Status: published

Published: April 2, 2025

Full Details
Review Paper

Data Privacy and Artificial Intelligence Governance for Marginalized Communities in the United States: How Important is Inclusivity?

The study, “Data Privacy and AI Governance for Marginalized Communities in the United States,” examines the digital divide affecting marginalized groups and its exacerbation by biased AI governance. With the objectives of assessing data privacy risks, analyzing biases in AI systems, and proposing inclusive policies to improve AI governance, the research highlights key findings, including that marginalized communities, particularly racial minorities and low-income populations, face disproportionate risks from surveillance capitalism, biased facial recognition, and AI-driven hiring processes. Healthcare is also affected by the technological bias as AI models less accurately serve marginalized groups owing to unrepresentative data sets. In response, the study recommends stringent data protection laws akin to the European Union’s GDPR, ethical AI standards focused on transparency, as well as mandatory diversity in AI development teams to ensure demographic representation. To address biases in surveillance, the enactment of the George Floyd Justice in Policing Act and the Facial Recognition and Biometric Technology Moratorium Act are recommended. The work concludes with an emphasis on the need for digital inclusion and equitable AI governance to prevent further marginalization and foster fair participation in a digital society.

Published by: Idara Bassey

Author: Idara Bassey

Paper ID: V11I1-1469

Paper Status: published

Published: March 27, 2025

Full Details
Research Paper

Cab Fare Prediction Machine Learning Model

Predicting cab fares accurately is crucial for urban transportation, benefiting both passengers and service providers. This research explores machine learning techniques to enhance fare prediction using real-world trip data. Various models, including Linear Regression, Decision Trees, Random Forest, Gradient Boosting, and XGBoost, were evaluated. The Gradient Boosting Regressor emerged as the best-performing model after hyperparameter tuning, achieving high prediction accuracy. The study highlights the significance of trip distance and pickup time in fare estimation. Future enhancements include integrating weather data and deploying the model as a real-time API service to improve usability and precision.

Published by: Purvank Chauhan, Shubham Upadhyay

Author: Purvank Chauhan

Paper ID: V11I1-1480

Paper Status: published

Published: March 27, 2025

Full Details
Request a Call
If someone in your research area is available then we will connect you both or our counsellor will get in touch with you.

    [honeypot honeypot-378]

    X
    Journal's Support Form
    For any query, please fill up the short form below. Try to explain your query in detail so that our counsellor can guide you. All fields are mandatory.

      X
       Enquiry Form
      Contact Board Member

        Member Name

        [honeypot honeypot-527]

        X
        Contact Editorial Board

          X

            [honeypot honeypot-310]

            X