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Research Paper

A Comprehensive Analysis of Why Startups Fail

Young enterprises significantly contribute to fostering creativity and boosting national prosperity; however, many of them encounter substantial setbacks during their early stages. The study examines the major factors contributing to business failures by integrating scholarly works and analyzing real-world examples. Research suggests that an unmet marketplace need, coupled with insufficiently compelling offerings, continues to be the primary reason for failure in business ventures. Lack of financial resources, such as insufficient funds and poor management of cash flows, intensifies volatility. Business strategies lacking in scalability or profit potential frequently result from inadequate strategic foresight, leading to premature failure at the inception stages. Moreover, poor teamwork, disagreements among leaders, and a lack of flexible abilities impede productivity and strategic thinking. Exogenous factors like compliance hurdles, innovation shifts, and global economic fluctuations exacerbate inherent organizational flaws. This research incorporates findings from reports like the Startup Genome Report and analysis by CB Insights to classify failures based on both intrinsic factors related to strategy, finances, management, and extrinsic elements affecting market conditions and environments. The document underscores that achieving successful startups requires skill in strategy, precise market fit validation, robust management skills, and continuous improvement through repetition. This research provides an analytical model of how startups fail, helping business owners, financiers, and government officials manage risks effectively and make well-informed choices.

Published by: Gowardhan Veerdhawal Dafale, Omkar Shirish Kshirsagar, Vaishnavi Baban Ugale, Sanika Sunil Sankpal, Kunjan Atul Bhate, Mohit Satish Saindane

Author: Gowardhan Veerdhawal Dafale

Paper ID: V11I5-1312

Paper Status: published

Published: November 11, 2025

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Research Paper

A Comparative Study of Machine Learning Models for Predictive Analytics in Detecting Security Breaches Across Industrial IoT-Based Critical Infrastructure in U.S. Organizations

Industrial Internet of Things (IIoT) technologies have emerged with significant security challenges due to increasing interconnectivity and network complexity. Thus, this study proposes and tests a centralized deep-learning intrusion detection system (IDS) particularly designed for IIoT networks. Convolutional Neural Networks (CNNs) and Multilayer Perceptrons (MLPs) were implemented in PyTorch and TensorFlow, and their performance was assessed on the CIC IoT-DIAD 2024 dataset to simulate real industrial traffic and varied attack vectors. Accuracy, precision, recall, F1-score, and confusion matrices were used for the evaluation metrics. Results showed that the TensorFlow CNN achieved the highest detection rate (80.1%), followed very closely by the PyTorch CNN (77.3%), highlighting the superior performance of CNN architectures, especially on TensorFlow, in recognizing intricate spatial patterns in IIoT traffic. The comparative research enhances IIoT cybersecurity research by identifying efficient deep learning models for intrusion detection and proposing a framework for adoption in industrial systems to improve resilience and mitigate vulnerability to advanced cyberattacks.

Published by: Tolulope Onasanya, Adeogo Olajide, Oduwunmi Odukoya, Hannah I. Tanimowo

Author: Tolulope Onasanya

Paper ID: V11I5-1314

Paper Status: published

Published: November 11, 2025

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Research Paper

Experimental Investigation of Coconut Shell as a Lightweight Aggregate in Concrete

This experimental study investigates the feasibility of utilising coconut shell as a partial replacement for conventional coarse aggregates in M20 grade concrete. The aim is to evaluate the mechanical and physical properties of lightweight concrete produced using varying percentages of coconut shell aggregates (0%, 10%, 20%, and 30%). Experimental parameters such as workability, density, and compressive strength at 7, 14, and 28 days were analysed. Results indicated that a 20% replacement of coarse aggregates with coconut shells provided an optimal balance between strength and weight reduction, making it suitable for non-structural and low-load-bearing applications. The study concludes that coconut shell concrete is an eco-friendly alternative for sustainable construction practices.

Published by: Samuel Abraham D, Gururaj R, Mubarak A, Sarathy K, Vimal Singh K

Author: Samuel Abraham D

Paper ID: V11I5-1292

Paper Status: published

Published: November 7, 2025

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Research Paper

Impact of AI and Automation on Employee Upskilling Needs

Artificial Intelligence (AI) and automation are transforming the global labour market by redefining job roles, required competencies, and organisational learning priorities. This study investigates the growing need for upskilling among employees as workplaces adopt AI-enabled systems. The study combines insights from established global and Indian literature with sample-based data to analyze how AI adoption impacts workforce readiness and skill development. Data from institutional reports such as the International Association of Workforce Professionals (2024), All Multidisciplinary Journal (2025), SDMIMD HR Conference (2023), and Taylor & Francis (2021) were examined alongside sample dataset analysis. The findings indicate that while automation displaces repetitive jobs, it simultaneously generates demand for complex cognitive, technical, and interpersonal skills. Indian organizations are rapidly adopting AI tools but often lack structured training mechanisms to address the emerging skill gap. The study emphasizes that strategic upskilling programs, leadership involvement, and policy support are critical for sustaining employability and competitiveness in the AI era.

Published by: Aishwarya Nikhal, Aanchal Amodkar, Aditya Yanpallewar, Adesh Bhosale, Aastha Sharma

Author: Aishwarya Nikhal

Paper ID: V11I5-1268

Paper Status: published

Published: November 5, 2025

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Review Paper

Smart Irrigation System Using IoT

This paper presents the design and implementation of a Smart Irrigation System using Internet of Things (IoT) technologies for efficient agricultural water management. The system utilizes an Arduino Uno microcontroller, soil moisture sensors, and a GSM communication module to automate irrigation processes. By integrating real-time soil data with cloud-based storage through Firebase, it ensures data accessibility, analysis, and remote monitoring. The experimental results demonstrate water savings of approximately 35–40% and an energy reduction of 20% compared to conventional irrigation methods. The proposed system enhances sustainability and supports precision agriculture practices.

Published by: Prabjyot Singh Solar, Manoj Mishra

Author: Prabjyot Singh Solar

Paper ID: V11I5-1297

Paper Status: published

Published: November 5, 2025

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Research Paper

Judicial Accountability and Institutional Reform: A Methodological Framework for Assessing the Amendment to the Judicial Conduct & Removal Regime in India via the Yashwant Verma Affair

The integrity and independence of the judiciary are the twin pillars of constitutional democracy. However, the recent Justice Yashwant Varma affair—involving a probe initiated under the supervision of Chief Justice D.Y. Chandrachud and recommendations by Justice Sanjiv Khanna— has reignited national debate on the adequacy of India’s mechanisms for judicial accountability. This research seeks to evaluate the potential amendment and reform of the judicial conduct and removal regime through a combined doctrinal-empirical approach. It will analyse the constitutional and statutory framework governing judicial conduct (Arts. 124–137, 217–222 of the Constitution; Judges [Inquiry] Act 2, 1968), examine procedural lacunae revealed by the Varma inquiry, and propose a methodological framework to assess future reforms. The study situates the case within the broader question of how India can reconcile judicial independence with accountability and transparency. This research explores how the Justice Varma episode and Justice Khanna’s proactive stance may signal the beginning of a long-overdue amendment to the judicial accountability framework in India. Adopting a mixed-method approach that integrates doctrinal legal analysis with empirical qualitative research, the study examines constitutional provisions (Articles 124–147 and 217–222), the Judges (Inquiry) Act, 1968, and the 1999 in-house procedure to identify institutional gaps and reform needs. It further draws comparative insights from other common-law jurisdictions such as the United Kingdom and Canada, where judicial conduct mechanisms operate with transparency and independence. By framing a methodological model that evaluates both legal norms and real-world perceptions, this research aims to contribute to scholarly and policy discourse on how India can evolve a codified, transparent, and ethically resilient framework for judicial accountability—one that safeguards both public confidence and judicial autonomy.

Published by: Srihari

Author: Srihari

Paper ID: V11I5-1275

Paper Status: published

Published: November 4, 2025

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