Category Archives: Uncategorized

Authors: Mr. Ashish Kumar, Dr. Satender Kumar

Abstract: The study of anomaly detection in time series has become one of the key topics in intelligent monitoring systems such as industrial automation, cybersecurity, healthcare, finance, IoT. The traditional approaches to anomaly detection primarily focused on detecting any signs of anomalous behaviour following their occurrence. However, in many cases, reactive anomaly detection does not allow for timely response to detected anomalies. Recently, some researchers have suggested the novel idea of Precursor-of-Anomaly (PoA) detection to detect and analyse warning signs prior to anomalies' occurrence. The present paper provides a review and experimental framework of PoA detection in time series. The paper outlines approaches to traditional anomaly detection, deep learning based forecasting models, uncertainty-aware models, and early warning approaches. Also, the paper outlines a practical framework of PoA analysis using industrial SWaT dataset and Isolation Forest approach. Experimental results prove that uncertainty-aware PoA detection is capable of delivering early warning signals before critical anomalies occur. The paper considers modern limitations and challenges in designing proactive anomaly prediction systems.

DOI: https://doi.org/10.5281/zenodo.20631084

Published by: vikaspatanker

Authors: Associate Professor Mahesh Thakare, Pooja Choudhary, Sakshi Harihar, Vijaykumar Kale, Associate professor Vaibhav Narwade

Abstract: Approximately 85% of teenagers suffer from acne vulgaris, which can last until adulthood. Teenagers see doctors approximately two million times a year, and the US spends more than $1 billion on acne treatments directly. There are many different therapy options for acne vulgaris, such as hormonal, anti- androgen, or anti seborrheic medications, as well as retinoids, isoprenoids, keratolytic soaps, alpha hydroxy acids, azelaic acid, and salicylic acid. All of these techniques do have some negative effects, though, and it's unclear exactly how they fit into therapy. This paper not only presents the potential causes of acne vulgaris, medications that can treat it, and recently released research on the usage of medicinal herbs to treat the condition were examined. Topical formulations (herbal cream) have been developed containing Ocimum sanctum (Tulsi) extract, Aloe barbadensis miller (Aloe-vera Gel), Melaleuca Oil (Tea Tree Oil). These medicinal herbs and essential oil (TTO) show anti-bacterial activity against acne causing bacteria like Propionibacterium and staphylococcus aures. Various batches containing above Herbs and Essential oil are prepared and their comparative studies are performed. Certain evaluation tests are performed like Irritancy, Washability, pH, Greasiness to check whether cream is suitable for human skin. In the end anti-bacterial activity of the cream was carried out using agar well diffusion method against staphylococcus aures.

DOI: http://doi.org/

Published by: vikaspatanker

Authors: Assistant Professor Dr. Vijaykumar Kale, Ms.Rutuja Popat Chavan, Ms.Pratiksha Ashok Jaybhay, Dr. Mahesh Thakare, Mr. Vaibhav Narwade

Abstract: Herbal cosmetics have gained significant importance due to their safety, effectiveness, and minimal side effects compared to synthetic products. The present research project focuses on the formulation and development of herbal hair oil using Betel Leaf as the major active ingredient. Betel leaf is traditionally known for its antimicrobial, antifungal, antioxidant, and anti-inflammatory properties, which are beneficial for maintaining healthy hair and scalp conditions The herbal hair oil was prepared using betel leaf along with other natural ingredients such as coconut oil, curry leaves, hibiscus, and aloe vera. The formulation was developed by heating the herbal materials with the base oil to extract the active constituents effectively. The prepared oil was filtered and evaluated for various physicochemical parameters including color, odor, pH, viscosity, specific gravity, irritation test, and stability study. The formulated herbal hair oil showed satisfactory physical appearance, good stability, and acceptable consistency without causing skin irritation. The presence of betel leaf in the formulation may help reduce dandruff, scalp infections, and hair fall due to its medicinal properties. The study concludes that the prepared herbal hair oil can serve as a safe, economical, and natural alternative for hair care management. This research supports the growing demand for herbal cosmetic products and highlights the potential. [1]

Published by: vikaspatanker

Authors: By Mr. Basavaraj Swamy

Abstract: Techniques from Machine learning and deep learning are usually helpful in classification of data. A dataset is processed through a CNN before it is used for classification. Text mining, image processing, and score prediction techniques are very much important in the field of analytics. In paper, we used classification and data prediction methods to demonstrate image and numerical analysis. Analytics show that traditional backup methods have been improved with better ways of managing data. This process of supervised learning produces comparable present outcomes with accurate predicted values.

Published by: vikaspatanker

Authors: Amal prawin, Sanjay P K, Mrs.Haseena

Abstract: The surge in digital payment systems, facilitated through mobile phones, has revolutionized the financial landscape, promising convenience, accessibility, and efficiency. However, amid this rapid digital transformation, various challenges and problems have emerged, necessitating comprehensive examination. This study delves into the intricate fabric of mobile phone-based digital payment systems, aiming to identify and analyse the multifaceted hurdles impeding their seamless operation. Drawing upon extensive literature review and empirical research, this study navigates through the labyrinth of challenges encountered in digital payment ecosystems. From technological limitations to socio-economic disparities, from security concerns to regulatory complexities, the spectrum of impediments is diverse and far-reaching. The research employs both qualitative and quantitative methodologies to unravel the underlying dynamics and discern patterns amidst the chaos.

DOI: http://doi.org/10.5281/zenodo.20617421

Published by: vikaspatanker

Authors: Ms. Anisha S, Ms. Rathika R, Dr. N. Rajendran

Abstract: This study investigates the role of Corporate Social Responsibility (CSR) in marketing, highlighting its increasing significance as a strategic component in today’s business landscape. As consumers become more socially and environmentally conscious, companies are compelled to integrate CSR initiatives into their marketing strategies to align with evolving consumer expectations. The study aims to examine the influence of CSR on consumer purchasing behavior, evaluate its role in enhancing brand image and reputation, and identify the challenges businesses face in authenticating CSR within their marketing efforts. Through a comprehensive analysis, the study reveals that CSR initiatives positively impact consumer purchasing decisions, particularly among younger generations who prioritize ethical practices and sustainability. It emphasizes the importance of authenticity in CSR efforts, noting that companies that genuinely engage in responsible practices are perceived as more trustworthy and responsible, which enhances their brand reputation. The findings also indicate that the effectiveness of CSR marketing varies across industries, suggesting that tailored strategies are essential for resonating with target audiences. However, companies encounter challenges such as skepticism about insincere CSR activities and difficulties in effectively communicating their initiatives. Recommendations for effective CSR integration include ensuring authenticity, tailoring initiatives to industry specific needs, committing to long-term sustainability efforts, and actively engaging stakeholders. This study concludes that when strategically incorporated into marketing, CSR can strengthen brand loyalty, enhance corporate reputation, and contribute to positive social and environmental impacts, ultimately driving long-term business success.

DOI: http://doi.org/10.5281/zenodo.20614759

Published by: vikaspatanker

Authors: Ms. Anisha, Ms. Divyabharathi, Mrs. Jeya Padma Deepa I

Abstract: In the contemporary digital era, ethical commerce has emerged as a critical dimension of business strategy, extending beyond profit maximization to include social responsibility, environmental sustainability, and ethical governance. Corporate Social Responsibility (CSR) in a digital age is shaped by rapid technological advancements, e-commerce platforms, social media, data analytics, and increased stakeholder awareness. Businesses today are expected to operate transparently, protect consumer data, ensure fair digital practices, and contribute positively to society while leveraging digital tools for growth. This article examines the concept of ethical commerce and the evolving role of CSR in a technology-driven business environment. It explores how digital platforms influence CSR initiatives, enhance stakeholder engagement, and promote sustainable business practices. The study also highlights challenges such as digital inequality, data privacy concerns, and greenwashing. By adopting ethical digital strategies, organizations can build trust, strengthen brand reputation, and achieve long-term sustainability. The article aims to provide undergraduate students with a comprehensive understanding of ethical commerce and the significance of CSR in the modern digital business landscape.

DOI: http://doi.org/10.5281/zenodo.20614573

Published by: vikaspatanker

Authors: Mr. Aadhi Keerthi P, Mr. Logesh B, Mrs. Chitra B

Abstract: Consumer buying behaviour plays a vital role in the success of the electronic gadgets industry. The increasing use of smartphones, laptops, tablets, smartwatches, and other electronic devices has significantly influenced consumer lifestyles and purchasing patterns. This study titled “A Study on Consumer Buying Behaviour towards Electronic Gadgets with Special Reference to Coimbatore” aims to examine the factors affecting consumer preferences and buying decisions related to electronic gadgets. The study focuses on understanding how factors such as price, brand image, product quality, technological features, advertisements, social media influence, and after-sales service impact consumer purchasing behaviour. Both primary and secondary data are used for the research. Primary data were collected through a structured questionnaire distributed among consumers in Coimbatore city, while secondary data were collected from journals, books, websites, and previous studies. Statistical tools like percentage analysis and ranking methods are applied for data interpretation. The findings indicate that consumers highly prefer branded electronic gadgets with advanced features and reasonable prices. Online reviews, digital marketing, and social influence also affect purchasing decisions. The study concludes that electronic gadget companies should focus on innovation, quality improvement, customer satisfaction, and effective promotional strategies to strengthen their market position and meet changing consumer expectations.

DOI: http://doi.org/10.5281/zenodo.20612956

Published by: vikaspatanker

Authors: Nidhi Singh, Dr Navneet Seth

Abstract: The financial sector is undergoing a profound metamorphosis, driven by the accelerating integration of Artificial Intelligence (AI) into core decision-making processes. This paper investigates the multi-dimensional impact of AI on financial decision-making, encompassing investment analysis, credit risk assessment, fraud detection, financial forecasting, and customer service. Employing a descriptive-quantitative research design with a structured questionnaire administered to 100 respondents comprising banking professionals, financial analysts, investors, and accountants, the study deploys percentage analysis, frequency distribution, mean scoring, and Chi-Square hypothesis testing to derive empirical evidence. Findings reveal that 85% of respondents demonstrate awareness of AI-enabled financial tools, 75% affirm that AI materially elevates decision-making accuracy, and 80% express high satisfaction with AI-powered financial services. The Chi-Square test confirms a statistically significant relationship between AI adoption and financial decision-making effectiveness (χ² = 18.64, p < 0.05). Notwithstanding these benefits, data privacy concerns (35%), cybersecurity vulnerabilities (25%), and elevated implementation costs (20%) constitute critical impediments. The paper concludes that AI is not merely an operational efficiency enhancer but a strategic imperative for modern financial institutions, and advocates for responsible, ethics-driven AI governance frameworks to sustain its transformative potential.

Published by: vikaspatanker

Authors: Alexander Stewart, Elizabeth Watson, Andrew Peterson, Natalie Brooks, Chaitanya Srinivas, Rishi Kumar

Abstract: Modern enterprises rely heavily on complex digital infrastructures, cloud-native applications, distributed networks, and real-time operational systems that generate massive volumes of monitoring data continuously. Traditional monitoring approaches often struggle to identify emerging system failures, operational anomalies, cybersecurity threats, and performance degradation in a timely manner, leading to increased downtime, financial losses, and reduced service reliability. Smart monitoring systems powered by artificial intelligence and intelligent analytics have emerged as advanced solutions for proactive incident prediction and detection in dynamic enterprise environments. This research paper explores the integration of artificial intelligence, machine learning, real-time analytics, and event-driven monitoring architectures to enhance operational visibility and predictive incident management capabilities. The study examines how intelligent monitoring platforms leverage anomaly detection, predictive analytics, behavioral analysis, automated alerting, and cloud-native observability tools to identify potential incidents before they impact business operations. Furthermore, the paper discusses the role of distributed data streaming, automated response systems, infrastructure monitoring, and AI-assisted decision intelligence in improving operational resilience and system reliability. Key challenges including scalability, false-positive reduction, data consistency, cybersecurity protection, and monitoring complexity are also analyzed. Through comprehensive evaluation and industry-oriented insights, the research demonstrates how smart monitoring systems enable proactive incident prevention, intelligent operational management, faster root-cause analysis, and continuous service optimization across modern digital enterprise ecosystems.

DOI: http://doi.org/10.5281/zenodo.20608477

Published by: vikaspatanker