Authors: Sandhya, Mamatha U, Siddegowda

 

Abstract: This article delves into the transformative role of nanotechnology in logistics, particularly emphasizing its applications within cold chain management and smart packaging solutions. Cold chain logistics, critical for industries like pharmaceuticals and food, involves maintaining strict temperature controls to preserve product quality and safety during transportation and storage. Nanotechnology offers innovative tools such as nanosensors, nanomaterials, and nano-coatings that enable real-time, highly accurate monitoring of environmental conditions including temperature, humidity, and contamination risks. These nanoscale innovations can detect minute changes, alerting stakeholders immediately to potential breaches that could compromise product integrity. This capability not only significantly reduces spoilage and waste but also extends the shelf life of perishable goods, ensuring safer delivery to end consumers. Moreover, nanotechnology enhances smart packaging by integrating intelligent features directly into packaging materials. Nanocoatings can provide antimicrobial properties, improve barrier protection against oxygen and moisture, and facilitate controlled release of preservatives or freshness indicators. Combined with nanosensors embedded in packaging, businesses gain detailed insights into the product’s condition throughout the supply chain, promoting transparency and trust between producers, distributors, and consumers. This data can be integrated with Internet of Things (IoT) platforms and analyzed through artificial intelligence (AI) to optimize logistics, forecast demand, and respond dynamically to supply chain disruptions. Ultimately, this article offers strategic insights for enterprises eager to leverage nanotechnology as a means to build resilient, sustainable, and smart supply chains. By embracing these innovations, businesses can meet the increasing global demand for product safety, environmental responsibility, and operational efficiency, positioning themselves competitively in a rapidly evolving logistics landscape.

DOI: http://doi.org/10.61137/ijsret.vol.10.issue6.658

 

Published by: vikaspatanker

Authors: Meenakshi, Manju Prasad, Selva.P

 

Abstract: The COVID-19 pandemic profoundly disrupted global business landscapes, compelling organizations to reassess and transform their traditional business models. This article examines the critical lessons in resilience and technological adaptation that have emerged in the post-pandemic era, highlighting how agility, digital transformation, and customer-centric innovation have become essential for survival and growth. It explores shifts in business paradigms towards flexible operations, hybrid models, and platform ecosystems that blend physical and digital engagement. The discussion also addresses key challenges such as regulatory complexities, cybersecurity risks, and digital divides, emphasizing the importance of strategic investment in technology, workforce development, and collaborative innovation. By analyzing successful adaptation strategies and emerging trends, this study provides actionable insights for business leaders, entrepreneurs, and policymakers aiming to foster sustainable and competitive enterprises in a rapidly evolving, uncertain environment.

DOI: http://doi.org/10.61137/ijsret.vol.10.issue6.657

 

Published by: vikaspatanker

Authors: Noushad Pasha

 

 

Abstract: Nanotechnology is revolutionizing the healthcare industry by enabling unprecedented precision in diagnostics, drug delivery, and disease management. Operating at the molecular and atomic levels, nanotechnology introduces new tools and techniques that enhance the efficiency, accuracy, and personalization of medical interventions. This article explores the fundamental principles of nanotechnology in medicine and its transformative applications in early diagnostics and targeted drug delivery. It further examines evolving market dynamics, investment trends, and commercialization strategies within the healthcare business. Additionally, the paper addresses critical challenges such as regulatory ambiguity, ethical concerns, and scalability of nanotechnological solutions. Finally, it discusses future trends, including the integration of nanotech with artificial intelligence and personalized medicine, highlighting the potential for a paradigm shift toward more predictive, preventive, and patient-centered care. Through a multidisciplinary lens, the article provides a comprehensive overview of how nanotechnology is redefining the healthcare landscape and its implications for global health systems.

DOI: http://doi.org/10.61137/ijsret.vol.10.issue6.656

 

 

Published by: vikaspatanker

Authors: Ashu Gulia, Sangeeta Rani, Monika Saini

Abstract: In the realm of cybersecurity, the continuous evolution and sophistication of malware pose significant challenges to the detection and mitigation of cyber threats. This research paper delves into the analysis of anomaly detection of malware using Support Vector Machines (SVM), a powerful machine learning algorithm known for its effectiveness in classification tasks. By leveraging SVM for anomaly detection, this study aims to explore the potential of SVM in identifying malicious behavior patterns that deviate from normal system activities. The paper provides insights into implementing SVM-based anomaly detection for malware, including data preprocessing, feature extraction, model training, and evaluation. Furthermore, the research investigates the performance of SVM in detecting various types of malware and assesses its effectiveness in real-world scenarios. Through a comprehensive analysis, this paper contributes to the understanding of SVM-based anomaly detection techniques for malware. It provides valuable insights into the efficacy and limitations of SVM in combating cyber threats.

 

 

Published by: vikaspatanker

Authors: Amuncio, Jun Rey, Crisostomo, Kenneth, Gatinao, Hannah Michaela G, Palomo, Gerber Jay L, Paculanan, Kristian Jay C, Cedie E. Gabriel MIT

Abstract: The study presents the development and evaluation of a smart wearable system to monitor student appearance and activity participation through ID scanning at South East Asian Institute of Technology (SEAIT), Tupi, South Kotabato. Methods of traditional appearance in educational institutions are often disabled, error-prone and susceptible to manipulation. The project integrates human-computer interaction (HCI) principles into a smart wearable device that uses ID scanning to automate the attendance and recording of student participation. The system aims to improve accuracy, reduce administrative burden, and increase the user experience through user -friendly interfaces and real -time data processing. The purposeful test and performance assessment demonstrated that the system provides more efficiency and satisfaction than traditional methods, although some users expressed concern over the need for privacy and additional support. Overall, the system shows strong ability to increase institutional operations in the resource-limit environment.

Published by: vikaspatanker

Authors: Amuncio, Jun Rey, Crisostomo, Kenneth, Gatinao, Hannah Michaela G, Palomo, Gerber Jay L, Paculanan, Kristian Jay C, Cedie E. Gabriel MIT

Abstract: The study presents the development and evaluation of a smart wearable system to monitor student appearance and activity participation through ID scanning at South East Asian Institute of Technology (SEAIT), Tupi, South Kotabato. Methods of traditional appearance in educational institutions are often disabled, error-prone and susceptible to manipulation. The project integrates human-computer interaction (HCI) principles into a smart wearable device that uses ID scanning to automate the attendance and recording of student participation. The system aims to improve accuracy, reduce administrative burden, and increase the user experience through user -friendly interfaces and real -time data processing. The purposeful test and performance assessment demonstrated that the system provides more efficiency and satisfaction than traditional methods, although some users expressed concern over the need for privacy and additional support. Overall, the system shows strong ability to increase institutional operations in the resource-limit environment.

Published by: vikaspatanker

Authors: Dhvani Marthak

 

Abstract: Social media was simply a tool for communication but has become an ubiquitous aspect of daily life in today's hyperconnected world. Its excess has taken an eyebrow from media observers, researchers, and therapists due to its unique capability to provide communication as well as content consumption. Social media such as Instagram, Facebook, Twitter, and TikTok provide liquid spaces that blend private information, entertainment, news reporting, and friendship, hence making them irreplaceable. Yet, the psychological price of such hyperconnectivity has turned too instant. The impact of a social media detox, or "social media detox," on participants aged between 16 and 50 years is analyzed in this study. The main objectives are to investigate the changes in emotion, behaviour, and psychology that occur during and after detox and whether these can be sustained in the longer term. The study is a mixed-methods approach, where qualitative interviewing of the response of respondents via 250 questions in a questionnaire produce richness and generalizability. Quantitative data were analyzed via SPSS, but thematic analysis of open questions yields subjective experience. Findings are a radical improvement in sleep quality, concentration, emotional control, and productivity on detox. Participants also manifested greater self-knowledge and social affiliation in the offline world. Though these findings reveal positive short-term improvements, the study further demonstrates high levels of variability concerning the duration over which such improvements are maintained after detox, along with some suggestion of return towards baseline levels of behavior. Besides, initial dependency level, age, and length of detox also appeared to play key mediating roles. Current research thus adds empirical evidence concerning the potential and limitations of social media detox, hence contributing to the literature surrounding digital well-being, mental health promotion, and potential for self-regulation.

DOI: http://doi.org/

 

Published by: vikaspatanker

Authors: Mr. Akshay M. Bodule, Dr. D.N. Chaudhari, Dr. A.P. Jadhao, Professor D.G. Ingale

 

 

Abstract: With the exponential rise in cloud storage usage and the growing demand for cross-platform accessibility, efficient file synchronization has become a critical requirement in modern computing environments. Traditional synchronization techniques, which often rely on full-file transfers and timestamp-based comparisons, are no longer sufficient—particularly in bandwidth-constrained or resource-limited scenarios such as mobile networks and edge computing systems. This paper presents a hybrid synchronization approach that integrates Two-Way Synchronization and Differential Synchronization to improve efficiency, reduce bandwidth consumption, and enhance data consistency. Two-Way Synchronization enables the detection and resolution of file changes from both local and cloud sources, supporting intelligent decision-making for conflict resolution, deletion propagation, and duplicate handling. Differential Synchronization enhances this process by transmitting only the modified segments of files, using techniques such as block-level comparison and rolling hashes, thereby significantly minimizing data transfer volume and synchronization time. The paper outlines the architecture, entities, processes, and data flows involved in each technique, along with corresponding algorithms and flowcharts. Finally, the paper identifies future challenges, focusing on component-level implementation, delta generation, metadata management, and cloud integration. The proposed solution offers a scalable and bandwidth-efficient synchronization framework suitable for real-time collaboration, offline-to-online transitions, and deployment in distributed and hybrid cloud environments.

DOI: http://doi.org/10.61137/ijsret.vol.11.issue3.120

 

 

Published by: vikaspatanker

Authors: Nishant Verma, Associate Professor Dr. Mehak

Abstract: This paper explores risk management practices in Small and Medium Enterprises (SMEs) through the interdisciplinary lenses of psychology, economics, and linguistics, emphasizing the role of lifelong learning in achieving sustainable futures. By examining how SMEs perceive, communicate, and economically strategize around risk, we uncover the cognitive, communicative, and systemic factors shaping risk resilience. This study draws on empirical data, theoretical frameworks, and case studies to advocate for integrative, adaptive, and continuous learning mechanisms to enhance SMEs’ sustainability and competitiveness in an increasingly volatile global market.Risk management is a critical component of business strategy, particularly for Small and Medium Enterprises (SMES) that often lack the resources of larger corporations. This paper investigates the risk management practices adopted by SMES, exploring their effectiveness, challenges, and the role of organizational culture, awareness, and external support. Using a mixed-methods approach, the study identifies common risks faced by SMES, evaluates current mitigation strategies, and proposes a framework for improved risk management. The findings highlight a need for enhanced awareness, training, and integration of risk management into business planning. This paper investigates the current landscape of risk management practices among SMES, with a focus on how they perceive, assess, and respond to various types of risks. Drawing on a mixed-methods research approach, including quantitative surveys and qualitative interviews with SME owners and managers, the study reveals that while most SMES recognize the existence of critical risks, few possess structured or formal risk management systems. Instead, risk responses are often reactive, ad hoc, and based on the intuition and personal experiences of the business owner rather than systematic analysis.

Published by: vikaspatanker

Authors: Md Shareef, P Sri Sindu, M Surya Teja, B Prasun Reddy

Abstract: Lung cancer remains a leading cause of cancer-related mortality worldwide, underscoring the critical need for effective predictive models to aid in early detection and intervention. This study presents a comprehensive approach to lung cancer prediction, leveraging advanced machine learning techniques and multimodal data integration. By incorporating diverse sources of information, including medical imaging scans, clinical records, and genetic markers, our proposed model aims to capture the complex interplay of factors influencing lung cancer risk. We employ a combination of feature engineering, feature selection, and ensemble learning methods to develop robust predictive models capable of accurately identifying individuals at elevated risk of developing lung cancer. Furthermore, we explore the interpretability of our models to gain insights into the underlying factors driving lung cancer susceptibility. Through extensive experimentation and validation on large-scale datasets, we demonstrate the efficacy of our approach in achieving superior predictive performance compared to existing methods. The proposed model holds significant promise for facilitating early detection, personalized risk assessment, and targeted interventions in lung cancer management, ultimately improving patient outcomes and reducing the burden of this devastating disease.

Published by: vikaspatanker