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Enhancing greedy web proxy caching using weighted random indexing based data mining classifier /
Egyptian Informatics Journal, Vol.20, Issue 2, pp. 117-130, ISSN No. 1110-8665. -
Enhancements to greedy web proxy caching algorithms using data mining method and weight assignment policy /
International Journal of Innovative Computing, Information And Control, Vol.14, Issue 4, pp.1311-1326, ISSN No. 1349-4198. -
Detection of cyber crime based on facial pattern enhancement using machine learning and image processing techniques
Cybercrime has several antecedents, including the rapid expansion of the internet and the wide variety of users around the world. It is now possible to use this data for a variety of purposes, whether for profit, non-profit, or purely for the benefit of the individual. As a result, tracing and detecting online acts of terrorism requires the development of a sound technique. Detection and prevention of cybercrime has been the subject of numerous studies and investigations throughout the years. An effective criminal detection system based on face recognition has been developed to prevent this from happening. Principle component analysis (PCA) and linear discriminant analysis (LDA) algorithms can be used to identify criminals based on facial recognition data. Quality, illumination, and vision are all factors that affect the efficiency of the system. The goal of this chapter is to improve accuracy in the facial recognition process for criminal identification over currently used conventional methods. Using proposed hybrid model, we can get the accuracy of 99.9.5%. 2022, IGI Global. All rights reserved. -
Photocatalytic Degradation of Textile Dyes Using Artemisia stelleriana Besser Mediated Nanoparticles
Artemisia stelleriana is widely used as an ornamental plant and belongs to the family Asteraceae. In the current study, A. stelleriana-mediated Zinc oxide newlinenanoparticles (AS-ZnONPs), Silver nanoparticles (AS-AgNPs) and Silver/Zinc oxide bimetallic nanoparticles (AS-Ag/ZnONPs) were synthesised using one-pot method. The UV-Vis spectral analysis revealed characteristic peaks at 358 nm for AS-ZnONPs, newline425 nm for AS-AgNPs, and 357 nm and 473 nm for AS-Ag/ZnONPs. Fourier transform infrared spectroscopy (FTIR) analysis identified phytoconstituents taking part in newlinenanoparticle synthesis, manifesting the presence of alkaloids, phenols, saponins, and newlineflavonoids. The synthesised AS-ZnONPs, AS-AgNPs, and AS-Ag/ZnONPs have a crystalline nature and were confirmed using X-ray diffraction (XRD) analysis. The crystallite sizes of the AS-ZnONPs, AS-AgNPs, and AS-Ag/ZnONPs were 22.54 nm, 18.67 nm, and 10.4 nm, respectively. Spherical-shaped Ag nanoparticles and hexagonal, cylindrical, and spherical-shaped ZnO nanoparticles were synthesized from the leaf extract of A. stelleriana. The average size of the synthesised nanoparticles was 37.6 nm and 71.2 nm for AS-ZnONPs and AS-AgNPs, respectively. On the other hand, spherical-shaped AS-Ag/ZnONPs were synthesized with an average size of 35.3 nm. The photocatalytic degradation activity of AS-ZnONPs showed 93.44%, 47%, 94.76%, 99.9%, and 74.82% degradation for Reactive Blue 220 (RB220), Reactive Blue 222A (RB222A), Reactive Red 120 (RR120), Reactive Yellow 145 (RY145) and newlineReactive Yellow 86 (RY86) dyes respectively after 320 min of UV light exposure. ASZnONPs showed positive results for all five dyes and a better percentage of degradation was observed in a 5 ppm concentration of dye treated with 1 mg/mL concentration of newlineAS-ZnONPs. In the case of AS-AgNPs, RB220 and RB222A dyes showed positive results but no degradation was observed in the remaining three dyes. After 320 min of UV light exposure, AS-AgNPs showed 95.98%, and 100% degradation of RB220 and RB222A dyes respectively. -
Social media activism: Delving into Generation Zs experiences
Generation Z, a digitally tethered cohort, widely utilises social media platforms for activism. As their influence within organisational and political spheres rises, their digital activism will likely redefine the sociopolitical landscape, especially in India, where youth civic participation is pivotal. However, despite its prominence, there is a significant dearth of research exploring what goes on behind the screens. Therefore, this study aimed to explore the experiences of Generation Zs social media activists, particularly their perceived identity, roles, underlying motivations, real-world and self-impact. Employing a phenomenological qualitative research design, 10 semi-structured interviews were conducted. Thematic analysis revealed that while both internal and external catalysts drive Generation Zs social media activism, it is also characterised by intersecting identities, emotional turbulence, adverse psychological effects, uncertainty, self-devised coping mechanisms and opportunities for personal growth. Thus, this study presents a comprehensive portrait of the typical Generation Z social media activist, with wide-ranging implications. 2025 Australian and Aotearoa New Zealand Communication Association. -
Maximizing Efficiency: Unveiling thePotential ofKubernetes Metrics
In the realm of Kubernetes cluster management, the importance of metrics cannot be overstated. Metrics serve as a powerful lens, providing a quantitative perspective into a clusters performance, behavior, and resource utilization. In the ever-evolving landscape of cloud-native computing, metrics are the key to informed decision-making. They empower administrators to navigate scaling, resource allocation, and the holistic optimization of Kubernetes clusters with a data-driven confidence. This paper stands as a vital contribution, placing metrics at the forefront of the discussion. It underscores their transformative potential by shedding light on how they drive administrators decisions, enable the identification of performance bottlenecks, and enhance application responsiveness. Moreover, metrics play a pivotal role in proactive capacity planning, ensuring resources are allocated with precision to meet both current and future workload demands. In essence, this papers core contribution lies in providing a comprehensive overview of Kubernetes metrics and highlighting their profound impact on Autoscaling strategies. By revealing the constraints that metrics may impose on the efficient scaling of application resources, it equips administrators with a navigational tool for building dynamic and resilient computing environments within Kubernetes clusters. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Reinforcement Learning based Autoscaling for Kafka-centric Microservices in Kubernetes
Microservices and Kafka have become a perfect match for enabling the Event-driven Architecture and this encourages microservices integration with various opensource platforms in the world of Cloud Native applications. Kubernetes is an opensource container orchestration platform, that can enable high availability, and scalability for Kafkacentric microservices. Kubernetes supports diverse autoscaling mechanisms like Horizontal Pod Autoscaler (HPA), Vertical Pod Autoscaler (VPA) and Cluster Autoscaler (CA). Among others, HPA automatically scales the number of pods based on the default Resource Metrics, which includes CPU and memory usage. With Prometheus integration, custom metrics for an application can be monitored. In a Kafkacentric microservices, processing time and speed depends on the number of messages published. There is a need for auto scaling policy which can be based on the number of messages processed. This paper proposes a new autoscaling policy, which scales Kafka-centric microservices deployed in an eventdriven deployment architecture, using a Reinforcement Learning model. 2022 IEEE. -
Enhancing Kubernetes Auto-Scaling: Leveraging Metrics for Improved Workload Performance
Kubernetes is an open-source production-grade container orchestration platform, that can enable high availability and scalability for various types of workloads. Maximizing the performance and reducing the cost are two major challenges modern applications encounter. To achieve this, resource management and proactively deploying resources to meet specific application requirements becomes utmost important. Adopting Kubernetes auto-scaler to fit one's needs are important to maximize the performance. This study aims to perform a comprehensive analysis of Kubernetes auto-scaling policies. This paper also lists out the various parameters considered for auto-scaling, and prediction methods used to efficiently handle resource requirements of applications. The research findings reveal a scarcity in the existing work regarding the variety of workload based auto-scaling and custom metrics. This paper provides a concise overview of a forthcoming research endeavor that explores the utilization of custom metrics in conjunction with auto-scaling. 2023 IEEE. -
Reclaiming Selfhood: Transfeminine Identity in the Poetry of Justice Ameer and Golden
Despite increased visibility of trans identities in contemporary US discourse, Black transfeminine individuals remain subjected to systemic violence, societal misrecognition, and cultural erasure, exacerbated by the fraught political climate under administrations that alternately advance and restrict transgender rights. This paper explores the transformative potential of Black transfeminine poetry as a site of self-representation and resistance against hegemonic frameworks of gender, race, and identity. Through a close reading of select poems by Justice Ameer and Golden, the analysis highlights how their works challenge cisnormative and patriarchal narratives, reclaim authority over gender representation and illuminate the fluidity of identity as a process of resilience and resistance. Drawing on themes of memory, trauma, community, and agency, this paper situates their poetry as both a critique of systemic marginalisation and a radical act of reimagination. By positioning their works within the broader socio-political context of the United States, the paper underscores how Black transfeminine poetics not only confront societal erasure but also construct spaces of affirmation and liberation. Through these explorations, the paper demonstrates the capacity of poetry to subvert oppressive narratives, assert the multiplicity of identity, and envision transformative possibilities for transfeminine existence. 2025 Informa UK Limited, trading as Taylor & Francis Group. -
Brain-friendly approach to work environment and its motivational influence on ambidexterity and engagement of faculty in higher education
Purpose: As the higher education landscape continues to evolve, educational managers need to be adaptable and embrace versatility and interactivity in their management methods. The research investigates the interplay between brain-friendly work environment, motivation, ambidexterity and engagement among higher education faculty. Design/methodology/approach: This research investigates the relationships and mechanisms among various variables in higher education using a quantitative approach. Data were collected through surveys administered to educators in South India, focusing on their perceptions of brain-friendly work environments, motivation, ambidexterity and engagement. The questionnaire employed established standard scales, and a thorough analysis was conducted on the 437 responses received. Findings: The study establishes the significance of creating environments conducive to brain functioning, leading to the development of motivated, ambidextrous and engaged educators. Research limitations/implications: The study paves the way for experimental research, which can add rigour to the current findings. Additionally, other factors beyond the SCARF dimensions which can promote ambidexterity and engagement can be explored in future research. The findings of the study can be applied and tested in other organisational settings. Practical implications: A brain-friendly experience will function as a powerful motivational tool that enhances the productivity of faculty in the higher education sector. The insights of the study will help educational leaders in designing a productive work environment and governments in making policies which help to improve the quality of the higher education sector. Social implications: The quality and contributions of faculty members in the higher education sector are crucial for shaping society. This research contributes to the knowledge of creating motivated, ambidextrous and engaged faculty who can mould the future in todays competitive society. Originality/value: The concept of a workplace that prioritizes cognitive well-being is becoming increasingly relevant in education. Research results contribute significantly to existing knowledge and highlight the importance of creating an environment that supports optimal brain function, leading to enhanced employee performance. These findings offer valuable insights for educational leaders and policymakers seeking to improve working conditions. 2025, Emerald Publishing Limited. -
Employee Social Experiences and Performance Management Systems: A Brain-Friendly Approach in Organizations
In the wake of the COVID-19 pandemic, organizations are undergoing significant changes that call for more effective people management strategies. With new competitive challenges and constantly evolving environments, modern organizations need toadapt to ensure their continued success. One valuable tool for achieving this goal is a performance management system. However, it is crucial to update the theories and techniques of this system to meet the current demands. This study explores how the performance management system affects employees social experiences from a neuroscience perspective. Using a quantitative approach, the study gathered information from 268 employees across various industries in India, considering ten performance management criteria and evaluating social experience components using the SCARF model based on neuroscience. The results reveal that specific aspects of the performance appraisal system significantly impact employees social experiences. Based on their understanding of the link between different factors in the performance appraisal process and the quality of social experience, researchers recommend a performance appraisal model that promotes a brain-friendly work environment. These findings are especially relevant to managers and organizations, as they offer valuable insights into critical factors to consider when planning and implementing performance appraisal systems in modern workplaces. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Evaluating Technostress: Work-Life Balance and Well-Being in Varied Work Contexts
In the contemporary digital landscape, the phenomenon of technostress, defined as stress induced by technology usage, has emerged as a crucial factor influencing work-life balance and employee well-being. This study will explore the impact of technostress in varied work modes such as traditional office-based, remote, and hybrid models. Employing a quantitative approach, the researcher conducted surveys on a representative sample of employees across multiple industries. The results indicate that technostress adversely influences work-life balance and well-being, and the difference in various work modes is observable. Further, it has also been observed that there are significant differences in technostress and well-being concerning the various work modes; working from home comes out to be a positive option, which is related to lesser levels of technostress and higher outcomes of well-being. The present study shows how organisational interventions may be implemented in mitigating technostress-inducing effects: induction of digital literacy, instillation of appropriate communication policies, and embedding of supportive work culture. Essentially, an intervention could help organisations improve well-being 0f employees and achieve better work-life balance in a digital environment. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Towards Smarter Transit Systems: An Artificial Intelligence based IoT Approach
Transportation today is paramount, and difficulties such as unreliable bus schedules and overcrowding are still found due to inadequate managerial practices. While cities are confronted with rapid urbanization and population growth, public transit remains a strong reliance of the middle class, especially in India. Individuals are subsequently subjected to overcrowded, and unreliable modes of transit, which lead them to seek private solutions that ultimately leads to increased private vehicle usage, which is directly related to more congestion and pollution. Therefore, utilising an IoT/machine learning based solution which provides commuters with updated bus locations and occupancy via their mobile phones to make more informed travel decisions, thus reducing wait times is proposed. Accurately tracking the buses via gps, is beneficial for providing timely information, where sensors are used for estimating occupancy based on passenger counts. The traffic prediction provided to users is generated from a Random Classifier machine learning model that would otherwise improve commuting efficiency and urban mobility. The model is found to have 98% accurate on cross-validation and 99% on test data, while the average F1-score over various traffic situations is 0.99. The described solution assists transit users by providing up to date service information improving the passengers quality of travel, heightened their sense of safety, and creates a more integrated urban experience, which promotes long-term sustainable development to meet the interconnectedness challenges cities confront with rapid urban expansion. 2025 IEEE. -
Detection and Sensing of Human Body Micro-Motions Using 24GHz mm-Waves: A Case Study
The paper presents a 24 GHz millimeter-wave (mm-Wave) system for real-time human presence and distance detection, leveraging the 24 GHz band's balance of range, resolution, and power efficiency for applications in smart environments. The system uses Doppler-based reflections from signals to accurately detect presence and estimate distances with 12cm accuracy up to 5 meters with little needed infrastructure. The challenges presented by signal attenuation and multipath interference are addressed using beamforming and Massive MIMO with 5G-enabled IoT as the framework. The use of Ultra-Reliable Low Latency Communication and Massive-Machine-Type Communication allows a framework for rapid data processing and scalability. This system enables automated smart home lighting, healthcare occupancy detection, and security intrusion alert applications, with very high detection accuracies. The limits are reduced detection performance beyond a distance of 6 meters and interference from reflective surfaces. Future work includes investigating the 60 GHz bands, which will yield higher resolution in the detection, and using machine learning techniques to develop adaptive detection, as a scalable and cost effective method of real-time automation in a range of settings. 2025 IEEE. -
Deep Learning for Mental Health: Attention-Driven Multilayer CNN for Audio Depression Detection
Depressive Disorder is a common mental health problem that affects millions of people around the world. This study proposes a Self-attention based Multi-layer Convolutional Neural Network (CNN) model to perform enhanced depression detection from audio modality. The model employs a diverse array of filters, kernel sizes, and pooling strategies across multiple CNN layers to capture local features, while the attention mechanism prioritizes emotionally salient parts of the speech signal, such as regions of low energy and lengthened pauses by assigning higher weights. Measured against the RAVDESS and TESS emotional speech datasets, the method attains an F1 score of 0.81, an accuracy of 83% and ROC-AUC of 0.96 when using attention, beating the baseline CNN model, F1 score of 0.77 and 83% accuracy without attention. The results demonstrate the effectiveness of attention-enhanced architectures in detecting depressive cues from speech and support the feasibility of developing real-world, speech-based mental health screening tools. 2025 IEEE. -
Exploring the Interplay Between Economic Growth and Sustainable Development: A Complex Systems Approach to GSDP and SDGs in Indian States
Pursuing Sustainable Development Goals (SDGs) necessitates aligning business and management practices on a global scale. This paper delves into the intricate dynamics between Gross State Domestic Product (GSDP) and SDGs across diverse states in India, offering nuanced insights to policymakers, businesses, and stakeholders. This paper explores the dynamic relationship between Gross State Domestic Product (GSDP) and the Sustainable Development Goals (SDGs) in the context of India's diverse states by applying modern machine learning techniques such as XG boost, Decision trees, and K mean clustering. The study delves into how economic growth influences the progress towards SDGs. The research integrates complex systems methodologies, combining exploratory data analysis, correlation analysis, and clustering to offer actionable insights for policymakers and businesses. The paper emphasizes the need for tailored strategies that consider the economic development stages of states to achieve sustainable development goals more effectively. Through this multidimensional approach, the study provides a comprehensive understanding of how GSDP can guide the pursuit of SDGs and proposes innovative, data-driven solutions for fostering sustainable growth across India. 2025, Binghamton University Libraries. All rights reserved. -
Numerical Evaluation of the Strength of Concrete Columns with Different Types of Confinement
The structural performance of reinforced concrete (RC) columns is significantly influenced by their cross-sectional shape and the confinement methods employed. Confinement is a widely adopted technique to enhance the load-carrying capacity and ductility of concrete columns, thereby improving their structural performance and seismic resistance. A large number of experimental and numerical studies are available to demonstrate the confinement effect of columns. This study presents a numerical evaluation of the strength of circular (316 mm diameter), square (280 280 mm), and rectangular (300 260 mm) RC columns confined by using various techniques. Modelling and analysis of columns are done in Ansys software. The confining strategies, adopted are varying the spacing of lateral ties, wrapping with different types of Fiber Reinforced Polymers (FRPs) and wrapping with FRP combined with lateral ties. The results show significant enhancement of compressive strength in the confined columns. Among the adopted confining strategies, CFRP with lateral ties gives maximum percentage strength enhancement (13.4%). The comprehensive understanding of the behaviour of the confined columns under axial load further leads to the study of confined columns under lateral and dynamic loads. This would contribute the safety and resilience of structures constructed specially in earthquake-prone regions. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
A study of thinking style, teacher effectiveness and emotional intelligence of secondary school teachers of Bangalore city
Education is a social process by which knowledge is transferred to students through the intermediaries, the teachers. It can be had from non - formal and formal systems of Education. All formal systems are based on the classroom teaching. "The destiny of India is being shaped in her classroom", has been pointed out by the Indian Education Commission (KOTHARI COMMISSION) (1964-66) and to that, it may be safely added that the destiny of these classrooms is being shaped by the teachers. According to the American Commission, the quality of the nation depends upon the quality of the citizens. The quality of its citizens depends, not exclusively, but in critical measure upon the quality of their Education. The quality of their education depends more upon the quality of teachers. Humayun Kabir rightly said once, "Without good teachers even the best of system is bound to fall, with good teachers, even the defects of a system can be largely overcome". The teacher is the flywheel of the whole educational machine. Elaborate blue prints, modern school plans, the best equipment, the newest of the new
media or progressive methods will remain dead fossils unless there is the right use of teachers. The document, Challenge of Education -A Policy Perspective (1985) has highlighted that teacher performance is the most crucial input in Education. No development has reached the threshold of development of new technology which is likely to revolutionize the classroom teaching. -
Smart internet of things (IOT) enabled agricultural farming system /
"Patent Number: 202241047525, Applicant: Justin Joy.
Smart Internet of Things (IoT) enabled agricultural farming system that aims to extract the values of soil parameters by using IoT sensors and appropriately control the watering of crops. Thus, this system allows crop cultivation even in a hot and dry climate. Crops can be watered remotely and temperature controlled to be maintained within an appropriate range. Automated irrigation systems using WSN (Wireless Sensor Networks) and GPRS (General Packet Radio Service) modules assist in optimizing water use for agriculture crops. This system comprises a distributed wireless sensor network with soil moisture and temperature sensor in WSN.