This article explores the use and impact of voting using blockchain technology. As a result of mounting worries about the honesty and security of conventional voting methods, especially in the digital era, the study tackles the requirement for an open, impenetrable, and robust method of conducting elections. A decentralized application on a blockchain platform is designed and implemented using the technique, which makes use of smart contracts for voter registration, ballot generation, and vote counting. The viability of blockchain technology in (...) guaranteeing voter anonymity, data integrity, and cryptographic security are important discoveries. Online voting can be done securely and digitally using blockchain technology. It has great potential to reduce costs and increase voter turnout. Using Blockchain we can secure any application and work securely for that application. Therefore, cryptocurrency, healthcare, real estate, etc. Many applications use blockchain technology. *Blockchain technology encrypts votes, preventing any votes from being tampered with. It allows voters to vote for a candidate only once. The system reduces labor costs and counting errors by providing quick access to election results. This article explains solutions to solve the above problems. Our solution is to use an online voting syst. (shrink)

This paper presents the design and development of a Fitness App that integrates workout plans, dietary recommendations, and motivational features to help users maintain a healthy lifestyle. The app aims to provide users with personalized workout routines, meal plans, and motivational content to keep them engaged throughout their fitness journey. The goal is to create a comprehensive app that empowers users to take control of their health by providing them with the tools and resources they need to achieve their fitness (...) goals effectively. (shrink)

This case study is a retrospection of my family’s experiences that highlight several ELE facets. Following a description, we attempt to explain some of these phenomena from the perspectives of science and other germane disciplines.

This book is a compilation of the work published by the present authors in various scientific journals mainly focused on understanding how quantum physics could decipher the experiences observed and reported during near-death and end-of-life situations. The authors claim that various theories and models proposed herein (though not propounding to be a complete one) are just an attempt to understand few aspects associated with such experiences connected to the phenomenon of death. They investigate the possible role of the quantum phenomenon (...) in the occurrence of these events and call for a detailed scientific investigation to validate any hypotheses made. (shrink)

An attendance system allows to add the attendance of the employee/student who is present on that day. This attendance system helps in maintaining the attendance details of every student efficiently. The attendance is generated if the student is present in that particular lecture. While the attendance is maintained on daily basis, the staffs have unique usernames and passwords to mark students if the student is present or absent. Subjects are handled by respective faculty to mark the attendance of all students. (...) Total attendance is generated by calculating the total number of days present divided by the total number of lectures. The reports generated are based on semester and are consolidated regularly. This system can add faculty, student, and their subjects respectively, also the system can put an attendance structure for a particular subject. (shrink)

How do we know what we know? • How do we perceive ourselves and the world around? • Is what we perceive the only reality that exists? (or) • Is there a different reality other than what we perceive? (Not referring to the source of C, but to the CoC, in the very limit of our physical structure).

Origin of life on earth transpired once and from then on, it emerges as an endless eternal process. Matter and energy are constants of the cosmos and the hypothesis is that the origin of life is a moment when these constants intertwined or interacted. Energy from the cosmos interacted with inorganic matter to support matter with retention of this riveted energy, as energy to be circulated within the primitive channelized structures to conserve energy by the materialization of the proton homeostasis (...) mechanisms developed from the obtainable inorganic matter. The driver for these processes as we now confirm, exists in the quantum world and through quantum phenomenal processes could have combined these constants to create the magic of life. Primitive earth was a chemical reactive system that triggered a macromolecular evolution by means of open thermodynamic systems, driven by cyclic gradients of temperature, electromagnetic radiation and chemical potentials which sustained life and proto-consciousness in the first life forms driven by the quantum processes. The origin of life is always an intriguing topic but the purpose for finding the cause should never be inclined towards obliterating it; for if that is the case, the further we seek, the farther it will go. (shrink)

In this paper, we present a case of a boy – Noah Wall, who till today surprises the world of neuroscience with his will to grow his brain and survive. The case presented in this study sets a stepping stone in understanding the advent of the will to make a choice, from a neuro-quantum mechanics interpretation. We propose that besides our internal states of choices (neurogenesis, neuroplasticity, cell differentiation, etc.) we also relate with external states of choices (love, compassion, empathy, (...) emotions, etc.) that contributes to its emergence. Quantum uncertainty seems to support the existence of a fundamental property based on which the universe functions; which means that even the nothing of free space has a small chance of containing something. Outcomes are not determined by prior or random events but by consciousness that gives rise to these outcomes. This provides us a lead into understanding the existence of the will and the origin of choice when we look deeper into the realms of the implausible interpretations of quantum mechanics. Free will is the ability for the mind to choose between possible outcomes. Willful power is therefore not only a psychological intervention but also a biological and quantum intervention, where we have the capacity to make choices about what direction we will take, making a change to the systematic functioning of our body. (shrink)

IoT Security Enhancement Using Machine Learning for Real-Time Threat Detection. The Internet of Things (IoT) is a network of interconnected devices that communicate over the internet, offering convenience and efficiency but also posing significant security risks. This project focuses on enhancing IoT security by detecting cyber threats such as DDoS, DoS, reconnaissance, and data theft in real-time. The main objective is to improve the accuracy and efficiency of threat detection using machine learning models like Random Forest. The system analyzes key (...) network behaviors, including data flow, traffic anomalies, and device interaction patterns. Unlike traditional rule-based intrusion detection systems, this approach dynamically monitors network activities to identify potential threats. The system has wide applications across domains such as smart homes, industrial IoT, healthcare, and autonomous systems, contributing to a more secure and resilient IoT ecosystem. (shrink)

What happens to the inner light of consciousness with the death of the individual body and brain? Reductive materialism assumes it simply fades to black. Others think of consciousness as indicating a continuation of self, a transformation, an awakening or even alternatives based on the quality of life experience. In this issue, speculation drawn from theoretic research are presented. -/- Table of Contents Epigraph: From “The Immortal”, Jorge Luis Borges iii Editor’s Introduction: I Killed a Squirrel the Other Day, Gregory (...) M. Nixon iv-xi Research Essays The Tilde Fallacy and Reincarnation: Variations on a "Skeptical" Argument Teed Rockwell 862-881 Death, Consciousness, and Phenomenology, Steve Bindeman 882-899 The Idealist View of Consciousness After Death, Bernardo Kastrup 900-909 Consciousness, a Cosmic Phenomenon—A Hypothesis, Eva Déli 910-930 The Theory of a Natural Afterlife: A Newfound, Real Possibility for What Awaits Us at Death, Bryon K. Ehlmann 931-950 Near-Death Cases Desegregating Non-Locality/Disembodiment via Quantum Mediated Consciousness: An Extended Version of the Cell-Soul Pathway, Contzen Pereira & J Shashi Kiran Reddy 951-968 On the Possible Existence of Quantum Consciousness After Brain Death, Massimo Pregnolato & Alfredo Pereira Jr. 969-991 Science and Postmortem Survival, Edward F. Kelly 992-1011 Explorations ISS Theory: Cosmic Consciousness, Self, and Life Beyond Death in a Hyperdimensional Physics, Chris H. Hardy 1012-1035 Does the Consciousness End, Remain Awake, or Transform After Death? Radivoj Stankovich (with Micho Durdevich) 1036-1050 Big Bang Spirituality, Life, and Death, Ken Bausch 1051-1063 Death, Consciousness and the Quantum Paradigm, Ronald Peter Glasberg 1064-1077 Living With Limits: The Continuum of Consciousness, Donald Brackett 1078-1098 Mysticism, Consciousness, Death, Mike Sosteric 1099-1118 What Dies? Eternalism and the Afterlife in William James, Jonathan Bricklin 1119-1140 Theories of Consciousness and Death: Does Consciousness End, Continue, Awaken, or Transform When the Body Dies? Roger Cook 1141-1153 It’s the Other Way Around: Matter is a Form of Consciousness and Death is the End of the Illusion of Life in the World, James P. Kowall & Pradeep B. Deshpande 1154-1208 Statements A Feminine Vision for the World Consciousness, & a New Outrageous Ontology, Lorna Green 1209-1217 The Mask of Eternity: The Quest for Immortality and the Afterlife, Iona Miller 1218-1228 Are We Really “such stuff as dreams are made on”? Chris Nunn 1229-1225 Is the Afterlife a Non-Question? (Let's Hope Not), Deepak Chopra 1226-1230 Life After Death? An Improbable Essay, Stuart Kauffman 1231-1236. (shrink)

The success of AI models largely depends on the availability of large and high-quality datasets. However, in many real-world scenarios—such as medical diagnostics, remote sensing, or low-resource languages— gathering such data is difficult or even impossible due to privacy, cost, or scarcity. Synthetic data offers a compelling alternative. This paper proposes a comprehensive synthetic data pipeline tailored for data-scarce domains. It includes domain understanding, synthetic data generation using simulation, generative models (e.g., GANs, diffusion models), data augmentation, validation, and integration with (...) downstream AI models. Experimental evaluation in healthcare imaging and industrial defect detection demonstrates improved model accuracy and generalizability using synthetic data pipelines. (shrink)

Broadening access to both computational and educational resources is crit- ical to diffusing machine learning (ML) innovation. However, today, most ML resources and experts are siloed in a few countries and organizations. In this article, we describe our pedagogical approach to increasing access to applied ML through a massive open online course (MOOC) on Tiny Machine Learning (TinyML). We suggest that TinyML, applied ML on resource-constrained embedded devices, is an attractive means to widen access because TinyML leverages low-cost and globally (...) accessible hardware and encourages the development of complete, self-contained applications, from data collection to deployment. To this end, a collaboration between academia and industry produced a four part MOOC that provides application-oriented instruction on how to develop solutions using TinyML. The series is openly available on the edX MOOC platform, has no prerequisites beyond basic programming, and is designed for global learners from a variety of backgrounds. It introduces real-world applications, ML algorithms, data-set engineering, and the ethi- cal considerations of these technologies through hands-on programming and deployment of TinyML applications in both the cloud and on their own microcontrollers. To facili- tate continued learning, community building, and collaboration beyond the courses, we launched a standalone website, a forum, a chat, and an optional course-project com- petition. We also open-sourced the course materials, hoping they will inspire the next generation of ML practitioners and educators and further broaden access to cutting-edge ML technologies. (shrink)

I prove both the mathematical conjectures P ≠ NP and the Continuum Hypothesis are eternally unprovable using the same fundamental idea. Starting with the Saunders Maclane idea that a proof is eternal or it is not a proof, I use the indeterminacy of human biological capabilities in the eternal future to show that since both conjectures are independent of Axioms and have definitions connected with human biological capabilities, it would be impossible to prove them eternally without the creation and widespread (...) acceptance of new axioms. I also show that the same fundamental concepts cannot be used to demonstrate the eternal unprovability of many other mathematical theorems and open conjectures. Finally I investigate the idea’s implications for the foundations of mathematics including its relation to Godel’s Incompleteness Theorem and Tarsky’s Undefinability Theorem. (shrink)

Many trading desks across the financial industry still rely heavily on Excel-based tools for pricing, risk assessment, and reporting workflows. While these spreadsheets offer flexibility and familiarity, they present challenges in scalability, collaboration, version control, and integration with modern trading infrastructure. This paper presents a cloud-native migration framework that transforms trader-centric Excel tools into robust, scalable applications using Java and Python. The framework incorporates modular microservices, RESTful APIs, AWS services, and real-time data processing. It also addresses migration challenges such as (...) formula translation, data validation, and end-user adoption. The resulting system improves performance, auditability, and maintainability while retaining the usability traders expect. (shrink)

This essay delves into the essentialities of object-giving sources within the formulation of epistemic objectivity. It explores the relationship between objectivity and intentional states, particularly in the context of immediate and transcendent experiences. A key focus of this paradigm is the examination of inferences and how they are held in X’s intentional processes. These claims about inferences contribute to the perception of objectivity by highlighting the epistemological transitions of things that occur in the constitutive ideation. Additionally, the activity within X’s (...) episteme leads to significant articulations that reflect a structural realism of experiences. The essay also introduces a convention of the experiential-intentional process so that the causality manipulations could be avoided by the precents of sources of ideation. In this instance, the central niche is occupied by transcendental reflections of intentionality, which are fundamentally founded on experiences and objectivity, and they possess a distinct rhetorical quality. They manifest as acts, propositional forms, and constituents, all of which contribute to the understanding and justification of objectivity. To establish such a framework that upholds objectivity, certain prerequisites must be met. Firstly, the framework must possess justificational resources that prevent causality manipulations. Secondly, pre-reflective sources should not inter-define causality in epistemic circumstances, although this does not exclude the emergence of causal relations, and thus this approach offers a correlational explanation. Lastly, transcendental reflections should remain compatible with the experiential-intentional process, allowing for the accommodation of subjectivity in the justification of objectivity. (shrink)

Taxation must be remained an integral feature in terms of government-wide revenues, fiscal financial investments as well as individuals' saving and investment patterns within а economic system. The key point of introduction of the new income tax regime to Union's Budget 2020 was to provide an option of the current tax system towards a unified tax system with lesser dependencies on exemptions & deductions. Under the new regime lower rates have been introduced but it removed most of the deductions as (...) available earlier under the old regime; thus making significant dilemma either to shift or to remain with old regime, depending on the financial position of the taxpayers. This study, however, goes in detail through old tax versus new tax regime and upon the tax rates and exemptions and deductions and also checks out the total cost implications. The research is based on primary data obtained from 90 respondents with a projection sample of 130 through structured questionnaires. Descriptive and statistical analysis technique such as t-tests, chi-square test, regression analysis has been used to analyze taxpayer preference, savings behavior and compliance under both tax systems. The results show that taxpayers with less investment and deductions support the new tax regime because of its ease, whereas those with large investments in tax-saving vehicles still hold on to the old tax regime. Further, budgetary adjustments in 2024-2025 and 2025-2026 have also changed tax slabs and rebate structures, which affect the choices of taxpayers. The research points out that tax regime choice is influenced significantly by factors other than income levels, including investment behavior, long-term savings, and financial literacy. (shrink)

This remains the case because cyberattacks are becoming more frequent and sophisticated, and as a result, the IDS must also be innovative and evolving to protect sensitive networks. Traditional intrusion detection techniques are replaced by more advanced and dynamic Methodologies based on Machine Learning (ML) algorithms. These dynamic systems capture significant data flows, search for potentially pathological patterns, and forecast threats in real time. By simulating and analyzing real-time cases, this paper discusses the architecture for ML-based IDS, how this function (...) is implemented, and its effectiveness. The primary issues of data quality, model scaling, and interpretability are presented with solutions to address them and support the reliable functioning of the system. (shrink)

The current paper critically reviews the most significant announcements in presenting the "Union Budget (2025-26)" by Hon'ble Finance Minister Mrs. Nirmala Sitharaman, specifically from the viewpoint of their tax policy and economic development implications. It emphasizes how the government seeks to meet the fiscal requirements of diverse socio-economic groups, including the middle class and lower-income communities. By analysing changes in tax slab rates and implementing new tax policies, the research will determine the problems and advantages that these measures have for (...) taxpayers and service sectors looking for relief and opportunities for growth. The paper also discusses how these fiscal policies are structured to spur economic activity, increase disposable income, and encourage investment in major sectors. It examines the likely effect of these changes on consumer expenditure, savings, and overall economic stability. The research also attempts to forecast future economic cycles and their probable implications for sustainable development and social well-being in India. Based on an examination of the allround approach adopted in the Union Budget, this study attempts to offer insights into how effective the proposed tax reforms are going to be and how they contribute towards creating a more inclusive and robust economy, leading to the prosperity of the nation. (shrink)

The health industry is experiencing change, the newest forerunner of which is being propelled by spatial computing and generative AI. Spatial computing simply refers to the ability to interface with physical space through computation and digital devices; on the other hand, generative AI means using advanced machine learning to generate new output. This paper examines the roles and the combined possibilities of these two technologies with the view of transforming health care and diagnostics in the field of patient care. Precision (...) medicine unveils new opportunities of integrating precise spatial computing components and generative artificial intelligence to provide a personalized treatment for patients and data visualization for surgeons. The paper examines major use cases, concerns, and future of this convergence specifically in the fields of medicine. (shrink)

Generative AI has proven itself as an efficient innovation in many fields including writing and even analyzing data. For spatial computing, it provides a potential solution for solving such issues related to data manipulation and analysis within the spatial computing domain. This paper aims to discuss the probabilities of applying generative AI to graph-based spatial computing; to describe new approaches in detail; to shed light on their use cases; and to demonstrate the value that they add. This technique thus incorporates (...) graph theory, generative models to model spatial relations, generate new spatial forms and improve on spatial decision-making processes. The paper surveys such methods, describes typical applications, and outlines further development of the subject. (shrink)

By integration with cloud computing, cybersecurity and generative AI, the insurance industry is being transformed from high efficiency, low cost, and better customer service. However, these advanced technologies can also be used by insurers to automate and streamline processes like claims handling, underwriting, and policy generation, which are majorly time consuming and error prone. In predictive analytics, fraud detection, and personalized customer experience, generative AI makes it possible for insurers to mitigate risks and, at the same time, provide more personalized (...) services to customers. With cloud platforms, data management is scalable, flexible and secure, offering real time access to data that drives value by accelerating sound decisions in the insurance value chain. Sensitive data is protected against cybersecurity threats, staying compliant with regulations and marginally reducing risk. Guidewire’s unified technology stack allows insurers to leverage the integrated nature of these technologies through end-to-end integration to improve operational resilience and customer satisfaction. It is these synergies that are the future of insurance which is why transparency, ethical practices in AI as well as proactive cybersecurity are vital. It will become an arms race for insurers to keep pace with these changes and move away from being rigid and slow to adapt; they will need to stay agile and quick, especially with the landscape changing so rapidly. (shrink)

This chapter situates Karl Marx’s dissertation The Difference between the Democritean and Epicurean Philosophy of Nature (1841) within his intellectual biography. It explores the role of a German ideal known as Bildung, translated as “education”, “cultivation” or “culture”, within Marx’s classical education in the Gymnasium and the dissertation itself. Both Wilhelm von Humboldt, who reformed the Gymnasium curriculum prior to Marx’s attendance, and philosopher G.W.F. Hegel have classically inspired notions of Bildung. Each presents the white European man as the model (...) for this “education” or “cultivation”. This chapter argues that the dissertation assimilates Epicurus and his atom into this Eurocentric paradigm, with Marx taking for granted his predecessors’ racist teleology of history and applying their conception of the individual to the atom. Then, it addresses the dissertation’s influence in the development of historical materialism, a facet of Marxism already critiqued for its Eurocentrism. This chapter concludes by showing how non-White and non-Western Marxists have updated Marxist thought through constant critique of its Eurocentrism instead of abandoning its revolutionary vision. It suggests that Marxism is relevant to scholars of antiquity not because of the dissertation but the tradition’s self-interrogation of its foundational ideas and persistent focus on improving the conditions of the marginalised. (shrink)

Today e-commerce has had tremendous growth in the past years primarily due to changes in technology and customer’s buying behavior. One of the big shifts in the process has been the use of ML in advertising which has the capability to transform the marketing domain together with consumer interactions. This paper discusses the viability of using machine learning for designing realistic models of advertising to increase effectiveness of target and personalized advertising, as well as conversion rates in e-commerce. Several techniques (...) are explored in the study, such as supervised and unsupervised learning, recommender systems, and content optimization with natural language processing. By using case studies and experimental models, we discuss how and to what extent ML is beneficial in e-commerce advertising transformation. The results presented in this paper indicate that using machine learning in advertising has a potential of dramatically improving the customer experience while simultaneously increasing brand recognition and sales. (shrink)

Accurate and timely validation of trade inputs is critical in high-frequency commodity and financial trading environments. Manual or delayed validation can result in erroneous trades, compliance risks, and operational inefficiencies. This paper presents a real-time input validation system for traders, implemented using low-latency Java APIs and AWS Kinesis. The system ensures that inputs are checked against business rules and market constraints in milliseconds before proceeding to execution workflows. Our architecture leverages AWS Kinesis for high-throughput data streaming, Java-based microservices for synchronous (...) rule enforcement, and DynamoDB for persistent rule management and transaction tracking. The system demonstrates strong scalability, low latency, and adaptability across diverse trading desks. (shrink)

PostgreSQL has established itself as a powerful and feature-rich open-source relational database management system, increasingly adopted in modern cloud-native applications. As organizations transition to serverless computing for scalability and operational efficiency, integrating traditional stateful systems like PostgreSQL within stateless, event-driven workflows poses unique performance and architectural challenges. This research investigates the performance characteristics of PostgreSQL in such environments by leveraging key AWS services, including AWS Lambda and Amazon S3, to orchestrate serverless data pipelines. The study simulates a range of real-world (...) scenarios, including high-throughput bulk data inserts, concurrent data access, and complex analytical queries, to assess PostgreSQL’s behavior under load in an event-driven setup. Performance metrics such as query latency, throughput, system scalability, and cost-effectiveness are examined in depth. Furthermore, we present a case study modeled on production-scale workloads to highlight common bottlenecks, the impact of cold starts, database connection limits, and strategies to mitigate these issues through architectural and configuration optimizations. The findings contribute actionable insights for developers and architects designing scalable and efficient serverless systems with relational databases. (shrink)

As in today's fast-changing technological context, organizations more and more need cost-effectiveness to maintain competitiveness and enhance organizational performance. Leading drivers of these trends are automation, cloud technology, data-based decision-making, and agile. Automation improves performance through minimizing redundancy and human mistake, especially supply chain, financial, and customer care processes. Predictive analysis also helps maintain cost savings with forecasting demand and optimization of assets. Cloud computing offers scalable and elastic infrastructure solutions, reducing the costs of traditional IT. Companies such as Netflix (...) and Amazon Web Services illustrate how cloud platforms facilitate dynamic resource allocation and cost-efficient service delivery. Datadriven decision-making enables businesses to gain a deeper understanding of consumer behaviour and market trends. Businesses such as Tesla and Google use big data analytics to optimize supply chains and minimize operational waste, improving responsiveness and profitability. Remote and blended work arrangements, enabled by tools like Zoom and Microsoft Teams, minimize overhead for office space and transportation, with additional saving opportunities. Lean and agile systems, embraced by companies like Toyota and Tesla, enhance flexibility and minimize waste through production and project management. Cybersecurity is an ongoing issue as digital integration continues to grow. Investments made by companies such as IBM and Microsoft in sophisticated security systems reduce financial and reputational risks. Although these measures have definite advantages, difficulties like large initial investment, resistance to change, and data security threats remain. Phased implementation facilitates smooth transitions. Finally, organizations adopting smart technologies and innovation stand a better chance of realizing sustainable cost reductions and long-term profitability. (shrink)

The emergence of multimodal solutions in various fields has significantly transformed industries, bridging the gap between different types of media, data, and human interaction. These solutions combine text, audio, visual, and sensor-based inputs to create richer, more dynamic systems. This paper explores the evolution and impact of multimodal solutions, examining their application in sectors such as healthcare, education, and artificial intelligence. Key challenges, such as data integration, user experience, and privacy concerns, are also addressed.

Taxation is an important aspect of economic policy, influencing individual financial choices and national revenue generation. India's tax structure was revolutionized by the implementation of a new tax regime, which eliminates the complexity of tax rates but eliminates the majority of deductions. The change in policy offers taxpayers a choice between taking up the new regime or staying in the old system, which maintains deductions but is more intricate. This paper makes a comparative evaluation of both tax regimes, examining their (...) structure, effect on various income groups, and overall economic effects. Through scenario-based simulations, the research estimates differences in tax liability and potential gains for taxpayers. The results indicate that although the new tax regime simplifies compliance, the old regime is still more desirable for those who effectively use deductions. These insights can assist policymakers in refining tax structures for greater equity and efficiency. (shrink)

Strategic Cost Management (SCM) is a key area of financial planning that enables companies to maximize the utilization of resources, enhance profitability, and reach long-term financial wellness. Differing from traditional cost-cutting, SCM integrates costing, budgeting, and decision-making as an essential part of an overall strategic framework. Techniques such as Activity-Based Costing (ABC), Target Costing, and Life Cycle Costing help organizations determine drivers of cost and align their cost structures with company objectives. SCM also helps in developing budget models, risk minimization (...) strategies, and financial projections that help in ensuring sustainable business development. In spite of its strategic advantage, most companies persist in applying aged practices that only care about reducing costs in the short term at the expense of the long run. The benefits of tools like AI-based cost analysis and real-time financial surveillance are not tapped to their fullest potential, particularly among small and medium-sized firms (SMEs), due to resource inadequacies and skilled manpower deficits. This research delves into SCM's contributions to financial planning and decision-making and provides implementable recommendations to companies, finance professionals, and policymakers. (shrink)

: Serverless computing has revolutionized the way modern cloud-native applications are developed and deployed, offering a paradigm in which developers can focus solely on writing code without the burden of managing infrastructure. Among the various Function-as-a-Service (FaaS) offerings, AWS Lambda stands out as a widely adopted platform due to its automatic scaling, event-driven execution, and pay-per-use pricing model—making it ideal for applications ranging from microservices to complex event-driven workflows. However, serverless architectures present challenges in cold start latency, performance tuning, and (...) cost optimization, particularly when using heavyweight runtimes like Java or under sporadic invocation patterns. This study systematically evaluates AWS Lambda’s performance under varying load conditions by analyzing runtime performance (Java vs. Python), memory allocation, payload size, and traffic types including steady, burst, and spiky patterns. Key metrics such as cold start time, average execution duration, and cost per invocation are examined using real-world traffic simulations and observability tools like AWS CloudWatch and X-Ray. The findings demonstrate that tuning memory allocation, applying provisioned concurrency, and selecting lightweight runtimes can significantly improve latency and cost-efficiency. The paper concludes with best practices for serverless workload optimization, offering actionable insights for software architects and DevOps teams aiming to balance scalability, responsiveness, and operational cost in cloud-native deployments. (shrink)

With the growing complexity of AI models and the vast computational resources required for their development, it is becoming increasingly important to optimize machine learning workflows for both efficiency and sustainability. This paper explores the various Python tools and techniques available for improving AI workflows while minimizing energy consumption and reducing carbon footprints. By incorporating best practices in model optimization, hardware acceleration, efficient data handling, and deployment strategies, AI development can be made more energyefficient and eco-friendly. Through the exploration of (...) libraries like TensorFlow, PyTorch, and specialized tools for green computing, this paper emphasizes the role of Python in advancing both efficient and sustainable AI workflows. (shrink)

The integration of cloud architecture into Human Capital Management (HCM) systems has revolutionized the way organizations manage their workforce. Cloud-based HCM solutions offer enhanced scalability, flexibility, and accessibility, enabling organizations to streamline HR processes, improve data management, and foster greater employee engagement. This paper explores the impact of cloud architecture on HCM processes, highlighting key benefits such as cost-effectiveness, real-time data access, and seamless integration with other business systems. Through a comprehensive literature review and analysis of case studies from diverse (...) industries, the study demonstrates how cloud-based HCM systems optimize talent acquisition, performance management, learning and development, and workforce analytics. Additionally, the research addresses the challenges associated with transitioning to cloud-based HCM solutions, including data security, privacy concerns, and change management. Best practices for implementing cloud architecture in HCM are discussed, emphasizing the importance of strategic planning, stakeholder engagement, and continuous evaluation. The findings underscore the pivotal role of cloud architecture in enhancing organizational efficiency, agility, and competitive advantage in today’s dynamic business environment. (shrink)

Automating data transformations is a critical component of modern data workflows, enabling organizations to enhance data processing efficiency, reduce manual intervention, and ensure more reliable and scalable data pipelines. DBT (Data Build Tool) has emerged as a leading solution for automating data transformations, allowing data engineers to leverage SQL-based models, version control, and testing frameworks for building, executing, and documenting data transformations directly within cloud data warehouses. This paper examines how DBT automates data transformation workflows, its integration with modern cloud-based (...) data platforms, and the benefits and challenges associated with its use. Through case studies and a detailed analysis of DBT’s features, this paper highlights how data teams can automate and streamline their data transformation processes to achieve higher data quality, scalability, and operational efficiency. (shrink)

The Home Depot data breach, which occurred in 2014, marked a significant turning point in the cybersecurity landscape, drawing attention to the increasing prevalence of ransomware and cyberattacks targeting large-scale retail organizations. This breach exposed the personal and financial information of over 56 million customers and highlighted the vulnerabilities in the systems used by major corporations. The attack was attributed to a sophisticated ransomware operation that gained access through a third-party vendor’s compromised credentials, ultimately enabling cybercriminals to infiltrate Home Depot’s (...) network. This paper explores the Home Depot breach, focusing on its relation to the rise of ransomware as a common cyber threat. It delves into the tactics, techniques, and procedures (TTPs) employed by the attackers, the vulnerabilities exploited, and the broader implications for the retail industry and cybersecurity at large. Additionally, the study examines how ransomware has evolved from a relatively niche threat to a significant weapon in the cybercriminal arsenal, affecting organizations across all sectors. By analyzing the breach and its aftermath, this paper offers insights into best practices for cybersecurity resilience and incident response strategies that can help mitigate future threats of similar magnitude. (shrink)

The increase in claim sophistication in both the insurance and legal domains is a result of an increase in stokes and heterogeneity of data needed to assess the claim validity. Originally, this task was performed by some sort of subjectivity assessments and graphical rule sets, which is very slow and may be inherently erroneous due to its purely manual nature. Hence, with progressivity in multimodal learning, specifically in AI, there is now a unique chance of solving these challenges through the (...) use of text data, which may include policies, reports and images, which may include accident images, evidence images, videos such as surveillance, cam videos among others. However, existing AI-based solutions usually address only one of the modalities, which makes it difficult to evaluate an integrated situation. This has led to the need for systems that will integrate information from all these modalities and come up with an accurate, efficient, and transparent processing system. Indeed, this paper seeks to discuss the use of Multimodal generative AI to address this need as one of the most recent approaches that rely on high-performing models that can process and integrate text, image, and video data. The proposed system combines these modalities to ensure that the system captures relevant data from each data type and combines all in a way that provides more comprehensive and enriched decision support. An initial system was designed and empirically tested against current claim adjudication techniques and was found to yield substantial enhancements in all utilization rates, throughput and main rationale for the claim decisions. The findings shown in the study stress the capability of multimodal generative AI for revolutionizing the present approaches of claims analysis and developing more efficient, accurate, and capable responses to various real-life conditions. This integration of technologies is an unprecedented advance towards advancing functional processes in the insurance and legal industries. (shrink)

P&C insurers have an important role in addressing financial risk management needs but now struggle to respond to the new forms of risk. Historical analysis and actuarial calculations, which form the backbone of classical approaches to risk measurement and management, are not well suited to such new kinds of risks as climate change, cyber risks, and business cycle risks. These conventional approaches are also a static method for selling, which has limited potential in changing quickly with new market and consumer (...) changes. However, the development of AI, big data, or advanced predictive analytics has provided a new paradigm to such challenges to cope with and analyze big data dynamically to derive Applying a combination of best Machine Learning (ML), natural language processing (NLP) and other AI techniques, it will become possible to predict risks exposures, as well as optimize underwriting and claims processing. In this paper, the author investigates the opportunities that AI carries within the sphere of reformation of risk evaluation approaches in P&C insurance. In particular, it discusses the ever-emerging field with AI models integrated into operations, underwriting, fraud detection, claims modelling, and loss computation. The applied research uses a comprehensive bibliographical review to present past and present practices and assess modern AI implementations. This paper uses research approaches and case studies to prove that AI can solve some problems and bring cost-saving solutions. Moreover, it emphasizes the ability of predictive analytics to enhance customer satisfaction at the policy level as well as optimize operations. However, the paper also explores the dirty side of implementation, including the stipulations surrounding compliance and data privacy and thus provides an objective analysis of the future of AI use in the P&C Insurance Industry. (shrink)

This abstract summarizes, in essence, what generative AI means to the insurance industry. The kind of promise generated AI offers to insurance is huge: in risk assessment, customer experience, and operational efficiency. Natural disaster impact, financial market volatility, and cyber threat are augmented with techniques of real time scenario generation and modeling as well as predictive simulation based on synthetic data. One of the challenges that stand in the way of deploying these AI methods, however, is data privacy, model reliability (...) and interpretability. The insurance industry must address these issues if it is to comply with regulations like GDPR and CCPA or mitigate reputational risks, as anybody can make complaints about any company based on any perceived data breach. Indeed, generative AI models, often convoluted and biased, can propagate unfair outcomes, especially in pricing and policy access. Navigating these challenges requires a whole new frayed society of AI specialists in collaboration with the industry’s insurers to offer bespoke solutions that address the firm’s needs. Based on this work, future developments will center on designing and implementing ethical and regulatory frameworks around AI-driven decisions that are transparent, fair and sustainable. Generative AI has historically been the most feared phenomenon in the history of western civilization, but with predictive analytics and risk simulation capabilities taking shape, generative AI is set to disrupt the insurance industry and add real-time decision support, automating claims processing and personalized interaction. To successfully integrate generative AI, technical, ethical and regulatory challenges will need to be addressed, and a trust-driven ecosystem will emerge to serve evolving customer needs. (shrink)

Recent studies show that racism still exists in the American medical profession, the fact of which legitimizes the historically long-legacy of mistrust towards medical profession and health authorities among African Americans. Thus, it was suspected that the participation of black patients in end-of-life care has always been significantly low stemmed primarily from their mistrust of the medical profession. On the other hand, much research finds that there are other reasons than the mistrust which makes African Americans feel reluctant to the (...) end-of-life care, such as cultural-religious difference and genuine misunderstanding of the services. If so, two crucial questions are raised. One is how pervasive or significant the mistrust is, compared to the other factors, when they opt out of the end-of-life care. The other is if there is a remedy or solution to the seemingly broken relationship. While no studies available answer these questions, we have conducted an experiment to explore them. The research was performed at two Philadelphia hospitals of Mercy Health System, and the result shows that Black patients’ mistrust is not too great to overcome and that education can remove the epistemic obstacles as well as overcome the mistrust. (shrink)

The advent of cloud computing has fundamentally transformed various business operations, with Human Capital Management (HCM) standing out as a significant beneficiary. Cloud-based HCM solutions offer unparalleled scalability, accessibility, and integration capabilities, enabling organizations to manage their workforce more efficiently and strategically. This paper explores the revolutionary impact of cloud computing on HCM, highlighting key advancements such as enhanced data analytics, improved employee engagement, cost-effectiveness, and support for remote and hybrid work models. Through a comprehensive literature review and analysis of (...) case studies from diverse industries, the study demonstrates how cloud computing facilitates real-time data access, seamless system integration, and the implementation of advanced technologies like artificial intelligence (AI) and machine learning (ML) within HCM frameworks. Additionally, the research addresses challenges associated with cloud-based HCM adoption, including data security, privacy concerns, and change management. Future research directions are proposed to further leverage cloud computing capabilities, emphasizing the integration of emerging technologies and the continuous evolution of cloud-based HCM tools. The findings underscore the pivotal role of cloud computing in enhancing organizational agility, optimizing human capital, and driving sustainable business growth. (shrink)

The proposed project is a smart parking reservation system that offers clients an easy way to reserve a parking space online. It overcomes the problem of Finding a parking area in industrial or commercial areas that is useful consumes time. As a result, this challenge provides an internet-based reservation machine where customers can view numerous parking regions and select the space to view whether an area is to be had or not. If the reserved space is available, he can book (...) it for a specific time slot. The booked area might be marked yellow and could no longer be available for all of us for the specified time. This gadget affords the additional characteristic of cancelling the bookings. Each time, the user can cancel their books area. Users can make payment online via Credit card, UPI, etc. Users are notified approximately after making the payment, the booking via email along with a particular parking number. Online Vehicle Leaving Framework, as portrayed above, can prompt mistake free, secure, solid and quick administration framework. (shrink)

Generative artificial intelligence (Gen AI) and machine learning (ML) technologies are changing the way the insurance industry looks, particularly by integrating Gen AI & ML technologies. As a leading platform for property and casualty insurance, Guidewire provides a perfect platform for deploying intelligent claims processing workflows that can dramatically improve efficiency, accuracy and customer satisfaction. The seamless integration of Gen AI and ML capabilities into Guidewire to autonomously process claims is explored in this paper. Insurers can use advanced models to (...) drive self-driving workflows that are capable of automating tasks like claims triage, fraud detection, damage assessment and settlement optimization. But most importantly, these technologies reduce operational costs, and reduce the human intervention involved such that claims can be handled faster and with more accuracy. In this work, we discuss what technical and strategic considerations need to be taken into account when implementing such workflows, such as data integration, model training, and ethical AI practices. This paper also demonstrates several real-world use cases, the challenges you in each, and the potential to scale these solutions across lines of business. With an eye on the future, autonomous claims processing enables insurers to find their next competitive edge by providing innovative solutions that alter the course of expectations of customers while qualifying to regulatory and compliance standards. Self-driving workflows powered by Gen AI and ML in claims are the future of insurance and their ability to transform the entire process of claims management. (shrink)

Traditional steganography systems suffer from outdated compression and encryption methods, leading to large key sizes, high computational complexity, and increased vulnerability to steganalysis attacks. These limitations make conventional steganography inefficient and less secure. Additionally, advancements in AI-driven image analysis have made image steganography increasingly ineffective, as modern algorithms can easily detect hidden data within images. In contrast, audio steganography remains an underexplored field with significant potential, though existing solutions are often underdeveloped and lack robust security measures. To address these challenges, (...) we propose an Enhanced Audio Steganography System that integrates modern lossless compression algorithms (e.g., Zstandard, Brotli) with state-of-the-art encryption techniques (e.g., AES-256, ChaCha20). Our system employs Least Significant Bit (LSB) steganography, enhanced with dynamic algorithm selection and randomization, to maximize security and efficiency. By intelligently combining compression, encryption, and adaptive embedding techniques, our approach significantly improves imperceptibility, robustness, and adaptability, making it ideal for secure communication and covert data transfer. By leveraging advanced cryptographic and compression techniques, our system achieves high security with minimal computational overhead, effectively overcoming the limitations of traditional methods while ensuring efficient and secure audio- based data concealment. (shrink)

Zero-day vulnerabilities are critical security risks that exploit previously unknown flaws in software systems, making them difficult to detect and defend against. As such vulnerabilities are discovered by attackers before the software vendor is aware of them, they provide a significant advantage to malicious entities. The exploitation of zero-day vulnerabilities is a major concern for both individuals and organizations, as it can lead to unauthorized data access, loss of information, and compromised systems. This paper aims to explore the nature of (...) zero-day vulnerabilities, their discovery and exploitation, and the current strategies for mitigating these risks. By reviewing existing literature and case studies, the research identifies the core challenges in addressing zero-day vulnerabilities, discusses existing countermeasures, and evaluates the potential future direction of cybersecurity techniques aimed at reducing exposure to these threats. The study highlights the need for continuous software monitoring, rapid patch deployment, and enhanced awareness in the security community to mitigate zero-day risks effectively. (shrink)

The generative AI system is being adopted across the several fields to provide novel solutions for text generation, image synthesis, and decision-making. But when they are used in multi-agent and multi-cloud systems, they are expensive in terms of computation and finance. Regarding the aforementioned factors, this paper aims to examine methods of reducing such costs while achieving system efficiency. Such measures as dynamic workload distribution, resource scaling, as well as cost-conscious model selection is described. Through the examples of case studies (...) and simulations, we show that incorporating these strategies can drastically decrease expenses and ensure immediate and accurate scalability across clouds of different ecosystems. (shrink)

CVDs continue to be the number one cause of death, therefore early detection and treatment is crucial. Currently, the application of Artificial Intelligence (AI) in the cardiac image analysis has become popular due to increased accuracy, productivity, and modelling. In this paper, the use of the AI system to study the echocardiogram, CT, MRI, and other images of the heart and blood vessels to view the risk factors for cardiovascular diseases is discussed. We focus on the current methods of artificial (...) intelligence, how it is implemented in clinical practice, problems, and prospects for AI development. (shrink)

The Internet of Things (IoT) is a rapidly growing technology that connects and integrates billions of smart devices, generating vast volumes of data and impacting various aspects of daily life and industrial systems. However, the inherent characteristics of IoT devices, including limited battery life, universal connectivity, resource-constrained design, and mobility, make them highly vulnerable to cybersecurity attacks, which are increasing at an alarming rate. As a result, IoT security and privacy have gained significant research attention, with a particular focus on (...) developing anomaly detection systems. In recent years, machine learning (ML) has made remarkable progress, evolving from a lab novelty to a powerful tool in critical applications. ML has been proposed as a promising solution for addressing IoT security and privacy challenges. In this article, we conducted a study of the existing security and privacy challenges in the IoT environment. Subsequently, we present the latest ML-based models and solutions to address these challenges, summarizing them in a table that highlights the key parameters of each proposed model. Additionally, we thoroughly studied available datasets related to IoT technology. Through this article, readers will gain a detailed understanding of IoT architecture, security attacks, and countermeasures using ML techniques, utilizing available datasets. We also discuss future research directions for ML-based IoT security and privacy. Our aim is to provide valuable insights into the current state of research in this field and contribute to the advancement of IoT security and privacy. (shrink)

Through a combination of Guidewire platforms, cloud computing and cybersecurity frameworks, the insurance industry in miniature is being transformed into a digitally transformed, ever resilient ecosystem. This ecosystem enables insurers to modernize core operations of policy management, claims processing and billing while continuing to provide secure, scalable and efficient service delivery. Insurers using cloud infrastructure have elastic resources capable of scaling to meet dynamic workloads and can provide high availability and fast disaster recovery. They have liberated data analytics to run (...) on the cloud with advanced capabilities to churn out actionable insights to optimize operations and create personalized offerings for their customers. Sensitive customer data and important systems are securely protected from cyber security threats by a robust cybersecurity layer, which includes data encryption, controls access, and detects threats proactively. Integration and cloud adoption challenges like costly implementation, cybersecurity risk and legacy system migration will be handled by deft and effective strategies such as phased adoption, workforce upskilling and adoption of a zero-trust security model. Within operational efficiency, stronger resilience and innovative business models enabled, i.e. behavior-based insurance pricing through IoT and real time analytics, are the opportunities. However, moisture and regulatory complexity can be barriers to change, and investments in modern technology, workforce development, and partnerships with insurtech and cybersecurity experts can enable insurers to survive and thrive in a more competitive, digital-first landscape. This convergence engenders customer trust, unlocks its operational agility and ensures compliance with changing requirements, thereby enabling insurers to sustain their growth, build resilience and rival digital transformation. (shrink)

The digital transformation of the insurance industry is unprecedented, urged by the changing expectations of customers, the necessity to embrace regulatory requirements and the necessity to enhance operational efficiency. This paper examines the convergence of three leading-edge technologies, Guidewire, Amazon Web Services (AWS) and Snowflake, to enable scalable, resilient and data-driven solutions for insurers. AWS and Snowflake provide unmatched cloud infrastructure in terms of security and scalability. They also provide industry-specific applications and frameworks for modernizing core systems for Guidewire, such (...) as Snowflake data warehousing and analytics. By working together, these platforms allow insurers to leverage the combined power of integrated ecosystems, real-time insights, and automation to meet current challenges and adapt to future disruptions. A key focus of this study is providing a roadmap for insurance would-be insurgents looking to capitalize on agility, customer-centricity, or both in one of the most rapidly changing industries in terms of distribution. (shrink)

Property and Casualty (P&C) insurers are adopting multi-cloud environments as a strategic imperative because of their increasing data volumes and complexities in regulatory compliance, customer expectations and technological advancements. This paper discusses how Snowflake’s cloud-agnostic, unified platform enables insurers to create resilient, efficient, and compliant multi cloud data strategies. Using Snowflake’s elastic scalability, real-time analytics, secure data sharing and seamless cloud interoperability, insurers can optimize claims processing, augment fraud detection, and support customer engagement. The study offers core design principles for (...) multi cloud data architectures and sheds light on problems in data fragmentation, latency, and security risks. It points to how Snowflake enables data resilience, including data replication, encryption, GDPR, and CCPA compliance. Details are provided. Practical implementation strategies of phased data migration ETL pipelines and integration with existing enterprise system to ensure a smooth deployment. Snowflake is seen as a clear win through a cost-benefit analysis with metrics like RTO and RPO that define how well Snowflake performs disaster recovery and business continuity. Additionally, the paper also looks at the emergence of tech like AI, blockchain and edge computing which could additionally bolster multi-cloud strategies even further. Finally, Snowflake enables the journey for P&C insurers through cloud ecosystem pitfalls, enabling operational resilience, regulatory compliance, along competitive advantage in a data-driven industry. (shrink)