The rise of social media platforms has led to an unprecedented amount of unstructured text data. This presents Business Intelligence (BI) with a great chance to learn more about public ideas, feelings, and market dynamics. This study looks into new ways to use social media analytics, like opinion mining and sentiment analysis, to improve business intelligence (BI) tools. The report talks about how standard BI systems have trouble interpreting social media data that is noisy, high-volume, and fast-moving, as well as how hard it is to use these insights to make strategic decisions. It stresses the necessity for advanced methods for collecting and preparing data, as well as advanced opinion mining and sentiment analysis using Natural Language Processing (NLP), Machine Learning (ML), and Deep Learning (DL), coupled with comprehending the context and making predictions.
Growing dependence on digital surroundings for data storage, transaction handling, and communication has led to newer concerns involving security, privacy, and transparency. Classic centralized systems suffer heavily from cyber attacks, data breach scenarios, and improper modifications that require the implementation of more efficient security frameworks. In that regard, blockchain technology, based on decentralized cryptographic security, is a solution to these aforementioned problems. Aside from guaranteeing immutability, transparency, and security from vulnerabilities, blockchain is also one such technology that acts as a distributed ledger.
The domain of rehabilitation has changed so much, even with the COVID-19 pandemic. Given the high rate of long-term physical, respiratory, and cognitive impairment after SARS-CoV-2 infection, home-based rehabilitation has proved to be an essential alternative to the often-limiting brick-and-mortar rehabilitation. The rationale for home-based rehabilitation in the post-COVID context is reviewed in this review, along with core clinical protocols including physical therapy, respiratory training, and cognitive rehabilitation. Further, such interventions are also explored in regard to their clinical effectiveness, where outpatient, functional outcomes, pulmonary recovery, and improvements in mental health and quality of life are considered.
With growing sophistication and numbers of digital finance systems, the risk of fraud in accounts payable (AP) and automated payment systems has deepened. Legacy rule-based controls cannot cope with detecting sophisticated threats like invoice forgery, vendor impersonation, and duplicate disbursements. This review examines the combination of machine learning (ML) and AI with AP processes, showing how smart systems enhance anomaly detection, reduce false positives, and enable scalable fraud protection. It gives best AI techniques, including deep learning, unsupervised outlier detection, explainable AI (XAI), and federated learning.
As large language models (LLMs) evolve into core infrastructure for intelligent systems, the need for practical architectural guidance grows ever more urgent. This review takes the perspective of a Generative AI (GenAI) architect tasked with designing, building, and deploying LLM-powered applications from the ground up. Drawing from foundational research and real-world implementations, it outlines the modular architecture of such systems, from user interface orchestration to memory, inference, and alignment layers. It discusses the challenges of scaling, trust, latency, retrieval augmentation, and tool integration.
The world of telecommunications is changing quickly, thus tools need to do more than just meet technical goals. They also need to connect with the real needs of project teams. This article talks about how persona-based design may be used in telecom project tools. It shows how personas can help connect what users want with how these systems work. The analysis combines together important research findings and shows measurable benefits, like fewer mistakes and more efficient work completion. It also gives a theoretical basis for putting the ideas into practice. Telecom companies may create better, more inclusive, and more flexible solutions that fit with the challenges of modern network operations by using user-centered design concepts.
This case study looks at Adler Consulting's digital systems security architecture in depth and makes suggestions for how to improve it. Adler Consulting is a well-known organisation that provides IT solutions all around the world. Adler Consulting has more than 20,000 workers and brings in more than $1 billion a year. Because of this, they need to have strong security to deal with new cyber dangers that come up. The study goes into detail on the organization's existing security setup, which includes SIEM/SEM, WAF, and multi-cloud environments. It also points out the most relevant flaws and threats.
RISC-V is an open and extendable instruction set architecture that is widely used in both commercial and research processor designs. It is very important to make sure that its control routes are accurate, especially for applications in areas where safety and performance are very important. This paper looks at the different scalable formal verification approaches that can be used with RISC-V control logic. These include symbolic execution, bounded model checking, AI-assisted theorem proving, and invariant-based methods. We summarise the most important research results, experimental tests, and theoretical models, and suggest new areas of investigation.
Intelligent Electronic Devices play a critical role in substation protection, control and monitoring functionalities. Smart grid deployments need the seamless flow of data between relays and controllers, through public communication networks. This kind of deployments lead to inherent requirements for secure communication, strong user authentication and authorization to be considered in distributed line protection and control relays. The cyber security protocols used for communication between devices have to be secured. Securing data over the network involves ensuring confidentiality, integrity and authenticity.
Charging batteries of light electric vehicles require chargers with high efficiency and a high power factor. To meet this need, this paper presents a bridge-less single-power-conversion battery charger composed of an isolated step-up AC-DC converter with a series-resonance circuit. The bridgeless configuration reduces the conduction losses associated with the input diode rectifier, and the series-resonance circuit reduces the reverse- recovery losses of the output diodes by providing zero current switching. In addition, direct and series-resonance current injection enables bidirectional core excitation by the transformer, thereby allowing high power capability.
Pipelines of traditional clouds, especially those ADF-based, are not dynamically or adequately optimized for throughput and reliability, as well as the cost, depending on varying enterprise analytics workloads. Most often, these limitations manifest themselves as poor performance accompanied by heightened levels of operating expenditure. This paper proposes an innovative intelligent framework integrated into Azure Data Factory, utilizing predictive analytics and reinforcement learning for adaptive resource allocation, which supports intelligent anomaly detection and is accompanied by self-healing capabilities.
An in-depth empirical study comparing the two architectural paradigms MVVM and VIPER within the scope of modern iOS development with SwiftUI and Combine is presented here. It therefore puts an emphasis on software quality attributes — i.e., performance (render time, memory consumption, CPU productivity), scalability, and maintainability of the code — during migration of legacy applications built on top of UIKit to an architecture based on SwiftUI and Combine. Two real-world iOS applications of varying complexity were partially re-engineered under both architectures to compare practical results.
This paper examines how the Waterfall methods have changed to the Agile approach in project management, mainly discussing how these methods can be merged in a hybrid way. Using Waterfall and Agile as bases, we present a new process that maintains Waterfall’s planning structure and helps retain Agile’s ability to be flexible which improves both the stability and adaptability of projects. The paper points out the ways in which the hybrid model could better manage risks, please stakeholders and make projects more efficient.
The use of AI within SaaS platforms has greatly improved how worldwide Agile groups team up. The review examines how using AI in collaboration can help engineering teams from different parts of the world and time zones. This paper introduces the AI-Enhanced Engineering Collaboration Model (AI-EECM) based on an analysis of existing theories and models, including standard Agile development methods, cloud services and AI based SaaS tools. It connects predictive analysis, smart task dividing, better communication methods and ongoing learning to make project management more efficient and responsive.
Utilization of supplier portals in enterprise systems is an emerging organization's priority that aims at faster procurement, vendor satisfaction, and process automation. The review will look at the PeopleSoft Supplier Portal and the strategic value of the product to a company in supplier engagement, the architectural constraints it has, and the strategies to optimize the portal based on empirical experiences and best industry practices. A hypothetical model is presented, which describes modules of improvement in the areas of onboarding, workflow automation, document submission, and analytics.
Advanced analytics is a key component of the financial services transformation and provides financial institutions with tools to exploit massive data flows for predictive intelligence, automation, and customer-oriented innovation. This paper reviews the use of advanced analytics in risk modelling, fraud operations, enhancing customer attraction and retention as well as improving operational efficiency across core financial functions. The Financial Analytics Value Enablement Model (FAVEM) is presented as a conceptual framework that addresses the difficulties financial organizations face with analytics adoption, including challenges related to explainability, regulatory considerations, and antiquated infrastructure.
Artificial Intelligence (AI) has been integrated into cloud infrastructure, making it revolutionizing modern computing by automating, scaling, and improving efficiency. The first of these is Kubernetes, and the second is serverless computing. Kubernetes, a container orchestration platform, benefits from AI-driven enhancements in workload scheduling, auto-scaling, and resource optimization. By combining AI-based predictive analytics with container deployment, overhead is reduced in terms of operational overhead as well as fault tolerance. However, serverless computing takes away the management of infrastructure, leaving the developers free to write application logic.
This paper introduces a novel hybrid test automation framework that integrates National Instruments LabVIEW and Python scripting to optimize the validation of analog and digital circuits [1]. The architecture addresses the rising complexity and time-to-market pressures in multi-product environments by enabling parallelized test execution and efficient resource management. The framework's core strength is its ability to leverage the distinct advantages of both LabVIEW and Python, creating a synergistic environment for test automation. Experimental validation shows a 40% reduction in the overall test cycle time compared to traditional sequential methods.
The rapid cloud-native adoption architecture defined by loosely coupled components (microservices) has fundamentally changed the enterprise IT landscapes. These dynamic, distributed systems require an equally dynamic and granular access control mechanism that cannot be provided traditionally. Though traditional Identity Governance and Administration (IGA) systems are very good at managing static roles, they do not relate to the contextual, real-time decisions needed in modern applications.
The physics of pigment dispersion is directly linked with the efficiency of the high-speed inkjet prints and flexographically (flexo) printing. The performance and desired chemical stability of pigments held in suspension by these inks become especially relevant as printing systems are strained to new speed systems, new specific resolutions, and to designs that are more sustainable. The article addresses physicochemical mechanisms, dispersion techniques, and applicable formulations of pigments in the mechanisms of stabilizing pigments in these new printing processes.
With distributed computing, hybrid cloud adoption, and global workforce trends, managing digital identities and accessing sensitive data has taken a central stage for complex organizations. IAM goes beyond traditional role assignment and is now a dynamic security framework that incorporates Zero Trust principles, risk-based authentication, and AI-based automation. The review looks at modern advanced IAM techniques and their importance for cyber risk avoidance, posture for compliance, and protection of sensitive data and applications.
Social Media Analytics, Opinion Mining and Sentiment Analysis for Business IntelligenceUpendra Kanuru, Sirisha Cheepuri
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The rise of social media platforms has led to an unprecedented amount of unstructured text data. This presents Business Intelligence (BI) with a great chance to learn more about public ideas, feelings, and market dynamics. This study looks into new ways to use social media analytics, like opinion mining and sentiment analysis, to improve business intelligence (BI) tools. The report talks about how standard BI systems have trouble interpreting social media data that is noisy, high-volume, and fast-moving, as well as how hard it is to use these insights to make strategic decisions. It stresses the necessity for advanced methods for collecting and preparing data, as well as advanced opinion mining and sentiment analysis using Natural Language Processing (NLP), Machine Learning (ML), and Deep Learning (DL), coupled with comprehending the context and making predictions.
Enhancing Data Security and Transparency Through Blockchain TechnologySrinath Muralinathan
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Growing dependence on digital surroundings for data storage, transaction handling, and communication has led to newer concerns involving security, privacy, and transparency. Classic centralized systems suffer heavily from cyber attacks, data breach scenarios, and improper modifications that require the implementation of more efficient security frameworks. In that regard, blockchain technology, based on decentralized cryptographic security, is a solution to these aforementioned problems. Aside from guaranteeing immutability, transparency, and security from vulnerabilities, blockchain is also one such technology that acts as a distributed ledger.
Home-Based Rehabilitation Post-COVID-19: A Review of Protocols, Clinical Outcomes, and Lessons Learned.Priti Nathani
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The domain of rehabilitation has changed so much, even with the COVID-19 pandemic. Given the high rate of long-term physical, respiratory, and cognitive impairment after SARS-CoV-2 infection, home-based rehabilitation has proved to be an essential alternative to the often-limiting brick-and-mortar rehabilitation. The rationale for home-based rehabilitation in the post-COVID context is reviewed in this review, along with core clinical protocols including physical therapy, respiratory training, and cognitive rehabilitation. Further, such interventions are also explored in regard to their clinical effectiveness, where outpatient, functional outcomes, pulmonary recovery, and improvements in mental health and quality of life are considered.
AI-Based Fraud Detection in Accounts Payable and Payment Automation SystemsDeepesh Vinodkumar Semlani, Sudha Rani Pujari
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With growing sophistication and numbers of digital finance systems, the risk of fraud in accounts payable (AP) and automated payment systems has deepened. Legacy rule-based controls cannot cope with detecting sophisticated threats like invoice forgery, vendor impersonation, and duplicate disbursements. This review examines the combination of machine learning (ML) and AI with AP processes, showing how smart systems enhance anomaly detection, reduce false positives, and enable scalable fraud protection. It gives best AI techniques, including deep learning, unsupervised outlier detection, explainable AI (XAI), and federated learning.
Building LLM Powered Applications from Scratch - GEN AI Architect perspectiveBhanuvardhan Nune
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As large language models (LLMs) evolve into core infrastructure for intelligent systems, the need for practical architectural guidance grows ever more urgent. This review takes the perspective of a Generative AI (GenAI) architect tasked with designing, building, and deploying LLM-powered applications from the ground up. Drawing from foundational research and real-world implementations, it outlines the modular architecture of such systems, from user interface orchestration to memory, inference, and alignment layers. It discusses the challenges of scaling, trust, latency, retrieval augmentation, and tool integration.
Persona-Based Design for Telecom Project ToolsShirish Kashinath Borkar
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The world of telecommunications is changing quickly, thus tools need to do more than just meet technical goals. They also need to connect with the real needs of project teams. This article talks about how persona-based design may be used in telecom project tools. It shows how personas can help connect what users want with how these systems work. The analysis combines together important research findings and shows measurable benefits, like fewer mistakes and more efficient work completion. It also gives a theoretical basis for putting the ideas into practice. Telecom companies may create better, more inclusive, and more flexible solutions that fit with the challenges of modern network operations by using user-centered design concepts.
Digital Systems Security: Case Study of an IT Consulting firmUpendra Kanuru, Odiase Irumudomon
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This case study looks at Adler Consulting's digital systems security architecture in depth and makes suggestions for how to improve it. Adler Consulting is a well-known organisation that provides IT solutions all around the world. Adler Consulting has more than 20,000 workers and brings in more than $1 billion a year. Because of this, they need to have strong security to deal with new cyber dangers that come up. The study goes into detail on the organization's existing security setup, which includes SIEM/SEM, WAF, and multi-cloud environments. It also points out the most relevant flaws and threats.
Scalable Formal Verification Strategies for RISC-V Based Control Paths: A ReviewAparna Mohan
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RISC-V is an open and extendable instruction set architecture that is widely used in both commercial and research processor designs. It is very important to make sure that its control routes are accurate, especially for applications in areas where safety and performance are very important. This paper looks at the different scalable formal verification approaches that can be used with RISC-V control logic. These include symbolic execution, bounded model checking, AI-assisted theorem proving, and invariant-based methods. We summarise the most important research results, experimental tests, and theoretical models, and suggest new areas of investigation.
Cyber Secure Substation Distributed Line Protection RelayDr. S. Ganesh, Gomathi. A
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Intelligent Electronic Devices play a critical role in substation protection, control and monitoring functionalities. Smart grid deployments need the seamless flow of data between relays and controllers, through public communication networks. This kind of deployments lead to inherent requirements for secure communication, strong user authentication and authorization to be considered in distributed line protection and control relays. The cyber security protocols used for communication between devices have to be secured. Securing data over the network involves ensuring confidentiality, integrity and authenticity.
Single-Stage Bridgeless Battery Charging System for LEVsMurugan S, Gayathri P
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Charging batteries of light electric vehicles require chargers with high efficiency and a high power factor. To meet this need, this paper presents a bridge-less single-power-conversion battery charger composed of an isolated step-up AC-DC converter with a series-resonance circuit. The bridgeless configuration reduces the conduction losses associated with the input diode rectifier, and the series-resonance circuit reduces the reverse- recovery losses of the output diodes by providing zero current switching. In addition, direct and series-resonance current injection enables bidirectional core excitation by the transformer, thereby allowing high power capability.
AI-Enhanced Data Pipeline Optimization in Azure: A Scalable Framework for Enterprise Analytics Using Azure Data Factory
Suresh Pairu Subramanyam
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Pipelines of traditional clouds, especially those ADF-based, are not dynamically or adequately optimized for throughput and reliability, as well as the cost, depending on varying enterprise analytics workloads. Most often, these limitations manifest themselves as poor performance accompanied by heightened levels of operating expenditure. This paper proposes an innovative intelligent framework integrated into Azure Data Factory, utilizing predictive analytics and reinforcement learning for adaptive resource allocation, which supports intelligent anomaly detection and is accompanied by self-healing capabilities.
Optimizing IOS App Performance Using SwiftUI and Combine: A Comparative Study of MVVM vs. VIPER Architectures
Indrajit Shanbhag, Rutul Desai
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An in-depth empirical study comparing the two architectural paradigms MVVM and VIPER within the scope of modern iOS development with SwiftUI and Combine is presented here. It therefore puts an emphasis on software quality attributes — i.e., performance (render time, memory consumption, CPU productivity), scalability, and maintainability of the code — during migration of legacy applications built on top of UIKit to an architecture based on SwiftUI and Combine. Two real-world iOS applications of varying complexity were partially re-engineered under both architectures to compare practical results.
From Waterfall to Agile: A Case Study in Organizational Transformation and Hybrid Project Management Approaches
Ullas Das
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This paper examines how the Waterfall methods have changed to the Agile approach in project management, mainly discussing how these methods can be merged in a hybrid way. Using Waterfall and Agile as bases, we present a new process that maintains Waterfall’s planning structure and helps retain Agile’s ability to be flexible which improves both the stability and adaptability of projects. The paper points out the ways in which the hybrid model could better manage risks, please stakeholders and make projects more efficient.
AI-Enhanced Engineering Collaboration: Transforming Globalized Agile Teams with Cloud-Based SaaS SolutionsUllas Das
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The use of AI within SaaS platforms has greatly improved how worldwide Agile groups team up. The review examines how using AI in collaboration can help engineering teams from different parts of the world and time zones. This paper introduces the AI-Enhanced Engineering Collaboration Model (AI-EECM) based on an analysis of existing theories and models, including standard Agile development methods, cloud services and AI based SaaS tools. It connects predictive analysis, smart task dividing, better communication methods and ongoing learning to make project management more efficient and responsive.
Optimizing Supplier Portal in PeopleSoft for Enhanced Supplier Engagement and EfficiencyChandan Mishra
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Utilization of supplier portals in enterprise systems is an emerging organization's priority that aims at faster procurement, vendor satisfaction, and process automation. The review will look at the PeopleSoft Supplier Portal and the strategic value of the product to a company in supplier engagement, the architectural constraints it has, and the strategies to optimize the portal based on empirical experiences and best industry practices. A hypothetical model is presented, which describes modules of improvement in the areas of onboarding, workflow automation, document submission, and analytics.
The Role of Advanced Analytics in Financial Services TransformationLaxmi Vanam
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Advanced analytics is a key component of the financial services transformation and provides financial institutions with tools to exploit massive data flows for predictive intelligence, automation, and customer-oriented innovation. This paper reviews the use of advanced analytics in risk modelling, fraud operations, enhancing customer attraction and retention as well as improving operational efficiency across core financial functions. The Financial Analytics Value Enablement Model (FAVEM) is presented as a conceptual framework that addresses the difficulties financial organizations face with analytics adoption, including challenges related to explainability, regulatory considerations, and antiquated infrastructure.
AI-Driven Cloud Infrastructure: Advances in Kubernetes and Serverless ComputingMahi Ratan Reddy Deva
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Artificial Intelligence (AI) has been integrated into cloud infrastructure, making it revolutionizing modern computing by automating, scaling, and improving efficiency. The first of these is Kubernetes, and the second is serverless computing. Kubernetes, a container orchestration platform, benefits from AI-driven enhancements in workload scheduling, auto-scaling, and resource optimization. By combining AI-based predictive analytics with container deployment, overhead is reduced in terms of operational overhead as well as fault tolerance. However, serverless computing takes away the management of infrastructure, leaving the developers free to write application logic.
Intelligent Test Automation: A Hybrid LabVIEW–Python–GenAI Framework for High-Throughput IoT ValidationNikunj Gajera
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This paper introduces a novel hybrid test automation framework that integrates National Instruments LabVIEW and Python scripting to optimize the validation of analog and digital circuits [1]. The architecture addresses the rising complexity and time-to-market pressures in multi-product environments by enabling parallelized test execution and efficient resource management. The framework's core strength is its ability to leverage the distinct advantages of both LabVIEW and Python, creating a synergistic environment for test automation. Experimental validation shows a 40% reduction in the overall test cycle time compared to traditional sequential methods.
A Dynamic, Attribute-Based Access Control (ABAC) Model for Microservices and Cloud-Native Applications Integrated with
Traditional IGASunnykumar Kamani
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The rapid cloud-native adoption architecture defined by loosely coupled components (microservices) has fundamentally changed the enterprise IT landscapes. These dynamic, distributed systems require an equally dynamic and granular access control mechanism that cannot be provided traditionally. Though traditional Identity Governance and Administration (IGA) systems are very good at managing static roles, they do not relate to the contextual, real-time decisions needed in modern applications.
Pigment Dispersion Science in High-Speed Inkjet and Flexo InksJigarkumar Bhailalbhai Patel
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The physics of pigment dispersion is directly linked with the efficiency of the high-speed inkjet prints and flexographically (flexo) printing. The performance and desired chemical stability of pigments held in suspension by these inks become especially relevant as printing systems are strained to new speed systems, new specific resolutions, and to designs that are more sustainable. The article addresses physicochemical mechanisms, dispersion techniques, and applicable formulations of pigments in the mechanisms of stabilizing pigments in these new printing processes.
Advanced IAM Strategies for Securing Sensitive Data and Applications in Complex OrganizationsIlakiya Ulaganathan
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With distributed computing, hybrid cloud adoption, and global workforce trends, managing digital identities and accessing sensitive data has taken a central stage for complex organizations. IAM goes beyond traditional role assignment and is now a dynamic security framework that incorporates Zero Trust principles, risk-based authentication, and AI-based automation. The review looks at modern advanced IAM techniques and their importance for cyber risk avoidance, posture for compliance, and protection of sensitive data and applications.