Human factors significantly affect the productivity of AI-related underwriting systems, with trust, cognitive load, and quality of decision being the leading factors. The implementation of AI has made the data collection process automatic, improved the decision-making accuracy, and opened up avenues for sophisticated risk assessment.
For two decades, the atomic unit of e-commerce has been the keyword. However, as AI evolves from a tool that helps humans find products to an agent that buys them on our behalf, the keyword is no longer sufficient. This article examines the watershed moment of multimodal search—the transition where digital catalogs stop being static lists of text and become dynamic ecosystems that can "see" and "listen." We break down the physics of meaning behind vector embeddings, the battle between "build vs. buy" search strategies, and the rise of 3D spatial indexing.
The automotive industry is undergoing a paradigm shift driven by the exponential growth of data from connected vehicles and evolving customer expectations. This transformation introduces both opportunities and challenges, compelling manufacturers to adopt advanced AI technologies. Retrieval-Augmented Generation (RAG) emerges as a pivotal enabler in this context, offering capabilities that span product development, manufacturing optimization, predictive maintenance, and hyper-personalized in-vehicle experiences.
Sustainability has become a critical aspect of railway manufacturing engineering projects due to environmental concerns, regulatory requirements, and the need for long-term economic viability of large-scale infrastructure systems. Beyond strict regulations, innovative technologies, and stakeholder coordination, Germany is one of the examples of the progressive implementation of sustainability principles in the railroad industry. The paper provides a concept synthesis of the sustainable practices in the railway engineering project based on the literature in manufacturing engineering, railway systems, project management and sustainability research.
One of the challenges that has posed the greatest difficulty in the development process of full-stack applications today is the high level of user intent-invoked backend services, particularly as the level of difficulty of the application has been raised. Integration protocols that are default APIs in Java systems are likely to force programmers to directly couple front-end processes to the facilities at the back end. In this way, Java systems are also more expensive to create and slow.
The operational challenges experienced by healthcare systems worldwide due to increased patient volumes, shortages of personnel, and complex care processes. The predictive analytics is a new way of combating these inefficiencies through the use of data-driven models and workflow decisions. The paper examines the usability and limitations of predictive analytics in healthcare workflow optimization. It gathers evidence on the available literature that includes all varieties of models, implementation strategies and operational outcomes of patient flow management, emergency department capacity planning, staff scheduling, and resource allocation.
The cloud computing has become a significant component of the majority of the current digital infrastructures. But with its extensive usage has come several complicated security challenges which are difficult to address using the traditional models of depending on perimeters. Among the effective ways of addressing these threats is the concept of Zero Trust Architecture (ZTA), which is premised upon the idea of never trust, always verify. Simultaneously, it is possible to find more complex and unknown cyber threats in the dynamic cloud environment with great potential of AI and ML technologies.
Cloud computing, which makes use of shared, Internet-based computing resources, has emerged as a dominant model in software development in recent years. It makes the software development process easy and fast by offering the backbone to the applications. This paper examines the history, architectural principles, and current backend practices that are informing the modern web development, focusing especially on the .NET ecosystem, the MVC principles of architectural design, and API-based backend design.
The Customer Service workspace channels like SMS and webchat are a tough nut to crack to automate within the CRM systems. Mainly because of the unstructured, informal and context dependent nature of human language. Classical chatbots work based on the traditional rule based and key word driven workflows. They often fail with the real-world conversational variability leading to poor customer experiences and agent workload increase. The latest improvements in Natural Language Processing (NLP), especially with the large language models (LMs) fundamentally shifted how CRM systems interpret and respond to customer messages.
Identity and Access Management (IAM) is an important factor in ensuring secure and effective access control in cloud computing environments. This work presents a sequential machine-learning-based model to optimize IAM policies using a high-dimensional Cloud Access Control Parameter Management dataset. The paradigm incorporates systematic preprocessing of data, feature engineering, label encoding, feature selection using Boruta, feature scaling, and hybrid data balancing, 80: 20 train -test split and 5-fold cross-validation.
MySQL is an open-source relational database management system that is most popular and recognized by its reliability, flexibility, performance, as well as high security properties. With growing data-driven application use in the healthcare sectors, among others, such as finance, e-commerce, and cloud computing, MySQL database management becomes more of a best practice in terms of system upkeep, information quality, and efficiency. This paper provides an in-depth overview of MySQL database administration methods and best practices including its architecture, storage, transaction management, security, performance optimization, backup and recovery mechanisms, and high-availability solutions.
As urban complexity deepens and critical infrastructure needs around our cities become more demanding, it is paramount that resilient and real-time network serviceability becomes a centerpiece of how disruptive technologies are designed for the future. This review discusses the integration of Artificial Intelligence (AI), electronic Geographic Information Systems (eGIS), and streaming data pipelines and how they can reform network monitoring targeted in diagnostics and fail prediction. It systematically reviews AI models such as Random Forests, LSTM, and Graph Neural Networks (GNNs) used within geospatial structures to examine their performance with real-world datasets and simulations.
With the growing use of digital therapeutics (DTx) in behavioural health, there are serious challenges associated with regulatory compliance, data privacy and software security, particularly given sensitive patient data and the current development of global standards including HIPAA, GDPR and the Digital Personal Data Protection (DPDP) Act. The current DevOps practices, which are maximally agile delivery and scalable, do not involve any inherent mechanisms of active security enforcement and ongoing regulatory compliance. The paper presents the concept of DevSecOps, which is the expansion of DevOps that incorporates the concept of security and compliance into the software development life cycle, in advancing the safety, transparency, and reliability of behavioural health DTx platforms.
A Review of Human Factors in AI-Powered Underwriting Systems: Trust, Cognitive Load, and Decision Quality
Kirti Vedi
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Human factors significantly affect the productivity of AI-related underwriting systems, with trust, cognitive load, and quality of decision being the leading factors. The implementation of AI has made the data collection process automatic, improved the decision-making accuracy, and opened up avenues for sophisticated risk assessment.
Revolutionizing Online Shopping: The Power of Multimodal Search in E-CommerceNitin Patki
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For two decades, the atomic unit of e-commerce has been the keyword. However, as AI evolves from a tool that helps humans find products to an agent that buys them on our behalf, the keyword is no longer sufficient. This article examines the watershed moment of multimodal search—the transition where digital catalogs stop being static lists of text and become dynamic ecosystems that can "see" and "listen." We break down the physics of meaning behind vector embeddings, the battle between "build vs. buy" search strategies, and the rise of 3D spatial indexing.
Leveraging Retrieval-Augmented Generation (RAG) AI for Transforming Automotive Design, Manufacturing, and In-Vehicle
ExperiencesNaveen Kumar Bonagiri
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The automotive industry is undergoing a paradigm shift driven by the exponential growth of data from connected vehicles and evolving customer expectations. This transformation introduces both opportunities and challenges, compelling manufacturers to adopt advanced AI technologies. Retrieval-Augmented Generation (RAG) emerges as a pivotal enabler in this context, offering capabilities that span product development, manufacturing optimization, predictive maintenance, and hyper-personalized in-vehicle experiences.
Sustainability Integration in Railway Manufacturing Engineering Projects: A Conceptual ReviewAravindh Balan
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Sustainability has become a critical aspect of railway manufacturing engineering projects due to environmental concerns, regulatory requirements, and the need for long-term economic viability of large-scale infrastructure systems. Beyond strict regulations, innovative technologies, and stakeholder coordination, Germany is one of the examples of the progressive implementation of sustainability principles in the railroad industry. The paper provides a concept synthesis of the sustainable practices in the railway engineering project based on the literature in manufacturing engineering, railway systems, project management and sustainability research.
LLM-Enhanced Java APIs for Intent-Driven Backend Invocation in Full-Stack SystemsSohith Sri Ammineedu Yalamati
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One of the challenges that has posed the greatest difficulty in the development process of full-stack applications today is the high level of user intent-invoked backend services, particularly as the level of difficulty of the application has been raised. Integration protocols that are default APIs in Java systems are likely to force programmers to directly couple front-end processes to the facilities at the back end. In this way, Java systems are also more expensive to create and slow.
A Predictive Analytics Approach to Optimizing Workflow Efficiency in Healthcare SystemsSohan Manmeet Sethi
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The operational challenges experienced by healthcare systems worldwide due to increased patient volumes, shortages of personnel, and complex care processes. The predictive analytics is a new way of combating these inefficiencies through the use of data-driven models and workflow decisions. The paper examines the usability and limitations of predictive analytics in healthcare workflow optimization. It gathers evidence on the available literature that includes all varieties of models, implementation strategies and operational outcomes of patient flow management, emergency department capacity planning, staff scheduling, and resource allocation.
Advances AI-Enabled Identification of Threats within Zero-Trust Architectures for Secure Cloud Infrastructures: A
Comprehensive Survey Rajendra Prasad Sola
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The cloud computing has become a significant component of the majority of the current digital infrastructures. But with its extensive usage has come several complicated security challenges which are difficult to address using the traditional models of depending on perimeters. Among the effective ways of addressing these threats is the concept of Zero Trust Architecture (ZTA), which is premised upon the idea of never trust, always verify. Simultaneously, it is possible to find more complex and unknown cyber threats in the dynamic cloud environment with great potential of AI and ML technologies.
An Overview of MVC-Based and API-Centric Backend Architectures in .NET Ecosystems Rajeev Kallayil
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Cloud computing, which makes use of shared, Internet-based computing resources, has emerged as a dominant model in software development in recent years. It makes the software development process easy and fast by offering the backbone to the applications. This paper examines the history, architectural principles, and current backend practices that are informing the modern web development, focusing especially on the .NET ecosystem, the MVC principles of architectural design, and API-based backend design.
AI & NLP in CRM: How Large Language Models are Changing Customer Interactions in SMS & Webchat Krishna Chaithanya Vuppala
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The Customer Service workspace channels like SMS and webchat are a tough nut to crack to automate within the CRM systems. Mainly because of the unstructured, informal and context dependent nature of human language. Classical chatbots work based on the traditional rule based and key word driven workflows. They often fail with the real-world conversational variability leading to poor customer experiences and agent workload increase. The latest improvements in Natural Language Processing (NLP), especially with the large language models (LMs) fundamentally shifted how CRM systems interpret and respond to customer messages.
An Intelligent Machine Learning Framework for Optimizing Identity and Access Management (IAM) Policies in Cloud
InfrastructureJiwan Prakash Gupta
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Identity and Access Management (IAM) is an important factor in ensuring secure and effective access control in cloud computing environments. This work presents a sequential machine-learning-based model to optimize IAM policies using a high-dimensional Cloud Access Control Parameter Management dataset. The paradigm incorporates systematic preprocessing of data, feature engineering, label encoding, feature selection using Boruta, feature scaling, and hybrid data balancing, 80: 20 train -test split and 5-fold cross-validation.
A Survey of MySQL Database Administration Techniques and Best PracticesHari Babu Dama
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MySQL is an open-source relational database management system that is most popular and recognized by its reliability, flexibility, performance, as well as high security properties. With growing data-driven application use in the healthcare sectors, among others, such as finance, e-commerce, and cloud computing, MySQL database management becomes more of a best practice in terms of system upkeep, information quality, and efficiency. This paper provides an in-depth overview of MySQL database administration methods and best practices including its architecture, storage, transaction management, security, performance optimization, backup and recovery mechanisms, and high-availability solutions.
AI-Driven Network Serviceability Mapping Using eGIS and Streaming Data PipelineVikas Gupta
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As urban complexity deepens and critical infrastructure needs around our cities become more demanding, it is paramount that resilient and real-time network serviceability becomes a centerpiece of how disruptive technologies are designed for the future. This review discusses the integration of Artificial Intelligence (AI), electronic Geographic Information Systems (eGIS), and streaming data pipelines and how they can reform network monitoring targeted in diagnostics and fail prediction. It systematically reviews AI models such as Random Forests, LSTM, and Graph Neural Networks (GNNs) used within geospatial structures to examine their performance with real-world datasets and simulations.
The Role of DevSecOps in Enhancing Digital Therapeutics Platforms for Behavioural HealthSunjhla Handa
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With the growing use of digital therapeutics (DTx) in behavioural health, there are serious challenges associated with regulatory compliance, data privacy and software security, particularly given sensitive patient data and the current development of global standards including HIPAA, GDPR and the Digital Personal Data Protection (DPDP) Act. The current DevOps practices, which are maximally agile delivery and scalable, do not involve any inherent mechanisms of active security enforcement and ongoing regulatory compliance. The paper presents the concept of DevSecOps, which is the expansion of DevOps that incorporates the concept of security and compliance into the software development life cycle, in advancing the safety, transparency, and reliability of behavioural health DTx platforms.