The maritime fleet industry is undergoing a paradigm shift due to rapid advancements in digital technologies, automation, and artificial intelligence (AI). This paper presents an in-depth research into the interplay of AI-driven maritime logistics, focusing on port management, advanced operations automation, and customer relationship management (CRM) integration for optimized performance and efficiency.
The proliferation of the Internet of Things (IoT) has brought numerous benefits, but it has also raised concerns about security and efficiency. The interconnected nature of IoT devices and networks exposes them to various vulnerabilities and risks. To address these challenges, cloud computing and machine learning have emerged as powerful technologies with the potential to enhance IoT security and efficiency.
In the era of digital transformation, customer relationship management (CRM) has become a key component of business success. Traditional CRM systems, however, often fail to provide the level of personalization and responsiveness required to meet customers' ever-evolving expectations.
Web-based media have gotten more consideration. Twitter is one of the web-based media that is acquiring fame. Twitter offers associations a quick and viable approach to dissect clients' points of view toward the basic to accomplishment in the commercial center.
In this examination, a Bridge wellbeing checking framework utilizing IoT is created utilizing remote innovation. The assistance of progression in sensor innovation has brought the computerized continuous extension wellbeing checking framework.
Disaster Management application can be utilized as a client manual for think about catastrophic events, a calamity the executive's life cycle, first aid pack. Debacle causes different levels of impact and can make casualties needing critical assistance for food, wellbeing, or help.
Geometric mean filter is commonly used in image processing application to remove Gaussian noise. In filter stage requires more number addition and multiplication process. Pruning is an approximation technique used to achieve a low power processing.
In this paper, the fundamental work is to control traffic density in significant urban communities which has been a mainstream research subject among researchers and modern experts.
In the rapidly evolving world of healthcare, the integration of machine learning and artificial intelligence (AI) has marked a transformative era, especially in the realm of disease prediction and prevention. This movement is not just about technological advancement; it’s about a profound shift towards a more data-driven approach in medicine that promises to enhance patient outcomes, reduce costs, and improve overall health system efficiency.
In today's cloud-driven world, managing costs while maintaining robust and scalable Kubernetes deployments is a critical challenge for organizations. This article delves into practical and effective cost optimization strategies for Kubernetes deployments in cloud environments. We explore the use of spot instances, a cost-efficient option for running non-critical workloads at a fraction of the price of on-demand instances.
In this study, we examine several performance indicators of heat pumps used in cold regions, especially the amount of COP and SPF given. Heating pumps are gradually gaining a reputation as one of the most efficient solutions that can replace traditional heating equipment. That said, their benefits are yet to be realized where there are extremely unfavorable weather conditions during winter.
With the help of various sources of unstructured and structured data like system and application monitoring streams, open-source knowledge capture, and on-demand simulation output, exascale data environments are quickly approaching. With storage prices so low, the challenge today lies in turning massive data repositories into useful information. Any company, organisation, or agency can use log data as a definitive recording of what's happening, and it's frequently an underutilised resource for troubleshooting and supporting larger business goals.
The integration of Artificial Intelligence (AI) into wireless networks represents a transformative leap towards achieving ultra-connectivity in the 21st century. This paper explores the groundbreaking advancements driven by AI technologies in the realm of wireless network management, highlighting their profound impact on network performance, scalability, and efficiency. Unlike traditional network management systems, AI-powered solutions leverage machine learning algorithms and predictive analytics to proactively manage network resources, enhance fault detection and resolution, and optimize traffic flow in real-time.
The case of retrofitting energy-efficient HVAC in historical buildings is rather specific in terms of challenges as well as potential benefits. This paper seeks to uncover the fine line between the preservation of the structural and aesthetic nature of heritage structures and the necessary introduction of contemporary HVAC technologies that work in harmony with the promotion of sustainability and energy efficiency. It is not enough to retain the looks and cultural message of historical constructions; circulation and utilisability of the constructions in today’s world should also be maintained.
IT is evolving at an incredible pace, and this has greatly changed the perimeter of the network that is distributed. As such, the traditional concepts of security are not enough. Today, port-based firewalls have become virtually useless because, as more and more businesses use analytics, cloud computing, and other forms of automation to speed up their progress in creating new products and services to meet the public’s demand, smart cyber threats are being created to exploit the gaps left behind by traditional security tools.
Digital twins are essentially detailed computer models of respective physical systems, and when it comes to DevOps, these digital twins provide a highly effective environment for deployment and infrastructure changes, as well as software tests. Such virtual models make it possible for an organization to test and optimize the systems in ways that are safe from failing, thus improving the quality and effectiveness of the management and use of software development and operations. In this paper, I describe the application of the digital twin in DevOps and give a comprehensive analysis of how it can be used in the improvement of DevOps concerning the elements involved.
Accurate forecasting of home prices is crucial for all stakeholders in the real estate market, including buyers, sellers, and investors. This study examines the efficacy of various machine learning algorithms in predicting house prices by analyzing large datasets that encompass diverse property attributes such as size, location, and bedroom count. Linear Regression is a baseline among the models investigated due to its simplicity and interpretability. Random Forest, known for its capability to model complex, non-linear relationships between features, provides a robust ensemble approach. Enhancing prediction accuracy further, XGBoost, a gradient-boosting technique, demonstrates superior performance.
This comprehensive research paper explores the intricate landscape of market expansion for Web3 and EdTech start-ups in the Asia-Pacific (APAC) region. The study investigates the convergence of block chain technology and educational innovation, analysing market trends, regulatory frameworks, and cultural nuances across diverse APAC economies. By examining the unique challenges and opportunities presented by this dynamic region, the research aims to provide actionable insights for start-ups, investors, and policymakers navigating the complex intersection of Web3 and EdTech in APAC's rapidly evolving digital ecosystem.
Managing costs in cloud-based financial data lakes is crucial for companies aiming to balance performance with budget constraints. In an era where data is a key asset, financial institutions must navigate the complexities of storing and processing vast amounts of information without overspending. This article delves into practical techniques for cost optimization in cloud-based financial data lakes, providing real-world case studies to illustrate successful implementations. We begin by exploring foundational strategies such as choosing the right cloud provider and leveraging cost-effective storage solutions like tiered storage and data compression.
With the increase in information available, especially due to the embrace of the use of technology in the current generation, there has been an alteration in the ways data is used in businesses and organizations. It has been noted that real-time data integration has become highly valuable or critical in areas that require real-time or near real-time decision-making, including the finance, e-commerce, health care and manufacturing industries. In this paper, we are going to discuss about many tools and techniques as well as several best practices related to real-time data integration.
In today’s fiercely competitive e-commerce landscape, customer retention has become as crucial as customer acquisition. While many businesses focus on attracting new customers, the true challenge lies in keeping them engaged and loyal. This is where innovative Customer Relationship Management (CRM) strategies come into play. By leveraging cutting-edge technologies and personalized approaches, e-commerce businesses can build deeper connections with their customers, enhance their shopping experience, and foster long-term loyalty. This article explores various innovative CRM strategies that e-commerce platforms can implement to boost customer retention.
Global warming is considered one of the main factors that affect the insurance business and calls for new Creative and Effective Insurance Risk Management. Specified climate-related events, including hurricanes, floods, and wildfires, have upgraded the traditional underwriting criteria and claims management consequently, due to the rising frequency and severity of numerous natural dangers. Paid losses have risen sharply, and this has underlined the need for the insurers to advance their methods of assessment.
Authentication and authorization are crucial components in the security of internal applications within software. Internal applications in software companies play a crucial role in facilitating efficient operations, data management, and collaboration among employees. However, these applications often deal with sensitive information and require robust security measures to prevent unauthorized access and misuse. This paper explores the challenges and best practices in implementing effective authentication and authorization mechanisms for internal applications in software companies.
Online signature verification systems play a pivotal role in ensuring the authenticity of users in digital transactions. With the surge in real-time processing demands, traditional systems often fall short in handling dynamic, large-scale, and distributed signature data. This paper introduces a novel framework leveraging event-driven architectures (EDAs) to enhance the responsiveness, scalability, and reliability of signature verification systems. By integrating principles of EDAs, microservices, and distributed computing, this approach ensures real-time event processing, efficient data orchestration, and fault tolerance.
Distributed tracing and performance optimization are two important factors required to keep microservices-based architecture flexible and fault-tolerant. However, as the adoption of microservices grows within organizations, monitoring and dealing with latency, issues, and inter-service coupling arises. This paper discusses the approach to doing distributed tracing or distributed logging in a system with one or more microservices and as explores ways to improve the efficiency of the same. We use Open Telemetry for tracing efforts, Kubernetes for scalable deployment, and machine learning for anomaly detection.
The transition to mass work-from-home (WFH) environments has exposed enterprise codebases to heightened risks of social engineering attacks, including phishing, impersonation, pretexting, and baiting. These techniques exploit human vulnerabilities, targeting remote developers to gain unauthorized access to sensitive repositories, steal credentials, or manipulate source code. This paper explores the specific risks posed by these social engineering tactics in distributed work settings and their implications for codebase security.
This study investigates the effectiveness of AI-driven solutions in overcoming the challenges of automated testing within Salesforce Lightning environments, characterized by dynamic content and frequent updates. The research aimed to evaluate how AI technologies such as machine learning, natural language processing, and computer vision can enhance testing efficiency and accuracy compared to traditional methods. Using simulated Salesforce Lightning scenarios, the study compared the performance of AI-driven and conventional testing approaches across key metrics including defect detection rates, test execution time, and test coverage.
In the manufacturing sector, the increasing complexity of operations and competitive pressures demand a shift toward data-driven decision-making (DDDM). By integrating advanced analytics, real-time data monitoring, and predictive modeling, manufacturers can significantly enhance productivity, reduce costs, and improve product quality. This paper explores the transformative impact of DDDM on manufacturing, highlighting its applications in predictive maintenance, supply chain optimization, and quality control. It also examines challenges such as data silos, lack of governance, and workforce adaptability, offering practical solutions and a roadmap for successful implementation.
Legacy systems are often plagued by code smells - indicators of poor design and implementation choices - that compromise software quality and increase technical debt. Addressing these issues is essential for ensuring system maintainability and long-term health. Traditional static code analysis tools, while widely used, are prone to generating false positives and require considerable manual effort, making them less suitable for large, complex codebases.
Organizations are migrating their policy management systems from the ground to the cloud, changing how they manage, secure and scale their operations. This paper analyses how Amazon Web Services (AWS) and Snowflake support robust and efficient cloud-based policy management solutions. This marriage of sort of AWS, which has an almost panoply of cloud services, and Snowflake, which is very well known for its data warehousing and analytics capabilities, makes sense because it is an enterprise in which you will want to modernize your policy management. Ways to explore Amazon’s infrastructural offerings, such as IAM (Identity and Access Management) and Security Hub, are also discussed as key components in the path to governance and compliance in a cloud environment.
The financial industry is one of the most important industries in the US, and it acts as a key driver of capital and credit formation. However, it has to be noted that banks enjoy a softened legal environment; that is, there are numerous rules and regulations at the national and international levels intended to provide a stiff structure of financial stability, consumer protection, and the avoidance of systemic risk. The requisite component is the preparation of regulatory reports, which are filed with authorities such as the Federal Reserve, OCC and FDIC. These reports highlight the strengths, weaknesses, opportunities, and threats that revolve around banking institutions' financial health and operations risk.
This paper compares the North American Electric Reliability Corporation Critical Infrastructure Protection (NERC-CIP) and the National Institute of Standards and Technology (NIST) cybersecurity frameworks, analysing their strengths, weaknesses, and implementation challenges. While NERC-CIP focuses on mandatory requirements for the bulk electric system, NIST provides a voluntary and adaptable framework for broader cybersecurity risk management. The study highlights the complementary nature of both frameworks and proposes a comprehensive approach to building cyber risk-free infrastructure, incorporating elements like risk-based prioritization, defense-in-depth strategies, continuous monitoring, and collaboration.
This paper discusses the automation of design approval workflows in the manufacturing sector with Teamcenter, a comprehensive digital lifecycle management system, aimed at involving stakeholders and improving operational efficiency. Teamcenter is a management tool that handles both product and production information through the whole product lifecycle, thus allowing for real-time collaboration among global teams and stakeholders. This paper focuses on the automation of approval processes, the advantages of digital workflows, and handlers in integrating business decisions. By digitizing the workflows, manufacturers will be able to improve process management, reduce costs, minimize errors, and speed up time-to-market.
Interplay of AI-Driven Maritime Logistics: An In-Depth Research into Port Management, Advanced Operations Automation, and
CRM Integration for Optimized Performance and EfficiencySharda Kumari
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The maritime fleet industry is undergoing a paradigm shift due to rapid advancements in digital technologies, automation, and artificial intelligence (AI). This paper presents an in-depth research into the interplay of AI-driven maritime logistics, focusing on port management, advanced operations automation, and customer relationship management (CRM) integration for optimized performance and efficiency.
Enhancing IoT Security and Efficiency: The Role of Cloud Computing and Machine LearningSatyanarayan Kanungo
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The proliferation of the Internet of Things (IoT) has brought numerous benefits, but it has also raised concerns about security and efficiency. The interconnected nature of IoT devices and networks exposes them to various vulnerabilities and risks. To address these challenges, cloud computing and machine learning have emerged as powerful technologies with the potential to enhance IoT security and efficiency.
Context-Aware AI-Driven CRM: Enhancing Customer Journeys Through Real-Time Personalization and
Predictive AnalyticsSharda Kumari
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In the era of digital transformation, customer relationship management (CRM) has become a key component of business success. Traditional CRM systems, however, often fail to provide the level of personalization and responsiveness required to meet customers' ever-evolving expectations.
Twitter Sentimental AnalysisJohn K.Victor, Ilo stanely Uzochukwu, Dr.N.Egu
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Web-based media have gotten more consideration. Twitter is one of the web-based media that is acquiring fame. Twitter offers associations a quick and viable approach to dissect clients' points of view toward the basic to accomplishment in the commercial center.
Bridge Safety Monitoring System Using IOTMohammed Mehdi Rashidi, Mohammed Yousuf, Dr. Mubarak Jawahar Ali Khan
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In this examination, a Bridge wellbeing checking framework utilizing IoT is created utilizing remote innovation. The assistance of progression in sensor innovation has brought the computerized continuous extension wellbeing checking framework.
Raising Hand Disaster Management Mobile ApplicationNirmal Kumar, Dr.Ram Sarvesh, Dr.S.Hari Shanker
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Disaster Management application can be utilized as a client manual for think about catastrophic events, a calamity the executive's life cycle, first aid pack. Debacle causes different levels of impact and can make casualties needing critical assistance for food, wellbeing, or help.
Low Power Design of Geometric Mean Filter Using GWO PruningDr. B. Sakthivel
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Geometric mean filter is commonly used in image processing application to remove Gaussian noise. In filter stage requires more number addition and multiplication process. Pruning is an approximation technique used to achieve a low power processing.
Traffic Density Estimation Based On Video ProcessingEva Maria, Sidhin Thomas, Dr.Arun Kumar
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In this paper, the fundamental work is to control traffic density in significant urban communities which has been a mainstream research subject among researchers and modern experts.
Data-Driven Healthcare: Trends in Machine Learning and AI for Disease Prediction and PreventionSarika Mulukuntla,
Mounika Gaddam
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In the rapidly evolving world of healthcare, the integration of machine learning and artificial intelligence (AI) has marked a transformative era, especially in the realm of disease prediction and prevention. This movement is not just about technological advancement; it’s about a profound shift towards a more data-driven approach in medicine that promises to enhance patient outcomes, reduce costs, and improve overall health system efficiency.
Cost Optimization Strategies for Kubernetes Deployments in Cloud EnvironmentsAnirudh Mustyala, Sumanth Tatineni
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In today's cloud-driven world, managing costs while maintaining robust and scalable Kubernetes deployments is a critical challenge for organizations. This article delves into practical and effective cost optimization strategies for Kubernetes deployments in cloud environments. We explore the use of spot instances, a cost-efficient option for running non-critical workloads at a fraction of the price of on-demand instances.
Assessing the Efficiency of Heat Pumps in Cold Climates: A Study Focused on Performance MetricsAnkitkumar Tejani
Download
In this study, we examine several performance indicators of heat pumps used in cold regions, especially the amount of COP and SPF given. Heating pumps are gradually gaining a reputation as one of the most efficient solutions that can replace traditional heating equipment. That said, their benefits are yet to be realized where there are extremely unfavorable weather conditions during winter.
Utilizing Splunk for Proactive Issue Resolution in Full Stack Development ProjectsRanjit Kumar Gupta, Sagar Shukla,
Anaswara Thekkan Rajan, Sneha Aravind
Download
With the help of various sources of unstructured and structured data like system and application monitoring streams, open-source knowledge capture, and on-demand simulation output, exascale data environments are quickly approaching. With storage prices so low, the challenge today lies in turning massive data repositories into useful information. Any company, organisation, or agency can use log data as a definitive recording of what's happening, and it's frequently an underutilised resource for troubleshooting and supporting larger business goals.
Wireless Network Powered by AI: A Leap towards Ultra-ConnectivityVikram Nattamai Sankaran, Dr. N. Rajkumar
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The integration of Artificial Intelligence (AI) into wireless networks represents a transformative leap towards achieving ultra-connectivity in the 21st century. This paper explores the groundbreaking advancements driven by AI technologies in the realm of wireless network management, highlighting their profound impact on network performance, scalability, and efficiency. Unlike traditional network management systems, AI-powered solutions leverage machine learning algorithms and predictive analytics to proactively manage network resources, enhance fault detection and resolution, and optimize traffic flow in real-time.
Integrating Energy-Efficient HVAC Systems into Historical Buildings: Challenges and Solutions for Balancing Preservation
and ModernizationAnkitkumar Tejani
Download
The case of retrofitting energy-efficient HVAC in historical buildings is rather specific in terms of challenges as well as potential benefits. This paper seeks to uncover the fine line between the preservation of the structural and aesthetic nature of heritage structures and the necessary introduction of contemporary HVAC technologies that work in harmony with the promotion of sustainability and energy efficiency. It is not enough to retain the looks and cultural message of historical constructions; circulation and utilisability of the constructions in today’s world should also be maintained.
Next-Generation Firewall in the Cloud: Advanced Firewall Solutions to the CloudHimanshu Sharma
Download
IT is evolving at an incredible pace, and this has greatly changed the perimeter of the network that is distributed. As such, the traditional concepts of security are not enough. Today, port-based firewalls have become virtually useless because, as more and more businesses use analytics, cloud computing, and other forms of automation to speed up their progress in creating new products and services to meet the public’s demand, smart cyber threats are being created to exploit the gaps left behind by traditional security tools.
Utilizing Digital Twins in DevOpsYogesh Ramaswamy
Download
Digital twins are essentially detailed computer models of respective physical systems, and when it comes to DevOps, these digital twins provide a highly effective environment for deployment and infrastructure changes, as well as software tests. Such virtual models make it possible for an organization to test and optimize the systems in ways that are safe from failing, thus improving the quality and effectiveness of the management and use of software development and operations. In this paper, I describe the application of the digital twin in DevOps and give a comprehensive analysis of how it can be used in the improvement of DevOps concerning the elements involved.
Forecasting Home Prices Employing Machine Learning Algorithms: XGBoost, Random Forest, and Linear RegressionMadan
Mohan Tito Ayyalasomayajula, Santhosh Bussa, Sailaja Ayyalasomayajula
Download
Accurate forecasting of home prices is crucial for all stakeholders in the real estate market, including buyers, sellers, and investors. This study examines the efficacy of various machine learning algorithms in predicting house prices by analyzing large datasets that encompass diverse property attributes such as size, location, and bedroom count. Linear Regression is a baseline among the models investigated due to its simplicity and interpretability. Random Forest, known for its capability to model complex, non-linear relationships between features, provides a robust ensemble approach. Enhancing prediction accuracy further, XGBoost, a gradient-boosting technique, demonstrates superior performance.
Web3 and Edtech Startups’ Market Expansion in APACAnkur Mehra
Download
This comprehensive research paper explores the intricate landscape of market expansion for Web3 and EdTech start-ups in the Asia-Pacific (APAC) region. The study investigates the convergence of block chain technology and educational innovation, analysing market trends, regulatory frameworks, and cultural nuances across diverse APAC economies. By examining the unique challenges and opportunities presented by this dynamic region, the research aims to provide actionable insights for start-ups, investors, and policymakers navigating the complex intersection of Web3 and EdTech in APAC's rapidly evolving digital ecosystem.
Cost Optimization in Cloud-Based Financial Data Lakes: Techniques and Case StudiesAbhilash Katari, Dinesh Kalla
Download
Managing costs in cloud-based financial data lakes is crucial for companies aiming to balance performance with budget constraints. In an era where data is a key asset, financial institutions must navigate the complexities of storing and processing vast amounts of information without overspending. This article delves into practical techniques for cost optimization in cloud-based financial data lakes, providing real-world case studies to illustrate successful implementations. We begin by exploring foundational strategies such as choosing the right cloud provider and leveraging cost-effective storage solutions like tiered storage and data compression.
Real-Time Data Integration: Tools, Techniques, and Best PracticesSantosh Kumar Singu
Download
With the increase in information available, especially due to the embrace of the use of technology in the current generation, there has been an alteration in the ways data is used in businesses and organizations. It has been noted that real-time data integration has become highly valuable or critical in areas that require real-time or near real-time decision-making, including the finance, e-commerce, health care and manufacturing industries. In this paper, we are going to discuss about many tools and techniques as well as several best practices related to real-time data integration.
Innovative CRM Strategies for Customer Retention in E-CommerceVenkat Raviteja Boppana
Download
In today’s fiercely competitive e-commerce landscape, customer retention has become as crucial as customer acquisition. While many businesses focus on attracting new customers, the true challenge lies in keeping them engaged and loyal. This is where innovative Customer Relationship Management (CRM) strategies come into play. By leveraging cutting-edge technologies and personalized approaches, e-commerce businesses can build deeper connections with their customers, enhance their shopping experience, and foster long-term loyalty. This article explores various innovative CRM strategies that e-commerce platforms can implement to boost customer retention.
Climate Change and Insurance: Using Predictive Analytics to Navigate Emerging RisksDevidas Kanchetti
Download
Global warming is considered one of the main factors that affect the insurance business and calls for new Creative and Effective Insurance Risk Management. Specified climate-related events, including hurricanes, floods, and wildfires, have upgraded the traditional underwriting criteria and claims management consequently, due to the rising frequency and severity of numerous natural dangers. Paid losses have risen sharply, and this has underlined the need for the insurers to advance their methods of assessment.
Authentication and Authorization of Internal Applications in Software CompaniesSaidaiah Yechuri
Download
Authentication and authorization are crucial components in the security of internal applications within software. Internal applications in software companies play a crucial role in facilitating efficient operations, data management, and collaboration among employees. However, these applications often deal with sensitive information and require robust security measures to prevent unauthorized access and misuse. This paper explores the challenges and best practices in implementing effective authentication and authorization mechanisms for internal applications in software companies.
Enhancing Online Signature Verification Systems through Event-Driven ArchitecturesManoj Chavan
Download
Online signature verification systems play a pivotal role in ensuring the authenticity of users in digital transactions. With the surge in real-time processing demands, traditional systems often fall short in handling dynamic, large-scale, and distributed signature data. This paper introduces a novel framework leveraging event-driven architectures (EDAs) to enhance the responsiveness, scalability, and reliability of signature verification systems. By integrating principles of EDAs, microservices, and distributed computing, this approach ensures real-time event processing, efficient data orchestration, and fault tolerance.
Scalable Distributed Tracing and Performance Optimization in MicroservicesAbhishek Gupta
Download
Distributed tracing and performance optimization are two important factors required to keep microservices-based architecture flexible and fault-tolerant. However, as the adoption of microservices grows within organizations, monitoring and dealing with latency, issues, and inter-service coupling arises. This paper discusses the approach to doing distributed tracing or distributed logging in a system with one or more microservices and as explores ways to improve the efficiency of the same. We use Open Telemetry for tracing efforts, Kubernetes for scalable deployment, and machine learning for anomaly detection.
Securing Codebases in the Era of Mass Work-From-Home: Mitigating Social Engineering Risks such as Phishing, Impersonation,
Pretexting, and BaitingMithilesh Ramaswamy
Download
The transition to mass work-from-home (WFH) environments has exposed enterprise codebases to heightened risks of social engineering attacks, including phishing, impersonation, pretexting, and baiting. These techniques exploit human vulnerabilities, targeting remote developers to gain unauthorized access to sensitive repositories, steal credentials, or manipulate source code. This paper explores the specific risks posed by these social engineering tactics in distributed work settings and their implications for codebase security.
Overcoming Challenges in Salesforce Lightning Testing with AI SolutionsNagaraj Mandaloju, Vinod kumar Karne, Noone Srinivas,
Siddhartha Varma Nadimpalli
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This study investigates the effectiveness of AI-driven solutions in overcoming the challenges of automated testing within Salesforce Lightning environments, characterized by dynamic content and frequent updates. The research aimed to evaluate how AI technologies such as machine learning, natural language processing, and computer vision can enhance testing efficiency and accuracy compared to traditional methods. Using simulated Salesforce Lightning scenarios, the study compared the performance of AI-driven and conventional testing approaches across key metrics including defect detection rates, test execution time, and test coverage.
Empowering Data-Driven Decision Making In ManufacturingSrujana Manigonda
Download
In the manufacturing sector, the increasing complexity of operations and competitive pressures demand a shift toward data-driven decision-making (DDDM). By integrating advanced analytics, real-time data monitoring, and predictive modeling, manufacturers can significantly enhance productivity, reduce costs, and improve product quality. This paper explores the transformative impact of DDDM on manufacturing, highlighting its applications in predictive maintenance, supply chain optimization, and quality control. It also examines challenges such as data silos, lack of governance, and workforce adaptability, offering practical solutions and a roadmap for successful implementation.
Improving Legacy Software Quality through AI-Driven Code Smell DetectionAbhinav Balasubramanian
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Legacy systems are often plagued by code smells - indicators of poor design and implementation choices - that compromise software quality and increase technical debt. Addressing these issues is essential for ensuring system maintainability and long-term health. Traditional static code analysis tools, while widely used, are prone to generating false positives and require considerable manual effort, making them less suitable for large, complex codebases.
Policy Center to the Cloud: An Analysis of AWS and Snowflake’s Role in Cloud-Based Policy Management Solutions
Mr. Sateesh Reddy Adavelli
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Organizations are migrating their policy management systems from the ground to the cloud, changing how they manage, secure and scale their operations. This paper analyses how Amazon Web Services (AWS) and Snowflake support robust and efficient cloud-based policy management solutions. This marriage of sort of AWS, which has an almost panoply of cloud services, and Snowflake, which is very well known for its data warehousing and analytics capabilities, makes sense because it is an enterprise in which you will want to modernize your policy management. Ways to explore Amazon’s infrastructural offerings, such as IAM (Identity and Access Management) and Security Hub, are also discussed as key components in the path to governance and compliance in a cloud environment.
Role of Regulation Report in US Banks and How IT Will Help Accomplish ItSanjeev Prakash
Download
The financial industry is one of the most important industries in the US, and it acts as a key driver of capital and credit formation. However, it has to be noted that banks enjoy a softened legal environment; that is, there are numerous rules and regulations at the national and international levels intended to provide a stiff structure of financial stability, consumer protection, and the avoidance of systemic risk. The requisite component is the preparation of regulatory reports, which are filed with authorities such as the Federal Reserve, OCC and FDIC. These reports highlight the strengths, weaknesses, opportunities, and threats that revolve around banking institutions' financial health and operations risk.
A Comparative Study between NERC-CIP and NIST Compliance- Defining the Critical Framework for Building Cyberrisk Free
InfrastructureSuchismita Chatterjee
Download
This paper compares the North American Electric Reliability Corporation Critical Infrastructure Protection (NERC-CIP) and the National Institute of Standards and Technology (NIST) cybersecurity frameworks, analysing their strengths, weaknesses, and implementation challenges. While NERC-CIP focuses on mandatory requirements for the bulk electric system, NIST provides a voluntary and adaptable framework for broader cybersecurity risk management. The study highlights the complementary nature of both frameworks and proposes a comprehensive approach to building cyber risk-free infrastructure, incorporating elements like risk-based prioritization, defense-in-depth strategies, continuous monitoring, and collaboration.
Streamlining Stakeholder Engagement: Automating Design Approval Workflows in the Manufacturing Sector
Saranya Balasubramaniyan
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This paper discusses the automation of design approval workflows in the manufacturing sector with Teamcenter, a comprehensive digital lifecycle management system, aimed at involving stakeholders and improving operational efficiency. Teamcenter is a management tool that handles both product and production information through the whole product lifecycle, thus allowing for real-time collaboration among global teams and stakeholders. This paper focuses on the automation of approval processes, the advantages of digital workflows, and handlers in integrating business decisions. By digitizing the workflows, manufacturers will be able to improve process management, reduce costs, minimize errors, and speed up time-to-market.