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.
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
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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
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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
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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
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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
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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
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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.