Wireless sensor network used as a main element in today world. The sensor network transfers sensed data wireless to the other nodes in the presence of attackers.
Web applications are broadly used in nowadays. The demand of e-commerce websites are also increase today and it fully depends on cash exchange services like on-line banking, e-shopping, on-line charge installment, Currency exchange, and more.
Straight-line drawing calculations depend on steady techniques, Inincremental allotted line begins with a straight point then, at that point, some fixed incrementable is added to the ongoing point to get the following point on the web and some are proceeded with all as far as it goes.
As the frequency of crimes, assaults on the public, and thefts worldwide has increased significantly, general public safety is now a crucial aspect. In such circumstances, we must consider the public's safety precautions.
Many internet users now utilise social media platforms to discuss new ideas, learn about the most recent developments, and exchange the most recent updates internationally from one region to another.
In today's fast-paced digital landscape, managing high-volume data processing is a critical challenge for many organizations. Kubernetes, an open-source container orchestration platform, has emerged as a powerful solution for automating scaling and load balancing, ensuring that applications remain performant and reliable under heavy loads. This abstract explores the capabilities of Kubernetes in handling large-scale data processing tasks, focusing on its automated scaling and load balancing features.
The drive towards sustainable development has ensured that net-zero energy buildings NZEBs have become one of the elements of design in the current world. These buildings generate the amount of energy they use in a year, often by using renewable sources of power on the buildings’ own premises. HVAC systems are systems of balance in this sense because they bear the highest percentage of energy consumption in most buildings.
The hospitality industry is facing increasing demands for personalized and efficient customer service, driven by the rise of digital technologies and evolving customer expectations. Chatbots have emerged as a promising solution to address these challenges, offering the potential to enhance customer experiences, streamline operations, and improve service delivery. This paper presents a comprehensive framework for designing an enterprise-grade, cloud-native chatbot solution for the hospitality industry, leveraging the capabilities of Azure QnA Maker and Azure LUIS.
In the fast-paced world of financial services, maintaining accurate, consistent, and historical data is crucial. Delta Lake, an open-source storage layer, brings robust data versioning and time travel capabilities that significantly enhance data management for financial applications. This paper explores how Delta Lake's features can be implemented to address common challenges in the financial sector, such as regulatory compliance, auditing and accurate historical data analysis. Data versioning in Delta Lake ensures that every change to the data is tracked, enabling financial institutions to maintain a complete history of all transactions and modifications.
ETL stands for Extract, Transform, and load, is a fundamental process in the operation of data warehousing and business intelligence. It refers to a process whereby data is pulled from different sources and is transformed and then uploaded in a data warehouse. Some of the specific justification for automating the ETL process includes the following; Organizations dealing with large and complex data need to have it automated in order to ensure efficiency, scalability and accuracy of the process. This article goes deeper into understanding the tools and technologies employed in automating the ETL processes, and the major ones include Apache Nifi, Talend Informatica and others.
Data science has greatly impacted insurance and has enabled insurance companies to handle risk and fraud and manage individual attention. Nevertheless, insurance businesses using innovative technology such as machine learning and artificial intelligence (AI) raise ethical privacy, fairness, and transparency issues. This paper aims to discuss the ethical issues concerning data science in insurance, emphasizing how innovation can be achieved without compromising the customer's rights to privacy and fairness in decision-making. Insurance companies depend on personal data to issue premiums, assess claims and decide on coverage.
As organizations grow and expand their software delivery pipelines, scaling DevOps practices becomes essential to maintain agility and efficiency. However, managing large and distributed teams introduces complex challenges that impact collaboration, tool alignment, communication, and overall productivity. These challenges stem from differences in time zones, cultural variances, fragmented tooling choices, and difficulties in managing visibility across geographically dispersed teams. This paper explores the critical challenges associated with scaling DevOps across distributed teams and offers solutions such as standardizing toolchains, adopting automation, enhancing communication channels, and fostering cultural alignment.
This paper addresses the challenge of reliable and cost-efficient event processing at scale, a critical requirement for growing companies. Traditional stateless processing approaches often introduce latency and compromise reliability. We propose a solution based on stateful processing and in-memory caching to overcome these limitations. Our approach leverages stateful processing to ensure reliable event handling and reduce latency. Furthermore, by utilizing in-memory caching, we minimize the cost associated with processing large volumes of events. The paper provides a detailed analysis of our proposed solution, demonstrating its effectiveness in achieving both reliability and cost efficiency for large-scale event processing.
Serverless computing has changed the cloud computing paradigm, where developers do not have to worry about where the code is running or any access to the server. Although it is entirely different from infrastructure as a Service (IaaS) or Platform as a Service (PaaS), serverless offers flexibility through the dynamic nature of the application’s usage. This implies that resources are committed, based on certain event occurrences, dynamically, and so both cost and value are optimized. Unlike the traditional models where one would need to over-provision or spend time and effort to control the idle resources as costs are billed on the basis of the actual time spent executing the functions, serverless computing is therefore fitting for solutions with unpredictable usage and demand.
This study investigates the integration of artificial intelligence (AI) and machine learning (ML) into Salesforce development to optimize code and configuration processes. The primary purpose was to evaluate how AI-powered recommendation engines enhance development efficiency, code quality, and user satisfaction. Using a combination of simulated data and empirical analysis, the study developed an AI recommendation engine and assessed its impact on key performance metrics including development speed, error rates, and customization accuracy.
An Effective Malware Detection Algorithm for WSNShamsuddin Ali Akbari A J, Mohammed Ali Hussian
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Wireless sensor network used as a main element in today world. The sensor network transfers sensed data wireless to the other nodes in the presence of attackers.
SQL Injection Attack Detection in WebsitesV. Saranya, Havisha Monal. A
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Web applications are broadly used in nowadays. The demand of e-commerce websites are also increase today and it fully depends on cash exchange services like on-line banking, e-shopping, on-line charge installment, Currency exchange, and more.
Line Drawing Algorithms in Computer GraphicsM. Sangeetha, S. Amaresan
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Straight-line drawing calculations depend on steady techniques, Inincremental allotted line begins with a straight point then, at that point, some fixed incrementable is added to the ongoing point to get the following point on the web and some are proceeded with all as far as it goes.
A Practical Method for Person Tracking and Alerting System in Risky SituationsP.Gowtham, Maharaj Manohar
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As the frequency of crimes, assaults on the public, and thefts worldwide has increased significantly, general public safety is now a crucial aspect. In such circumstances, we must consider the public's safety precautions.
How to Spot and Stop Social Media Bullying CommunicationMohammed Zahir Ali Khan, M.Amuthavaani, R.Kalai Selvi
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Many internet users now utilise social media platforms to discuss new ideas, learn about the most recent developments, and exchange the most recent updates internationally from one region to another.
Automated Scaling and Load Balancing in Kubernetes for High-Volume Data ProcessingAnirudh Mustyala, Karthik Allam
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In today's fast-paced digital landscape, managing high-volume data processing is a critical challenge for many organizations. Kubernetes, an open-source container orchestration platform, has emerged as a powerful solution for automating scaling and load balancing, ensuring that applications remain performant and reliable under heavy loads. This abstract explores the capabilities of Kubernetes in handling large-scale data processing tasks, focusing on its automated scaling and load balancing features.
Achieving Net-Zero Energy Buildings: The Strategic Role of HVAC Systems in Design and ImplementationAnkitkumar Tejani,
Jyoti Yadav, Vinay Toshniwal, Harsha Gajjar
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The drive towards sustainable development has ensured that net-zero energy buildings NZEBs have become one of the elements of design in the current world. These buildings generate the amount of energy they use in a year, often by using renewable sources of power on the buildings’ own premises. HVAC systems are systems of balance in this sense because they bear the highest percentage of energy consumption in most buildings.
Designing an Enterprise-Grade, Cloud-Native Chatbot Solution for the Hospitality Industry Using Azure QnA Maker and
Azure LUISRadhika Kanubaddhi
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The hospitality industry is facing increasing demands for personalized and efficient customer service, driven by the rise of digital technologies and evolving customer expectations. Chatbots have emerged as a promising solution to address these challenges, offering the potential to enhance customer experiences, streamline operations, and improve service delivery. This paper presents a comprehensive framework for designing an enterprise-grade, cloud-native chatbot solution for the hospitality industry, leveraging the capabilities of Azure QnA Maker and Azure LUIS.
Data Versioning and Time Travel In Delta Lake for Financial Services: Use Cases and ImplementationAbhilash Katari, Madhu Ankam,
Ravi Shankar
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In the fast-paced world of financial services, maintaining accurate, consistent, and historical data is crucial. Delta Lake, an open-source storage layer, brings robust data versioning and time travel capabilities that significantly enhance data management for financial applications. This paper explores how Delta Lake's features can be implemented to address common challenges in the financial sector, such as regulatory compliance, auditing and accurate historical data analysis. Data versioning in Delta Lake ensures that every change to the data is tracked, enabling financial institutions to maintain a complete history of all transactions and modifications.
ETL Process Automation: Tools and Techniques Santosh Kumar Singu
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ETL stands for Extract, Transform, and load, is a fundamental process in the operation of data warehousing and business intelligence. It refers to a process whereby data is pulled from different sources and is transformed and then uploaded in a data warehouse. Some of the specific justification for automating the ETL process includes the following; Organizations dealing with large and complex data need to have it automated in order to ensure efficiency, scalability and accuracy of the process. This article goes deeper into understanding the tools and technologies employed in automating the ETL processes, and the major ones include Apache Nifi, Talend Informatica and others.
The Ethics of Data Science in Insurance: Balancing Innovation with Privacy and FairnessDevidas Kanchetti
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Data science has greatly impacted insurance and has enabled insurance companies to handle risk and fraud and manage individual attention. Nevertheless, insurance businesses using innovative technology such as machine learning and artificial intelligence (AI) raise ethical privacy, fairness, and transparency issues. This paper aims to discuss the ethical issues concerning data science in insurance, emphasizing how innovation can be achieved without compromising the customer's rights to privacy and fairness in decision-making. Insurance companies depend on personal data to issue premiums, assess claims and decide on coverage.
Scaling DevOps: Challenges in Managing Large and Distributed TeamsYogeswara Reddy Avuthu
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As organizations grow and expand their software delivery pipelines, scaling DevOps practices becomes essential to maintain agility and efficiency. However, managing large and distributed teams introduces complex challenges that impact collaboration, tool alignment, communication, and overall productivity. These challenges stem from differences in time zones, cultural variances, fragmented tooling choices, and difficulties in managing visibility across geographically dispersed teams. This paper explores the critical challenges associated with scaling DevOps across distributed teams and offers solutions such as standardizing toolchains, adopting automation, enhancing communication channels, and fostering cultural alignment.
Real-Time Event Processing In Security Camera Systems: An Auto-Sharding and In-Memory Caching Approach Effectively
Auto Sharding to Increase Reliability and Cost EfficientSibin Thomas
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This paper addresses the challenge of reliable and cost-efficient event processing at scale, a critical requirement for growing companies. Traditional stateless processing approaches often introduce latency and compromise reliability. We propose a solution based on stateful processing and in-memory caching to overcome these limitations. Our approach leverages stateful processing to ensure reliable event handling and reduce latency. Furthermore, by utilizing in-memory caching, we minimize the cost associated with processing large volumes of events. The paper provides a detailed analysis of our proposed solution, demonstrating its effectiveness in achieving both reliability and cost efficiency for large-scale event processing.
The Rise of Serverless: Redefining Scalability and Flexibility in the CloudJoseph Franklin Santhosh Kumar
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Serverless computing has changed the cloud computing paradigm, where developers do not have to worry about where the code is running or any access to the server. Although it is entirely different from infrastructure as a Service (IaaS) or Platform as a Service (PaaS), serverless offers flexibility through the dynamic nature of the application’s usage. This implies that resources are committed, based on certain event occurrences, dynamically, and so both cost and value are optimized. Unlike the traditional models where one would need to over-provision or spend time and effort to control the idle resources as costs are billed on the basis of the actual time spent executing the functions, serverless computing is therefore fitting for solutions with unpredictable usage and demand.
Revolutionizing Salesforce Development with AI and Machine Learning: A Pathway to Intelligent CustomizationsNagaraj
Mandaloju, Vinod kumar Karne, Noone Srinivas, Siddhartha Varma Nadimpalli
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This study investigates the integration of artificial intelligence (AI) and machine learning (ML) into Salesforce development to optimize code and configuration processes. The primary purpose was to evaluate how AI-powered recommendation engines enhance development efficiency, code quality, and user satisfaction. Using a combination of simulated data and empirical analysis, the study developed an AI recommendation engine and assessed its impact on key performance metrics including development speed, error rates, and customization accuracy.