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AI-Driven Test Automation for Big data Systems in Cloud Environments 1

AI-Driven Test Automation for Big Data Systems in Cloud Envi...

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1st international conference on advances in Computer science, Electrical, Electronics, and Communication technologies, CE2CT 2025

作者： Gupta, Ankit Kumar Govindankutty, Sreeprasad Nandyala, Avinash Reddy Maria Thason, Justin Rajakumar Pippal, Sanjeev Gupta, Gopal Kumar Uttar Pradesh Technical University Uttar Pradesh Lucknow India Rochester Institute of Technology RochesterNY14623 United States Texas State University San MarcosTX United States Maniapl University Sikkim Gangtok737102 India Greater Noida201306 India Nagpur Campus Pune440008 India

ISBN: (纸本)9798331518578

AI-based Test Automation for Cloud-Based Big Advanced data Systems this method used AI and other new data science methods such as big data, cloud computing, etc. Current testing methodologies do not suit the environments of modern big data systems in a cloud-based environment. AI based test automation approaches: Automated test scenario preparation, examination of test events to identify defects and generation of testing issues. Big data systems, on the other hand, can periodically scan for maximum performance with an all-AI approach, carry out A/B testing, and fine-tune performance. This is particularly important for cloud environments when the architecture of the system and data processing continually changes at a high rate. Additionally, AI in test automation is capable of detecting anomalies and predicting possible system breakdown, providing early warning of issues to ensure mitigation and thereby avoiding costly downtime. This way various scenarios and data sets can be tested and covered to ensure that the best results are covered. © 2025 IEEE.

关键词： data centers

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Ambulance Optimal Routine Path Detection Using Folium and Polygonal Path Finding

Ambulance Optimal Routine Path Detection Using Folium and Po...

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2024 international conference on advances in data Engineering and Intelligent computing Systems, ADICS 2024

作者： Ruthvik, Vejju Krishna Sai Rao, B. G. D. N. Malleswara Asha Judi, V.M.E. Sathyabama University Computer Science And Engineering Chennai India

ISBN: (纸本)9798350364828

This paper proposes an efficient ambulance routing solution using the polygonal path finding algorithm and the folium library. By integrating real-time ambulance location tracking with GIS data, it optimizes ambulance routes to reduce response times and enhance emergency medical services. The folium library visualizes GIS data, aiding in ambulance allocation based on road conditions and hospital accessibility. The polygonal path finding method considers variables like distance, traffic, and road conditions to determine the shortest routes. Evaluation on real data confirms reduced response times. Real-time ambulance tracking ensures continuous route adaptation to traffic and road changes. This research streamlines ambulance routes, improving emergency care and potentially saving lives, highlighting the benefits of advanced technologies in emergency management. © 2024 IEEE.

关键词： Traffic congestion

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Components of Information Diffusion and Its Models in Online Social Networks;a Comparative Study

Components of Information Diffusion and Its Models in Online...

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international conference on advances in data science and computing technologies, asdc 2022

作者： Ganai, Aaquib Hussain Hashmy, Rana Khanday, Hilal Ahmad Department of Computer Science University of Kashmir Srinagar Hazarathbal India

ISBN: (纸本)9789819936557

The age of our times could be better understood if we call it as an online age;where everything happens to be online. These online systems wholly or partially involve people to have online interactions that ranges from simple textual cum audio visual to hidden signals such as likes and dislikes. Such online systems that involve social agents with their interactions have termed out to be online social networks. These online social networks have governed an ocean of interactive data and mutual relationships;such online social interactions and relationships have evolved in spatiotemporal framework and thus have resulted into a new phenomenon called as information diffusion in online social networks. This process of information diffusion is literally termed as data diffusion;but in real, it is a data diffusion that results in relationship diffusion. Since the emergence of online social networks, people have shown their enthusiasm in studying this broad domain of information diffusion in online social networks, directly in the form of modeling information diffusion in online social networks or indirectly in the form of community detection in online social networks, influence maximization, or in content dissemination, etc. In this paper, we are going to make a comparative study of components of information diffusion and its well-known models in online social networks. Each component of information diffusion in online social networks can be studied in isolation. The models of information diffusion can be used to tackle the process of information diffusion in online social networks. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Social networking (online)

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A Comparative Study on the Implementation of Advanced Neural Networks for Predictive Modelling of Carbon Emissions in India 2

A Comparative Study on the Implementation of Advanced Neural...

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2nd IEEE international conference on Emerging Research in Computational science, ICERCS 2024

作者： Varma, Smridh Menta, Nikshith Alice, K. SRM Institute of Science and Technology Department of Computing Technologies Chennai India

ISBN: (纸本)9798331534950

One of today's most important issues is climate change, primarily due to carbon emissions. Accurate carbon emissions forecasting is crucial in developing countries like India to inform effective policy decisions and reduce environmental harm. This study addresses the gap by modeling and forecasting carbon emissions per capita based on a dataset of 172 data points from 1850 to 2022, with a special focus on emissions in India. The proposed methodology combines efficient pre-processing and data preparation with a thorough model selection process, which includes training models such as RNN, LSTM, Bidirectional LSTM, GRU and CNN-GRU. To enhance the performance of the models, hyperparameter tuning was performed. The models' performance was evaluated using measures including mean square error (MSE), mean absolute error (MAE), and R2. The study successfully advances the use of neural networks for carbon emission prediction, which can aid in the development of climate change policy. © 2024 IEEE.

关键词： Carbon sequestration

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Smart Elevator System with Intelligent Floor Level Prioritization using Object Detection

Smart Elevator System with Intelligent Floor Level Prioritiz...

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2024 international conference on advances in data Engineering and Intelligent computing Systems, ADICS 2024

作者： Suraparaju, Rohith Varma Anjemeti, Venkata Sai Revathy, S. Hindustan Institute Of Technology And Science Department Of Computer Science & Engineering Chennai India

ISBN: (纸本)9798350364828

The increasing need for effective vertical transit systems in present-day areas has led to the creation of clever elevator system solutions. In order to improve floor-level prioritizing, this study presents a Smart Elevator System (SES) that incorporates innovative object-detecting technologies. The proposed approach automatically alters elevator priority in realtime by using strong computer vision algorithms to identify and assess the number of passengers waiting on each floor. Computer vision algorithms identify and track passengers in realtime, allowing for the dynamic adjustment of elevator priorities based on the object detection count. Through the use of machine learning models, the system can detect user counts and make intelligent adjustments to reduce waiting times and energy usage. The integration of Internet of Things (IoT) devices, which improves system responsiveness overall, Our proposed work shows notable gains in waiting time and energy savings through intelligent floor-level prioritization. © 2024 IEEE.

关键词： Object detection

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Web Application Development using Flask - Faculty Directory Management 14

Web Application Development using Flask - Faculty Directory ...

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14th international conference on advances in computing, Control, and Telecommunication technologies, ACT 2023

作者： Tarunika, R. Rohit Ram, S.S. Sujithra, M. Sudha Devi, D. Department of Computing-Data Science Coimbatore Institute of Technology India Department of Computing-Data Science Coimbatore Institute of Technology India

The main goal of web development is to create, build and maintain websites. It is what allows the user to experience seamless performance when accessing a website. The web applications landscape has evolved tremendously over the years using various web development frameworks. A web development framework is a set of resources and tools for software developers to build and manage web applications, web services and websites. One such framework is Flask written in Python. The objective is to create a faculty directory using Flask with a goal to provide a centralized resource that can be used by students, staff, and administrators to easily find and connect with faculty members. By improving access to information about faculty members, the directory project aims to promote collaboration and facilitate the sharing of knowledge within the academic community. © Grenze Scientific Society, 2023.

关键词： Python

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Security of Images Using Pascal's Triangle Chaotic Encryption Scheme and with Biometric Authentication in Cloud Storage 4

Security of Images Using Pascal's Triangle Chaotic Encryptio...

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4th international conference on advances in Electrical, computing, Communication and Sustainable technologies, ICAECT 2024

作者： Gupta, Raghav Gullapalli, Manasa Suseela, G. School of Computing Science and Engineering Srm Institute of Science and Technology Department of Networking and Communications Tamil Nadu Kattankulathur603203 India School of Computing Science and Engineering Faculty of Engineering and Technology Srm Institute of Science and Technology Department of Networking and Communications Tamil Nadu Kattankulathur603203 India

ISBN: (纸本)9798350343670

A key component of cloud computing is cloud storage, which allows data to be stored on remote servers. The result is a reduction in the amount of storage space required on local devices, allowing data to be accessed from anywhere with an internet connection. Furthermore, cloud storage is more secure than local storage due to the use of encryption and other security measures by professional providers. This is a practical and cost-effective solution to store large images required to be safeguarded from malicious black hat hackers. Images are the most valuable yet vulnerable form of data that can be used to track down user activities and taken advantage by hackers, used to commit identity theft, fraud. Issues concerning the security and privacy of images saved in the cloud have arisen as cloud storage has grown in popularity. The proposed method will focus on the encryption of images using a chaotic encryption scheme based on Pascal's triangle. The user will authenticate their identity before uploading images to cloud storage and likewise confirm their authentication in the process of retrieval of an image. Such a secure system is better than traditional security methods for password settings as it cannot be easily stolen. Additionally, this method is more secure than other methods due to its complex encryption mechanisms, making it impossible to guess or steal the encryption key. In addition to providing extra security for sensitive images, biometric authentication will offer a stronger method of verifying and validating users on the cloud. © 2024 IEEE.

关键词： AWS Rekognition Chaotic systems Cloud Security Confusion Diffusion Facial Authentication Image Encryption Image Shuffling Pascal's Triangle Transform

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A Review of Machine Learning Models Developed for Solar Radiation Forecasting for Indian Regions 15

A Review of Machine Learning Models Developed for Solar Radi...

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15th international conference on advances in computing, Control, and Telecommunication technologies, ACT 2024

作者： Ajgar, Yogita Krishnamoorthy, N.R. Department of Electronics Sathyabhama Institute of science and technology Chennai India Department of Electronics and communication Sathyabhama Institute of science and technology Chennai India

ISBN: (纸本)9798331300579

These Ever after since the development in technology, many applications are evolved which are based on solar energy utilization and importance of Global solar radiation (GSR) information is consistently increasing. However, due to the changes in solar-radiation and lac of measurement infrastructure, availability of accurate information on GSR data is poor. To deal with this employment of AI based solution is considered. Many machine learning models are developed for forecasting the GSR by virtue of its capacity to handle large and complex nonlinearly correlated data and derive meaningful information from it. This derived information is further utilized for forecasting GSR. Thus, for India, being a country of many climatologically and geographically different zones, approach of employing AI models in GSR prediction becomes very beneficial. This manuscript presents the various machine learning model approaches for GSR forecasting. Recent developments in this view are comprehensively and systematically reviewed considering the aspects like location, selection of input parameters, feature selection and model development. Current situation and future scope of research related to GSR forecasting accuracy improvement across the Indian regions is also discussed. © Grenze Scientific Society, 2024.

关键词： Solar irradiance

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Simple Encryption and Decryption of Password for Cyber Security Application 4

Simple Encryption and Decryption of Password for Cyber Secur...

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4th international conference on advances in Electrical, computing, Communication and Sustainable technologies, ICAECT 2024

作者： Devi, Supriya Vinay Kumar, H.S. Alliance University Department of Applied Mathematics Bangalore India Alliance University Department of Computer Science Bangalore India

ISBN: (纸本)9798350343670

Information about encryption and a dozen practical importance of it can be visualized in the last three decades due to the development in the field of computer science data resource and Internet sharing. Re-visiting the concept says in short sentences, to convert your given information to a different source format which is only recognized or repacked by its required receiver. This research paper is about a simple encryption that can be made using elementary programming languages rather than any other official encryption methods on the internet which indeed are hard and require large steps to understand. This algorithm can be used when the device could be customized or old enough to access communication services like email but, not a communication application because any access through them while using the internet is usually universally programmed and implemented which could be traceable in the end by an unknown source or program. The main aim of the program is to implement through offline and send the encrypted data totally programmed manually for cyber security applications. © 2024 IEEE.

关键词： account login binary algorithm Decryption easy Encryption Internet redundancy Programmable protection Simple Supercomputer

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Privacy Preservation of Cluster Integrity on Web-Scraped Hospital data 5

Privacy Preservation of Cluster Integrity on Web-Scraped Hos...

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5th IEEE international conference on advances in Electrical, computing, Communication and Sustainable technologies, ICAECT 2025

作者： Bojnal, Hrishik Sai Dharmisht, S.V.K. Kaarthik, J. Krishna Kotian, Dhyaan Virupaksha, Shashidhar Rv Institute of Technology and Management Department of Computer Science and Engineering Karnataka Bengaluru India Visvesvaraya Technological University Karnataka Belagavi India

ISBN: (纸本)9798350356236

This paper proposes a method for anonymizing geospatial healthcare data that preserves the natural clustering of locations. A dataset is built with each healthcare facility's location, ratings, and review count by scraping it off an online maps platform. This enables the calculation of each facility's regional influence. The approach retains spatial clusters by restricting the displacements on each facility's geospatial coordinates to at most the minimum radius of the cluster while also factoring for the prominence of the facility in the region. This ensures that the shape and magnitude distribution of clusters is maintained, thereby preserving dataset quality. Impactful insights can be drawn from this anonymized dataset without having to identify any individual facility. © 2025 IEEE.

关键词： Nutrition

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