Academic literature on the topic 'Amazon Kinesis'

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Journal articles on the topic "Amazon Kinesis"

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Zhukov, S. I., and K. A. Zubrilin. "Using Amazon Kinesis Service for Data Transfer from IoT Devices to Cloud Infrastructure." Programmnaya Ingeneria 14, no. 4 (2023): 187–94. http://dx.doi.org/10.17587/prin.14.187-194.

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IoT devices connected to the Amazon Web Services (AWS) cloud use the loT interface and the MQTT protocol for communication purposes. In addition to these basic communication tools, AWS has developed specialized services for transmitting telemetry data from smart devices. Firehose allows you to upload data directly to the AWS S3 data warehouse (cloud-specific file system). Kinesis service is even more powerful; it enables the user to build back-end data logic, which is automatically applied when data arrives. Also, Kinesis allows running analytics of the telemetry data using artificial intellig
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Girish, Ganachari, and Lakshmanasamy Rameshbabu. "Apache Kafka vs. Amazon Kinesis: A Detailed Comparison of Streaming Data Platforms for Real-Time Data Processing." European Journal of Advances in Engineering and Technology 8, no. 5 (2021): 45–50. https://doi.org/10.5281/zenodo.13790075.

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This paper compares the architecture, performance, and scalability of Apache Kafka and Amazon Kinesis, as well as identifies whether using the latter can be more cost-efficient for real-time data processing. The aim of the study is to assist organisations in identifying the most suitable platform depending on the organisation needs and the conditions under which it will be operating.
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Rakshit Khare. "AI-Powered Patient Risk Analytics in Healthcare: Leveraging Cloud Data Architecture for Improved Clinical Outcomes." Journal of Computer Science and Technology Studies 7, no. 6 (2025): 167–75. https://doi.org/10.32996/jcsts.2025.7.6.19.

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This article presents a comprehensive technical architecture for an innovative healthcare analytics system that leverages artificial intelligence to identify patient deterioration risks in real-time. Built on AWS HealthLake, the solution integrates diverse clinical data sources, including electronic medical records, intensive care unit sensor streams, and laboratory results within a unified cloud data lakehouse. The architecture implements FHIR-compliant streaming pipelines connecting Amazon Kinesis, AWS Lambda, Amazon Redshift Serverless and Amazon QuickSight, enabling healthcare providers to
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Sankaralingam, Kuthalingam. "Leveraging Cloud AI for Real-time Fraud Detection and Prevention in Financial Transactions." European Journal of Computer Science and Information Technology 13, no. 3 (2025): 79–90. https://doi.org/10.37745/ejcsit.2013/vol13n37990.

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Financial fraud has increasingly become sophisticated, making it imperative for organizations to implement advanced, scalable solutions for real-time detection and prevention. Cloud-based artificial intelligence (AI) offers financial institutions a powerful advantage, enabling them to analyze vast transaction datasets, swiftly detect anomalies, and effectively mitigate fraudulent activities. This paper confidently demonstrates how Amazon Web Services (AWS) serves as a robust AI-driven framework for fraud detection, harnessing the capabilities of machine learning (ML), anomaly detection, and re
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Frank Kiven B. Ablao, Thelma D. Palaoag. "AI-Driven Collaborative Cybersecurity Development: A Prototype Implementation of a Cybersecurity Framework for Educational Institutions of Camarines Norte." Journal of Information Systems Engineering and Management 10, no. 33s (2025): 317–25. https://doi.org/10.52783/jisem.v10i33s.5534.

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Cyber threats targeting educational institutions have become increasingly sophisticated, requiring proactive detection and rapid response measures. This study presents an integrated framework that combines an AI-driven threat detection system with the Malware Information Sharing Platform (MISP) to enhance cyber defenses in school networks. Leveraging a Design Science Research methodology, the project unfolds across four phases: system design and architecture, prototype implementation, pilot testing, and evaluation. In the system design phase, requirements were gathered to develop an end-to-end
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Kudrynskyi, Pavlo, and Oleksandr Zvenihorodskyi. "Adaptive performance monitoring in cloud environments via recurrent neural networks." Information Technology and Computer Engineering 22, no. 1 (2025): 79–92. https://doi.org/10.63341/vitce/1.2025.79.

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The study aimed to develop an adaptive methodology for analysing the performance of cloud computing infrastructures to improve the efficiency of resource management and reduce maintenance costs. The research addressed the implementation of the latest approaches to automate monitoring and analysis processes. The research methodology included the integration of data from monitoring platforms (Amazon Web Services CloudWatch, Google Cloud Monitoring, Prometheus) to collect key performance indicators. Data processing was conducted using Python libraries (NumPy, pandas, scikit-learn) to detect anoma
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Narayanan R, Suriya, and Haripriya R. "Pothole Detection in Roads using Pretrained Model and Cloud Computing." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 10 (2023): 1–11. http://dx.doi.org/10.55041/ijsrem26088.

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Abstract—The fundamental objective of this project is to make use of the advanced capabilities offered by technology that is cur- rently available on the market in order to locate and accurately identify potholes. The research identifies potholes in real-time video feeds obtained from vehicles by employing YOLOv8, a dependable pre-trained model for object detection. Utilising an Internet of Things (IoT) gateway, which creates a connection with Kinesis Video Streams in order to collect the video data, makes the procedure simpler and more efficient.The combination of the YOLOv8 algorithm with th
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Кирсанов, О. О., та С. А. Кривенко. "СЦЕНАРІЙ ВИКОРИСТАННЯ АНАЛІТИКИ КЛІНІЧНОГО ІНТЕРНЕТУ РЕЧЕЙ (IOT)". Інфокомунікаційні та комп’ютерні технології 2, № 08 (2024): 9–19. https://doi.org/10.36994/2788-5518-2024-02-08-01.

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Стаття присвячена сценарію використання аналітики Інтернету речей (IoT) для збору та аналізу даних з електровелосипедів, обладнаних IoT-пристроями, з метою підвищення фізичної активності населення, що сприятиме профілактиці серцево-судинних захворювань. Запропонована архітектура системи базується на AWS і охоплює три ключові рівні: прийом та обробку даних, їхнє зберігання, а також аналіз і візуалізацію результатів. На першому етапі підключення IoT-пристроїв до AWS IoT Core забезпечує передачу даних з електровелосипедів через протокол MQTT. Дані регулярно надходять до Kinesis Data Firehose, де
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Ashok, Reddy Annaram. "Unlocking Real-Time Insights: Integrating AWS Kinesis with BPM Tools for Enhanced Business Processes." June 30, 2022. https://doi.org/10.5281/zenodo.11079679.

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This article explores the integration of Amazon Web Services (AWS) Kinesis, a real-time data streaming service, with Business Process Management (BPM) tools to enhance data processing and workflow automation capabilities. AWS Kinesis offers scalable and durable data streaming capabilities, allowing organizations to ingest, process, and analyze large volumes of data in real-time. By integrating Kinesis with BPM tools, organizations can leverage real-time data insights to optimize business processes, improve decision-making, and drive operational efficiency. This article provides a comprehensive
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"Sensor Data Collection and Its Architecture with Internet of Things." International Journal of Engineering and Advanced Technology 9, no. 1 (2019): 2056–60. http://dx.doi.org/10.35940/ijeat.a9564.109119.

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Sensors are gadgets, which can screen temperature, moistness, weight, commotion levels, setting mindfulness, lighting condition and identify speed, position, and size of an Object. Sensor information are getting accumulated in gigantic amount thus they are overseen utilizing NOSQL. The information will be gathered in an IOT cloud stage where it will be additionally prepared with machine learning methods for prescient examination. What's more, eventually with the required answer for the business structure will be created. This paper explain the proposed system for IoT data collection with AWS (
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Dissertations / Theses on the topic "Amazon Kinesis"

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Elsenbeer, Helmut, Keith Cassel, and W. Tinner. "A daily rainfall erosivity model for Western Amazonia." Universität Potsdam, 1993. http://opus.kobv.de/ubp/volltexte/2008/1696/.

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Rainfall erosivities as defined by the R factor from the universal soil loss equation were determined for all events during a two-year period at the station La Cuenca in western Amazonia. Three methods based on a power relationship between rainfall amount and erosivity were then applied to estimate event and daily rainfall erosivities from the respective rainfall amounts. A test of the resulting regression equations against an independent data set proved all three methods equally adequate in predicting rainfall erosivity from daily rainfall amount. We recommend the Richardson model for testing
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Books on the topic "Amazon Kinesis"

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Gulabani, Sunil. Practical Amazon EC2, SQS, Kinesis, and S3. Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2841-8.

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Scalable Data Streaming with Amazon Kinesis: Design and Secure Highly Available, Cost-Effective Data Streaming Applications with Amazon Kinesis. Packt Publishing, Limited, 2021.

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Gulabani, Sunil. Practical Amazon EC2, SQS, Kinesis, and S3: A Hands-On Approach to AWS. Apress, 2017.

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Book chapters on the topic "Amazon Kinesis"

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Gulabani, Sunil. "Hands-on Kinesis." In Practical Amazon EC2, SQS, Kinesis, and S3. Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2841-8_4.

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Gulabani, Sunil. "Getting Started with AWS." In Practical Amazon EC2, SQS, Kinesis, and S3. Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2841-8_1.

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Gulabani, Sunil. "Hands-on Elastic Compute Cloud." In Practical Amazon EC2, SQS, Kinesis, and S3. Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2841-8_2.

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Gulabani, Sunil. "Hands-on Simple Queue Service (SQS)." In Practical Amazon EC2, SQS, Kinesis, and S3. Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2841-8_3.

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Gulabani, Sunil. "Hands-on Simple Storage Service (S3)." In Practical Amazon EC2, SQS, Kinesis, and S3. Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2841-8_5.

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Dubey, Parul, Arvind Kumar Tiwari, and Rohit Raja. "Cloud Integrations." In Amazon Web Services: the Definitive Guide for Beginners and Advanced Users. BENTHAM SCIENCE PUBLISHERS, 2023. http://dx.doi.org/10.2174/9789815165821123010010.

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This chapter delves into the application integration services offered by AWS, which proves particularly beneficial for microservices, distributed systems, and serverless applications. These services facilitate seamless communication between loosely related components. The chapter provides an overview of various AWS integration services, emphasizing their importance in integration processes. Key topics covered in this chapter include SQS (Simple Queue Service), SNS (Simple Notification Service), Kinesis, Pinpoint, and Amazon MQ. Furthermore, the chapter offers practical guidance through hands-on illustrations focused on SQS, allowing readers to gain valuable experience in utilizing these services. By exploring these AWS application integration services, readers can enhance the efficiency and effectiveness of their integration processes. This chapter serves as a comprehensive guide for understanding and utilizing services like SQS, SNS, Kinesis, Pinpoint, and Amazon MQ, enabling seamless communication and integration within AWS environments.
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Arif, Khizra, Abdul Shakoor, Muhammad Awais, et al. "Graphene-based Materials for Electrochemical Energy Storage Devices-EESDs; Opportunities and Future Perspective." In The 2-Dimensional World of Graphene. BENTHAM SCIENCE PUBLISHERS, 2024. http://dx.doi.org/10.2174/9789815238938124010011.

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The material's exciting properties, which have substantially expanded the field of study, include its enormous surface area, outstanding electrical conductivity, extreme thinness, amazing electron kinesis, and cutting-edge mechanical control. These topographies are largely active for various energy-storage devices (EESDs) such as supercapacitors, hybrid cathode and anode materials, lithium-sulfur batteries, lithiumion batteries, lithium-oxygen batteries, and sodium-ion batteries. The scalability, stability, and uniformity of nanomaterials made of carbon are essential for the development of graphene-based energy storage devices.
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Shakoor, Abdul, Rabia Siddiqui, Malika Rani, et al. "Synthesis, Preparation, and Properties of 2DGraphene for Electrochemical Energy Storage and Conversion." In The 2-Dimensional World of Graphene. BENTHAM SCIENCE PUBLISHERS, 2024. http://dx.doi.org/10.2174/9789815238938124010009.

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Stimulating properties of two 2D-Graphene, like its huge surface area, exceptional electrical conductivity, extreme thinness, amazing electron kinesis, and state-of-the-art mechanical regulation, have added an enormous investigative concern. This background exhibits significant dynamism and find widespread application in various energy storage devices like Li-sulfur batteries, Li-ion batteries, Li-oxygen batteries, sodium Ion batteries and also as a hybrid cathode/anode material for supercapacitors. Scaled-up, stable production and correspondence of carbon-based nano-materials are essential conditions for the preparation of graphene-based EESDs. This chapter diagnostically explains the synthesis methods of graphene and the properties of graphene-nanomaterials with various dimensions in adaptable EESDs. The main tasks and scenarios in this field are also discussed.
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"Enzyme Kinetics for Novice Learners: Numerical Simulation in Excel." In Applications of Spreadsheets in Education The Amazing Power of a Simple Tool, edited by Scott A. Sinex and Barbara A. Gage. BENTHAM SCIENCE PUBLISHERS, 2012. http://dx.doi.org/10.2174/978160805276911101010107.

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Shaw, James A. M., and Kevin Docherty. "Gene therapy in diabetes mellitus." In Oxford Textbook of Endocrinology and Diabetes. Oxford University Press, 2011. http://dx.doi.org/10.1093/med/9780199235292.003.1603.

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The distinctions between what has previously been termed cell therapy and gene therapy have become blurred. Cell therapy traditionally implied the in vitro expansion of cells that could subsequently be engrafted into patients to elicit a therapeutic effect, while gene therapy was a term applied to the genetic manipulation of tissues or cells in vivo or ex vivo. With the amazing advances that have been achieved using transcription factors to reprogramme cells, this distinction, at least for regenerative medicine applications, no longer exists. In this chapter, following the statement of the unmet clinical need, we review potential sources of new β‎ cells and approaches to β‎ cell replacement therapy; discuss how recent advances in safety and efficacy of gene transfer technology can augment cellular therapeutic approaches, and summarize pure gene therapy approaches dependent on expression of genes encoding insulin and other glucose-lowering hormones in the recipient’s own cells. Since both type 1 and type 2 diabetes are associated with a decline in β‎ cell mass, cell and gene therapy targeted at the β‎ cell and insulin replacement have potential applications for both forms of the disease. In type 1 diabetes, uninterrupted compliance with insulin injection therapy is necessary to prevent potentially fatal ketoacidosis. The landmark Diabetes Control and Complications Trial and Epidemiology of Diabetes Interventions and Complications follow-up study have confirmed that chronic hyperglycaemic microvascular and macrovascular complications can be prevented by tight glycaemic control, but this was at the expense of a threefold increase in severe hypoglycaemia—one of the greatest fears of those living with daily insulin injections. Overall, the health implications and economic costs of type 1 diabetes are massive, and increasing annually. There is, therefore, an unquestionable clinical need for new therapeutic options. While transplantation of whole pancreas together with its blood supply can entirely normalize blood glucose levels, the major surgery required is associated with 5% mortality in the first year, even in the most experienced centres. Isolation and transplantation of purified insulin-secreting islets of Langerhans from a donor pancreas requires only minimally invasive cannulation of the portal vein transhepatically under X-ray guidance. This offers the promise of more widespread implementation restoring excellent control, preventing both long-term complications and severe hypoglycaemia. Capacity will, however, be severely limited by the scarcity of deceased donor organs: currently sufficient for fewer than 1% of those who might benefit from this form of treatment. This has provided impetus to efforts to produce a replenishable supply of glucose-responsive insulin-secreting cells that could be used in transplantation. One potential source might involve the in vitro differentiation of stem cells derived from embryonic and adult tissue. Type 2 diabetes is marked by both a resistance of target tissue to the effects of insulin and impaired function of the β‎ cell. The major β‎-cell defects relate to an impaired secretory response to glucose, altered kinetics of secretion including pulsatility, accumulation of islet amyloid polypeptide, an increase in glucagon-secreting α‎ cells, and a decline in β‎-cell mass. Current therapy for type 2 diabetes involves a combination of drugs directed at improvements in both insulin sensitivity and β‎-cell function, together with management of associated cardiovascular risk factors. Conventional treatment modalities have not been able to prevent the inexorable progressive loss of β‎-cell function necessitating insulin replacement in the majority over time, but this is often insufficient to sustainably achieve target glucose levels outwith intensive clinical trials. It is envisaged that novel cell therapy approaches will enable restoration of β‎-cell mass.
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Conference papers on the topic "Amazon Kinesis"

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Koschel, Arne, Irina Astrova, Anna Pakosch, Christian Gerner, Christin Schulze, and Matthias Tyca. "Is Amazon Kinesis Data Analytics Suitable as Core for an Event Processing Network Model?" In 16th International Conference on Agents and Artificial Intelligence. SCITEPRESS - Science and Technology Publications, 2024. http://dx.doi.org/10.5220/0012432800003636.

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Evermann, Joerg, Jana-Rebecca Rehse, and Peter Fettke. "Process Discovery from Event Stream Data in the Cloud - A Scalable, Distributed Implementation of the Flexible Heuristics Miner on the Amazon Kinesis Cloud Infrastructure." In 2016 IEEE International Conference on Cloud Computing Technology and Science (CloudCom). IEEE, 2016. http://dx.doi.org/10.1109/cloudcom.2016.0111.

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Saxena, Ashok, and Kip O. Findley. "Modelling the Effects of Hydrogen Pressure on Fatigue Crack Growth Behavior in SA372 Pressure Vessel Steels." In ASME 2022 Pressure Vessels & Piping Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/pvp2022-83958.

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Abstract Low alloy ferritic steels used in fabricating cost-effective cylinders for hydrogen storage are susceptible to hydrogen embrittlement. A model first proposed by Amaro et al. (ARFiDS model) for predicting the effects of hydrogen pressure on the kinetics of hydrogen assisted fatigue crack growth (HA-FCG) in X-100 pipeline steels for pressure between 1 and 20 MPa is adapted in this study and used for predicting the HA-FCG behavior of SA372 Grade J Class 70 pressure vessel steels for pressures ranging between 10 and 102 MPa. The crack growth kinetics in these steels exhibit a typical two-
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