Log in

Relevant bibliographies by topics / Streaming Data Analysis / Journal articles

To see the other types of publications on this topic, follow the link: Streaming Data Analysis.

Journal articles on the topic 'Streaming Data Analysis'

Author: Grafiati

Published: 10 December 2022

Last updated: 31 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Streaming Data Analysis.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Chowdhury, Sugnik Roy. "Twitter Data Analysis by Live Streaming." Journal of Computational and Theoretical Nanoscience 16, no. 8 (2019): 3178–82. http://dx.doi.org/10.1166/jctn.2019.8156.

Full text

Abstract:

Streaming now a days have been of great use when comes to Social Media. Streaming of data have made it easy for Companies to understand the pros and cons of their product. Streaming acts as a survey now a days which a few years ago were done by a team of individual using pen and papers. In order to collect and process the streaming data from various streaming sites to produce an analytical report that helps to get a clear pictorial representation of events, the assets of streaming process generates a huge volume of real time data mainly referred to as “Big Data.” In order to aggregate, store a

APA, Harvard, Vancouver, ISO, and other styles

2

Ibrahim, Omar A., Yiqing Wang, and James M. Keller. "Analysis of Incremental Cluster Validity for Big Data Applications." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 26, Suppl. 2 (2018): 47–62. http://dx.doi.org/10.1142/s0218488518400111.

Full text

Abstract:

Online clustering has attracted attention due to the explosion of ubiquitous continuous sensing. Streaming clustering algorithms need to look for new structures and adapt as the data evolves, such that outliers are detected, and that new emerging clusters are automatically formed. The performance of a streaming clustering algorithm needs to be monitored over time to understand the behavior of the streaming data in terms of new emerging clusters and number of outlier data points. Small datasets with 2 or 3 dimensions can be monitored by plotting the clustering results as data evolves. However,

APA, Harvard, Vancouver, ISO, and other styles

3

Ambika, L. G. "Analysis of Twitter Streaming Data and Historical Data." International Journal for Research in Engineering Application & Management (IJREAM) 08, no. 10 (2023): 18–22. https://doi.org/10.5281/zenodo.7704092.

Full text

Abstract:

Twitter can be used to share useful information. Keeping track of user postings and commonly used hashtags can also help you figure out what topics are getting the most attention on Twitter. It can also assist in discerning what issues are being discussed the most on Twitter, allowing users to make rapid and informed judgments based on current events. Analyzing Twitter trends allow us to learn more about what people are interested in, which aids corporate organisations or brands in increasing sales, political parties in better understanding people’s feelings and wants, and movie studios

APA, Harvard, Vancouver, ISO, and other styles

4

Bagui, Sikha, and Katie Jin. "A Survey of Challenges Facing Streaming Data." Transactions on Machine Learning and Artificial Intelligence 8, no. 4 (2020): 63–73. http://dx.doi.org/10.14738/tmlai.84.8579.

Full text

Abstract:

This survey performs a thorough enumeration and analysis of existing methods for data stream processing. It is a survey of the challenges facing streaming data. The challenges addressed are preprocessing of streaming data, detection and dealing with concept drifts in streaming data, data reduction in the face of data streams, approximate queries and blocking operations in streaming data.

APA, Harvard, Vancouver, ISO, and other styles

5

Kim, Kyeongjoo. "Real-time Streaming Data Analysis using Spark." International Journal of Emerging Trends in Engineering Research 6, no. 1 (2018): 1–5. http://dx.doi.org/10.30534/ijeter/2018/01612018.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Guo, Shu-Hui, and Xin Lu. "Live streaming: Data mining and behavior analysis." Acta Physica Sinica 69, no. 8 (2020): 088908. http://dx.doi.org/10.7498/aps.69.20191776.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Matteussi, Kassiano J., Julio C. S. dos Anjos, Valderi R. Q. Leithardt, and Claudio F. R. Geyer. "Performance Evaluation Analysis of Spark Streaming Backpressure for Data-Intensive Pipelines." Sensors 22, no. 13 (2022): 4756. http://dx.doi.org/10.3390/s22134756.

Full text

Abstract:

A significant rise in the adoption of streaming applications has changed the decision-making processes in the last decade. This movement has led to the emergence of several Big Data technologies for in-memory processing, such as the systems Apache Storm, Spark, Heron, Samza, Flink, and others. Spark Streaming, a widespread open-source implementation, processes data-intensive applications that often require large amounts of memory. However, Spark Unified Memory Manager cannot properly manage sudden or intensive data surges and their related in-memory caching needs, resulting in performance and

APA, Harvard, Vancouver, ISO, and other styles

8

Narendra Reddy Sanikommu. "Real-time stream processing engines: Architectural analysis and implementation considerations." World Journal of Advanced Research and Reviews 26, no. 2 (2025): 3006–16. https://doi.org/10.30574/wjarr.2025.26.2.1916.

Full text

Abstract:

This article provides an in-depth architectural analysis of three leading stream processing engines: Apache Spark Streaming, Apache Flink, and Kafka Streams. As organizations increasingly rely on real-time data processing capabilities to drive decision-making, understanding the fundamental architectural differences between these technologies has become crucial for successful implementation. The analysis explores how Spark Streaming's micro-batch approach prioritizes throughput and integration with the Spark ecosystem, while Flink's true streaming design enables minimal latency and sophisticate

APA, Harvard, Vancouver, ISO, and other styles

9

Yuan, Zhehu, Yinqi Sun, and Dennis Shasha. "Forgetful Forests: Data Structures for Machine Learning on Streaming Data under Concept Drift." Algorithms 16, no. 6 (2023): 278. http://dx.doi.org/10.3390/a16060278.

Full text

Abstract:

Database and data structure research can improve machine learning performance in many ways. One way is to design better algorithms on data structures. This paper combines the use of incremental computation as well as sequential and probabilistic filtering to enable “forgetful” tree-based learning algorithms to cope with streaming data that suffers from concept drift. (Concept drift occurs when the functional mapping from input to classification changes over time). The forgetful algorithms described in this paper achieve high performance while maintaining high quality predictions on streaming d

APA, Harvard, Vancouver, ISO, and other styles

10

López-Lagunas, Abelardo, and Sek Chai. "Streaming Data Movement for Real-Time Image Analysis." Journal of Signal Processing Systems 62, no. 1 (2009): 29–42. http://dx.doi.org/10.1007/s11265-008-0336-x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

11

Chandrakanth, Lekkala. "Advancements in Data Ingestion: Building High-Throughput Pipelines with Kafka and Spark Streaming." Journal of Scientific and Engineering Research 7, no. 7 (2020): 253–59. https://doi.org/10.5281/zenodo.11489050.

Full text

Abstract:

This paper conducts Kafka and Spark Streaming to enrich the data ingestion rate through the pipeline with high throughput. This paper aims to investigate the features, functionality, and building-up platforms from Kafka and Spark Streaming, designed to address complicated real-time streaming-related issues. Research methodology plans this research with a deeper analysis of Kafka and Spark Streaming architectures, best practices, caveats, and strong and weak aspects of the methods. This analysis revealed some main results that indicate the strength of Kafka as an existing Spark Streaming progra

APA, Harvard, Vancouver, ISO, and other styles

12

Zhang, Hong, Zhenchao Xu, Yunxiang Wang, and Yupeng Shen. "An innovative parameter optimization of Spark Streaming based on D3QN with Gaussian process regression." Mathematical Biosciences and Engineering 20, no. 8 (2023): 14464–86. http://dx.doi.org/10.3934/mbe.2023647.

Full text

Abstract:

<abstract><p>Nowadays, Spark Streaming, a computing framework based on Spark, is widely used to process streaming data such as social media data, IoT sensor data or web logs. Due to the extensive utilization of streaming media data analysis, performance optimization for Spark Streaming has gradually developed into a popular research topic. Several methods for enhancing Spark Streaming's performance include task scheduling, resource allocation and data skew optimization, which primarily focus on how to manually tune the parameter configuration. However, it is indeed very challenging

APA, Harvard, Vancouver, ISO, and other styles

13

Giannakis, Dimitrios, Amelia Henriksen, Joel A. Tropp, and Rachel Ward. "Learning to Forecast Dynamical Systems from Streaming Data." SIAM Journal on Applied Dynamical Systems 22, no. 2 (2023): 527–58. http://dx.doi.org/10.1137/21m144983x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

Lee, Heung Ki, Jaehee Jung, Kyung Jin Ahn, Hwa-Young Jeong, and Gangman Yi. "Numeric Analysis for Relationship-Aware Scalable Streaming Scheme." Journal of Applied Mathematics 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/195781.

Full text

Abstract:

Frequent packet loss of media data is a critical problem that degrades the quality of streaming services over mobile networks. Packet loss invalidates frames containing lost packets and other related frames at the same time. Indirect loss caused by losing packets decreases the quality of streaming. A scalable streaming service can decrease the amount of dropped multimedia resulting from a single packet loss. Content providers typically divide one large media stream into several layers through a scalable streaming service and then provide each scalable layer to the user depending on the mobile

APA, Harvard, Vancouver, ISO, and other styles

15

Okan, Emmanuel Tettey. "Forensic Analysis on Streaming Multimedia." Advances in Multidisciplinary and scientific Research Journal Publication 1, no. 1 (2022): 221–26. http://dx.doi.org/10.22624/aims/crp-bk3-p36.

Full text

Abstract:

Since the advent of technology and digitalization of multimedia, there has been a massive increase in cybercrime. During streaming, with the availability of a network or internet source, multimedia; audio and visual can easily be accessed whiles being aired live. This technology dates as far back as 1990s. Similar to still videos and images, the user is able to download, pause, reverse or forward the show. The ability to stream multimedia has made it easier for users to partake or retrieve multimedia from the comfort of their homes, offices or personal spaces without necessarily being present.

APA, Harvard, Vancouver, ISO, and other styles

16

Adewole, Kayode S., Taofeekat T. Salau-Ibrahim, Agbotiname Lucky Imoize, et al. "Empirical Analysis of Data Streaming and Batch Learning Models for Network Intrusion Detection." Electronics 11, no. 19 (2022): 3109. http://dx.doi.org/10.3390/electronics11193109.

Full text

Abstract:

Network intrusion, such as denial of service, probing attacks, and phishing, comprises some of the complex threats that have put the online community at risk. The increase in the number of these attacks has given rise to a serious interest in the research community to curb the menace. One of the research efforts is to have an intrusion detection mechanism in place. Batch learning and data streaming are approaches used for processing the huge amount of data required for proper intrusion detection. Batch learning, despite its advantages, has been faulted for poor scalability due to the constant

APA, Harvard, Vancouver, ISO, and other styles

17

TKACHUK, Halyna, Oleksii MUKOVIZ та Rostislav MOTSYK. "OPTIMIZATION OF СLOUD TRAFFIC FOR STREAMING APPLICATIONS: ANALYSIS AND MONITORING APPROACHES". Collection of scientific papers Kamianets-Podilsky Ivan Ohienko National University Pedagogical series 30 (18 грудня 2024): 26–30. https://doi.org/10.32626/2307-4507.2024-30.26-30.

Full text

Abstract:

The article explores innovative strategies for improving the efficiency of data transmission in cloud streaming services. It addresses advanced coding techniques aimed at reducing latency and bandwidth consumption while preserving data integrity. The study provides a comprehensive overview of analysis and monitoring approaches that track performance metrics and optimize traffic flow. Using adaptive coding and real-time monitoring tools, the paper demonstrates how to achieve cost-effective and reliable streaming. The article offers practical recommendations for optimizing cloud traffic for deve

APA, Harvard, Vancouver, ISO, and other styles

18

G., Bramhani, Bharathi M., Aditya Sai Srinivas T., and Bhuvaneswari M. "Slicing and Streaming: A Python Analysis of Netflix's Big Picture." Recent Trends in Information Technology and its Application 7, no. 2 (2024): 120–26. https://doi.org/10.5281/zenodo.10628143.

Full text

Abstract:

<em>Venture into the vast landscape of online streaming with Netflix, a titan in the realm of digital entertainment. Bolstered by a colossal subscriber base, Netflix amasses an ocean of data, ripe for exploration. Join me on a riveting journey through a Python-fueled data science project, unraveling the intricate tapestry of Netflix's content universe. Beyond its origins in on-demand DVD rentals, Netflix has metamorphosed, placing paramount emphasis on original show productions. This article delves into the art of deciphering Netflix's evolving narrative, employing Python to dissect troves of

APA, Harvard, Vancouver, ISO, and other styles

19

Haries Anom Susetyo Aji Nugroho, Sonhaji, and Andika Chandra Prasetyo. "YouTube Streaming Performance Over Wi-Fi: A Resolution-Based Analysis." PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic 13, no. 1 (2025): 29–38. https://doi.org/10.33558/piksel.v13i1.10580.

Full text

Abstract:

The quality of YouTube video streaming services affects the learning process through video streaming. With poor video service quality, it will disrupt the process of obtaining information. Therefore, there is a need for good video service quality following existing service quality standards on the internet network, according to ITU. Streaming video on YouTube consists of several resolutions. The higher the video resolution, the better the video quality but inversely proportional to the greater the internet bandwidth required. This research tries to compare the quality of YouTube video streamin

APA, Harvard, Vancouver, ISO, and other styles

20

Kube, R., R. M. Churchill, C. S. Chang, et al. "Near real-time streaming analysis of big fusion data." Plasma Physics and Controlled Fusion 64, no. 3 (2022): 035015. http://dx.doi.org/10.1088/1361-6587/ac3f42.

Full text

Abstract:

Abstract Experiments on fusion plasmas produce high-dimensional data time series with ever-increasing magnitude and velocity, but turn-around times for analysis of this data have not kept up. For example, many data analysis tasks are often performed in a manual, ad-hoc manner some time after an experiment. In this article, we introduce the Delta framework that facilitates near real-time streaming analysis of big and fast fusion data. By streaming measurement data from fusion experiments to a high-performance compute center, Delta allows computationally expensive data analysis tasks to be perfo

APA, Harvard, Vancouver, ISO, and other styles

21

Issa, Shadi A., Romeo Kienzler, Mohamed El-Kalioby, et al. "Streaming Support for Data Intensive Cloud-Based Sequence Analysis." BioMed Research International 2013 (2013): 1–16. http://dx.doi.org/10.1155/2013/791051.

Full text

Abstract:

Cloud computing provides a promising solution to the genomics data deluge problem resulting from the advent of next-generation sequencing (NGS) technology. Based on the concepts of “resources-on-demand” and “pay-as-you-go”, scientists with no or limited infrastructure can have access to scalable and cost-effective computational resources. However, the large size of NGS data causes a significant data transfer latency from the client’s site to the cloud, which presents a bottleneck for using cloud computing services. In this paper, we provide a streaming-based scheme to overcome this problem, wh

APA, Harvard, Vancouver, ISO, and other styles

22

Zeng, Xue-Qiang, and Guo-Zheng Li. "Incremental partial least squares analysis of big streaming data." Pattern Recognition 47, no. 11 (2014): 3726–35. http://dx.doi.org/10.1016/j.patcog.2014.05.022.

Full text

APA, Harvard, Vancouver, ISO, and other styles

23

Law, Jonathan, and Darren J. Wilkinson. "Composable models for online Bayesian analysis of streaming data." Statistics and Computing 28, no. 6 (2017): 1119–37. http://dx.doi.org/10.1007/s11222-017-9783-1.

Full text

APA, Harvard, Vancouver, ISO, and other styles

24

Thomas, Mathew, Kerstin Kleese-van Dam, Matthew J. Marshall, et al. "Towards Adaptive, Streaming Analysis of X-ray Tomography Data." Synchrotron Radiation News 28, no. 2 (2015): 10–14. http://dx.doi.org/10.1080/08940886.2015.1013414.

Full text

APA, Harvard, Vancouver, ISO, and other styles

25

Fejfar, Jiří, Jiří Šťastný, Martin Pokorný, Jiří Balej, and Petr Zach. "Analysis of sound data streamed over the network." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 61, no. 7 (2013): 2105–10. http://dx.doi.org/10.11118/actaun201361072105.

Full text

Abstract:

In this paper we inspect a difference between original sound recording and signal captured after streaming this original recording over a network loaded with a heavy traffic. There are several kinds of failures occurring in the captured recording caused by network congestion. We try to find a method how to evaluate correctness of streamed audio. Usually there are metrics based on a human perception of a signal such as “signal is clear, without audible failures”, “signal is having some failures but it is understandable”, or “signal is inarticulate”. These approaches need to be statistically eva

APA, Harvard, Vancouver, ISO, and other styles

26

Lekha, R. Nair, D. Shetty Sujala, and Deepak Shetty Siddhant. "Streaming Big Data Analysis for Real-Time Sentiment based Targeted Advertising." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 1 (2017): 402–7. https://doi.org/10.11591/ijece.v7i1.pp402-407.

Full text

Abstract:

Big Data constituting from the information shared in the various social network sites have great relevance for research to be applied in diverse fields like marketing, politics, health or disaster management. Social network sites like Facebook and Twitter are now extensively used for conducting business, marketing products and services and collecting opinions and feedbacks regarding the same. Since data gathered from these sites regarding a product/brand are up-to-date and are mostly supplied voluntarily, it tends to be more realistic, massive and reflects the general public opinion. Its analy

APA, Harvard, Vancouver, ISO, and other styles

27

Banu, Syed Reshma, and B. Sravani. "Netflix Movies and Tv Shows Data Analysis." International Journal for Research in Applied Science and Engineering Technology 11, no. 10 (2023): 1068–72. http://dx.doi.org/10.22214/ijraset.2023.55802.

Full text

Abstract:

Abstract: Netflix stands as the leading on-demand streaming platform in current times, offering its services across a staggering 190 countries and featuring an extensive library of both movies and TV shows. In our research, we carried out an initial exploratory analysis utilizing data sourced from Flexible, a search engine dedicated to cataloging the content accessible on the Netflix platform. When Netflix made its debut in April, online video streaming was still in its early stages. Fast forward eighteen years, and Netflix has evolved into the world's foremost global Internet television platf

APA, Harvard, Vancouver, ISO, and other styles

28

Tian, Zixuan, Xiaoyue Xie, and Jian Shi. "Bayesian quantile regression for streaming data." AIMS Mathematics 9, no. 9 (2024): 26114–38. http://dx.doi.org/10.3934/math.20241276.

Full text

Abstract:

<p>Quantile regression has been widely used in many fields because of its robustness and comprehensiveness. However, it remains challenging to perform the quantile regression (QR) of streaming data by a conventional methods, as they are all based on the assumption that the memory can fit all the data. To address this issue, this paper proposes a Bayesian QR approach for streaming data, in which the posterior distribution was updated by utilizing the aggregated statistics of current and historical data. In addition, theoretical results are presented to confirm that the streaming posterior

APA, Harvard, Vancouver, ISO, and other styles

29

Hussein, Suhad S., and Karim Q. Hussein. "Optimization of Performance in Cloud Data Streaming: Comprehensive Review." International Journal of Membrane Science and Technology 10, no. 4 (2023): 1559–70. http://dx.doi.org/10.15379/ijmst.v10i4.2279.

Full text

Abstract:

With the proliferation of cloud computing, the landscape of data processing has undergone a transformative shift. Cloud data streaming, a linchpin of real-time data processing, has emerged as a critical enabler for organizations seeking timely insights and informed decision-making. However, optimizing the performance of cloud data streaming systems poses intricate challenges that necessitate exploration. This comprehensive review article navigates the multifaceted terrain of enhancing performance in cloud data streaming. It encompasses foundational concepts, performance evaluation metrics, pre

APA, Harvard, Vancouver, ISO, and other styles

30

Suhendar, Agus, and Murti Retnowo. "Rain conditions effect the transmission of Streaming video data on Aeromodelling." Compiler 12, no. 1 (2023): 59. http://dx.doi.org/10.28989/compiler.v12i1.1604.

Full text

Abstract:

Streaming is the process of sending data continuously or continuously that be broadcast over the internet. FPV (First-person view) is a method used to control radio control vehicles from the pilot. Analysis of live video streaming service on FPV aeromodelling with standard configurations to determine the maximum results for live video streaming service on FPV aeromodelling. Distance measurements and environmental conditions are also necessary to determine the performance of live video streaming. Then performed a Quality of Service (QoS) analysis, including measurement of delay, jitter, and thr

APA, Harvard, Vancouver, ISO, and other styles

31

Xiao, Wen, and Juan Hu. "SWEclat: a frequent itemset mining algorithm over streaming data using Spark Streaming." Journal of Supercomputing 76, no. 10 (2020): 7619–34. http://dx.doi.org/10.1007/s11227-020-03190-5.

Full text

Abstract:

Abstract Finding frequent itemsets in a continuous streaming data is an important data mining task which is widely used in network monitoring, Internet of Things data analysis and so on. In the era of big data, it is necessary to develop a distributed frequent itemset mining algorithm to meet the needs of massive streaming data processing. Apache Spark is a unified analytic engine for massive data processing which has been successfully used in many data mining fields. In this paper, we propose a distributed algorithm for mining frequent itemsets over massive streaming data named SWEclat. The a

APA, Harvard, Vancouver, ISO, and other styles

32

Miletić, Aleksa, Petar Lukovac, Tamara Naumović, Danijela Stojanović, and Aleksandra Labus. "A Data Streaming Architecture for Air Quality Monitoring in Smart Cities." Athens Journal of Τechnology & Engineering 10, no. 4 (2023): 215–27. http://dx.doi.org/10.30958/ajte.10-4-2.

Full text

Abstract:

This paper aims to present a modeling approach for the seamless data streaming process from smart IoT systems to Apache Kafka, leveraging the MQTT protocol. The paper begins by discussing the concept of real-time data streaming, emphasizing the need to transfer data from IoT/edge devices and sensors to Apache Kafka in a timely manner. The second part consists of a literature overview that shows the analysis and systematization of different types of architectures in the broad sense of crowdsensing, followed by specific architectures regarding edge and cloud computing. The methodology section wi

APA, Harvard, Vancouver, ISO, and other styles

33

Kumar, Sudhir. "Real-Time Data Streaming: Transforming FinTech Through Modern Data Architectures." European Journal of Computer Science and Information Technology 13, no. 18 (2025): 49–64. https://doi.org/10.37745/ejcsit.2013/vol13n184964.

Full text

Abstract:

This comprehensive article explores the transformative impact of real-time data streaming technologies in the financial services sector through four detailed case studies. It examines how leading financial institutions have leveraged modern data architectures, including Apache Kafka, Spark Streaming, AWS Kinesis, and cloud computing platforms, to address critical business challenges. The article demonstrates how these technologies enable instantaneous fraud detection, enhanced customer experience through personalized offerings, streamlined regulatory reporting, and optimized customer acquisiti

APA, Harvard, Vancouver, ISO, and other styles

34

Syamsuddin, Irfan, Rini Nur, Hafsah Nirwana, Ibrahim Abduh, and David Al-Dabass. "Decision Making Analysis of Video Streaming Algorithm for Private Cloud Computing Infrastructure." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 6 (2017): 3529. http://dx.doi.org/10.11591/ijece.v7i6.pp3529-3535.

Full text

Abstract:

The issue on how to effectively deliver video streaming contents over cloud computing infrastructures is tackled in this study. Basically, quality of service of video streaming is strongly influenced by bandwidth, jitter and data loss problems. A number of intelligent video streaming algorithms are proposed by using different techniques to deal with such issues. This study aims to propose and demonstrate a novel decision making analysis which combines ISO 9126 (international standard for software engineering) and Analytic Hierarchy Process to help experts selecting the best video streaming alg

APA, Harvard, Vancouver, ISO, and other styles

35

Irfan, Syamsuddin, Nur Rini, Nirwana Hafsah, Abduh Ibrahim, and Al-Dabass David. "Decision Making Analysis of Video Streaming Algorithm for Private Cloud Computing Infrastructure." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 6 (2017): 3529–35. https://doi.org/10.11591/ijece.v7i6.pp3529-3535.

Full text

Abstract:

The issue on how to effectively deliver video streaming contents over cloud computing infrastructures is tackled in this study. Basically, quality of service of video streaming is strongly influenced by bandwidth, jitter and data loss problems. A number of intelligent video streaming algorithms are proposed by using different techniques to deal with such issues. This study aims to propose and demonstrate a novel decision making analysis which combines ISO 9126 (international standard for software engineering) and Analytic Hierarchy Process to help experts selecting the best video streaming alg

APA, Harvard, Vancouver, ISO, and other styles

36

Alwaisi, Shaimaa Safaa Ahmed, Maan Nawaf Abbood, Luma Fayeq Jalil, et al. "A Review on Big Data Stream Processing Applications: Contributions, Benefits, and Limitations." JOIV : International Journal on Informatics Visualization 5, no. 4 (2021): 456. http://dx.doi.org/10.30630/joiv.5.4.737.

Full text

Abstract:

The amount of data in our world has been rapidly keep growing from time to time. In the era of big data, the efficient processing and analysis of big data using machine learning algorithm is highly required, especially when the data comes in form of streams. There is no doubt that big data has become an important source of information and knowledge in making decision process. Nevertheless, dealing with this kind of data comes with great difficulties; thus, several techniques have been used in analyzing the data in the form of streams. Many techniques have been proposed and studied to handle bi

APA, Harvard, Vancouver, ISO, and other styles

37

Foster, Anita K., and Gene R. Springs. "Running up the hill – long-term streaming video pilots: process, analysis and outcomes." Collection and Curation 41, no. 2 (2022): 37–46. http://dx.doi.org/10.1108/cc-12-2020-0046.

Full text

Abstract:

Purpose Academic libraries are struggling to support the growing demand for streaming video. The purpose of this paper is to detail the experience of running three long-term pilots with different streaming video platforms, including processes involved, lessons learned and next steps. Design/methodology/approach This paper uses a mixed methods approach, combining analysis of usage data with case study observations. Findings The length of the pilots allowed for deep understanding of the needs of this academic library’s community’s engagement with streaming video in the classroom, and confirmed a

APA, Harvard, Vancouver, ISO, and other styles

38

Chicherov, Denis. "ANALYSIS OF METHODS TO INCREASE QOE PARAMETERS FOR VIDEO STREAMING SERVICES." SYNCHROINFO JOURNAL 10, no. 2 (2024): 28–36. http://dx.doi.org/10.36724/2664-066x-2024-10-2-28-36.

Full text

Abstract:

Video streaming services represent a new generation of television (DTV), which have become an integral part of modern digital culture. With the development of Internet technologies and the spread of broadband access, video streaming has become a popular and convenient way to consume multimedia content. Unlike traditional television, video streaming services provide the user with the ability to choose content, watch it at a convenient time and on different devices, which leads to new challenges and opportunities in improving the quality of user experience (QoE). One of the key elements that det

APA, Harvard, Vancouver, ISO, and other styles

39

Tu, Doan Quang, A. S. M. Kayes, Wenny Rahayu, and Kinh Nguyen. "IoT streaming data integration from multiple sources." Computing 102, no. 10 (2020): 2299–329. http://dx.doi.org/10.1007/s00607-020-00830-9.

Full text

APA, Harvard, Vancouver, ISO, and other styles

40

Li, Rong, Chaonan Liu, and Bei Li. "Analysis of Agricultural Marketing Data Flow and Optimisation Methods in Cross-Border E-Commerce Platforms." Journal of Combinatorial Mathematics and Combinatorial Computing 123, no. 1 (2024): 43–59. https://doi.org/10.61091/jcmcc123-04.

Full text

Abstract:

Big data technology makes it possible to scientifically analyse a large amount of marketing data, which plays an important role in the development of marketing strategies for products and the improvement of marketing effects. In this paper, a marketing data stream analysis system is designed based on the stream analysis method. The system designs and optimises the marketing data storage and retrieval, data acquisition and streaming calculation engine to achieve real-time user behaviour data streaming analysis. The average response time accuracy of the system’s data can reach 96%, the throughpu

APA, Harvard, Vancouver, ISO, and other styles

41

Akilandeswari, P., R. Harshita, and Sumanth KO.M. "Sentiment Analysis using Machine Learning through Twitter Streaming API." International Journal of Engineering & Technology 7, no. 3.12 (2018): 1168. http://dx.doi.org/10.14419/ijet.v7i3.12.17781.

Full text

Abstract:

Social media allows to share the experiences with many best suggestions and provides opportunities to share the ideas about any topics at any time. In the current trending, twitter is used to gather different kinds of information as user need and it is a social network service which enables the user for better communication and gaining of knowledge. Accurate representation of the user interactions can be done based on the facts sematic content. The pre-processed tweets which are stored in database are been identified and classified whether it relates to the user keywords related posts. The bes

APA, Harvard, Vancouver, ISO, and other styles

42

Li, Ping, Jiashi Feng, Xiaojie Jin, Luming Zhang, Xianghua Xu, and Shuicheng Yan. "Online Robust Low-Rank Tensor Modeling for Streaming Data Analysis." IEEE Transactions on Neural Networks and Learning Systems 30, no. 4 (2019): 1061–75. http://dx.doi.org/10.1109/tnnls.2018.2860964.

Full text

APA, Harvard, Vancouver, ISO, and other styles

43

Nedzhibov, Gyurhan. "Extended Online DMD and Weighted Modifications for Streaming Data Analysis." Computation 11, no. 6 (2023): 114. http://dx.doi.org/10.3390/computation11060114.

Full text

Abstract:

We present novel methods for computing the online dynamic mode decomposition (online DMD) for streaming datasets. We propose a framework that allows incremental updates to the DMD operator as data become available. Due to its ability to work on datasets with lower ranks, the proposed method is more advantageous than existing ones. A noteworthy feature of the method is that it is entirely data-driven and does not require knowledge of any underlying governing equations. Additionally, we present a modified version of our proposed approach that utilizes a weighted alternative to online DMD. The su

APA, Harvard, Vancouver, ISO, and other styles

44

Amori, Francesco, Stefano Antonelli, Vincenzo Ciaschini, et al. "General purpose data streaming platform for log analysis, anomaly detection and security protection." EPJ Web of Conferences 295 (2024): 01032. http://dx.doi.org/10.1051/epjconf/202429501032.

Full text

Abstract:

INFN-CNAF is one of the Worldwide LHC Computing Grid (WLCG) Tier-1 data centres, providing computing, networking and storage resources to a wide variety of scientific collaborations, not limited to the four LHC (Large Hadron Collider) experiments. The INFN-CNAF data centre will move to a new location next year. At the same time, the requirements from our experiments and users are becoming increasingly challenging and new scientific communities have started or will soon start exploiting our resources. Currently, we are reengineering several services, in particular our monitoring infrastructure,

APA, Harvard, Vancouver, ISO, and other styles

45

Wei, Jianfeng, Jian Yang, Xuewen Cheng, Jie Ding, and Shengquan Li. "Adaptive Regression Analysis of Heterogeneous Data Streams via Models with Dynamic Effects." Mathematics 11, no. 24 (2023): 4899. http://dx.doi.org/10.3390/math11244899.

Full text

Abstract:

Streaming data sequences arise from various areas in the era of big data, and it is challenging to explore efficient online models that adapt to them. To address the potential heterogeneity, we introduce a new online estimation procedure to analyze the constantly incoming streaming datasets. The underlying model structures are assumed to be the generalized linear models with dynamic regression coefficients. Our key idea lies in introducing a vector of unknown parameters to measure the differences between batch-specific regression coefficients from adjacent data blocks. This is followed by the

APA, Harvard, Vancouver, ISO, and other styles

46

Ren, Tonglin, Jingyuan Wang, and Yutong Zhang. "Analysis of the Live-Streaming Market." Advances in Economics, Management and Political Sciences 106, no. 1 (2024): 236–41. http://dx.doi.org/10.54254/2754-1169/106/20241526.

Full text

Abstract:

As society evolves throughout time, the complexity of relationships has brought social media and online apps under the spotlight. With more than 3 billion users worldwide, social media has developed far beyond its intention; rather than just a platform used to share stories and lifestyles or expand social circles, it has become a market where businesses can launch their products to all social media users. The broad use of this advanced platform allows companies to be creative and innovate in diverse ways essential to selling their products. Since the influence of online platforms is nonnegligi

APA, Harvard, Vancouver, ISO, and other styles

47

Ren, Tonglin, Jingyuan Wang, and Yutong Zhang. "Analysis of the Live-Streaming Market." Advances in Economics, Management and Political Sciences 81, no. 1 (2024): 318–23. http://dx.doi.org/10.54254/2754-1169/81/20241526.

Full text

Abstract:

As society evolves throughout time, the complexity of relationships has brought social media and online apps under the spotlight. With more than 3 billion users worldwide, social media has developed far beyond its intention; rather than just a platform used to share stories and lifestyles or expand social circles, it has become a market where businesses can launch their products to all social media users. The broad use of this advanced platform allows companies to be creative and innovate in diverse ways essential to selling their products. Since the influence of online platforms is nonnegligi

APA, Harvard, Vancouver, ISO, and other styles

48

Liu, Ziyi. "Analysis of Shopping Addiction Behavior of Douyin Users under the Background of New Media." Communications in Humanities Research 13, no. 1 (2023): 294–99. http://dx.doi.org/10.54254/2753-7064/13/20230367.

Full text

Abstract:

As a product of new media technology, live streaming commerce has emerged as a popular consumption trend. With its interactive nature, the variety of live streaming commerce formats continues to expand. Notably, food-related live streaming commerce has gained significant popularity among consumers. Increasingly, people are engaging in addictive behaviors, purchasing food products through these platforms. This paper focuses on examining the addictive behavior of new media users in food commercial live streaming, using Douyin as a case study. The research delves into the relationship between use

APA, Harvard, Vancouver, ISO, and other styles

49

Hu, Zhigang, Hui Kang, and Meiguang Zheng. "Stream Data Load Prediction for Resource Scaling Using Online Support Vector Regression." Algorithms 12, no. 2 (2019): 37. http://dx.doi.org/10.3390/a12020037.

Full text

Abstract:

A distributed data stream processing system handles real-time, changeable and sudden streaming data load. Its elastic resource allocation has become a fundamental and challenging problem with a fixed strategy that will result in waste of resources or a reduction in QoS (quality of service). Spark Streaming as an emerging system has been developed to process real time stream data analytics by using micro-batch approach. In this paper, first, we propose an improved SVR (support vector regression) based stream data load prediction scheme. Then, we design a spark-based maximum sustainable throughp

APA, Harvard, Vancouver, ISO, and other styles

50

Lin, Qiang, and Xilin Zhang. "Key Technologies of Media Big Data in-Depth Analysis System Based on 5G Platform." Journal of Physics: Conference Series 2294, no. 1 (2022): 012007. http://dx.doi.org/10.1088/1742-6596/2294/1/012007.

Full text

Abstract:

Abstract To meet the needs of large-scale users for personalized streaming media services with high speed, low delay, and high quality in a 5G mobile network environment, this paper studies the resource allocation mechanism of streaming media based on a 5G network from the perspective of user demand prediction, which can alleviate the pressure of mobile network, improve the utilization rate of streaming media resources and the quality of user service experience. The augmented reality visualization of large-scale social media data must rely on the computing power of distributed clusters. This p

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!