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Audit data analytics, machine learning, and full population testing
The Journal of Finance and Data Science, 2022 Emerging technologies like data analytics and machine learning are impacting the accounting profession. In particular, significant changes are anticipated in audit and assurance procedures because of those impacts. One such potential change is audit sampling.
Feiqi Huang +3 more
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Data analytics and machine learning with Java [PDF]
AIP Conference Proceedings, 2018 Data analysis is an important issue for companies as it provides deep business insights thus facilitating their performance. Usually enterprise applications and platforms for Big Data processing live in the Java ecosystem. Therefore it is important to investigate how Java-based platforms for data analytics and machine learning work and the ...
Svetoslav Zhelev, Anna Rozeva
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Reinforcement machine learning for predictive analytics in smart cities [PDF]
, 2017 The digitization of our lives cause a shift in the data production as well as in the required data management. Numerous nodes are capable of producing huge volumes of data in our everyday activities.
Anagnostopoulos, Christos +1 more
core +2 more sources
Sensors, 2018 Running has a positive impact on human health and is an accessible sport for most people. There is high demand for tracking running performance and progress for amateurs and professionals alike.
Markus Zrenner +4 more
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Sensors, 2021 Climbing stairs is a fundamental part of daily life, adding additional demands on the postural control system compared to level walking. Although real-world gait analysis studies likely contain stair ambulation sequences, algorithms dedicated to the ...
Nils Roth +5 more
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MaD GUI: An Open-Source Python Package for Annotation and Analysis of Time-Series Data
Sensors, 2022 Developing machine learning algorithms for time-series data often requires manual annotation of the data. To do so, graphical user interfaces (GUIs) are an important component. Existing Python packages for annotation and analysis of time-series data have
Malte Ollenschläger +7 more
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Scalable aggregation predictive analytics: a query-driven machine learning approach [PDF]
, 2017 We introduce a predictive modeling solution that provides high quality predictive analytics over aggregation queries in Big Data environments. Our predictive methodology is generally applicable in environments in which large-scale data owners may or may ...
Anagnostopoulos, Christos +2 more
core +1 more source
Applied Sciences, 2017 The second most common cause of diving fatalities is cardiovascular diseases. Monitoring the cardiovascular system in actual underwater conditions is necessary to gain insights into cardiac activity during immersion and to trigger preventive measures. We
Stefan Gradl +9 more
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Attributes of Big Data Analytics for Data-Driven Decision Making in Cyber-Physical Power Systems [PDF]
, 2019 Big data analytics is a virtually new term in power system terminology. This concept delves into the way a massive volume of data is acquired, processed, analyzed to extract insight from available data.
Gharehpetian, Gevork B. +4 more
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Data Mining, Machine Learning and Big Data Analytics [PDF]
International Transaction of Electrical and Computer Engineers System, 2017 This paper analyses deep learning and traditional data mining and machine learning methods; compares the advantages and disadvantage of the traditional methods; introduces enterprise needs, systems and data, IT challenges, and Big Data in an extended service infrastructure.
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