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Does Emotional Labor Matter for University Teaching? Examining the Antecedents and Consequences of University Teachers' Emotional Labor Strategies

Jiying Han, Hongbiao Yin, Xin Yang, Feifei Wang • Frontiers in Psychology (2021)

Following Grandey's integrative model of emotional labor and emotion regulation, this study examined the relationships between university teachers' reported use of various emotional labor strategies and some antecedents (i. e., perceived em...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpsyg.2021.731099

Research on Prediction of Movable Fluid Percentage in Unconventional Reservoir Based on Deep Learning

Jiuxin Wang, Yutian Luo, Zhengming Yang, Xinli Zhao et al. • Applied Sciences (2021)

In order to improve the measurement speed and prediction accuracy of unconventional reservoir parameters, the deep neural network (DNN) is used to predict movable fluid percentage of unconventional reservoirs. The Adam optimizer is used in ...

DOAJ Open Access (DOAJ) DOI: 10.3390/app11083589

UAV-Embedded Sensors and Deep Learning for Pathology Identification in Building Façades: A Review

Gabriel de Sousa Meira, João Victor Ferreira Guedes, Edilson de Souza Bias • Drones (2024)

The use of geotechnologies in the field of diagnostic engineering has become ever more present in the identification of pathological manifestations in buildings. The implementation of Unmanned Aerial Vehicles (UAVs) and embedded sensors has...

DOAJ Open Access (DOAJ) DOI: 10.3390/drones8070341

Introducing Deep Learning Self-Adaptive Misuse Network Intrusion Detection Systems

Dimitrios Papamartzivanos, Felix Gomez Marmol, Georgios Kambourakis • IEEE Access (2019)

The intrusion detection systems (IDSs) are essential elements when it comes to the protection of an ICT infrastructure. A misuse IDS is a stable method that can achieve high attack detection rates (ADR) while keeping false alarm rates under...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2019.2893871

Data Mining and Machine Learning

Mohammed Javeed Zaki, Wagner Meira • Cambridge University Press eBooks (2020)

The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business an...

OPENALEX DOI: https://doi.org/10.1017/9781108564175

Machine Learning in Nutrition Research

Daniel Kirk, E.J. Kok, Michele Tufano, Bedir Teki̇nerdoğan et al. • Advances in Nutrition (2022)

Data currently generated in the field of nutrition are becoming increasingly complex and high-dimensional, bringing with them new methods of data analysis. The characteristics of machine learning (ML) make it suitable for such analysis and ...

OPENALEX cc-by-nc DOI: https://doi.org/10.1093/advances/nmac103 PMC: 9776646

Machine Learning

Jason Bell • Wiley eBooks (2014)

Emotion recognition is an important research topic.Physiological signals seem to be an appropriate way for emotion recognition and specific sensors are required to collect these data.Therefore, laboratory sensors are commonly used while the...

OPENALEX DOI: https://doi.org/10.1002/9781119183464

Foundations of Machine Learning

Vishal Kumar Goar, Nagendra Singh Yadav • Advances in business information systems and analytics book series (2024)

This chapter focuses on providing a complete grasp of the foundations of machine learning (ML). Machine learning is a rapidly evolving domain with wide-ranging applications, from natural language processing to autonomous vehicles. This chap...

OPENALEX DOI: https://doi.org/10.4018/979-8-3693-1598-9.ch002

Fairness in Machine Learning: A Survey

Simon J. Caton, Christian Stefan Haas • ACM Computing Surveys (2023)

When Machine Learning technologies are used in contexts that affect citizens, companies as well as researchers need to be confident that there will not be any unexpected social implications, such as bias towards gender, ethnicity, and/or pe...

OPENALEX cc-by DOI: https://doi.org/10.1145/3616865

A Machine Learning-Oriented Survey on Tiny Machine Learning

Luigi Capogrosso, Federico Cunico, Dong Seon Cheng, Franco Fummi et al. • IEEE Access (2024)

The emergence of Tiny Machine Learning (TinyML) has positively revolutionized the field of Artificial Intelligence by promoting the joint design of resource-constrained IoT hardware devices and their learning-based software architectures. T...

OPENALEX cc-by DOI: https://doi.org/10.1109/access.2024.3365349