相关论文: Counter-Epidemiological Projections of e-Coaching
With the increase of distance learning, in general, and e-learning, in particular, having a system capable of determining the engagement of students is of primordial importance, and one of the biggest challenges, both for teachers,…
Emotion Prediction in Conversation (EPC) aims to forecast the emotions of forthcoming utterances by utilizing preceding dialogues. Previous EPC approaches relied on simple context modeling for emotion extraction, overlooking fine-grained…
Efficient energy management is essential for reliable and sustainable microgrid operation amid increasing renewable integration. In this paper, an imitation learning-based framework to approximate mixed-integer Economic Model Predictive…
Ensuring the reliability of power electronic converters is a matter of great importance, and data-driven condition monitoring techniques are cementing themselves as an important tool for this purpose. However, translating methods that work…
Providing accurate and reliable predictions about the future of an epidemic is an important problem for enabling informed public health decisions. Recent works have shown that leveraging data-driven solutions that utilize advances in deep…
The paper presents theoretical and empirical analyses of project dynamics and emergent complexity in new product development (NPD) projects. A model-driven approach is taken and mathematical models of cooperative work are formulated based…
The development of technologies of multimedia, linked to that of Internet and democratization of high outflow, has made henceforth E-learning possible for learners being in virtual classes and geographically distributed. The quality and…
In 2020, due to the COVID-19 pandemic, educational activities had to be done remotely as a way to avoid the spread of the disease. What happened was not exactly a shift to an online learning model but a transition to a new approach called…
Social media platforms provide a continuous stream of real-time news regarding crisis events on a global scale. Several machine learning methods utilize the crowd-sourced data for the automated detection of crises and the characterization…
In this paper, we propose a data-driven economic model predictive control (EMPC) scheme with generalized terminal constraint to control an unknown linear time-invariant system. Our scheme is based on the Fundamental Lemma to predict future…
The phase transition present in the linear-chain and square-lattice cases of the transverse Ising model is examined. The extended coupled cluster method (ECCM) can describe both sides of the phase transition with a unified approach. The…
Consumer demand forecasting is of high importance for many e-commerce applications, including supply chain optimization, advertisement placement, and delivery speed optimization. However, reliable time series sales forecasting for…
Background: Over the past few decades, numerous forecasting methods have been proposed in the field of epidemic forecasting. Such methods can be classified into different categories such as deterministic vs. probabilistic, comparative…
Information and communication technologies brought-in tools and techniques in the field of education that introduced new concepts of teaching and learning. Learning management system is one of the key tools used in educational institutes to…
Context. Due to the COVID-19 pandemic, software professionals had to abruptly shift to ostensibly temporary home offices, which affected teamwork in several ways. Goal. This study aims to explore how these professionals coped with remote…
The emergence of the world-wide COVID-19 pandemic has forced academic conferences to be held entirely in a virtual manner. While prior studies have advocated the merits of virtual conferences in terms of energy and cost savings, organizers…
Computer Anxiety is a phenomenon studied in multiple contexts and, in the actual COVID-19 scenario, it is gaining more and more importance as it impacts technology adoption and autonomy. People with Computer Anxiety (PwCA) might feel…
The capability to automatically detect human stress can benefit artificial intelligent agents involved in affective computing and human-computer interaction. Stress and emotion are both human affective states, and stress has proven to have…
As humanity pivots toward long-duration interplanetary travel, the psychological constraints of Isolated and Confined Environments (ICE) emerge as a primary mission risk. This paper presents COSMIC (COmpanion System for Mission Interaction…
Analysis of stress, depression and engagement is less common and more complex than that of frequently discussed emotions such as happiness, sadness, fear and anger. The importance of these psychological states has been increasingly…