scholarly journals Can I have More Problems to Practice? Student Usage and Course Success Related to Auto-graded, End-of-chapter Problems in a Material and Energy Balances Course

2021 ◽  
Author(s):  
Kayla Chapman ◽  
Matthew Liberatore
Keyword(s):  
Course Success ◽  
Energy Balances

Fiber energy efficiency Part I: Extended entropy model

2014 ◽  
Vol 29 (2) ◽  
pp. 322-331 ◽  
Author(s):  
Anders Karlström ◽  
Karin Eriksson
Keyword(s):  
Energy Efficiency ◽  
Temperature Profile ◽  
Dynamic Models ◽  
Fluid Dynamic ◽  
Multiscale Model ◽  
Process Conditions ◽  
Entropy Model ◽  
Refining Zone ◽  
Energy Balances ◽  
Flat Zone

Abstract This is the first in a series of papers presenting the development of a comprehensive multiscale model with focus on fiber energy efficiency in thermo mechanical pulp processes. The fiber energy efficiency is related to the defibration and fibrillation work obtained when fibers and fiber bundles interact with the refining bars. The fiber energy efficiency differs from the total refining energy efficiency which includes the thermodynamical work as well. Extracting defibration and fibrillation work along the radius in the refining zone gives information valuable for fiber development studies.Models for this process must handle physical variables as well as machine specific parameters at different scales. To span the material and energy balances, spatial measurements from the refining zone must be available. In this paper, measurements of temperature profile and plate gaps from a full-scale CD-refiner are considered as model inputs together with a number of process variables. This enables the distributed consistency in the refining zone as well as the split of the total work between the flat zone and the CD-zone to be derived. As the temperature profile and the plate gap are available in the flat zone and the CD-zone at different process conditions it is also shown that the distributed pulp dynamic viscosity can be obtained. This is normally unknown in refining processes but certainly useful for all fluid dynamic models describing the bar-to-fiber interactions. Finally, it is shown that the inclusion of the machine parameters will be vital to get good estimates of the refining conditions and especially the split between the thermodynamical work and the defibration/fibrillation work.

Innovative energy and mass balance of a continuous evaporating crystallizer

2019 ◽  
pp. 646-654
Author(s):  
Jan Iciek ◽  
Kornel Hulak ◽  
Radosław Gruska
Keyword(s):  
Energy Balance ◽  
Mass Balance ◽  
Working Conditions ◽  
Crystallization Process ◽  
Heat Losses ◽  
Inert Gas ◽  
Gas Removal ◽  
Energy Balances ◽  
Heat Released ◽  
Mass And Energy Balances

The article presents the mass and energy balances of the sucrose crystallization process in a continuous evaporating crystallizer. The developed algorithm allows to assess the working conditions of the continuous evaporating crystallizers and the technological and energy parameters. The energy balance algorithm takes into account the heat released during the crystallization of sucrose, which was analyzed in this study, heat losses to the environment and heat losses due the vapor used for inert gas removal.

scholarly journals Phenotypic clines, energy balances and ecological responses to climate change

2013 ◽  
Vol 83 (1) ◽  
pp. 41-50 ◽  
Author(s):  
Lauren B. Buckley ◽  
César R. Nufio ◽  
Joel G. Kingsolver
Keyword(s):  
Climate Change ◽  
Ecological Responses ◽  
Energy Balances

scholarly journals Multi-Agent System Observer: Intelligent Support for Engaged E-Learning

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1370
Author(s):  
Igor Vuković ◽  
Kristijan Kuk ◽  
Petar Čisar ◽  
Miloš Banđur ◽  
Đoko Banđur ◽  
...  
Keyword(s):  
Machine Learning ◽  
Machine Learning Algorithms ◽  
Intelligent Support ◽  
Course Success ◽  
States Of Emergency ◽  
Learning Platform ◽  
Rapid Spread ◽  
E Learning ◽  
Multi Agent ◽  
Observer System

Moodle is a widely deployed distance learning platform that provides numerous opportunities to enhance the learning process. Moodle’s importance in maintaining the continuity of education in states of emergency and other circumstances has been particularly demonstrated in the context of the COVID-19 virus’ rapid spread. However, there is a problem with personalizing the learning and monitoring of students’ work. There is room for upgrading the system by applying data mining and different machine-learning methods. The multi-agent Observer system proposed in our paper supports students engaged in learning by monitoring their work and making suggestions based on the prediction of their final course success, using indicators of engagement and machine-learning algorithms. A novelty is that Observer collects data independently of the Moodle database, autonomously creates a training set, and learns from gathered data. Since the data are anonymized, researchers and lecturers can freely use them for purposes broader than that specified for Observer. The paper shows how the methodology, technologies, and techniques used in Observer provide an autonomous system of personalized assistance for students within Moodle platforms.

Analyzing the Efficacy of ECoach in Supporting Gateway Course Success Through Tailored Support

2021 ◽  
Author(s):  
Rebecca Matz ◽  
Kyle Schulz ◽  
Elizabeth Hanley ◽  
Holly Derry ◽  
Benjamin Hayward ◽  
...  
Keyword(s):  
Course Success

Responses to exercise, fluid, and energy balances during ramadan in sedentary and active males

Nutrition ◽  
1999 ◽  
Vol 15 (10) ◽  
pp. 735-739 ◽  
Author(s):  
Jasem Ramadan ◽  
Girma Telahoun ◽  
Naji S Al-Zaid ◽  
M Barac-Nieto
Keyword(s):  
Energy Balances
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