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Title: Armour Tech News, April 09, 1928
Creator: Armour Institute of Technology
Date: 1928-04-09, 1928-04-09
Collection: Technology News Microfilm collection, 1928-1981

Title: Armour Tech News, February 28, 1933
Creator: Armour Institute of Technology
Date: 1933-02-28, 1933-02-28
Collection: Technology News Microfilm collection, 1928-1981

Title: Armour Tech News, March 14, 1933
Creator: Armour Institute of Technology
Date: 1933-03-14, 1933-03-14
Collection: Technology News Microfilm collection, 1928-1981

Title: Armour Tech News, March 21, 1933
Creator: Armour Institute of Technology
Date: 1933-03-21, 1933-03-21
Collection: Technology News Microfilm collection, 1928-1981

Title: Armour Tech News, April 11, 1933
Creator: Armour Institute of Technology
Date: 1933-04-11, 1933-04-11
Collection: Technology News Microfilm collection, 1928-1981

Title: Armour Tech News, March 07, 1933
Creator: Armour Institute of Technology
Date: 1933-03-07, 1933-03-07
Collection: Technology News Microfilm collection, 1928-1981

Title: Tech News
Creator: Illinois Institute of Technology
Date: 1928-
Publisher: Illinois Institute of Technology

Title: Armour Tech News, April 04, 1933
Creator: Armour Institute of Technology
Date: 1933-04-04, 1933-04-04
Collection: Technology News Microfilm collection, 1928-1981

Title: Armour Tech News, March 28, 1933
Creator: Armour Institute of Technology
Date: 1933-03-28, 1933-03-28
Collection: Technology News Microfilm collection, 1928-1981

Title: Armour Tech News, November 21, 1933
Creator: Armour Institute of Technology
Date: 1933-11-21, 1933-11-21
Collection: Technology News Microfilm collection, 1928-1981

Title: Armour Tech News, December 19, 1933
Creator: Armour Institute of Technology
Date: 1933-12-19, 1933-12-19
Collection: Technology News Microfilm collection, 1928-1981

Title: Armour Tech News, January 23, 1934
Creator: Armour Institute of Technology
Date: 1934-01-23, 1934-01-23
Collection: Technology News Microfilm collection, 1928-1981

Title: Armour Tech News, October 17, 1933
Creator: Armour Institute of Technology
Date: 1933-10-17, 1933-10-17
Collection: Technology News Microfilm collection, 1928-1981

Title: Armour Tech News, October 18, 1928
Creator: Armour Institute of Technology
Date: 1928-10-18, 1928-10-18
Collection: Technology News Microfilm collection, 1928-1981

Title: Armour Tech News, January 17, 1929
Creator: Armour Institute of Technology
Date: 1929-01-17, 1929-01-17
Collection: Technology News Microfilm collection, 1928-1981

Title: Armour Tech News, September 27, 1928
Creator: Armour Institute of Technology
Date: 1928-09-27, 1928-09-27
Collection: Technology News Microfilm collection, 1928-1981

Title: Armour Tech News, January 24, 1929
Creator: Armour Institute of Technology
Date: 1929-01-24, 1929-01-24
Collection: Technology News Microfilm collection, 1928-1981

Title: Armour Tech News, October 25, 1928
Creator: Armour Institute of Technology
Date: 1928-10-25, 1928-10-25
Collection: Technology News Microfilm collection, 1928-1981

Title: A Hybrid Data-Driven Simulation Framework For Integrated Energy-Air Quality (iE-AQ) Modeling at Multiple Urban Scales
Creator: Ashayeri, Mehdi
Date: 2020
Description: To date, limited work has been done to collectively incorporate two key urban challenges: climate change and air pollution for the design of...
Show moreTo date, limited work has been done to collectively incorporate two key urban challenges: climate change and air pollution for the design of sustainable and healthy built environments. Main limitations to doing so include the existence of large spatiotemporal gaps in local outdoor air pollution data and a lack of a formal theoretical framework to effectively integrate localized urban air pollution data into sustainable built environment design strategies such as natural ventilation in buildings. This work hypothesizes that emerging advanced computational modeling approaches, including artificial intelligence (AI) and machine learning (ML) techniques, along with big open data set initiatives, can be used to fill some of those gaps. This can be achieved if urban air quality explanatory factors are properly identified and effectively connected to the current building performance simulation workflows.Therefore, the primary objective of this dissertation is to develop a hybrid AI-based data-driven simulation framework for integrated Energy-Air Quality (iE-AQ) modeling to quantify the combined energy reduction profiles and health risks implications of sustainable built environment design. This framework (1) incorporates dynamic human-centered factors, including mobility and building occupancy among others into the model, (2) interlinks land use regression (LUR), inverse distance weighting (IDW), and building energy simulation (BES) approaches via the R computational platform for developing the model, and (3) develops a web-based platform and interactive tool for visualizing and communicating the results. A series of novel machine learning approaches are tested within the workflow to improve efficiency and accuracy of the simulation model. A multi-scale model of urban air quality (using PM2.5 concentrations as the end point) and weather localization model with high spatiotemporal resolution was developed for Chicago, IL using low-cost sensor data. The integrated energy and air quality model was tested for the prototype office building at multiple urban scales in Chicago through applying air pollution-adjusted natural ventilation suitable hours.Results showed that the proposed ML approaches improved model accuracy above traditional simulation and statistical modeling approaches and that incorporating dynamic building-related factors such as human activity patterns can further improve urban air quality prediction models. The results of integrated energy and air quality (iE-AQ) analysis highlight that the energy saving potentials for natural ventilation considering local ambient air pollution and micro-climate data vary from 5.2% to 17% within Chicago. The proposed framework and tool have the potential to aid architects, engineers, planners and urban health policymakers in designing sustainable cities and empowering analytical solutions for reducing human health risk.
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Title: A MULTIPLE CASE STUDY OF COLLEGE MATHEMATICS INSTRUCTORS’ TECHNOLOGICAL PEDAGOGICAL CONTENT KNOWLEDGE (TPACK) AND ITS RELATIONSHIP TO THE INTEGRATION OF INFORMATION AND COMMUNICATIONS TECHNOLOGY (ICT) IN THEIR TEACHING PRACTICES AND STUDENTS’ LEARNING
Creator: Alhejoj, Kawkab
Date: 2020
Description: This multiple-case study aimed to investigate the following essential aspects of instructors’ ICT integration in higher education: self...
Show moreThis multiple-case study aimed to investigate the following essential aspects of instructors’ ICT integration in higher education: self-reported technological pedagogical content knowledge (TPACK), level of ICT integration, and motivations-challenges to integrate specific ICT tools to teach particular mathematics concepts. Four college math instructors were selected purposefully from four community colleges. The TPACK conceptual framework was adopted through the use of the TPACK-M self-assessment survey to understand the perceived TPACK knowledge of the instructors. The model of Niess et al (2009), which describes the teacher’s level of practical ICT integration in the light of their TPACK, assisted in exploring the way college math instructors used ICT. Data collection involved surveys, semi-structured interviews, and direct classroom observations. Quantitative data was analyzed using descriptive statistics, while Atlas.ti software was applied for qualitative data. The findings showed that the total TPACK-M was rated high, with TPK the lowest among all the constructs. In terms of the ICT integration model, one instructor fitted into the recognizing level, another into the adapting level, and two others into the accepting level. There was a misalignment between the self-reported TPACK knowledge and the in-class level of ICT integration. Instructors need more support in developing practical TPACK abilities via effective PD and activating the “teacher model” to help college math instructors integrate ICT in creative and successful practice. Also, more research in higher education is recommended using a larger sample in the area of designing a TPACK instrument for college math instructors to help capture their perceptions and recognize any gap between what they know and what they do in higher education contexts.
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