923 research outputs found

    Seniors Seeking Housing, Health, and Climate Justice, An Oral History of Hurricane Recovery in the Gulf Coast

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    On the Gulf Coast of Texas, a large disparity exists between the number of homes still in need of repair after Hurricane Harvey and the number of homes actually repaired by the City of Houston, Housing and Community Development, 6 years after the storm. This research was conducted through the lens of environmental justice, with attention to climate change impacts and the vulnerability of previously segregated neighborhoods over extended periods of time. The most vulnerable, seniors, were interviewed to collect their personal experiences post Hurricane Harvey to determine the true extent of home damage, how they recovered from the storm, and what impact that recovery period post-storm had on their health and displacement from the home. In the context of a just planning model and through the lens of environmental justice, their ecological knowledge and participation should be used to improve housing recovery. Oral histories allow others an alternative perspective to their own and offer policy makers insight into complex nuances, actors, and events that have transpired post-disaster

    Image-based Decision Support Systems: Technical Concepts, Design Knowledge, and Applications for Sustainability

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    Unstructured data accounts for 80-90% of all data generated, with image data contributing its largest portion. In recent years, the field of computer vision, fueled by deep learning techniques, has made significant advances in exploiting this data to generate value. However, often computer vision models are not sufficient for value creation. In these cases, image-based decision support systems (IB-DSSs), i.e., decision support systems that rely on images and computer vision, can be used to create value by combining human and artificial intelligence. Despite its potential, there is only little work on IB-DSSs so far. In this thesis, we develop technical foundations and design knowledge for IBDSSs and demonstrate the possible positive effect of IB-DSSs on environmental sustainability. The theoretical contributions of this work are based on and evaluated in a series of artifacts in practical use cases: First, we use technical experiments to demonstrate the feasibility of innovative approaches to exploit images for IBDSSs. We show the feasibility of deep-learning-based computer vision and identify future research opportunities based on one of our practical use cases. Building on this, we develop and evaluate a novel approach for combining human and artificial intelligence for value creation from image data. Second, we develop design knowledge that can serve as a blueprint for future IB-DSSs. We perform two design science research studies to formulate generalizable principles for purposeful design — one for IB-DSSs and one for the subclass of image-mining-based decision support systems (IM-DSSs). While IB-DSSs can provide decision support based on single images, IM-DSSs are suitable when large amounts of image data are available and required for decision-making. Third, we demonstrate the viability of applying IBDSSs to enhance environmental sustainability by performing life cycle assessments for two practical use cases — one in which the IB-DSS enables a prolonged product lifetime and one in which the IB-DSS facilitates an improvement of manufacturing processes. We hope this thesis will contribute to expand the use and effectiveness of imagebased decision support systems in practice and will provide directions for future research

    Tradition and Innovation in Construction Project Management

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    This book is a reprint of the Special Issue 'Tradition and Innovation in Construction Project Management' that was published in the journal Buildings

    Towards a Model of Follower Development: Exploring the Success Differentials in Leader and Follower Development Outcomes as Experienced by Bankers in Nigeria.

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    The aim of this qualitative study was to understand the leader and follower development experiences of middle-level managers in the Nigerian banking industry regarding developing followers into leaders. I used two research questions to explore the perception and treatment of followers and the levels of leader and follower development as influences on the development of followers into leaders. The research was set in Nigeria, with a purposive sample of middle-level managers in the Nigerian banking industry. I used a descriptive phenomenological technique to conduct long, deep interviews with 12 middle-level managers via Zoom video and then transcribed them with Otter.ai software. My findings indicate that followers are treated very poorly in the Nigerian banking sector and are perceived as work tools and people with no choice by industry leaders. In addition, leader development is prioritized over follower development, which has been relegated to academic and job-specific training programs that lack leadership skills development. Followers are not intentionally and strategically developed into leaders but rather leaders emerge from those who meet deposit mobilization targets. Banks use the funds mobilized to build their asset base and for trading and lending. Leader development is prioritized, and despite being undertaken through expensive offshore executive training programs, outcomes of the learning points from these programs are not being applied to improve organizations in the industry and their staff because of the leaders’ lackadaisical attitude toward training attendance. The followers, however, attain valuable outcomes from their training programs, which help with performance appraisal and service improvement processes

    2023 GREAT Day Program

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    SUNY Geneseo’s Seventeenth Annual GREAT Day. Geneseo Recognizing Excellence, Achievement & Talent Day is a college-wide symposium celebrating the creative and scholarly endeavors of our students. http://www.geneseo.edu/great_dayhttps://knightscholar.geneseo.edu/program-2007/1017/thumbnail.jp

    Book of Abstracts:9th International Conference on Smart Energy Systems

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