Geo-Information Technology and Its Applications

Geo-information technology has been playing an ever more important role in environmental monitoring, land resource quantification and mapping, geo-disaster damage and risk assessment, urban planning and smart city development. This book focuses on the fundamental and applied research in these domains, aiming to promote exchanges and communications, share the research outcomes of scientists worldwide and to put these achievements better social use. This Special Issue collects fourteen high-quality research papers and is expected to provide a useful reference and technical support for graduate students, scientists, civil engineers and experts of governments to valorize scientific research

Economic theory and asset bubbles

The author summarizes what economic theory tells us about when asset price bubbles can occur and what the welfare implications are from bursting them. In some cases, bursting a bubble may make society worse off by exacerbating the market distortions that give rise to the bubble in the first place.Asset-liability management ; Asset pricing

The BG News January 17, 1989

The BGSU campus student newspaper January 17, 1989. Volume 71 - Issue 69https://scholarworks.bgsu.edu/bg-news/5883/thumbnail.jp

The BG News January 17, 1989

The BGSU campus student newspaper January 17, 1989. Volume 71 - Issue 69https://scholarworks.bgsu.edu/bg-news/5883/thumbnail.jp

ACM SIGMIS CPR Panel Report: Should Information Systems Professors be More Techno-savvy than Students? (And What Would that Mean for Teaching in Times of the COVID-19 Crisis?)

Rapid advances in information and communication technologies present a challenge to information systems (IS) professors. Not only do these advances frequently make course materials out of date, but also IS professors may struggle to stay current with popular technology applications. In a sense, these forces lead to a paradox that students may be more techno-savvy than their professors (at least in certain areas). Furthermore, students may feel frustrated when techno-savvy professors cannot efficiently teach them in learning technologies. In this paper, we synthesize the panel titled “The Elephant in the Classroom: Do Information Systems Professors Need to be more Techno-Savvy than Students?” at the 55th ACM SIGMIS Computer and People Research Conference in Nashville, Tennessee. Thomas Ferratt, Michael Gallivan, Yaojie Li, Thomas Stafford, Mary Sumner, and Crag Van Slyke served as panelists. We use their discussion to develop techno-savviness as a construct in the IS education context and to describe distinct types of techno-savviness

Andrew W. Mellon Foundation - 1999 Annual Report

Contains president's message, program information, summary of foundation initiatives, grants list, financial statements, and list of staff

Research in the iSchools: An Examination

The iSchool movement is not merely a reaction of the information science community to the criticism that there is a mismatch between LIS education and needs of the information job market but also represents the growing recognition that there is a need to elevate the status of the discipline in the higher education system to a level on par with other professions/disciplines. This paper attempts to construct the domain of interest to the iSchools by profiling the ongoing and recent research in the iSchools. The profiling is carried out by examining the publications emanating from six iSchools. The findings suggest that there is as yet no clear construct of what constitutes the domain of interest of iSchools. The research profiles of these iSchools also appear to differ significantly. The study also suggests the emergence of certain new information specialities

Machine Learning and Data Mining Applications in Power Systems

This Special Issue was intended as a forum to advance research and apply machine-learning and data-mining methods to facilitate the development of modern electric power systems, grids and devices, and smart grids and protection devices, as well as to develop tools for more accurate and efficient power system analysis. Conventional signal processing is no longer adequate to extract all the relevant information from distorted signals through filtering, estimation, and detection to facilitate decision-making and control actions. Machine learning algorithms, optimization techniques and efficient numerical algorithms, distributed signal processing, machine learning, data-mining statistical signal detection, and estimation may help to solve contemporary challenges in modern power systems. The increased use of digital information and control technology can improve the grid’s reliability, security, and efficiency; the dynamic optimization of grid operations; demand response; the incorporation of demand-side resources and integration of energy-efficient resources; distribution automation; and the integration of smart appliances and consumer devices. Signal processing offers the tools needed to convert measurement data to information, and to transform information into actionable intelligence. This Special Issue includes fifteen articles, authored by international research teams from several countries

COVID-2019 Impacts on Education Systems and Future of Higher Education

The rapid outbreak of the COVID-19 has presented unprecedented challenges on education systems. Closing schools and universities and cancelling face-to-face activities have become a COVID-19 inevitable reality in most parts of the world. To be business-as-usual, many higher education providers have taken steps toward digital transformation, and implementing a range of remote teaching, learning and assessment approaches. This book provides timely research on COVID-19 impacts on education systems and seeks to bring together scholars, educators, policymakers and practitioners to collectively and critically identify, investigate and share best practices that lead to rethinking and reframing the way we deliver education in future