15133 research outputs found
Sort by
Depth of the Lake
No full texthttps://digitalcommons.montclair.edu/iapc_nature_gallery/1013/thumbnail.jp
Eyes and the Impossible
No full texthttps://digitalcommons.montclair.edu/iapc_nature_gallery/1016/thumbnail.jp
Standard operating procedures for the laser particle size analysis of terrigenous sediments and soils
Full text linkThis report details the preferred standard operating procedures for use of the Malvern Mastersizer 3000 (MS 3000) laser particle sizer in the analysis of terrigenous sediments and soils. Materials with median grain size \u3c 500 µm can be measured on the MS3000. Preparation methods of sediment and soil samples before placing them in the laser particle sizer are described and the details of and rational behind the instrument standard operating protocols
Shea at Mendham 2024
No full texthttps://digitalcommons.montclair.edu/iapc_pshea_gallery/1005/thumbnail.jp
Suzuki Harunobu: Couple Reading a Letter (1770)
No full texthttps://digitalcommons.montclair.edu/iapc_thinking_gallery/1009/thumbnail.jp
Boy Reading a Magazine by Patty Rodgers
No full textUsed with permission of the artist.https://digitalcommons.montclair.edu/iapc_thinking_gallery/1020/thumbnail.jp
Making fractals: Expanding learning opportunities in the classroom
Full text linkFractals have long been appreciated for their beautiful, self-similar structure and infinite complexity. Commonly found in art and architecture, fractals are not only visually appealing but they have been found to reduce stress in individuals because of their patterns’ connections to nature. Fractal structures can even be seen in familiar real-life objects like trees or cauliflowers. Fractal geometry, with its ability to create complicated effects from simple formulas, provides a way to connect mathematics with visual results that are “spontaneously attractive, and often breathtakingly beautiful . The act of creating fractals can spark curiosity, enabling participants to generate vastly different results by introducing seemingly small changes
Smart cities, smart systems: A comprehensive review of system dynamics model applications in urban studies in the big data era
Full text linkThis paper addresses urban sustainability challenges amid global urbanization, emphasizing the need for innovative approaches aligned with the Sustainable Development Goals. While traditional tools and linear models offer insights, they fall short in presenting a holistic view of complex urban challenges. System dynamics (SD) models that are often utilized to provide holistic, systematic understanding of a research subject, like the urban system, emerge as valuable tools, but data scarcity and theoretical inadequacy pose challenges. The research reviews relevant papers on recent SD model applications in urban sustainability since 2018, categorizing them based on nine key indicators. Among the reviewed papers, data limitations and model assumptions were identified as major challenges in applying SD models to urban sustainability. This led to exploring the transformative potential of big data analytics, a rare approach in this field as identified by this study, to enhance SD models’ empirical foundation. Integrating big data could provide data-driven calibration, potentially improving predictive accuracy and reducing reliance on simplified assumptions. The paper concludes by advocating for new approaches that reduce assumptions and promote real-time applicable models, contributing to a comprehensive understanding of urban sustainability through the synergy of big data and SD models
A comprehensive assessment approach for multiscale regional economic development: Fusion modeling of nighttime lights and OpenStreetMap data
Full text linkAssessing regional economic development is key for advancing towards the Sustainable Development Goals and ensuring sustainable societal progress. Traditional evaluation methods focus on basic economic metrics like population and capital, which may not fully reflect the complexities of economic activities. Nighttime light (NTL) has been validated as an alternative indicator for regional economic development, yet limitations persist in its evaluation. This study integrates OpenStreetMap (OSM) data and NTL data, providing a novel data integration approach for evaluating economic development. The study uses mainland of China as a case, applying ordinary least squares (OLS) and geographically weighted regression (GWR) to evaluate OSM and NTL data across provincial, municipal, and county levels. It compares OSM, NTL, and their combined use, providing key empirical insights for enhancing data fusion models. The study results reveal: (1) NTL data is more accurate for provincial-level economic activity, while OSM data excels at the county level. (2) GWR demonstrates superior capability over OLS in revealing the spatial dynamics of economic development across scales. (3) Through the integration of both datasets, it is observed that, compared to single-data modeling, the performance is enhanced at the city scale and county scale. The study demonstrates that combining OSM and NTL data effectively assesses economic development in both developed and underdeveloped areas at provincial, municipal, and county levels. The study offers a straightforward and efficient approach to data integration. The findings offer new research perspectives and scientific support for sustainable regional economic growth, particularly valuable in data-scarce, underdeveloped areas