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Operations Research, Systems Engineering and Industrial Engineering Commons™
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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian
Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian
I-GUIDE Forum
Given multi-model ensemble climate projections, the goal is to accurately and reliably predict future sea-level rise while lowering the uncertainty. This problem is important because sea-level rise affects millions of people in coastal communities and beyond due to climate change's impacts on polar ice sheets and the ocean. This problem is challenging due to spatial variability and unknowns such as possible tipping points (e.g., collapse of Greenland or West Antarctic ice-shelf), climate feedback loops (e.g., clouds, permafrost thawing), future policy decisions, and human actions. Most existing climate modeling approaches use the same set of weights globally, during either regression or …
Predictive Power And Validity Of Connectome Predictive Modeling: A Replication And Extension, Michael Wang, Joaquin Goni, Enrico Amico
Predictive Power And Validity Of Connectome Predictive Modeling: A Replication And Extension, Michael Wang, Joaquin Goni, Enrico Amico
The Summer Undergraduate Research Fellowship (SURF) Symposium
Neuroimaging, particularly functional magnetic resonance imaging (fMRI), is a rapidly growing research area and has applications ranging from disease classification to understanding neural development. With new advancements in imaging technology, researchers must employ new techniques to accommodate the influx of high resolution data sets. Here, we replicate a new technique: connectome-based predictive modeling (CPM), which constructs a linear predictive model of brain connectivity and behavior. CPM’s advantages over classic machine learning techniques include its relative ease of implementation and transparency compared to “black box” opaqueness and complexity. Is this method efficient, powerful, and reliable in the prediction of behavioral measures …
Improving Product Design Phase For Engineer To Order (Eto) Product With Knowledge Base Engineering (Kbe), Hanhdung Thi Dinh
Improving Product Design Phase For Engineer To Order (Eto) Product With Knowledge Base Engineering (Kbe), Hanhdung Thi Dinh
Open Access Theses
In industry currently Computer Aided Design (CAD) is an important tool for the modification, analysis, or optimization of the 3D virtual environment that replicates the physical product. CAD software is an efficient and reliable tool. However, as globalization increases customer demands, this process needs to be faster and more efficient to accommodate changing product design situations, especially for Engineer-to- Order (ETO) products. ^ The traditional method of product design process is to operate CAD software without argumentation. Design engineers create CAD prototypes and drawings based on available knowledge and information which comes from engineering experts, company standards, industrial practices as …
Calculus For Decision Systems, Jorge Antonio Samayoa Ranero
Calculus For Decision Systems, Jorge Antonio Samayoa Ranero
Open Access Dissertations
The conceptualization of the term "system" has become highly dependent on the application domain. What a physicist means by the term system might be different than what a sociologist means by the same term. In 1956, Bertalanffy [1] defined a system as " a set of units with relationships among them". This and many other definitions of system share the idea of a system as a black box that has parts or elements interacting between each other. This means that at some level of abstraction all systems are similar, what eventually differentiates one system from another is the set of …