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Full-Text Articles in Engineering
Biologically Inspired Design Of Context-Aware Smart Products, Ang Liu, Ivan Teo, Diandi Chen, Stephen Lu, Thorsten Wuest, Zhinan Zhang, Fei Tao
Biologically Inspired Design Of Context-Aware Smart Products, Ang Liu, Ivan Teo, Diandi Chen, Stephen Lu, Thorsten Wuest, Zhinan Zhang, Fei Tao
Faculty & Staff Scholarship
The rapid development of information and communication technologies (ICTs) and cyber–physical sys-tems (CPSs) has paved the way for the increasing popularity of smart products. Context-awareness isan important facet of product smartness. Unlike artifacts, various bio-systems are naturally characterizedby their extraordinary context-awareness. Biologically inspired design (BID) is one of the most commonlyemployed design strategies. However, few studies have examined the BID of context-aware smart prod-ucts to date. This paper presents a structured design framework to support the BID of context-awaresmart products. The meaning of context-awareness is defined from the perspective of product design.The framework is developed based on the theoretical foundations …
Overview Of Smart Manufacturing In West Virginia, Thorsten Wuest, Patrick Schmid, Brian Lego, Eric Bowen
Overview Of Smart Manufacturing In West Virginia, Thorsten Wuest, Patrick Schmid, Brian Lego, Eric Bowen
Bureau of Business & Economic Research
The manufacturing sector is currently reinventing itself by embracing the opportunities offered by the industrial internet, automation, and machine learning, just to name a few. This development is commonly referred to as the Fourth Industrial Revolution or Smart Manufacturing. While Smart Manufacturing can be observed around the globe, there are distinct differences in how it is adopted and embraced between countries, industries, and companies of different sizes. Small- and medium-sized manufacturers are generally understood as the backbone of the manufacturing sector. However, these manufacturers face specific challenges when it comes to the transition toward Smart Manufacturing. This report presents the …
Predictive Models For Charitable Giving Using Machine Learning Techniques, Leily Farrokhvar, Azadeh Ansari, Behrooz Kamali
Predictive Models For Charitable Giving Using Machine Learning Techniques, Leily Farrokhvar, Azadeh Ansari, Behrooz Kamali
Faculty & Staff Scholarship
Private giving represents more than three fourths of all U.S. charitable donations, about 2% of total Gross Domestic Product (GDP). Private giving is a significant factor in funding the nonprofit sector of the U.S. economy, which accounts for more than 10% of total GDP. Despite the abundance of data available through tax forms and other sources, it is unclear which factors influence private donation, and a reliable predictive mechanism remains elu- sive. This study aims to develop predictive models to accurately estimate future charitable giving based on a set of potentially influential factors. We have selected several factors, including unemployment …