University of Wisconsin–Milwaukee

About: University of Wisconsin–Milwaukee is a education organization based out in Milwaukee, Wisconsin, United States. It is known for research contribution in the topics: Population & Gravitational wave. The organization has 11839 authors who have published 28034 publications receiving 936438 citations. The organization is also known as: UWM & University of Wisconsin-Milwaukee.

Microgrid Generation Capacity Design With Renewables and Energy Storage Addressing Power Quality and Surety

Abstract: Microgrids are receiving attention due to the increasing need to integrate distributed generations and to insure power quality and to provide energy surety to critical loads. Since renewables need to be in the mix for energy surety, a high renewable-energy penetrated microgrid is analyzed in this paper. The standard IEEE 34 bus distribution feeder is adapted and managed as a microgrid by adding distributed generation and load profiles. The 25 kV system parameters are scaled down to 12 kV and renewable sources including solar PV and wind turbines, an energy storage system, and a diesel generator for islanded mode have been added to the 34-bus system. The distribution generations (DG) and renewables are modeled in detail using PSCAD software and practical constraints of the components are considered. The monitoring of the microgrid for measuring power quality and control requirements for these DGs and storage are modeled to maintain the power quality of the system when loads are varied. Renewable sources are modeled with seasonal variation at different locations. The microgrid is monitored at number of buses and the power quality issues are measured and indexes are calculated. This paper proposes a generalized approach to design (determine the capacity requirements) and demonstrates the management of microgrids with metrics to meet the power quality indexes.

E-manufacturing—fundamental, tools, and transformation

Abstract: Manufacturing industry worldwide has been facing unprecedented challenges brought by ever changing, global and competitive market conditions as well as changing social demands, regional, governmental and environmental regulations. E-commerce and Internet technologies injected “velocity” into the front business activities and enabled companies to shift their manufacturing operations from the traditional factory integration philosophy to a supply chain-based e-factory philosophy. It transforms companies from a local factory focus to a global enterprise and business focus. This paper introduces e-manufacturing as a new concept to answer the aforementioned needs of business strategies for complete integration of all business elements including suppliers, customer service network and manufacturing units by leveraging the Internet, web-enabling, tether-free technologies and computational tools. Enabling tools will be introduced to support e-manufacturing includes the ability to monitor the plant floor assets, and predict the variation and performance loss for dynamic rescheduling of production and maintenance operations, and synchronize with other related business actions to achieve a complete integration between manufacturing systems and upper-level enterprise applications. Finally, infotronics technologies for next-generation e-manufacturing transformation are discussed.

The influence of reviewer engagement characteristics on online review helpfulness: A text regression model

Abstract: The era of Web 2.0 is witnessing the proliferation of online social media platforms, which develop new business models by leveraging user-generated content. One rapidly growing source of user-generated data is online reviews, which play a very important role in disseminating information, facilitating trust, and promoting commerce in the e-marketplace. In this paper, we develop and compare several text regression models for predicting the helpfulness of online reviews. In addition to using review words as predictors, we examine the influence of reviewer engagement characteristics such as reputation, commitment, and current activity. We employ a reviewer's RFM (Recency, Frequency, Monetary Value) dimensions to characterize his/her overall engagement and investigate if the inclusion of those dimensions helps improve the prediction of online review helpfulness. Empirical findings from text mining experiments conducted using reviews from Yelp and Amazon offer strong support to our thesis. We find that both review text and reviewer engagement characteristics help predict review helpfulness. The hybrid approach of combining the textual features of bag-of-words model and RFM dimensions produces the best prediction results. Furthermore, our approach facilitates the estimation of the helpfulness of new reviews instantly, making it possible for social media platforms to dynamically adjust the presentation of those reviews on their websites.

Alginate/graphene double-network nanocomposite hydrogel beads with low-swelling, enhanced mechanical properties, and enhanced adsorption capacity

Abstract: As a novel material, double network hydrogels have attracted great attention in recent years for their excellent mechanical properties; however, several other characteristics are yet to be improved. Here we report the synthesis of a novel alginate/reduced graphene oxide (RGO) double-network (GAD) hydrogel through a facile method, and investigate the GAD's mechanical properties, stability, and adsorption capacity in comparison with those of an alginate/RGO single network hydrogel (GAS). To produce the GAD, the first network of alginate is formed with randomly distributed graphene oxide (GO), resulting in the GAS; then the GAS is treated by a hydrothermal reduction, through which the GO is reduced and self-assembles into a second RGO network interpenetrating with the first, alginate network, forming the double-network GAD. The mechanism of the GAD formation is investigated and the property differences between the GAS and the GAD are examined. The resulting GAD exhibits a higher Young's modulus than the GAS, and the modulus increases with GO concentrations. The GAD also has a lower swelling ratio than the GAS, which leads to improved gel stability in highly concentrated alkali/salt solutions. The GAD beads exhibit an excellent adsorption capacity (Cu2+, 169.5 mg g−1 and Cr2O72−, 72.5 mg g−1) for heavy metal ions, far better than that of the GAS. Even after 10 regeneration cycles, both GAS and GAD can still retain their considerable adsorption capacity for metals. The results of this work are of great significance to double network gel research, especially for environmental applications. With good stability, adsorption capacity, and regeneration ability, the double network gel could be a promising adsorbent nanomaterial for pollutant removal from aqueous solutions.