Lehigh University

About: Lehigh University is a education organization based out in Bethlehem, Pennsylvania, United States. It is known for research contribution in the topics: Catalysis & Fracture mechanics. The organization has 12684 authors who have published 26550 publications receiving 770061 citations.

Partial Oxidation of Methane

Abstract: Partial oxidation is a widely used process to convert hydrocarbons and alcohols to valuable oxygen-containing chemicals. Although methane is the simplest hydrocarbon which gives formaldehyde and methanol as partial oxidation products, the direct utilization of these reactions for the manufacture of formaldehyde and methanol has remained extremely difficult. During the 1940s, two processes for the conversion of methane to formaldehyde were developed in Germany [l]. The first process used NO as a catalyst, and a commercial plant using this process was known to have been in operation in Copsa Mica in Romania. The second process used a combination of ozone and barium peroxide as the catalyst. In the current industrial practice, however, methane is converted to HCHO through a three-step process involving high temperature steam reforming, low pressure methanol synthesis, and oxidative dehydrogenation of methanol to formaldehyde, as shown by Unlike steam reforming, direct oxidation does not require ener...

Goal Effects on Action and Cognition

Abstract: guslu. 198ö; Karnio"l & Rois, 1996; Karoly, 1993; Kruglan.kil ibgO, Mclntosh & Martin, 1992; Tetlock, 1992) on thii theme. The reasons for this are manifold' Some are rooted in the theoretical developments in the psychology of motivation (see Geen, 1995;-Gollwitzer, t99l; Heckh"or"t, 1991; Kuhl, 1983), others within the impact of the cognitive revolution on social psychology (see Fiske, f9ö3b; Higgins & Bargh, 1987; Smith, 1994; Stevens &

Discovering geographical topics in the twitter stream

Abstract: Micro-blogging services have become indispensable communication tools for online users for disseminating breaking news, eyewitness accounts, individual expression, and protest groups. Recently, Twitter, along with other online social networking services such as Foursquare, Gowalla, Facebook and Yelp, have started supporting location services in their messages, either explicitly, by letting users choose their places, or implicitly, by enabling geo-tagging, which is to associate messages with latitudes and longitudes. This functionality allows researchers to address an exciting set of questions: 1) How is information created and shared across geographical locations, 2) How do spatial and linguistic characteristics of people vary across regions, and 3) How to model human mobility. Although many attempts have been made for tackling these problems, previous methods are either complicated to be implemented or oversimplified that cannot yield reasonable performance. It is a challenge task to discover topics and identify users' interests from these geo-tagged messages due to the sheer amount of data and diversity of language variations used on these location sharing services. In this paper we focus on Twitter and present an algorithm by modeling diversity in tweets based on topical diversity, geographical diversity, and an interest distribution of the user. Furthermore, we take the Markovian nature of a user's location into account. Our model exploits sparse factorial coding of the attributes, thus allowing us to deal with a large and diverse set of covariates efficiently. Our approach is vital for applications such as user profiling, content recommendation and topic tracking. We show high accuracy in location estimation based on our model. Moreover, the algorithm identifies interesting topics based on location and language.

Wireless diversity through network coding

Abstract: This paper investigates the diversity gain offered by implementing network coding (R. Ahlswede et al., 2000) over wireless communication links. The network coding algorithm is applied to both a wireless network containing a distributed antenna system (DAS) as well as one that supports user cooperation between users. The results show that network-coded DAS leads to better diversity performance as compared to conventional DAS, at a lower hardware cost and higher spectral efficiency. In the case of user cooperation, network coding yields additional diversity, especially when there are multiple users

Innovation generation in supply chain relationships: A conceptual model and research propositions

Abstract: Innovation generation has increasingly been recognized as an outcome of interaction between a firm and various outside entities. According to this view, supplier involvement and alliances are routes to innovation generation. Despite this realization, there is a dearth of research, both conceptual and empirical, focusing on innovation generation in buyer-seller relationships in supply chains. In an attempt to fill this void, this article develops a conceptual model of innovation generation in buyer-seller relationships in upstream supply chains. The authors propose that innovation generation in supply chain relationships, both incremental and radical, is a consequence of interactions between buyers and sellers. They also delineate factors internal and external to the relationship that moderate the link between interaction and innovation generation. Finally, the authors discuss managerial implications of their research and offer guidelines for future empirical research.