Worcester Polytechnic Institute

About: Worcester Polytechnic Institute is a education organization based out in Worcester, Massachusetts, United States. It is known for research contribution in the topics: Computer science & Population. The organization has 6270 authors who have published 12704 publications receiving 332081 citations. The organization is also known as: WPI.

Integrating New Technical Staff: Implications for Acquiring New Technology

Abstract: Hiring new staff in R&D provides an important opportunity for a firm to acquire new technological knowledge. It also takes a considerable length of time before new R&D staff become fully integrated into the organization. This study compares the communication patterns of new and veteran R&D staff as a function of their work activities. The results suggest that both the benefits and problems in the hiring and integration of new R&D staff is moderated by the type of research, development or technical service work involved. Particular attention should be paid to the integration of new staff involved in new product or process development, where the benefits of bringing in new people are great, but the communication barriers to overcome are also found to be the most serious.

An input-output analysis of the construction sector in highly developed economies

Abstract: Using OECD input/output tables at current and constant prices, this paper analyses the performance of the construction sector of eight highly industrialized countries - Australia, Canada, Denmark, France, Germany, The Netherlands, Japan and the USA - in the 1970s and 1980s First, the main characteristics of the data set with country and time coverage are briefly introduced Then, a set of simple indicators is used for comparative purposes, namely to assess the construction sector's diminishing role in terms of share in gross output, value added and GNP Analysis focuses also on technologies, with emphasis on the relative role of manufacturing and services inputs Lastly, standard measures of linkages are used to determine the main sources of induced output that are created by the push and pull effects of the construction sector on the rest of the economy

Graph Convolutional Networks with Motif-based Attention

Abstract: The success of deep convolutional neural networks in the domains of computer vision and speech recognition has led researchers to investigate generalizations of the said architecture to graph-structured data. A recently-proposed method called Graph Convolutional Networks has been able to achieve state-of-the-art results in the task of node classification. However, since the proposed method relies on localized first-order approximations of spectral graph convolutions, it is unable to capture higher-order interactions between nodes in the graph. In this work, we propose a motif-based graph attention model, called Motif Convolutional Networks, which generalizes past approaches by using weighted multi-hop motif adjacency matrices to capture higher-order neighborhoods. A novel attention mechanism is used to allow each individual node to select the most relevant neighborhood to apply its filter. We evaluate our approach on graphs from different domains (social networks and bioinformatics) with results showing that it is able to outperform a set of competitive baselines on the semi-supervised node classification task. Additional results demonstrate the usefulness of attention, showing that different higher-order neighborhoods are prioritized by different kinds of nodes.