Description: In this paper, the authors introduce TextRank, a graph-based ranking model for text processing, and show how this model can be successfully used in natural language applications. In particular, the authors propose two innovative unsupervised methods for keyword and sentence extraction, and show that the results obtained compare favorably with previously published results on established benchmarks.

Description: In this article, an enhanced channel-assignment algorithm at the Access Points (APs) of a Wireless Local Area Network (WLAN) is validated. The algorithm aims to maximize the Signal-to-Interference Ratio (SIR) at the user level in order to determine the appropriate channel at the APs. The initial channel assignment step at the APs is based on minimizing the total interference between APs. Based on this initial assignment, the SIR for each user is calculated. Then, another channel assignment is performed based on maximizing the SIR at the users. The algorithm can be applied to any WLAN, irrespective of the user distribution and user load. Results show that the algorithm is capable of significantly increasing the SIR over the WLAN, which in turn should improve throughput. Therefore, the authors use OPNET simulation tool to construct several realistic scenarios in order to validate our results.

Description: This paper evaluates the hypothesis that pictorial representations can be used to effectively convey simple sentences across language barriers. Comparative evaluations show that a considerable amount of understanding can be achieved using visual descriptions of information, with evaluation figures within a comparable range of those obtained with linguistic representations produced by an automatic machine translation system.

Description: This paper discusses a transformational paradigm for engineering and engineering technology education. The knowledge explosion in science, technology, engineering & mathematics (STEM) over the past decades is unquestionably overwhelming. It is important that those involved in STEM quickly adapt. Life-long learning has taken a do-or-die slant, as technological breakthroughs turn obsolete within only a few years of their inception. Medical and law degree curricula became more "professional" and require a "pre-degree" status to be considered for admission. However, the traditional engineering degree plan is essentially the same as that of the mid 20th Century. Legislation in some states places additional pressure on baccalaureate degrees by questioning the need for anything above 120 credit hours. The result is (i) fewer engineering-specific courses; (ii) courses that heavily emphasize theory; and (iii) a subsequent reduction in hands-on, laboratory oriented, experimental learning. Engineering Technology curricula are designed to have experiential learning as the educational backbone. This forces a reduction in mathematical and scientific depth that is compensated by a richness of laboratory courses in almost one-to-one proportion to lecture courses, and which emphasize the application of engineering. The main challenges to establish and maintain experiential learning include (i) availability of slots in the curricula ...

Description: This paper describes an unsupervised graph-based method for word sense disambiguation, and presents comparative evaluations using several measures of word semantic similarity and several algorithms for graph centrality. The results indicate that the right combination of similarity metrics and graph centrality algorithms can lead to a performance competing with the state-of-the-art in unsupervised word sense disambiguation, as measured on standard data sets.