Exploring App-Based Taxi Movement Patterns from Large-Scale Geolocation Data

This study is designed to leverage ubiquitous mobile computing techniques on exploring app-based taxi movement patterns in large cities. To study patterns at different scales, we comprehensively explore both occupied and unoccupied vehicle movement characteristics through not only individual trips but also their aggregations. Moran’s I and its variations are applied to explore spatial autocorrelations among different rides. PageRank centrality is applied for a functional network representing traffic flows to discover places of interest. Gyration radius measures the scope of passenger mobility and driver passenger searching. Moreover, cumulative distribution and data visualization techniques are adopted for trip level characteristics and features analysis. The results indicate that the app-based taxi services are serving more neighborhoods other than downtown areas by taking large proportion of relatively shorter trips and contributing to net increase in total taxi ridership although net decrease in downtown areas. The spatial autocorrelations are significant not only within each service but also among services. With the smartphone-based applications, app-based taxi services are able to search passengers in a larger area and move more efficiently during both occupied and unoccupied periods. Mining from huge empty trip trajectory by app-based taxis, we also identify the existence of stationary/stops state and circulations.

Social Network for Game of Thrones

Along with growing interest and use, the concept of network analysis has taken a new direction to explore data and facts to find existing patterns. The paper highlights the importance of social network analysis in analyzing and mining useful information from the data across various domains. It provides an insight into need, importance and scope of Social Network Analysis. With the use of Social networking tool like NetworkX, data is being represented in the form of graph or network which is then analyzed in a more efficient way making it easier to study the interactions between different persons in Game of thrones and establishing trends existing in a network. A comparative analysis of various centrality measures such as Degree centrality, Betweenness centrality, Closeness centrality, PageRank centrality is performed to explore the features associated to find the most important character of the series based on obtained results.

Complex network model indicates a positive effect of inspiratory muscles pre-activation on performance parameters in a judo match

This study investigated the effects of inspiratory muscle pre-activation (IMPA) on the interactions among the technical-tactical, physical, physiological, and psychophysiological parameters in a simulated judo match, based on the centrality metrics by complex network model. Ten male athletes performed 4 experimental sessions. Firstly, anthropometric measurements, maximal inspiratory pressure (MIP) and global strenght of the inspiratory muscles were determined. In the following days, all athletes performed four-minute video-recorded judo matches, under three conditions: without IMPA (CON), after IMPA at 15% (IMPA15), and at 40% (IMPA40) of MIP using an exerciser device. Blood lactate, heart rate and rating of perceived exertion were monitored, and the technical-tactical parameters during the match were related to offensive actions and the time-motion. Based on the complex network, graphs were constructed for each scenario (CON, IMPA15, and IMPA40) to investigate the Degree and Pagerank centrality metrics. IMPA40 increased the connectivity of the physical and technical-tactical parameters in complex network and highlighted the combat frequency and average combat time in top-five ranked nodes. IMPA15 also favoured the interactions among the psychophysiological, physical, and physiological parameters. Our results suggest the positive effects of the IMPA, indicating this strategy to prepare the organism (IMPA15) and to improve performance (IMPA40) in judo match.

Concept Mapping in Magnetism and Electrostatics: Core Concepts and Development over Time

Conceptual change theories assume that knowledge structures grow during the learning process but also get reorganized. Yet, this reorganization process itself is hard to examine. By using concept maps, we examined the changes in students’ knowledge structures and linked it to conceptual change theory. In a longitudinal study, thirty high-achieving students (M = 14.41 years) drew concept maps at three timepoints across a teaching unit on magnetism and electrostatics. In total, 87 concept maps were analyzed using betweenness and PageRank centrality as well as a clustering algorithm. We also compared the students’ concept maps to four expert maps on the topic. Besides a growth of the knowledge network, the results indicated a reorganization, with first a fragmentation during the unit, followed by an integration of knowledge at the end of the unit. Thus, our analysis revealed that the process of conceptual change on this topic was non-linear. Moreover, the terms used in the concept maps varied in their centrality, with more abstract terms being more central and thus more important for the structure of the map. We also suggest ideas for the usage of concept maps in class.