Improving Multiclass Text Classification with the Support Vector Machine

We compare Naive Bayes and Support Vector Machines on the task of multiclass text classification. Using a variety of approaches to combine the underlying binary classifiers, we find that SVMs substantially outperform Naive Bayes. We present full multiclass results on two well-known text data sets, including the lowest error to date on both data sets. We develop a new indicator of binary performance to show that the SVM's lower multiclass error is a result of its improved binary performance. Furthermore, we demonstrate and explore the surprising result that one-vs-all classification performs favorably compared to other approaches even though it has no error-correcting properties

Using Social Networking for Educational and Cultural Adaptation: An Exploratory Study

This study investigates how an innovative technology, social networking, can be used in the process of building and maintaining social capital and exchanging knowledge in an educational setting. We employ a qualitative methodology, autoethnography, to examine how social networking can help students learn from other classmates and professors, exchange knowledge, and adjust both to a new program of study and to living in the United States. Using the theoretical foundation of social capital (Jacobs, 1960) and a social support framework created by Drentea and Moren-Cross (2005), autobiographical narratives are classified as instrumental support, emotional support, and community building. Our findings provide evidence that social networking sites can enhance social capital through these mechanisms in a doctoral education context, and our research serves as an important first step in addressing a gap in educational and cultural adaptation studies using social networking tools

Demonstration of a Thermally Coupled Row-Column SNSPD Imaging Array

While single-pixel superconducting nanowire single photon detectors (SNSPDs) have demonstrated remarkable efficiency and timing performance from the UV to near-IR, scaling these devices to large imaging arrays remains challenging. Here, we propose a new SNSPD multiplexing system using thermal coupling and detection correlations between two photosensitive layers of an array. Using this architecture with the channels of one layer oriented in rows and the second layer in columns, we demonstrate imaging capability in 16-pixel arrays with accurate spot tracking at the few-photon level. We also explore the performance trade-offs of orienting the top layer nanowires parallel and perpendicular to the bottom layer. The thermally coupled row-column scheme is readily able to scale to the kilopixel size with existing readout systems and, when combined with other multiplexing architectures, has the potential to enable megapixel scale SNSPD imaging arrays

Photon-weighted barycentric correction and its importance for precise radial velocities

When applying the barycentric correction to a precise radial velocity measurement, it is common practice to calculate its value only at the photon-weighted midpoint time of the observation instead of integrating over the entire exposure. However, since the barycentric correction does not change linearly with time, this leads to systematic errors in the derived radial velocities. The typical magnitude of this second-order effect is of order 10 cm s$^{-1}$, but it depends on several parameters, e.g. the latitude of the observatory, the position of the target on the sky, and the exposure time. We show that there are realistic observing scenarios, where the errors can amount to more than 1 ms$^{-1}$. We therefore recommend that instruments operating in this regime always record and store the exposure meter flux curve (or a similar measure) to be used as photon-weights for the barycentric correction. In existing data, if the flux curve is no longer available, we argue that second-order errors in the barycentric correction can be mitigated by adding a correction term assuming constant flux.Comment: 9 pages, 7 figures, accepted to MNRA

Flexible macrocycles as versatile supports for catalytically active metal clusters

Here we present three structurally diverse clusters stabilised by the same macrocyclic polyphenol; t-butylcalix[8]arene. This work demonstrates the range of conformations the flexible ligand is capable of adopting, highlighting its versatility in metal coordination. In addition, a Ti complex displays activity for the ring-opening polymerisation of lactide

TurbuStat: Turbulence Statistics in Python

We present TurbuStat (v1.0): a Python package for computing turbulence statistics in spectral-line data cubes. TurbuStat includes implementations of fourteen methods for recovering turbulent properties from observational data. Additional features of the software include: distance metrics for comparing two data sets; a segmented linear model for fitting lines with a break-point; a two-dimensional elliptical power-law model; multi-core fast-fourier-transform support; a suite for producing simulated observations of fractional Brownian Motion fields, including two-dimensional images and optically-thin HI data cubes; and functions for creating realistic world coordinate system information for synthetic observations. This paper summarizes the TurbuStat package and provides representative examples using several different methods. TurbuStat is an open-source package and we welcome community feedback and contributions.Comment: Accepted in AJ. 21 pages, 8 figure

Flight-Test Evaluation of Kinematic Precise Point Positioning of Small UAVs

An experimental analysis of Global Positioning System (GPS) flight data collected onboard a Small Unmanned Aerial Vehicle (SUAV) is conducted in order to demonstrate that postprocessed kinematic Precise Point Positioning (PPP) solutions with precisions approximately 6 cm 3D Residual Sum of Squares (RSOS) can be obtained on SUAVs that have short duration flights with limited observational periods (i.e., only ∼≤5 minutes of data). This is a significant result for the UAV flight testing community because an important and relevant benefit of the PPP technique over traditional Differential GPS (DGPS) techniques, such as Real-Time Kinematic (RTK), is that there is no requirement for maintaining a short baseline separation to a differential GNSS reference station. Because SUAVs are an attractive platform for applications such as aerial surveying, precision agriculture, and remote sensing, this paper offers an experimental evaluation of kinematic PPP estimation strategies using SUAV platform data. In particular, an analysis is presented in which the position solutions that are obtained from postprocessing recorded UAV flight data with various PPP software and strategies are compared to solutions that were obtained using traditional double-differenced ambiguity fixed carrier-phase Differential GPS (CP-DGPS). This offers valuable insight to assist designers of SUAV navigation systems whose applications require precise positionin

A Leadership Knowledge Management Model for E-Government: A Preliminary Empirical Test

Although technology has greatly enhanced the ability of government to provide resources electronically, there is still a need for the development of knowledge management systems that potentially improve flexibility and provide citizens with better service. As e-government continues to grow, a key area is the advancement of leadership to increasingly provide effective knowledge resources to the public sector. Drawing from the Malcolm Baldrige National Quality Award (MBNQA) leadership triad as a research framework, the purpose of this study is to develop and test a model that identifies the relationship between leadership and knowledge management within a city government. The study, conducted over a fiveweek period, indicated a strong relationship between the MBNQA leadership triad and knowledge management