Insecta Mundi: procedures, production, and publication

This article outlines changes in procedures and production policies for the journal Insecta Mundi. Background data and discussions leading to these necessary changes are explained. Updated instructions for authors are presented. A full current version of author instructions will be posted on the latest Center for Systematic Entomology URL

The Development of a Fiber Optic Raman Temperature Measurement System for Rocket Flows

A fiberoptic Raman diagnostic system for H2/O2 rocket flows is currently under development. This system is designed for measurement of temperature and major species concentration in the combustion chamber and part of the nozzle of a 100 Newton thrust rocket currently undergoing testing. This paper describes a measurement system based on the spontaneous Raman scattering phenomenon. An analysis of the principles behind the technique is given. Software is developed to measure temperature and major species concentrations by comparing theoretical Raman scattering spectra with experimentally obtained spectra. Equipment selection and experimental approach are summarized. This experimental program is part of a program, which is in progress, to evaluate Navier-Stokes based analyses for this class of rocket

Special Libraries, November 1953

Volume 44, Issue 9https://scholarworks.sjsu.edu/sla_sl_1953/1008/thumbnail.jp

Functional Data Analysis in Electronic Commerce Research

This paper describes opportunities and challenges of using functional data analysis (FDA) for the exploration and analysis of data originating from electronic commerce (eCommerce). We discuss the special data structures that arise in the online environment and why FDA is a natural approach for representing and analyzing such data. The paper reviews several FDA methods and motivates their usefulness in eCommerce research by providing a glimpse into new domain insights that they allow. We argue that the wedding of eCommerce with FDA leads to innovations both in statistical methodology, due to the challenges and complications that arise in eCommerce data, and in online research, by being able to ask (and subsequently answer) new research questions that classical statistical methods are not able to address, and also by expanding on research questions beyond the ones traditionally asked in the offline environment. We describe several applications originating from online transactions which are new to the statistics literature, and point out statistical challenges accompanied by some solutions. We also discuss some promising future directions for joint research efforts between researchers in eCommerce and statistics.Comment: Published at http://dx.doi.org/10.1214/088342306000000132 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

"Virus hunting" using radial distance weighted discrimination

Motivated by the challenge of using DNA-seq data to identify viruses in human blood samples, we propose a novel classification algorithm called "Radial Distance Weighted Discrimination" (or Radial DWD). This classifier is designed for binary classification, assuming one class is surrounded by the other class in very diverse radial directions, which is seen to be typical for our virus detection data. This separation of the 2 classes in multiple radial directions naturally motivates the development of Radial DWD. While classical machine learning methods such as the Support Vector Machine and linear Distance Weighted Discrimination can sometimes give reasonable answers for a given data set, their generalizability is severely compromised because of the linear separating boundary. Radial DWD addresses this challenge by using a more appropriate (in this particular case) spherical separating boundary. Simulations show that for appropriate radial contexts, this gives much better generalizability than linear methods, and also much better than conventional kernel based (nonlinear) Support Vector Machines, because the latter methods essentially use much of the information in the data for determining the shape of the separating boundary. The effectiveness of Radial DWD is demonstrated for real virus detection.Comment: Published at http://dx.doi.org/10.1214/15-AOAS869 in the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Special Libraries, November 1937

Volume 28, Issue 9https://scholarworks.sjsu.edu/sla_sl_1937/1008/thumbnail.jp