Spartan Daily, October 30, 2018

Volume 151, Issue 30https://scholarworks.sjsu.edu/spartan_daily_2018/1072/thumbnail.jp

Dolly Parton, gender, and country music

Book review of: Dolly Parton, Gender, and Country Music. Leigh H. Edwards. Bloomington: Indiana University Press, 2018, 265 pp., $21.00, 978-0-2530-3155-6 (paper)

Whalesong

Tuition rises -- Drunk at school, but not for fun -- What's going on? -- SAD: Beating the wretched darkness -- Halloween's origins rooted in ancient times -- UA in brief -- Go anywhere, do anything with NSE -- Alaska fails to improve affordability of education -- One person's trash is not another's treasure -- Special voting section -- Adventurer finds sanctuary at UAS -- Incident report -- College football at UAS involves a lot of flag -- Rock and roll: Mountaineering 101 -- Sports calendar -- Vegas atmosphere invades UAS -- Ballroom dance puts chancellor in the spotlight -- New editions drive textbook prices sky high -- Proclamation boosts booze awareness for college students -- Boozin' and losin' educates UAS students on drinking and abuse preventio

Spartan Daily, September 16, 2015

Volume 145, Issue 10https://scholarworks.sjsu.edu/spartandaily/8499/thumbnail.jp

April 3, 2014

The Breeze is the student newspaper of James Madison University in Harrisonburg, Virginia

Multimodal Classification of Urban Micro-Events

In this paper we seek methods to effectively detect urban micro-events. Urban micro-events are events which occur in cities, have limited geographical coverage and typically affect only a small group of citizens. Because of their scale these are difficult to identify in most data sources. However, by using citizen sensing to gather data, detecting them becomes feasible. The data gathered by citizen sensing is often multimodal and, as a consequence, the information required to detect urban micro-events is distributed over multiple modalities. This makes it essential to have a classifier capable of combining them. In this paper we explore several methods of creating such a classifier, including early, late, hybrid fusion and representation learning using multimodal graphs. We evaluate performance on a real world dataset obtained from a live citizen reporting system. We show that a multimodal approach yields higher performance than unimodal alternatives. Furthermore, we demonstrate that our hybrid combination of early and late fusion with multimodal embeddings performs best in classification of urban micro-events

Spartan Daily, April 7, 2008

Volume 130, Issue 36https://scholarworks.sjsu.edu/spartandaily/10462/thumbnail.jp

Spartan Daily, October 27, 1986

Volume 87, Issue 42https://scholarworks.sjsu.edu/spartandaily/7499/thumbnail.jp

Daily Eastern News: October 19, 2011

https://thekeep.eiu.edu/den_2011_oct/1007/thumbnail.jp