Calendar

Sponsored by the Northern Virginia Mineral Club & and the GMU Department of Atmospheric, Oceanic and Earth Sciences

Demonstrations, Exhibits, and Door Prizes. Mini-mines for children to dig in and get free fossils and minerals. Over 20 Dealers with Fossils, Minerals, Crystals and Gems for sale.

Presented by the Northern Virginia Mineral Club, Inc.
Sponsored by the Dept. of Atmospheric, Oceanic and Earth Sciences at GMU

Video overview of the 19th Annual Show

Coupon for $1 off adult admission (print and bring to show)

Show site:

The HUB Ballroom, George Mason University Campus.
Braddock Rd. & Route 123, Fairfax, VA

Address: 4400 University Drive. Fairfax, VA 22030

Hours:

Saturday 10:00 AM – 6:00 PM, Sunday 10:00 AM – 4:00 PM

Features:

• 20 plus Dealers selling Minerals, Fossils, Crystals, Gems, Jewelry, Carvings, Meteorites & more!
• Also, Demonstrations, Hands-On, Exhibits, Door Prizes, Kids’ Activities – including FREE Kid’s Mini-mines & Fossil Dig.
• Silent Auction on Sunday afternoon.

Admission:

• Adults: $6, Seniors: $4, Teens (13-17): $3
• Children 12 & under & Scouts in uniform are FREE
• GMU Students w/valid ID are FREE

Directions/Parking:

Use Parking lot A, enter Lot A from Nottaway River Lane.
Look for our Courtesy Shuttle & Designated Walking Path to Mineral Show

• GMU Campus is located at the intersection of Rte 123 & Braddock Road, Fairfax, Virginia
• Courtesy shuttle provided from Parking Lot A to the Mineral show. Shuttle vans will be designated “Mineral Show” and they will pick up & drop off alongside Nottoway River Lane entrance.
• Handicapped parking closest and most convenient to our show location, the HUB, has not yet been identified. That information will be added to our web page when it is determined.
• GMU Campus map: http://eagle.gmu.edu/map/fairfax.php

Notice and Invitation
Oral Defense of Doctoral Dissertation
Doctor of Philosophy in Computational Sciences and Informatics
Department of Computational and Data Sciences
College of Science
George Mason University
Joseph Shaheen
Bachelor of Science, Murray State University, 2003
Master of Professional Studies, Georgetown University, 2011
Master of Business Administration, Georgetown University, 2013
Data Explorations in Firm Dynamics:
Firm Birth, Life, & Death Through Age, Wage, Size & Labor
Monday, November 26, 2018, 12.30 p.m.
Research Hall
All are invited to attend.
Committee
Robert Axtell, Dissertation Director
Eduardo Lopez
John  Shortle
William Rand
Marc Smith
A better understanding of firm birth, life, and death yields a richer picture of firms’ life-cycle and dynamical labor processes. Through “big data” analysis of a collection of universal fundamental distributions and beginning with firm age, wage and size, I discuss stationarity, their functional form, and consequences emanating from their defects. I describe and delineate the potential complications of the firm age defect–caused by the Great Recession—and speculate on a stark future where a single firm may control the U.S. economy. I follow with an analysis of firm sizes, tensions in heavy-tailed model fitting, how firm growth depends on firm size and consequently, the apparent conflict between empirical evidence and Gibrat’s Law. Included is an introduction of the U.S. firm wage distribution. The ever-changing nature of firm dynamical processes played an important role in selecting the conditional distributions of age and size, and wage and size in my analysis. A closer look at these dynamical processes reveals the role played by mode wage and mode size in the dynamical processes of firms and thus in the firm life-cycle. Analysis of firm labor suggests preliminary evidence that the firm labor distribution conforms to scaling properties—that it is power law distributed. Moreover, I report empirical evidence supporting the existence of two separate and distinct labor processes—dubbed labor regimes—a primary and secondary, coupled with a third unknown regime. I hypothesize that this unknown regime must be drawn from the primary labor regime—that it is either emergent from systemic fraudulent activity or subjected to data corruption. The collection of explorations found in this dissertation product provide a fuller, richer picture of firm birth, life, and death through age, wage, size, and labor while supporting our understanding of firm dynamics in many directions.

Notice and Invitation
Oral Defense of Doctoral Dissertation
Doctor of Philosophy in Computational Sciences and Informatics
Department of Computational and Data Sciences
College of Science
George Mason University
Doug Reitz
Bachelor of Science, Pennsylvania State University, 1995
Master of Science, Binghamton University, 2007
Atomistic Monte Carlo Simulation and 
Machine Learning Data Analysis of 
Eutectic Alkali Metal Alloys 
Tuesday, November 27, 2018, 10:00 a.m.
Research Hall, Room 92
All are invited to attend.
Committee
Estela Blaisten-Barojas, Dissertation Director
Igor Griva
Dmitri Klimov
Howard Sheng
Combining atomistic simulations and machine learning techniques can significantly expedite the materials discovery process. Here an application of such methodological combination for the prediction of the configuration phase (liquid, amorphous solid, and crystalline solid), melting transition, and amorphous-solid behavior of three eutectic alkali metal alloys (Na-K, Na-Cs, K-Cs) is presented.  It is shown that efficient prediction of these properties is possible via machine learning methods trained on the topological local structural properties alone.  The atomic configurations resulting from Monte Carlo annealing of the eutectic alkali alloys are analyzed with topological attributes based on the Voronoi tessellation using expectation-maximization clustering, Random Forest classification, and Support Vector Machine classification.  It is shown that the Voronoi topological fingerprints make an accurate and fast prediction of the alloy thermal behavior by cataloging the atomic configurations into three distinct phases: liquid, amorphous solid, and crystalline solid.  Using as few as eight topological features the configurations can be categorized into these three phases.  With the proposed metrics, arrest-motion and melting temperature ranges are identified through a top down clustering of the atomic configurations cataloged as amorphous solid and liquid.
The methodology presented here is of direct relevance in identifying or screening unknown materials in a targeted class with desired combination of topological properties in an efficient manner with high fidelity.  The results demonstrate explicitly the exceptional power of domain-based machine learning in discovering topological influence on thermodynamic properties, and at the same time providing valuable guidance to machine learning workflows for the analysis of other condensed systems.  This statistical learning paradigm is not restricted to eutectic alloys or thermodynamics, extends the utility of topological attributes in a significant way, and harnesses the discovery of new material properties.

To facilitate open communication with all College of Science faculty, Dean Agouris is continuing to offer open door sessions periodically throughout the academic year.

Ideal topics for these faculty walk-in appointments include:

• new faculty introductions
• ideas for growth
• sharing research, teaching, or service activities
• multidisciplinary collaboration opportunities

Dean Agouris will be holding additional open door sessions on the following dates in Exploratory Hall 3200:

• October 24, 2018
• November 14, 2018
• November 27, 2018
• December 12, 2018
• January 15, 2019
• February 12, 2019
• February 27, 2019
• April 16, 2019
• March 27, 2019
• May 8, 2019
• May 21, 2019

Open door sessions will also be held at 3006 IABR on the SciTech Campus on the following dates from 10:30-12:30pm:

• October 9, 2018
• January 30, 2019
• February 19, 2019

Call ahead notification is not required. Just check in with Teri Fede in Suite 3200 Exploratory Hall (Fairfax) or at  IABR 3006 (SciTech).  If a queue forms during these periods, she will allocate time accordingly for those requesting it.

Computational Social Science Research Colloquium /Colloquium in Computational and Data Sciences
Sanjay Nayar
CSS PhD Student

Title: Interlocking Directorates Analysis: Evidence from India BSE-100
Friday, November 30, 3:00 p.m.
Center for Social Complexity, 3rd Floor Research Hall
All are welcome to attend.
Abstract:
Interlocked directorates among companies are common across the world and have been studied quite extensively in the Western World. This study focuses on interlocking directorates, also referred to as inter-organizational elite cooptation (Allen, 1974), among the top 100 publicly traded companies on the Bombay Stock Exchange (BSE-100) in India. The time period analyzed is between 2006 and 2010, the years spanning the recent great recession. While De (2012) looked at the performance effects of interlocking directorates within Indian business groups irrespective of their membership in BSE-100, it did not address in the analysis the key players, cliques, etc., the evolution of the interlocking over time, or any comparisons with the United States. This broad exploratory study is the first to look at the BSE-100 interlocking directorates’ network to see how it has or has not been dominated by a select group of individuals, companies or sectors during 2006-2010, along with the companies’ performances in the longer-term, given their position in the network. Some comparisons are also made with the US market using information available in published papers (Everard, 2002). This study also serves a secondary purpose of being an introduction to the interconnections between some of the biggest players in the Indian Economy/Stock Market and thus would also be of interest to those studying business in India.

Notice and Invitation
Oral Defense of Doctoral Dissertation
Doctor of Philosophy in Computational Sciences and Informatics
Department of Computational and Data Sciences
College of Science
George Mason University
Yang Xu
Bachelor of Science, Nanjing Normal University, 2006
Master of Science, University of Nebraska-Lincoln, 2009
Almost Regular Graphs and Hamiltonian Cycles
Tuesday, December 4, 2018, 3:00 p.m.
Research Hall, Room 92
All are invited to attend.
Committee
Edward Wegman, Dissertation Director
Eduardo Lopez
Geir Agnarrson
Joseph Mar
This dissertation is third in a series aimed at seeking a method to optimized computer architectures for robustness and efficiency. HADI graphs were first introduced in Hadi Rezazad’s dissertation and were further examined in Roger Shores’ dissertation. This dissertation explores this particular class of graph structure in details and defines this graph structure in a mathematical way. Hadi Graphs are a subset of almost regular graphs with certain invariants. The bound of edge numbers is presented to ensure the new structure Hamiltonian. Another interesting alternative interconnect graph that is called hypercube is discussed in this dissertation. The main focus is to find how many edges can be removed but still retain the Hamiltonian property

Computational Social Science Research Colloquium /
Colloquium in Computational and Data Sciences

Andrew Crooks, Assoc. Professor
Department of Computational and Data Sciences
George Mason University
Computational Modelling of Slums: Progress & Challenges
Friday, December  7,  3:00 p.m.
Center for Social Complexity, 3rd Floor Research Hall
All are welcome to attend.
Abstract:
Over the last 50 years the world has increasingly become more urbanized, much of this growth has occurred in less developed countries, which often lack the resources to accommodate such growth. This has led to the growth of slums, which is estimated to be home for other 1 Billion people. The UN-Habitat projects slum population to double by 2030, which would make them home for 2 in 5 people living in cities. In this talk I will introduce slums, discuss their growth, and provide an overview on what progress has been made to studying and modeling them. This will lead to a discussion of a series of key challenges that need to be addressed if we are to tackle slums from a computational perspective.

To facilitate open communication with all College of Science faculty, Dean Agouris is continuing to offer open door sessions periodically throughout the academic year.

Ideal topics for these faculty walk-in appointments include:

• new faculty introductions
• ideas for growth
• sharing research, teaching, or service activities
• multidisciplinary collaboration opportunities

Dean Agouris will be holding additional open door sessions on the following dates in Exploratory Hall 3200:

• October 24, 2018
• November 14, 2018
• November 27, 2018
• December 12, 2018
• January 15, 2019
• February 12, 2019
• February 27, 2019
• April 16, 2019
• March 27, 2019
• May 8, 2019
• May 21, 2019

Open door sessions will also be held at 3006 IABR on the SciTech Campus on the following dates from 10:30-12:30pm:

• October 9, 2018
• January 30, 2019
• February 19, 2019

Call ahead notification is not required. Just check in with Teri Fede in Suite 3200 Exploratory Hall (Fairfax) or at  IABR 3006 (SciTech).  If a queue forms during these periods, she will allocate time accordingly for those requesting it.