Physical Sciences and Mathematics Commons^™

Forecasting Country Conflict Using Statistical Learning Methods, Sarah Neumann, Darryl K. Ahner, Raymond R. Hill

Faculty Publications

Purpose — This paper aims to examine whether changing the clustering of countries within a United States Combatant Command (COCOM) area of responsibility promotes improved forecasting of conflict. Design/methodology/approach — In this paper statistical learning methods are used to create new country clusters that are then used in a comparative analysis of model-based conflict prediction. Findings — In this study a reorganization of the countries assigned to specific areas of responsibility are shown to provide improvements in the ability of models to predict conflict. Research limitations/implications — The study is based on actual historical data and is purely data driven. …

A Ground-Based Assessment Framework For Validating Diesel Particulate Emission Models And Applicability In Portland, Or, Kirsten Marie Sarle

Dissertations and Theses

Exposure to diesel emissions causes a range of health effects throughout the body, impairing; respiratory, cardiovascular, central nervous, renal, and cognitive systems. Diesel particulate matter (DPM) in Portland, Oregon is prevalent due to the layout of highly trafficked roadways, rail lines, and marine ports exposing a dense population to high levels of exhaust pollution. These high concentrations of ambient diesel emissions disproportionately impact minority and low-income populations.

Ground-based monitoring and modeling are two ways to assess ambient DPM. However, there are uncertainties in modeled DPM due to knowledge gaps in emissions inventories as well as lack of model validation against …

Creating The 2011 Area Classification For Output Areas (2011 Oac), Christopher G. Gale, Alexander D. Singleton, Andrew G. Bates, Paul A. Longley

Journal of Spatial Information Science

This paper presents the methodology that has been used to create the 2011 Area Classification for Output Areas (2011 OAC). This extends a lineage of widely used public domain census-only geodemographic classifications in the UK. It provides an update to the successful 2001 OAC methodology, and summarizes the social and physical structure of neighborhoods using data from the 2011 UK Census. The results of a user engagement exercise that underpinned the creation of an updated methodology for the 2011 OAC are also presented. The 2011 OAC comprises 8 Supergroups, 26 Groups, and 76 Subgroups. An example of the results of …

Statistical Methods And Artificial Neural Networks, Mammadagha Mammadov, Berna Yazici, Şenay Yolaçan, Atilla Aslanargun, Ali Fuat YüZer, Embiya Ağaoğlu

Journal of Modern Applied Statistical Methods

Artificial Neural Networks and statistical methods are applied on real data sets for forecasting, classification, and clustering problems. Hybrid models for two components are examined on different data sets; tourist arrival forecasting to Turkey, macro-economic problem on rescheduling of the countries’ international debts, and grouping twenty-five European Union member and four candidate countries according to macro-economic indicators.

Building Multi-Discipline, Multi-Format Digital Libraries Using Clusters And Buckets, Michael L. Nelson

Computer Science Theses & Dissertations

Our objective was to study the feasibility of extending the Dienst protocol to enable a multi-discipline, multi-format digital library. We implemented two new technologies: cluster functionality and publishing buckets. We have designed a possible implementation of clusters and buckets, and have prototyped some aspects of the resultant digital library.

Currently, digital libraries are segregated by the disciplines they serve ( computer science, aeronautics, etc.), and by the format of their holdings (reports, software, datasets, etc.). NCSTRL+ is a multi-discipline, multi-format digital library (DL) prototype created to explore the feasibility of the design and implementation issues involved with created a …