Artificial-Intelligence-Based Optimization of the Management of Snow Removal Assets and Resources Final Report, October 2002

Geographic information systems (GIS) and artificial intelligence (AI) techniques were used to develop an intelligent snow removal asset management system (SRAMS). The system has been evaluated through a case study examining snow removal from the roads in Black Hawk County, Iowa, for which the Iowa Department of Transportation (Iowa DOT) is responsible. The SRAMS is comprised of an expert system that contains the logical rules and expertise of the Iowa DOT’s snow removal experts in Black Hawk County, and a geographic information system to access and manage road data. The system is implemented on a mid-range PC by integrating MapObjects 2.1 (a GIS package), Visual Rule Studio 2.2 (an AI shell), and Visual Basic 6.0 (a programming tool). The system could efficiently be used to generate prioritized snowplowing routes in visual format, to optimize the allocation of assets for plowing, and to track materials (e.g., salt and sand). A test of the system reveals an improvement in snowplowing time by 1.9 percent for moderate snowfall and 9.7 percent for snowstorm conditions over the current manual system.

Modelos de tasas de interes en Chile: una revisión

Con este trabajo revisamos los Modelos de niveles de las tasas de intereses en Chile. Además de los Modelos de Nivel tradicionales por Chan, Karoly, Longstaff y Lijadoras (1992) en EE. UU, y Parisi (1998) en Chile, por el método de Probabilidad Maximun permitimos que la volatilidad condicional también incluya los procesos inesperados de la información (el modelo GARCH ) y también que la volatilidad sea la función del nivel de la tasa de intereses (modelo TVP-NIVELE) como en Brenner, Harjes y la Crona (1996). Para esto usamos producciones de mercado de bonos de reconocimiento, en cambio las producciones mensuales medias de subasta PDBC, y la ampliación del tamaño y la frecuencia de la muestra a 4 producciones semanales con términos(condiciones) diferentes a la madurez: 1 año, 5 años, 10 años y 15 años. Los resultados principales del estudio pueden ser resumidos en esto: la volatilidad de los cambios inesperados de las tarifas depende positivamente del nivel de las tarifas, sobre todo en el modelo de TVP-NIVEL. Obtenemos pruebas de reversión tacañas, tal que los incrementos en las tasas de intereses no eran independientes, contrariamente a lo obtenido por Brenner. en EE. UU. Los modelos de NIVELES no son capaces de ajustar apropiadamente la volatilidad en comparación con un modelo GARCH (1,1), y finalmente, el modelo de TVP-NIVEL no vence los resultados del modelo GARCH (1,1)

Targeted Small Business Link, Fall 2012

Targeted Small Business News from the Iowa Economic Development Authority

Review of targeted small business procurement activities for the year ended June 30, 2012

Review of targeted small business procurement activities for the year ended June 30, 2012

The ability model of emotional intelligence: Searching for valid measures

Current measures of ability emotional intelligence (EI)--including the well-known Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT)--suffer from several limitations, including low discriminant validity and questionable construct and incremental validity. We show that the MSCEIT is largely predicted by personality dimensions, general intelligence, and demographics having multiple R's with the MSCEIT branches up to .66; for the general EI factor this relation was even stronger (Multiple R = .76). As concerns the factor structure of the MSCEIT, we found support for four first-order factors, which had differential relations with personality, but no support for a higher-order global EI factor. We discuss implications for employing the MSCEIT, including (a) using the single branches scores rather than the total score, (b) always controlling for personality and general intelligence to ensure unbiased parameter estimates in the EI factors, and (c) correcting for measurement error. Failure to account for these methodological aspects may severely compromise predictive validity testing. We also discuss avenues for the improvement of ability-based tests.

Intelligence-led crime scene processing. Part II : Intelligence and crime scene examination.

A better integration of the information conveyed by traces within intelligence-led framework would allow forensic science to participate more intensively to security assessments through forensic intelligence (part I). In this view, the collection of data by examining crime scenes is an entire part of intelligence processes. This conception frames our proposal for a model that promotes to better use knowledge available in the organisation for driving and supporting crime scene examination. The suggested model also clarifies the uncomfortable situation of crime scene examiners who must simultaneously comply with justice needs and expectations, and serve organisations that are mostly driven by broader security objectives. It also opens new perspective for forensic science and crime scene investigation, by the proposal to follow other directions than the traditional path suggested by dominant movements in these fields.