Motor Vehicle Accident Fatalities for the Week Ending, June 1, 2007

Record of the Fatalities for Motor Vehicle Accidents in Iowa per week.

Motor Vehicle Accident Fatalities for the Week Ending, June 8, 2007

Record of the Fatalities for Motor Vehicle Accidents in Iowa per week.

Motor Vehicle Accident Fatalities for the Week Ending, June 15, 2007

Record of the Fatalities for Motor Vehicle Accidents in Iowa per week.

Quarterly Report of the Building Project for the Motor Vehicle Division

Pursuant to Section 1 of House File 466 of the 81st General Assembly, the Iowa Department of Transportation is required to make quarterly reports to the Legislative Council regarding the progress of the building project for the Motor Vehicle Division. During the quarter ending June 30, 2007, the project was delayed by two weeks. The Motor Vehicle Division moved into the new Ankeny facility on June 22 and was operational Monday, June 25. The driver's license stations reopened as scheduled Tuesday, June 26, at the Ankeny facility as well as the Oliver Plaza renewal location.

Motor Vehicle Accident Fatalities for the Week Ending, June 29, 2007

Record of the Fatalities for Motor Vehicle Accidents in Iowa per week.

Motor Vehicle Accident Fatalities for the Week Ending, June 22, 2007

Record of the Fatalities for Motor Vehicle Accidents in Iowa per week.

Motor Vehicle Accident Fatalities for the Week Ending, July 6, 2007

Record of the Fatalities for Motor Vehicle Accidents in Iowa per week.

An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System

The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.

Motor Vehicle Accident Fatalities for the Week Ending, July 20, 2007

Record of the Fatalities for Motor Vehicle Accidents in Iowa per week.

Motor Vehicle Accident Fatalities for the Week Ending, July 13, 2007

Record of the Fatalities for Motor Vehicle Accidents in Iowa per week.

Motor Vehicle Accident Fatalities for the Week Ending, July 27, 2007

Record of the Fatalities for Motor Vehicle Accidents in Iowa per week.

Motor Vehicle Accident Fatalities for the Week Ending, August 3, 2007

Record of the Fatalities for Motor Vehicle Accidents in Iowa per week.

Motor Vehicle Accident Fatalities for the Week Ending, August 10, 2007

Record of the Fatalities for Motor Vehicle Accidents in Iowa per week.

Multiparametric brainstem segmentation using a modified multivariate mixture of Gaussians

The human brainstem is a densely packed, complex but highly organised structure. It not only serves as a conduit for long projecting axons conveying motor and sensory information, but also is the location of multiple primary nuclei that control or modulate a vast array of functions, including homeostasis, consciousness, locomotion, and reflexive and emotive behaviours. Despite its importance, both in understanding normal brain function as well as neurodegenerative processes, it remains a sparsely studied structure in the neuroimaging literature. In part, this is due to the difficulties in imaging the internal architecture of the brainstem in vivo in a reliable and repeatable fashion. A modified multivariate mixture of Gaussians (mmMoG) was applied to the problem of multichannel tissue segmentation. By using quantitative magnetisation transfer and proton density maps acquired at 3 T with 0.8 mm isotropic resolution, tissue probability maps for four distinct tissue classes within the human brainstem were created. These were compared against an ex vivo fixated human brain, imaged at 0.5 mm, with excellent anatomical correspondence. These probability maps were used within SPM8 to create accurate individual subject segmentations, which were then used for further quantitative analysis. As an example, brainstem asymmetries were assessed across 34 right-handed individuals using voxel based morphometry (VBM) and tensor based morphometry (TBM), demonstrating highly significant differences within localised regions that corresponded to motor and vocalisation networks. This method may have important implications for future research into MRI biomarkers of pre-clinical neurodegenerative diseases such as Parkinson's disease.

Entrepreneurship, organization and economic performance among Spanish firms, 1930-1975. The case of the motor industry

Before the Civil War (1936-1939), Spain had seen the emergence offirms of complex organizational forms. However, the conflict andthe postwar years changed this pattern. The argument put forwardin this paper is based on historical experience, the efforts willbe addressed to explain the development of Spanish entrepreneurshipduring the second half of the twentieth century. To illustrate thechange in entrepreneurship and organizational patterns among theSpanish firms during the Francoist regime we will turn to the caseof the motor vehicle industry.