3D dose reconstruction for narrow beams using ion chamber array measurements.

3D dose reconstruction is a verification of the delivered absorbed dose. Our aim was to describe and evaluate a 3D dose reconstruction method applied to phantoms in the context of narrow beams. A solid water phantom and a phantom containing a bone-equivalent material were irradiated on a 6 MV linac. The transmitted dose was measured by using one array of a 2D ion chamber detector. The dose reconstruction was obtained by an iterative algorithm. A phantom set-up error and organ interfraction motion were simulated to test the algorithm sensitivity. In all configurations convergence was obtained within three iterations. A local reconstructed dose agreement of at least 3% / 3mm with respect to the planned dose was obtained, except in a few points of the penumbra. The reconstructed primary fluences were consistent with the planned ones, which validates the whole reconstruction process. The results validate our method in a simple geometry and for narrow beams. The method is sensitive to a set-up error of a heterogeneous phantom and interfraction heterogeneous organ motion.

The systematic profiling of false identity documents: method validation and performance evaluation using seizures known to originate from common and different sources

False identity documents constitute a potential powerful source of forensic intelligence because they are essential elements of transnational crime and provide cover for organized crime. In previous work, a systematic profiling method using false documents' visual features has been built within a forensic intelligence model. In the current study, the comparison process and metrics lying at the heart of this profiling method are described and evaluated. This evaluation takes advantage of 347 false identity documents of four different types seized in two countries whose sources were known to be common or different (following police investigations and dismantling of counterfeit factories). Intra-source and inter-sources variations were evaluated through the computation of more than 7500 similarity scores. The profiling method could thus be validated and its performance assessed using two complementary approaches to measuring type I and type II error rates: a binary classification and the computation of likelihood ratios. Very low error rates were measured across the four document types, demonstrating the validity and robustness of the method to link documents to a common source or to differentiate them. These results pave the way for an operational implementation of a systematic profiling process integrated in a developed forensic intelligence model.

Drug Court Process Evaluation Report, February 2008

The Iowa Consortium for Substance Abuse Research and Evaluation conducted a process evaluation in 2007 on the seven adult and juvenile drug courts existing in Iowa in 2003. (A list of adult and juvenile drug courts established in Iowa from 2004 through 2007 appears in the appendix.) The drug courts evaluated in this study differ on several important factors, including the judicial supervision model used, resources available, and the severity level of clients served. The divergent resources and clients should be considered when comparing outcomes across courts. Section 1 provides an overview of each drug court included in this study.

Statewide Process and Comparative Outcomes Study of 2003 Iowa Adult and Juvenile Drug Courts, August 2009

A statewide evaluation of the six adult and three juvenile drug courts in operation during calendar year 2003 was conducted. Completion rates, recidivism, substance abuse treatment, and supervision and placement (juveniles only) costs were examined by model (Judge and Community Panel) and by Judicial District. In addition, adult drug court participants were compared with a group of offenders who were screened and declined or were rejected by drug court in 2003 (referred) and a sample of offenders starting probation in 2003 (probationer). The adult participant and comparison groups were tracked from their entry into drug court, or the study, through December 31, 2007. This yielded an average post-program follow-up time of almost 3 years (2.9) for drug court participants. For the juvenile portion, drug court participants were compared with a group matched on several demographic and offense variables (Matched Comparison group) and juveniles referred to drug court who did not enter the program (Referred Comparison group). The juvenile participant and comparison groups were tracked from their entry into drug court, or the study, through approximately 16 quarters after program discharge with an end date of December 31, 2007.

Process and Outcome Evaluation of the STAR (Sisters Together Achieving Recovery) Program, September, 2010

In July of 2009, the Division of Criminal and Juvenile Justice Planning (CJJP) received Byrne Justice Assistance Grant/American Recovery and Reinvestment Act funding from the Governor’s Office of Drug Control Policy to conduct a process and outcome evaluation of the STAR (Sisters Together Achieving Recovery) program housed at the Iowa Correctional Institution for Women (ICIW) in Mitchellville, Iowa. The STAR Program is a licensed inpatient substance abuse treatment program that utilizes a Therapeutic Community model (TC). All offenders exiting the STAR program between October 1, 2004 and June 30, 2008 were included in the study (n=173). A comparison sample was drawn of offenders exiting the ICIW during the same release time frame with identified but untreated substance abuse needs (n= 173). March 31, 2010 was designated as the cut-off date for the study. This yielded an average post-program follow-up time of 3.1 years. The STAR group was further divided into two groups by time of program exit. Participants exiting the program between October 1, 2004 and June 30, 2006 were designated as STAR 1 (n=78) and those exiting the program between July 1, 2006 and June 30, 2008 were designated as STAR 2 (n=95). In order to have comparable tracking time between STAR groups, tracking time for STAR 1 concluded July 31, 2008. This yielded an average post release follow-up time of 2.4 years for both groups. Demographic, Program, Intervention, and Outcome data were examined. Comparisons were made between groups as well as categories of participation.

A process for mining science & technology documents databases, illustrated for the case of "knowledge discovery and data mining"

This paper presents a process of mining research & development abstract databases to profile current status and to project potential developments for target technologies, The process is called "technology opportunities analysis." This article steps through the process using a sample data set of abstracts from the INSPEC database on the topic o "knowledge discovery and data mining." The paper offers a set of specific indicators suitable for mining such databases to understand innovation prospects. In illustrating the uses of such indicators, it offers some insights into the status of knowledge discovery research*.

State of Iowa Appropriations Process, 2013

State of Iowa Appropriations Process. Flow chart of the process.

Budget Process in Iowa, September 18, 2008

Budget Process: The Governor and the State Legislature appropriate the state resources after the revenue receipts are estimated by the Revenue Estimating Conference.

The construction process of pedagogical knowledge among nursing professors

Didactic knowledge about contents is constructed through an idiosyncratic synthesis between knowledge about the subject area, students' general pedagogical knowledge and the teacher's biography. This study aimed to understand the construction process and the sources of Pedagogical Content Knowledge, as well as to analyze its manifestations and variations in interactive teaching by teachers whom the students considered competent. Data collection involved teachers from an undergraduate nursing program in the South of Brazil, through non-participant observation and semistructured interviews. Data analysis was submitted to the constant comparison method. The results disclose the need for initial education to cover pedagogical aspects for nurses; to assume permanent education as fundamental in view of the complexity of contents and teaching; to use mentoring/monitoring and the value learning with experienced teachers with a view to the development of quality teaching.

Review of Iowa Department of Human Services Drug Testing Process, December 2008

This report outlines the current drugs testing practices and using these practices for testing requirements.

Analysis and spatial modeling of the indoor radon Swiss data

The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.

Constructability in the Bridge Design Process, HR-320, 1991

In the United States many bridge structures have been designed without consideration for their unique construction problems. Many problems could have been avoided if construction knowledge and experience was utilized in the design process. A systematic process is needed to create and capture construction knowledge for use in the design process. This study was conducted to develop a system to capture construction considerations from field people and incorporate it into a knowledge-base for use by the bridge designers. This report presents the results of this study. As a part of this study a microcomputer-based constructability system has been developed. The system is a user-friendly microcomputer database which codifies construction knowledge, provides easy access to specifications, and provides simple design computation checks for the designer. A structure for the final database was developed and used in the prototype system. A process for collecting, developing and maintaining the database is presented and explained. The study involved a constructability survey, interviews with designers and constructors, and visits to construction sites to collect constuctability concepts. The report describes the development of the constructability system and addresses the future needs for the Iowa Department of Transportation to make the system operational. A user's manual for the system is included along with the report.

Development of a New Process for Determining Design Year Traffic Demands, TR-528, 2007

Researchers should continuously ask how to improve the models we rely on to make financial decisions in terms of the planning, design, construction, and maintenance of roadways. This project presents an alternative tool that will supplement local decision making but maintain a full appreciation of the complexity and sophistication of today’s regional model and local traffic impact study methodologies. This alternative method is tailored to the desires of local agencies, which requested a better, faster, and easier way to evaluate land uses and their impact on future traffic demands at the sub-area or project corridor levels. A particular emphasis was placed on scenario planning for currently undeveloped areas. The scenario planning tool was developed using actual land use and roadway information for the communities of Johnston and West Des Moines, Iowa. Both communities used the output from this process to make regular decisions regarding infrastructure investment, design, and land use planning. The City of Johnston case study included forecasting future traffic for the western portion of the city within a 2,600-acre area, which included 42 intersections. The City of West Des Moines case study included forecasting future traffic for the city’s western growth area covering over 30,000 acres and 331 intersections. Both studies included forecasting a.m. and p.m. peak-hour traffic volumes based upon a variety of different land use scenarios. The tool developed took goegraphic information system (GIS)-based parcel and roadway information, converted the data into a graphical spreadsheet tool, allowed the user to conduct trip generation, distribution, and assignment, and then to automatically convert the data into a Synchro roadway network which allows for capacity analysis and visualization. The operational delay outputs were converted back into a GIS thematic format for contrast and further scenario planning. This project has laid the groundwork for improving both planning and civil transportation decision making at the sub-regional, super-project level.