Class of 2009 Abstract / OBJECTIVES: To assess the performance of drug-drug interaction (DDI) software programs utilized in community and hospital pharmacies located in urban and rural settings. METHODS: A fictitious patient profile with 18 drugs and a penicillin allergy was entered into pharmacy computer systems throughout Arizona. Researchers recorded the software systems’ responses to 20 targeted combinations, 14 of which should have produced an alert and 6 that were not true interactions. The number of true positive, true negative, false positive and false negative responses was determined for each system. These data were subsequently used to calculate the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) overall and at each site. RESULTS: There were 35 participating pharmacies that used a total of 18 different software programs. The overall sensitivity was 0.8, and ranged from 0.21 to 1 between sites. Computer software failed to detect important interactions 20% of the time. The specificity ranged from 0.83 to 1; PPV ranged from 0.89 to 1; and NPV ranged from to 0.35 to 1. Nine sites, using five different software programs returned perfect results. However, some of those programs produced different results at other sites. CONCLUSIONS: This study shows that improvements are needed in software programs to help pharmacists accurately identify DDIs which could prevent potential adverse drug events. Many clinically important interactions remain undetected by software programs, and users should be mindful of current limitations in technology.

Thesis (Ph. D.)--University of Alabama at Birmingham, 2007. / Description based on contents viewed Oct. 7, 2007; title from title screen. Includes bibliographical references (p. 160-172).

This study considers the application of object oriented programming approach to develop a Windows based program for the design of reinforced concrete T -beam bridges in accordance with the newly adopted AASHTO LRFD Bridge Specification. The program can perform both the analysis and design of the deck and beam. The program is interactive in nature and it is possible to change all input data and design parameters during execution. A series of second-degree interpolating polynomial functions were developed for representing influence line coordinates for various load effects in the deck and beam subjected to moving loads. The analysis results using the program were compared with those obtained from the commercial programs. The design results obtained from the program were compared with example problems for several test structures. Both design and analysis comparisons gave satisfactory results. The successful performance of the program demonstrates the significant advantages of the object oriented programming. It was concluded that the benefits of object oriented programming approach make this a viable technique for the development of computer applications for structural engineering. / Master of Science

There are a number of techniques for automatic bug detection, most of them have a high false positive rate when used in practice. This work proposes an approach, named Strip-Miner, that combines simple dependency analysis of code with a data mining technique "frequent itemset mining" to reduce the false positive rate. We adopt a two phase approach 1) finding the potential bugs and 2) filtering the false positive ones. In the first phase we extract code elements and dependencies among them using static analysis and frequent itemset mining to find programming patterns where a deviation from these patterns is considered as a potential bug. In the second phase, we use the extracted dependencies to build dependency chains between program elements in a programming pattern and a lack of such a chain potentially makes a bug false positive. Our evaluation on a set of 7 benchmarks consisting of large software code including OpenSSL, PostgreSQL, Git, FFMPEG, SQLite, Binutils and Putty shows that combining simple de- pendency analysis with pattern mining can significantly decrease the number of generated bugs. Using our approach we are able to reduce the number of generated bugs by up to 99.9% with a false positive rate of 65.19% and true positive rate of 34.18% on average as compared to an earlier frequent itemset mining based approach "PR-Miner". / Master of Science / Every software code has bugs in it that can change its expected behavior. There have been a lot of efforts to automate the process of bug detection but most of the techniques proposed have a high rate of false alarms. Some of these techniques leverage the information available in software code to extract programming patterns that can be used to find potential bugs. Although such an approach has proved to be fruitful for finding bugs but large number of false alarms makes it almost useless in software development. The elements present in a software code have relationships among them formally known as dependencies and the process of finding them is known as dependency analysis. There is a technique known as market basket analysis used by large retailers to find association between items. It works by looking for combinations of items that occur together frequently in transactions. Similarly, in a software code combinations of elements that occur together, can be used to find association between them. This technique is formally known as frequent itemset mining in the data mining domain. This work proposes an approach, named Strip- Miner, that combines dependency analysis with frequent itemset mining to reduce the rate of false alarms. We adopt a two phase approach 1)finding the potential bugs in code and 2)filtering the false alarms. In the first phase we extract code elements and dependencies among them and use frequent itemset mining to find programming patterns where a deviation from these patterns is considered as a potential bug. In the second phase, we use the extracted dependencies to build dependency chains between program elements present in a programming pattern and lack of such a chain is an indication of false alarm. Our evaluation on a set of 7 benchmarks consisting of large software code including version control systems, database management systems, software security libraries and utility software like media players shows that combining simple dependency analysis with frequent itemset mining can significantly decrease the rate of false alarms. Using our approach we are able to reduce the number of generated bugs by up to 99.9% with a false alarms rate of 65.19% and real bugs rate of 34.18% on average as compared to an earlier frequent itemset mining based approach "PR-Miner".

Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references.

The aim of the these is to compare and evaluace of processing in choice Accounting software. Computer technology can be helpful in the process of accounting. Accounting software are is an integral part of accounting administration. Nowadays a lot of accounting and economic software are on the market. It is necessary to chaose a adequate software for effectiveness of the company. The right choice of software programme can be the first step of firm functioning.

We discuss a new approach to the construction of software systems. Instead of attempting to build a system that is as free of errors as possible, the designer instead identifies key properties that the execution must satisfy to be acceptable to its users. Together, these properties define the acceptability envelope of the system: the region that it must stay within to remain acceptable. The developer then augments the system with a layered set of components, each of which enforces one of the acceptability properties. The potential advantages of this approach include more flexible, resilient systems that recover from errors and behave acceptably across a wide range of operating environments, an appropriately prioritized investment of engineering resources, and the ability to productively incorporate unreliable components into the final software system. / Singapore-MIT Alliance (SMA)

This mixed methods study was designed to examine the effectiveness of the HearBuilder Phonological Awareness software program on the acquisition of phonological awareness in African-American preschool children. Additionally, the researcher investigated the relationship between the independent variables of student engagement, student motivation, student behavior, and student attendance on the dependent variable of acquisition of phonological awareness as measured by the gain score. Descriptive statistical analyses were used to describe, summarize, and interpret the data collected. After examining the aforesaid variables, the researcher found there were no significant relationships between the gain scores and any of the independent variables. But there were useful significant relationships between the independent variables of student motivation, student engagement, and student attendance. The researcher also examined the differences between the pretest and posttest for the experimental and control groups combined. A significant difference was found between these two tests suggesting that the HearBuilder Phonological Awareness software program was effective in improving student’s performance in the experimental group. There was no significant difference, however, between pre and posttest based on gender. So while one can see the effectiveness in the HearBuilder Phonological Awareness program based on the difference between the pre and posttest, the reason does not lie in the variables selected as independent variables, but in other variables not included in the study such as instructional strategies. Finally, the researcher investigated the difference in the performance of the experimental group and the control group as measured by the mean gain scores. Key results revealed that the experimental group scored higher than the control group on the HearBuilder Phonological Awareness posttest as measured by the gain score. Early Childhood administrators can utilize this investigation as a vehicle to advance their instructional leadership skills and teachers can improve their pedagogical practices.

The master thesis describes communication of PLC and touchscreen with purpose of high voltage control. The general information and framework are included. The thesis describes part of IVEP corporation development. Due to the beginning of a long-term development it is premature to come into conclusions within this master thesis. The first chapter deals with PLC and other components. The second chapter consists of matters about high voltage devices. The following chapter describes the programme part. The fourth and concluding chapter deals with the realization of the communication itself. A brief evaluation with prospects for the future is included in the conclusion.

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