16 resultados para Precision and recall

em Digital Commons at Florida International University


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The Intoxilyzer 5000 was tested for calibration curve linearity for ethanol vapor concentration between 0.020 and 0.400g/210L with excellent linearity. Calibration error using reference solutions outside of the allowed concentration range, response to the same ethanol reference solution at different temperatures between 34 and 38$\sp\circ$C, and its response to eleven chemicals, 10 mixtures of two at the time, and one mixture of four chemicals potentially found in human breath have been evaluated. Potential interferents were chosen on the basis of their infrared signatures and the concentration range of solutions corresponding to the non-lethal blood concentration range of various volatile organic compounds reported in the literature. The result of this study indicates that the instrument calibrates with solutions outside the allowed range up to $\pm$10% of target value. Headspace FID dual column GC analysis was used to confirm the concentrations of the solutions. Increasing the temperature of the reference solution from 34 to 38$\sp\circ$C resulted in linear increases in instrument recorded ethanol readings with an average increase of 6.25%/$\sp\circ$C. Of the eleven chemicals studied during this experiment, six, isopropanol, toluene, methyl ethyl ketone, trichloroethylene, acetaldehyde, and methanol could reasonably interfere with the test at non-lethal reported blood concentration ranges, the mixtures of those six chemicals showed linear additive results with a combined effect of as much as a 0.080g/210L reading (Florida's legal limit) without any ethanol present. ^

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Historically, memory has been evaluated by examining how much is remembered, however a more recent conception of memory focuses on the accuracy of memories. When using this accuracy-oriented conception of memory, unlike with the quantity-oriented approach, memory does not always deteriorate over time. A possible explanation for this seemingly surprising finding lies in the metacognitive processes of monitoring and control. Use of these processes allows people to withhold responses of which they are unsure, or to adjust the precision of responses to a level that is broad enough to be correct. The ability to accurately report memories has implications for investigators who interview witnesses to crimes, and those who evaluate witness testimony. ^ This research examined the amount of information provided, accuracy, and precision of responses provided during immediate and delayed interviews about a videotaped mock crime. The interview format was manipulated such that a single free narrative response was elicited, or a series of either yes/no or cued questions were asked. Instructions provided by the interviewer indicated to the participants that they should either stress being informative, or being accurate. The interviews were then transcribed and scored. ^ Results indicate that accuracy rates remained stable and high after a one week delay. Compared to those interviewed immediately, after a delay participants provided less information and responses that were less precise. Participants in the free narrative condition were the most accurate. Participants in the cued questions condition provided the most precise responses. Participants in the yes/no questions condition were most likely to say “I don’t know”. The results indicate that people are able to monitor their memories and modify their reports to maintain high accuracy. When control over precision was not possible, such as in the yes/no condition, people said “I don’t know” to maintain accuracy. However when withholding responses and adjusting precision were both possible, people utilized both methods. It seems that concerns that memories reported after a long retention interval might be inaccurate are unfounded. ^

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Historically, memory has been evaluated by examining how much is remembered, however a more recent conception of memory focuses on the accuracy of memories. When using this accuracy-oriented conception of memory, unlike with the quantity-oriented approach, memory does not always deteriorate over time. A possible explanation for this seemingly surprising finding lies in the metacognitive processes of monitoring and control. Use of these processes allows people to withhold responses of which they are unsure, or to adjust the precision of responses to a level that is broad enough to be correct. The ability to accurately report memories has implications for investigators who interview witnesses to crimes, and those who evaluate witness testimony. This research examined the amount of information provided, accuracy, and precision of responses provided during immediate and delayed interviews about a videotaped mock crime. The interview format was manipulated such that a single free narrative response was elicited, or a series of either yes/no or cued questions were asked. Instructions provided by the interviewer indicated to the participants that they should either stress being informative, or being accurate. The interviews were then transcribed and scored. Results indicate that accuracy rates remained stable and high after a one week delay. Compared to those interviewed immediately, after a delay participants provided less information and responses that were less precise. Participants in the free narrative condition were the most accurate. Participants in the cued questions condition provided the most precise responses. Participants in the yes/no questions condition were most likely to say “I don’t know”. The results indicate that people are able to monitor their memories and modify their reports to maintain high accuracy. When control over precision was not possible, such as in the yes/no condition, people said “I don’t know” to maintain accuracy. However when withholding responses and adjusting precision were both possible, people utilized both methods. It seems that concerns that memories reported after a long retention interval might be inaccurate are unfounded.

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Contrary to interviewing guidelines, a considerable portion of witness interviews are not recorded. Investigators’ memory, their interview notes, and any subsequent interview reports therefore become important pieces of evidence; the accuracy of interviewers’ memory or such reports is therefore of crucial importance when interviewers testify in court regarding witness interviews. A detailed recollection of the actual exchange during such interviews and how information was elicited from the witness will allow for a better assessment of statement veracity in court. ^ Two studies were designed to examine interviewers’ memory for a prior witness interview. Study One varied interviewer note-taking and type of subsequent interview report written by interviewers by including a sample of undergraduates and implementing a two-week delay between interview and recall. Study Two varied levels of interviewing experience in addition to report type and note-taking by comparing experienced police interviewers to a student sample. Participants interviewed a mock witness about a crime, while taking notes or not, and wrote an interview report two weeks later (Study One) or immediately after (Study Two). Interview reports were written either in a summarized format, which asked interviewers for a summary of everything that occurred during the interview, or verbatim format, which asked interviewers to record in transcript format the questions they asked and the witness’s responses. Interviews were videotaped and transcribed. Transcriptions were compared to interview reports to score for accuracy and omission of interview content. ^ Results from both studies indicate that much interview information is lost between interview and report especially after a two-week delay. The majority of information reported by interviewers is accurate, although even interviewers who recalled information immediately after still reported a troubling amount of inaccurate information. Note-taking was found to increase accuracy and completeness of interviewer reports especially after a two week delay. Report type only influenced recall of interviewer questions. Experienced police interviewers were not any better at recalling a prior witness interview than student interviewers. Results emphasize the need to record witness interviews to allow for more accurate and complete interview reconstruction by interviewers, even if interview notes are available. ^

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The necessity of elemental analysis techniques to solve forensic problems continues to expand as the samples collected from crime scenes grow in complexity. Laser ablation ICP-MS (LA-ICP-MS) has been shown to provide a high degree of discrimination between samples that originate from different sources. In the first part of this research, two laser ablation ICP-MS systems were compared, one using a nanosecond laser and another a femtosecond laser source for the forensic analysis of glass. The results showed that femtosecond LA-ICP-MS did not provide significant improvements in terms of accuracy, precision and discrimination, however femtosecond LA-ICP-MS did provide lower detection limits. In addition, it was determined that even for femtosecond LA-ICP-MS an internal standard should be utilized to obtain accurate analytical results for glass analyses. In the second part, a method using laser induced breakdown spectroscopy (LIBS) for the forensic analysis of glass was shown to provide excellent discrimination for a glass set consisting of 41 automotive fragments. The discrimination power was compared to two of the leading elemental analysis techniques, μXRF and LA-ICP-MS, and the results were similar; all methods generated >99% discrimination and the pairs found indistinguishable were similar. An extensive data analysis approach for LIBS glass analyses was developed to minimize Type I and II errors en route to a recommendation of 10 ratios to be used for glass comparisons. Finally, a LA-ICP-MS method for the qualitative analysis and discrimination of gel ink sources was developed and tested for a set of ink samples. In the first discrimination study, qualitative analysis was used to obtain 95.6% discrimination for a blind study consisting of 45 black gel ink samples provided by the United States Secret Service. A 0.4% false exclusion (Type I) error rate and a 3.9% false inclusion (Type II) error rate was obtained for this discrimination study. In the second discrimination study, 99% discrimination power was achieved for a black gel ink pen set consisting of 24 self collected samples. The two pairs found to be indistinguishable came from the same source of origin (the same manufacturer and type of pen purchased in different locations). It was also found that gel ink from the same pen, regardless of the age, was indistinguishable as were gel ink pens (four pens) originating from the same pack.

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Concurrent software executes multiple threads or processes to achieve high performance. However, concurrency results in a huge number of different system behaviors that are difficult to test and verify. The aim of this dissertation is to develop new methods and tools for modeling and analyzing concurrent software systems at design and code levels. This dissertation consists of several related results. First, a formal model of Mondex, an electronic purse system, is built using Petri nets from user requirements, which is formally verified using model checking. Second, Petri nets models are automatically mined from the event traces generated from scientific workflows. Third, partial order models are automatically extracted from some instrumented concurrent program execution, and potential atomicity violation bugs are automatically verified based on the partial order models using model checking. Our formal specification and verification of Mondex have contributed to the world wide effort in developing a verified software repository. Our method to mine Petri net models automatically from provenance offers a new approach to build scientific workflows. Our dynamic prediction tool, named McPatom, can predict several known bugs in real world systems including one that evades several other existing tools. McPatom is efficient and scalable as it takes advantage of the nature of atomicity violations and considers only a pair of threads and accesses to a single shared variable at one time. However, predictive tools need to consider the tradeoffs between precision and coverage. Based on McPatom, this dissertation presents two methods for improving the coverage and precision of atomicity violation predictions: 1) a post-prediction analysis method to increase coverage while ensuring precision; 2) a follow-up replaying method to further increase coverage. Both methods are implemented in a completely automatic tool.

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Contrary to interviewing guidelines, a considerable portion of witness interviews are not recorded. Investigators’ memory, their interview notes, and any subsequent interview reports therefore become important pieces of evidence; the accuracy of interviewers’ memory or such reports is therefore of crucial importance when interviewers testify in court regarding witness interviews. A detailed recollection of the actual exchange during such interviews and how information was elicited from the witness will allow for a better assessment of statement veracity in court. Two studies were designed to examine interviewers’ memory for a prior witness interview. Study One varied interviewer note-taking and type of subsequent interview report written by interviewers by including a sample of undergraduates and implementing a two-week delay between interview and recall. Study Two varied levels of interviewing experience in addition to report type and note-taking by comparing experienced police interviewers to a student sample. Participants interviewed a mock witness about a crime, while taking notes or not, and wrote an interview report two weeks later (Study One) or immediately after (Study Two). Interview reports were written either in a summarized format, which asked interviewers for a summary of everything that occurred during the interview, or verbatim format, which asked interviewers to record in transcript format the questions they asked and the witness’s responses. Interviews were videotaped and transcribed. Transcriptions were compared to interview reports to score for accuracy and omission of interview content. Results from both studies indicate that much interview information is lost between interview and report especially after a two-week delay. The majority of information reported by interviewers is accurate, although even interviewers who recalled information immediately after still reported a troubling amount of inaccurate information. Note-taking was found to increase accuracy and completeness of interviewer reports especially after a two week delay. Report type only influenced recall of interviewer questions. Experienced police interviewers were not any better at recalling a prior witness interview than student interviewers. Results emphasize the need to record witness interviews to allow for more accurate and complete interview reconstruction by interviewers, even if interview notes are available.

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The necessity of elemental analysis techniques to solve forensic problems continues to expand as the samples collected from crime scenes grow in complexity. Laser ablation ICP-MS (LA-ICP-MS) has been shown to provide a high degree of discrimination between samples that originate from different sources. In the first part of this research, two laser ablation ICP-MS systems were compared, one using a nanosecond laser and another a femtosecond laser source for the forensic analysis of glass. The results showed that femtosecond LA-ICP-MS did not provide significant improvements in terms of accuracy, precision and discrimination, however femtosecond LA-ICP-MS did provide lower detection limits. In addition, it was determined that even for femtosecond LA-ICP-MS an internal standard should be utilized to obtain accurate analytical results for glass analyses. In the second part, a method using laser induced breakdown spectroscopy (LIBS) for the forensic analysis of glass was shown to provide excellent discrimination for a glass set consisting of 41 automotive fragments. The discrimination power was compared to two of the leading elemental analysis techniques, µXRF and LA-ICP-MS, and the results were similar; all methods generated >99% discrimination and the pairs found indistinguishable were similar. An extensive data analysis approach for LIBS glass analyses was developed to minimize Type I and II errors en route to a recommendation of 10 ratios to be used for glass comparisons. Finally, a LA-ICP-MS method for the qualitative analysis and discrimination of gel ink sources was developed and tested for a set of ink samples. In the first discrimination study, qualitative analysis was used to obtain 95.6% discrimination for a blind study consisting of 45 black gel ink samples provided by the United States Secret Service. A 0.4% false exclusion (Type I) error rate and a 3.9% false inclusion (Type II) error rate was obtained for this discrimination study. In the second discrimination study, 99% discrimination power was achieved for a black gel ink pen set consisting of 24 self collected samples. The two pairs found to be indistinguishable came from the same source of origin (the same manufacturer and type of pen purchased in different locations). It was also found that gel ink from the same pen, regardless of the age, was indistinguishable as were gel ink pens (four pens) originating from the same pack.

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My study investigated internal consistency estimates of psychometric surveys as an operationalization of the state of measurement precision of constructs in industrial and organizational (I/O) psychology. Analyses were conducted of samples used in research articles published in the Journal of Applied Psychology between 1975 and 2010 in five year intervals (K = 934) from 480 articles yielding 1427 coefficients. Articles and their respective samples were coded for test-taker characteristics (e.g., age, gender, and ethnicity), research settings (e.g., lab and field studies), and actual tests (e.g., number of items and scale anchor points). A reliability and inter-item correlations depository was developed for I/O variables and construct groups. Personality measures had significantly lower inter-item correlations than other construct groups. Also, internal consistency estimates and reporting practices were evaluated over time, demonstrating an improvement in measurement precision and missing data.

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Concurrent software executes multiple threads or processes to achieve high performance. However, concurrency results in a huge number of different system behaviors that are difficult to test and verify. The aim of this dissertation is to develop new methods and tools for modeling and analyzing concurrent software systems at design and code levels. This dissertation consists of several related results. First, a formal model of Mondex, an electronic purse system, is built using Petri nets from user requirements, which is formally verified using model checking. Second, Petri nets models are automatically mined from the event traces generated from scientific workflows. Third, partial order models are automatically extracted from some instrumented concurrent program execution, and potential atomicity violation bugs are automatically verified based on the partial order models using model checking. Our formal specification and verification of Mondex have contributed to the world wide effort in developing a verified software repository. Our method to mine Petri net models automatically from provenance offers a new approach to build scientific workflows. Our dynamic prediction tool, named McPatom, can predict several known bugs in real world systems including one that evades several other existing tools. McPatom is efficient and scalable as it takes advantage of the nature of atomicity violations and considers only a pair of threads and accesses to a single shared variable at one time. However, predictive tools need to consider the tradeoffs between precision and coverage. Based on McPatom, this dissertation presents two methods for improving the coverage and precision of atomicity violation predictions: 1) a post-prediction analysis method to increase coverage while ensuring precision; 2) a follow-up replaying method to further increase coverage. Both methods are implemented in a completely automatic tool.

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Ensemble Stream Modeling and Data-cleaning are sensor information processing systems have different training and testing methods by which their goals are cross-validated. This research examines a mechanism, which seeks to extract novel patterns by generating ensembles from data. The main goal of label-less stream processing is to process the sensed events to eliminate the noises that are uncorrelated, and choose the most likely model without over fitting thus obtaining higher model confidence. Higher quality streams can be realized by combining many short streams into an ensemble which has the desired quality. The framework for the investigation is an existing data mining tool. First, to accommodate feature extraction such as a bush or natural forest-fire event we make an assumption of the burnt area (BA*), sensed ground truth as our target variable obtained from logs. Even though this is an obvious model choice the results are disappointing. The reasons for this are two: One, the histogram of fire activity is highly skewed. Two, the measured sensor parameters are highly correlated. Since using non descriptive features does not yield good results, we resort to temporal features. By doing so we carefully eliminate the averaging effects; the resulting histogram is more satisfactory and conceptual knowledge is learned from sensor streams. Second is the process of feature induction by cross-validating attributes with single or multi-target variables to minimize training error. We use F-measure score, which combines precision and accuracy to determine the false alarm rate of fire events. The multi-target data-cleaning trees use information purity of the target leaf-nodes to learn higher order features. A sensitive variance measure such as ƒ-test is performed during each node's split to select the best attribute. Ensemble stream model approach proved to improve when using complicated features with a simpler tree classifier. The ensemble framework for data-cleaning and the enhancements to quantify quality of fitness (30% spatial, 10% temporal, and 90% mobility reduction) of sensor led to the formation of streams for sensor-enabled applications. Which further motivates the novelty of stream quality labeling and its importance in solving vast amounts of real-time mobile streams generated today.

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New designer drugs are constantly emerging onto the illicit drug market and it is often difficult to validate and maintaincomprehensive analytical methods for accurate detection of these compounds. Generally, toxicology laboratories utilize a screening method, such as immunoassay, for the presumptive identification of drugs of abuse. When a positive result occurs, confirmatory methods, such as gas chromatography (GC) or liquid chromatography (LC) coupled with mass spectrometry (MS), are required for more sensitive and specific analyses. In recent years, the need to study the activities of these compounds in screening assays as well as to develop confirmatory techniques to detect them in biological specimens has been recognized. Severe intoxications and fatalities have been encountered with emerging designer drugs, presenting analytical challenges for detection and identification of such novel compounds. The first major task of this research was to evaluate the performance of commercially available immunoassays to determine if designer drugs were cross-reactive. The second major task was to develop and validate a confirmatory method, using LC-MS, to identify and quantify these designer drugs in biological specimens.^ Cross-reactivity towards the cathinone derivatives was found to be minimal. Several other phenethylamines demonstrated cross-reactivity at low concentrations, but results were consistent with those published by the assay manufacturer or as reported in the literature. Current immunoassay-based screening methods may not be ideal for presumptively identifying most designer drugs, including the "bath salts." For this reason, an LC-MS based confirmatory method was developed for 32 compounds, including eight cathinone derivatives, with limits of quantification in the range of 1-10 ng/mL. The method was fully validated for selectivity, matrix effects, stability, recovery, precision, and accuracy. In order to compare the screening and confirmatory techniques, several human specimens were analyzed to demonstrate the importance of using a specific analytical method, such as LC-MS, to detect designer drugs in serum as immunoassays lack cross-reactivity with the novel compounds. Overall, minimal cross-reactivity was observed, highlighting the conclusion that these presumptive screens cannot detect many of the designer drugs and that a confirmatory technique, such as the LC-MS, is required for the comprehensive forensic toxicological analysis of designer drugs.^

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Cutting tools less than 2mm diameter can be considered as micro-tool. Microtools are used in variety of applications where precision and accuracy are indispensable. In micro-machining operations, a small amount of material is removed and very small cutting forces are created. The small cross sectional area of the micro-tools drastically reduces their strength and makes their useful life short and unpredictable; so cutting parameters should be selected carefully to avoid premature tool breakage. The main objective of this study is to develop new techniques to select the optimal cutting conditions with minimum number of experiments and to evaluate the tool wear in machining operations. Several experimental setups were prepared and used to investigate the characteristics of cutting force and AE signals during the micro-end-milling of different materials including steel, aluminum and graphite electrodes. The proposed optimal cutting condition selection method required fewer experiments than conventional approaches and avoided premature tool breakage. The developed tool wear monitoring technique estimated the used tool life with ±10% accuracy from the machining data collected during the end-milling of non-metal materials.

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Ensemble Stream Modeling and Data-cleaning are sensor information processing systems have different training and testing methods by which their goals are cross-validated. This research examines a mechanism, which seeks to extract novel patterns by generating ensembles from data. The main goal of label-less stream processing is to process the sensed events to eliminate the noises that are uncorrelated, and choose the most likely model without over fitting thus obtaining higher model confidence. Higher quality streams can be realized by combining many short streams into an ensemble which has the desired quality. The framework for the investigation is an existing data mining tool. First, to accommodate feature extraction such as a bush or natural forest-fire event we make an assumption of the burnt area (BA*), sensed ground truth as our target variable obtained from logs. Even though this is an obvious model choice the results are disappointing. The reasons for this are two: One, the histogram of fire activity is highly skewed. Two, the measured sensor parameters are highly correlated. Since using non descriptive features does not yield good results, we resort to temporal features. By doing so we carefully eliminate the averaging effects; the resulting histogram is more satisfactory and conceptual knowledge is learned from sensor streams. Second is the process of feature induction by cross-validating attributes with single or multi-target variables to minimize training error. We use F-measure score, which combines precision and accuracy to determine the false alarm rate of fire events. The multi-target data-cleaning trees use information purity of the target leaf-nodes to learn higher order features. A sensitive variance measure such as f-test is performed during each node’s split to select the best attribute. Ensemble stream model approach proved to improve when using complicated features with a simpler tree classifier. The ensemble framework for data-cleaning and the enhancements to quantify quality of fitness (30% spatial, 10% temporal, and 90% mobility reduction) of sensor led to the formation of streams for sensor-enabled applications. Which further motivates the novelty of stream quality labeling and its importance in solving vast amounts of real-time mobile streams generated today.

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The purpose of this study is to investigate the effects of bilingual and monolingual videos on the reading comprehension of students with significant hearing impairments and/or deafness. Children with and without hearing losses need reading programs in which comprehension of meaning is the primary goal. This can occur only when print is represented in meaningful context, allowing children to create meaning from their own experience, background, and knowledge of language.^ Investigated in this study was whether students with significant hearing losses comprehended more information in a bilingual or monolingual instructional video format. There were three instructional videos produced: (a) the bilingual video which incorporated American Sign Language (ASL) with standard English captions, (b) a monolingual English video with standard English captions only, and (c) a monolingual ASL-only video. It was hypothesized that the effects of English captioning with ASL might serve as a bridge during instruction, increasing reading comprehension and written English for students. It was further hypothesized that this would allow students to integrate their own ASL knowledge to the printed text to construct meaning.^ Four separate analyses were conducted to see if the hypothesis was supported by the findings. However, all results indicated that there were no significant differences in students' written measures of reading comprehension recall across any of the three presentations of information (two monolingual and one bilingual condition). There were seven variables (word identification, word recall, sentence recall, story recall, written passage theme, written passage word count, and number of mature words) used to evaluate reading comprehension recall. No variable, either individually or grouped, demonstrated a significant difference between monolingual or bilingual instruction. ^