The World Wide Web provides a wealth of information about everything, including contemporary audio and visual art events, which are discussed on media outlets, blogs, and specialized websites alike. This information m...The World Wide Web provides a wealth of information about everything, including contemporary audio and visual art events, which are discussed on media outlets, blogs, and specialized websites alike. This information may become a robust source of real-world data, which may form the basis of an objective data-driven analysis. In this study, a methodology for collecting information about audio and visual art events in an automated manner from a large array of websites is presented in detail. This process uses cutting edge Semantic Web, Web Search and Generative AI technologies to convert website documents into a collection of structured data. The value of the methodology is demonstrated by creating a large dataset concerning audiovisual events in Greece. The collected information includes event characteristics, estimated metrics based on their text descriptions, outreach metrics based on the media that reported them, and a multi-layered classification of these events based on their type, subjects and methods used. This dataset is openly provided to the general and academic public through a Web application. Moreover, each event’s outreach is evaluated using these quantitative metrics, the results are analyzed with an emphasis on classification popularity and useful conclusions are drawn concerning the importance of artistic subjects, methods, and media.展开更多
Objective: The reports submitted to the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) from 1997 to 2011 were reviewed to assess the gender effects on muscular adverse events induced by t...Objective: The reports submitted to the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) from 1997 to 2011 were reviewed to assess the gender effects on muscular adverse events induced by the administration of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors (statins). Methods: After the deletion of duplicated submissions and the revision of arbitrary drug names, the reports involving pravastatin, simvastatin, atorvastatin, rosuvastatin, and cerivastatin were analyzed. Data mining algorithms were applied for the quantitative detection of signals, where a signal means a drug-associated adverse event, including the proportional reporting ratio, the reporting odds ratio, the information component, and the empirical Bayes geometric mean. Myopathy, myalgia, myositis, rhabdomyolysis, and an increase in creatine phosphokinase level were focused on as the muscular adverse events. Results: The total number of reports was 3,472,494. The signal scores suggested that all 5 statins were associated with 5 muscular adverse events in both male and female patients. The scores varied among statins, but were more noteworthy for cerivastatin. Conclusion: The data strongly suggested the necessity of well-organized clinical studies on statin-associated muscular adverse events.展开更多
In monitoring systems, multiple sensor nodes can detect a single target of interest simultaneously and the data collected are usually highly correlated and redundant. If each node sends data to the base station, energ...In monitoring systems, multiple sensor nodes can detect a single target of interest simultaneously and the data collected are usually highly correlated and redundant. If each node sends data to the base station, energy will be wasted and thus the network energy will be depleted quickly. Data aggregation is an important paradigm for compressing data so that the energy of the network is spent efficiently. In this paper, a novel data aggregation algorithm called Redundancy Elimination for Accurate Data Aggregation (READA) has been proposed. By exploiting the range of spatial correlations of data in the network, READA applies a grouping and compression mechanism to remove duplicate data in the aggregated set of data to be sent to the base station without largely losing the accuracy of the final aggregated data. One peculiarity of READA is that it uses a prediction model derived from cached values to confirm whether any outlier is actually an event which has occurred. From the various simulations conducted, it was observed that in READA the accuracy of data has been highly preserved taking into consideration the energy dissipated for aggregating the展开更多
Back of queue crashes on Interstates are a major concern for all state transportation departments. In 2020, Indiana DOT begin deploying queue warning trucks with message boards, flashers and digital alerts that could ...Back of queue crashes on Interstates are a major concern for all state transportation departments. In 2020, Indiana DOT begin deploying queue warning trucks with message boards, flashers and digital alerts that could be transmitted to navigation systems such as Waze. This study reports on the deployment and impact evaluation of digital alerts on motorist’s assistance patrols and 19 Queue trucks in Indiana. The motorist assistance patrol evaluation is provided qualitatively. A novel analysis of queue warning trucks equipped with digital alerts was conducted during the months of May-July in 2021 using connected vehicle data. This new data set reports locations of anonymous hard-braking events from connected vehicles on the Interstate. Hard-braking events were tabulated for when queueing occurred with and without the presence of a queue warning truck. Approximately 370 hours of queueing with queue trucks present and 58 hours of queueing without queue truck<span style="font-family:Verdana;">s</span><span style="font-family:Verdana;"> present were evaluated. Hard-braking events were found to decrease approximately 80% when queue warning trucks were used to alert motorists of impending queues.</span>展开更多
文摘The World Wide Web provides a wealth of information about everything, including contemporary audio and visual art events, which are discussed on media outlets, blogs, and specialized websites alike. This information may become a robust source of real-world data, which may form the basis of an objective data-driven analysis. In this study, a methodology for collecting information about audio and visual art events in an automated manner from a large array of websites is presented in detail. This process uses cutting edge Semantic Web, Web Search and Generative AI technologies to convert website documents into a collection of structured data. The value of the methodology is demonstrated by creating a large dataset concerning audiovisual events in Greece. The collected information includes event characteristics, estimated metrics based on their text descriptions, outreach metrics based on the media that reported them, and a multi-layered classification of these events based on their type, subjects and methods used. This dataset is openly provided to the general and academic public through a Web application. Moreover, each event’s outreach is evaluated using these quantitative metrics, the results are analyzed with an emphasis on classification popularity and useful conclusions are drawn concerning the importance of artistic subjects, methods, and media.
文摘Objective: The reports submitted to the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) from 1997 to 2011 were reviewed to assess the gender effects on muscular adverse events induced by the administration of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors (statins). Methods: After the deletion of duplicated submissions and the revision of arbitrary drug names, the reports involving pravastatin, simvastatin, atorvastatin, rosuvastatin, and cerivastatin were analyzed. Data mining algorithms were applied for the quantitative detection of signals, where a signal means a drug-associated adverse event, including the proportional reporting ratio, the reporting odds ratio, the information component, and the empirical Bayes geometric mean. Myopathy, myalgia, myositis, rhabdomyolysis, and an increase in creatine phosphokinase level were focused on as the muscular adverse events. Results: The total number of reports was 3,472,494. The signal scores suggested that all 5 statins were associated with 5 muscular adverse events in both male and female patients. The scores varied among statins, but were more noteworthy for cerivastatin. Conclusion: The data strongly suggested the necessity of well-organized clinical studies on statin-associated muscular adverse events.
文摘In monitoring systems, multiple sensor nodes can detect a single target of interest simultaneously and the data collected are usually highly correlated and redundant. If each node sends data to the base station, energy will be wasted and thus the network energy will be depleted quickly. Data aggregation is an important paradigm for compressing data so that the energy of the network is spent efficiently. In this paper, a novel data aggregation algorithm called Redundancy Elimination for Accurate Data Aggregation (READA) has been proposed. By exploiting the range of spatial correlations of data in the network, READA applies a grouping and compression mechanism to remove duplicate data in the aggregated set of data to be sent to the base station without largely losing the accuracy of the final aggregated data. One peculiarity of READA is that it uses a prediction model derived from cached values to confirm whether any outlier is actually an event which has occurred. From the various simulations conducted, it was observed that in READA the accuracy of data has been highly preserved taking into consideration the energy dissipated for aggregating the
文摘Back of queue crashes on Interstates are a major concern for all state transportation departments. In 2020, Indiana DOT begin deploying queue warning trucks with message boards, flashers and digital alerts that could be transmitted to navigation systems such as Waze. This study reports on the deployment and impact evaluation of digital alerts on motorist’s assistance patrols and 19 Queue trucks in Indiana. The motorist assistance patrol evaluation is provided qualitatively. A novel analysis of queue warning trucks equipped with digital alerts was conducted during the months of May-July in 2021 using connected vehicle data. This new data set reports locations of anonymous hard-braking events from connected vehicles on the Interstate. Hard-braking events were tabulated for when queueing occurred with and without the presence of a queue warning truck. Approximately 370 hours of queueing with queue trucks present and 58 hours of queueing without queue truck<span style="font-family:Verdana;">s</span><span style="font-family:Verdana;"> present were evaluated. Hard-braking events were found to decrease approximately 80% when queue warning trucks were used to alert motorists of impending queues.</span>
