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A Pilot Study: Integrating an Emergency Department with Indiana's Prescription Drug Monitoring Program

引用

7th International Conference on Universal Access in Human-Computer Interaction: Design Methods, Tools, and Interaction Techniques for eInclusion, UAHCI 2013, Held as Part of 15th International Conference on Human-Computer Interaction, HCI 2013

作者： Abedtash, Hamed Finnell, John T. School of Informatics and Computing Indiana University Indianapolis IN 46202 United States School of Medicine Indiana University Indianapolis IN 46202 United States Regenstrief Institute Indianapolis IN 46202 United States

ISBN: (纸本)9783642391934

Rapid increase in abuse and overdose of controlled substances was the main driving force of implementing Prescription Drug Monitoring Programs (PDMP). We aimed to describe how the integrated Indiana's PDMP (INSPECT) data into an electronic health record (EHR) can improve clinical workflow within an emergency department (ED). After integration, upon patient arrival into the ED, a PDMP report containing history of dispensed schedule II-V medications is retrieved and stored in the patient's medical record. The evaluation of the new system among physicians showed high satisfaction of having access to the patients' medication history through the existing EHR. We show that the PDMP data was easily accessible and more informative in the new integrated system. The PDMP report alters the pattern of prescribing narcotic medications to patients. In conclusion, enhancing workflow through PDMP reports integration with the patients' EHR is valued by the clinicians and reduces the number of narcotic prescriptions. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Emergency rooms

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Video Volume Segmentation for Event Detection

Video Volume Segmentation for Event Detection

引用

International Conference on Computer Graphics, Imaging and Visualization, CGIV

作者： Jing Wang Zhijie Xu Qian Xu Department of Informatics School of Computing and Engineering University of Huddersfield Huddersfield UK

Video processing for surveillance and security applications has become a research hotspot in the last decade. This paper reports a research into volume-based segmentation techniques for video event detection. It starts with an introduction of the structure in 3D video volumes denoted by spatio-temporal features extracted from video footages. The focus of the work is on devising an effective and efficient 3D segmentation technique suitable to the volumetric nature of video events through deploying innovative 3D clustering methods. It is supported by the design and experiment on the 3D data compression techniques for accelerating the pre-processing of the original video data. An evaluation on the performance of the developed methods is presented at the end.

关键词： Event detection Shape Video compression Feature extraction Image segmentation Surveillance Data mining Humans Data structures Computer graphics

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Predicting Disease-related RNA Associations based on Graph Convolutional Attention Network

Predicting Disease-related RNA Associations based on Graph C...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Jinli Zhang Xiaohua Hu Zongli Jiang Bo Song Wei Quan Zheng Chen Faculty of Information Technology Beijing University of Technology Beijing China College of Computing and Informatics nDrexel University Philadelphia USA College of Computing and Informatics Drexel University Philadelphia USA

Accumulating evidence has demonstrated that RNAs play an important role in identifying various complex human diseases. However, the number of known disease related RNAs is still small and many biological experiments are time-consuming and labor-intensive. Therefore, researchers have focused on developing useful computational algorithms to predict associations between diseases and RNAs. It is useful for people to identify complex human diseases at molecular level, especially in diseases diagnosis, therapy, prognosis and monitoring. In this paper, we propose a novel framework Graph Convolutional Attention Network(GCAN) to predict potential disease-RNAs associations. Facing thousands of associations, GCAN benefits from the efficiency of deep learning model. Compared to other disease-RNAs association prediction methods, GCAN operates the computation process from global structure of disease-RNAs network with graph convolution networks(GCN) and can also integrate local neighborhoods with the attention mechanism. What is more, GCAN is at the first attempt to utilize GCN to discover the feature representation of the latent nodes in disease-RNAs network. In order to evaluate the performance of GCAN, we conduct experiments on two different disease-RNAs networks: disease-miRNA and disease-lncRNA. Comparisons of several state-of-the-art methods using disease-RNAs networks show that our novel frameworks outperform baselines by a wide margin in potential disease-RNAs associations.

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Grouping and Categorizing Data from Social Networking Applications for Forensic Analysis

Grouping and Categorizing Data from Social Networking Applic...

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Artificial Intelligence, Blockchain, Cloud computing, and Data Analytics (ICoABCD), International Conference on

作者： Handoko Tejo Atmoko Niken Dwi Wahyu Cahyani Syofian Kurniawan School of Computing Telkom University Bandung Indonesia Informatics Applications Control Ministry of Communications and Informatics Jakarta Indonesia

ISBN: (数字)9798350368451

ISBN: (纸本)9798350368468

Social media has become a new trend in the lifestyle of modern society. It provides an indispensable data source for daily life, with widespread use worldwide. This research aims to simplify the complexity of social networking application data and provide key information needed in forensic investigations. Specifically, the objectives are to identify the types of data that can be collected from Twitter and Instagram and develop a methodology to efficiently and effectively group and categorize the data to answer the key forensic questions of Who, Where, What, When, Why, and How. The proposed methodology includes automated web crawling using Apify, grouping and categorizing data based on key parameters, and storing and managing PostgreSQL data. This research targets law enforcement and forensic analysts, providing them with a robust tool for digital forensic investigations. The results of this study show that the methodology successfully simplifies social media data, making it more structured and easier to analyze for forensic purposes.

关键词： Social networking (online) Law enforcement Soft sensors Digital forensics Blogs Market research Complexity theory Web sites Multimedia communication Object recognition

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Designing a Temperature Model to Understand the Thermal Challenges of Portable computing Platforms

Designing a Temperature Model to Understand the Thermal Chal...

引用

IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems

作者： Ying-Ju Yu Carole-Jean Wu School of Computing Informatics and Decision Systems Engineering Arizona State University

Modern high-performance processors are embedded in portable electronics, such as smartphones, self-driving automobiles, and augmented reality wearable. These computing platforms provide real-time direction navigation, high definition video entertainment, real-time sensing and control. One of the major performance limiting factors in these platforms is the poorly designed thermal solution to prevent overheating at the processor transistor junction and at the platform surface. The former limits the maximum operating temperature of transistors to guarantee reliability and lifetime whereas the latter limits the maximum platform surface temperature to ensure user ergonomic comfort. To design effective cooling solutions for high-performance, multi-layer, multi-processor platforms, an accurate and detailed platform level temperature model is needed. In this work, we present a detailed finite volume model to predict the temperature behavior of a tightly packaged, high-performance portable platform, from the system level down to the processor architecture level. We first characterize the thermal response of real-world, representative mobile workloads and perform parametric studies to predict the processor junction and platform surface temperature based on the properties of the platform. We observe that thermal hot spots are sensitive to workload computation characteristics. In particular, for mobile workloads, such as web browsing, computations often occur in short time burst, leading to instantaneous power spikes. This results in temperature spikes as thermal hot spots. To mitigate the thermal issue, modern systems implement dynamic voltage and frequency scaling during high performance and high power scenario to prevent cores from overheating. We validate the proposed temperature model used to predict the maximum temperature at the processor chip and at the platform surface, with measurements from the embedded temperature sensors and an infrared camera. The temperature pred

关键词： Thermal modeling Temperature prediction Thermal management Temperature-aware floor plan Portable electronics Smartphones Skin temperature

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A Log Aggregation Design Criteria for Robust SIEM (Security Information and Event Management) in Enhancing Threat Detection

A Log Aggregation Design Criteria for Robust SIEM (Security ...

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Recent Advances and Innovations in Engineering (ICRAIE)

作者： Mohsen Bin Mohamad Hata Mohamad Yusof Bin Darus Muhammad Zul Akmal Bin Shafiee Elvisianah Petrus Yasmin Athira Jamian College of Computing Informatics and Mathematics Universiti Teknologi MARA Selangor Malaysia

Security Operations Centers (SOCs) play a vital role in protecting organizations from cyber threats. Supported by skilled Security Analysts, they are the first line of defense, monitoring and responding to incidents. The Security Information and Event Management (SIEM) system is a critical tool for managing log data efficiently. This research focuses on optimizing log data aggregation within a SOC's SIEM framework. By exploring various log aggregation techniques, we aim to enhance the performance of data collectors, leading to quicker response times and improved security. This research contributes to a more robust defense against the ever-changing landscape of cyber threats. It empowers organizations to face evolving challenges with confidence and resilience.

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3D facial feature extraction based on the symmetry plane analysis

3D facial feature extraction based on the symmetry plane ana...

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14th IASTED International Conference on Signal and Image Processing, SIP 2012

作者： Al-Qatawneh, Sokyna M. Ipson, Stanly S. Qahwaji, Rami S. Department of Software Engineering Faculty of Science and Information Technology Al-Zaytoonah University of Jordan Amman Jordan Informatics Research Institute School of Computing Informatics and Media University of Bradford Richmond Road Bradford West Yorkshire BD7 1DP United Kingdom

ISBN: (纸本)9780889869493

Recently with the development of more affordable 3D acquisition systems and the availability of 3D face databases, 3D face recognition has been attracting interest to tackle the limitations in performance of most existing 2D systems. In this work, a novel method for the automatic processing of 3D facial data is presented. Here the input data can be in the form either of a 3D triangular facial mesh (containing the coordinate and connectivity information), or of a data point cloud. In the new approach, the main goal is to automatically determine a symmetry profile for the face. This is undertaken by computing the intersection between the symmetry plane (found by an automatic search) and the facial mesh, resulting in a planer curve that accurately represents the symmetry profile. This is then utilized to allocate the central region of the face and it extracts a set of profiles from that region which can be used for recognition purposes.

关键词： Extraction

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Online Flocking Control of UAVs with Mean-Field Approximation

Online Flocking Control of UAVs with Mean-Field Approximatio...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Malintha Fernando Luddy School of Informatics Computing and Engineering Indiana University Bloomington IN USA

We present a novel approach to the formation controlling of aerial robot swarms that demonstrates the flocking behavior. The proposed method stems from the Unmanned Aerial Vehicle (UAV) dynamics; thus, it prevents any unattainable control inputs from being produced and subsequently leads to feasible trajectories. By modeling the inter-agent relationships using a pairwise energy function, we show that interacting robot swarms constitute a Markov Random Field. Our algorithm builds on the Mean-Field Approximation and incorporates the collective behavioral rules: cohesion, separation, and velocity alignment. We follow a distributed control scheme and show that our method can control a swarm of UAVs to a formation and velocity consensus with real-time collision avoidance. We validate the proposed method with physical and high-fidelity simulation experiments.

关键词： Heuristic algorithms Decentralized control Unmanned aerial vehicles Real-time systems Trajectory Vehicle dynamics Collision avoidance

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Static analysis based business logic modelling from legacy system code: Business process model notation (BPMN) extraction using abstract syntax tree (AST)

Static analysis based business logic modelling from legacy s...

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International Symposium on Networks, Computers and Communications (ISNCC)

作者： Mohammed Alawairdhi College of Computing and Informatics Saudi Electronic University Riyadh Saudi Arabia

Business logic extraction is a very important concept in the realm of object oriented software engineering as it deals with reusability to a great extent. Proper reusability of existing systems (legacy systems) to accommodate required changes thereby transforming existing systems into new ones is an important consideration of object oriented development. This yields several significant advantages such as cost reduction, scheduled development and minimal learning overhead etc. In this paper, we propose a novel method for extracting business logic from existing system. The method developed for extracting business logic in an existing system follows a static-analysis based approach. The method relies on analyzing the source code of the system independently from any input which requires an execution of the system.

关键词： Business Unified modeling language Object oriented modeling Software systems Aging Analytical models

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Research on railroad line spatial information management technology

Research on railroad line spatial information management tec...

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2023 International Conference on Remote Sensing, Mapping, and Geographic Systems, RSMG 2023

作者： Li, Congxu Xu, Xiaolei Feng, Boqing Zhang, Maolin Institute of Computing Technologies China Academy of Railway Sciences Corporation Limited China Beijing University of Civil Engineering and Architecture School of Geomatics and Urban Spatial Informatics Beijing100044 China

ISBN: (纸本)9781510668898

With the completion of railroad line resurvey work, the measurement data are scattered in various units and lack unified storage and management, which brings many challenges and problems to railroad operation and maintenance. To solve this problem, this study proposes a multi-version, multi-temporal spatial data storage technology, as well as a distributed fast storage technology and a spatial service engine by studying the data management work, aiming to realize unified and fast storage, management and sharing of railroad survey data to improve the reliability, consistency and validity of data. First, this study focuses on the multi-version and multi-temporal spatial data storage technology. By adopting this technology, a large amount of spatial data generated by railroad line resurvey can be effectively handled, and the storage and management of different versions and temporal phases of data can be realized. Meanwhile, distributed fast storage technology is introduced to provide high-speed data access and processing capability to cope with the storage and processing demand of massive data. In addition, using the spatial service engine, fast query and analysis of measurement data can be realized. Second, this study also conducts an in-depth research on the railroad line measurement data management system. First, the overall architecture of the system is designed to ensure the scalability and flexibility of the system. Then, the data structure of the system was optimized to accommodate the storage and query requirements of multi-version and multi-temporal data. In terms of technical architecture, distributed storage technology is adopted to realize fast storage and retrieval of remote sensing, 2D vector and 3D model data. In addition, the sharing and exchange of measurement data is realized through information sharing and information interface. The innovation of this study is to propose a multi-version and multi-temporal spatial data storage technology, and to reali

关键词： Information management

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