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Audit Workpaper Automation at Boston College

EDPACS 2006年第7期27卷 1-8页

作者： Pamela Jerskey The IS audit manager at Boston College. She is responsible for conducting audits in information technology and distributed departmental applications. These assignments focus on controls over program security computer operations data file security system software network configurations and end-user computing. During 1999 Jerskey was the program manager of the Y2K project at Boston College. The Boston College Internal Audit World Wide Web home page can be accessed at: http://www.bc.edu/bc_org/fvp/ia/home/home.html

The Boston College Internal Audit Department has developed best practices that will enable its auditors to face the techno-logical challenges and changes of the next millennium. In ad-dition to automating the department's workpapers, the information-processing applications involved perform follow-up audits electronically. The department has accomplished these tasks not by purchasing an expensive software product, but by using existing software resources. The department cur-rently uses Microsoft Office for automating the creation and use of its workpapers; however, it developed this application before Microsoft Office was even a twinkle in Bill Gates' eye.

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Prevalence, rate, and predictors of virologic failure among adult HIV-Infected clients on second-line antiretroviral therapy (ART) in Tanzania (2018–2020): a retrospective cohort study

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Bulletin of the National Research Centre 2024年第1期48卷 1-13页

作者： Mwavika, Ester Timothy Kunambi, Peter Ponsian Masasi, Samuel Joseph Lema, Nsiande Kamori, Doreen Matee, Mecky Department of Epidemiology and Biostatistics Muhimbili University of Health and Allied Sciences Dar es Salaam Tanzania Tanzania Field Epidemiology and Laboratory Training Program Dar es Salaam Tanzania Department of Clinical Pharmacology Muhimbili University of Health and Allied Sciences Dar es Salaam Tanzania Department of Software Engineering University of Dar es Salaam Computing Centre Dar es Salaam Tanzania Department of Microbiology and Immunology School of Diagnostic Medicine Muhimbili University of Health and Allied Sciences Dar es Salaam Tanzania

Antiretroviral therapy (ART) has been proven to be highly effective in reducing the impact of human immunodeficiency virus (HIV) infection. However, as more people receive initial ART treatment, the risk of developing resistance and eventual treatment failure increases, leading to the need for second-line treatment regimens. Understanding the factors that contribute to virologic failure to second-line ART is crucial in preventing switching to the more expensive and toxic third-line regimens. This study provides information on the prevalence, rate, and predictors of virologic failure (VF) among clients on second-line ART in Tanzania. We followed 4718 clients for 15100 person-years (PY) of observations. Of them, 1402 (29.72%) experienced virologic failure at a rate of 92.85 per 1000 PY of observations (95% CI 88.11, 97.84). Factors that were associated with VF included: having a viral load count of ≥ 1000 copies/mL during first-line ART, with a hazard ratio (HR) 4.65 (95% CI 3.57, 6.07), using lopinavir (LPV/r) as a protease inhibitor during second-line ART (HR 4.20 (95% CI 3.12, 7.10), having a CD4 count < 200 cells/mm3 during second-line ART (HR 1.89 (95% CI 1.46, 2.44), and being on ART for 13–35 months (HR 8.22 (95% CI 2.21, 30.61). Paradoxically, having a CD4 count < 200 cells/mm3 during first-line ART treatment was associated with a reduced risk of virologic failure (HR 0.77 (95% CI 0.60, 0.99). In Tanzania, approximately 30% of adult clients on second-line ART experience VF at a rate of 92.71 per 1000 person-years. This high virologic failure rate underscores the urgent need for targeted interventions, such as enhancing adherence support, optimizing drug regimens, and regular viral load monitoring. These interventions will reduce the need for switching to the more costly and toxic third-line ART therapy and are also crucial for achieving the UNAIDS goal of 95% viral suppression among treated individuals by 2030.

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Real-time embedded system support for the BTeV level 1 muon trigger

Real-time embedded system support for the BTeV level 1 muon ...

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2003 IEEE Nuclear Science Symposium Conference Record - Nuclear Science Symposium, Medical Imaging Conference

作者： Haney, Michael J. Beauregard, D. Iyer, R. Kalbarczyk, Z. Liu, Q. Wang, L. Haney, M. Selen, M. Mosse, D. Shigiltchoff, O. Chopade, R. Hovey, L. Jung, M. Messie, D. Oh, J. Stone, S. Bapty, T. Neema, S. Nordstrom, S. Shetty, S. Vashishtha, S. Yao, D. Sheldon, P. Vaandering, E. Butler, J. Gottschalk, E. Kowalkowski, J. Votava, M. Appel, J. University of Illinois Urbana IL 61801 United States Des./Validation Reliable N.S.R.G. University of Illinois High Energy Physics Group Department of Physics University of Illinois Department of Computer Science Coll. in High Sch. Educ. Program University of Pittsburgh Department of Electrical Engineering Syracuse University High Energy Physics Group Department of Physics Syracuse University Inst. for Software Intgd. Systems Vanderbilt University Department of Physics BTeV Group Vanderbilt University BTeV Collaboration Particle Physics Division Fermi Natl. Accelerator Laboratory Computing Division Fermi Natl. Accelerator Laboratory Fermilab Education Office Fermi Natl. Accelerator Laboratory

The Level 1 Muon Trigger subsystem for BTeV will be implemented using the same architectural building blocks as the BTeV Level 1 Pixel Trigger: pipelined field programmable gate arrays feeding a farm of dedicated processing elements. The muon trigger algorithm identifies candidate tracks, and is sensitive to the muon charge (sign);candidate dimuon events are identified by complementary charge track-pairs. To insure that the trigger is operating effectively, the trigger development team is actively collaborating in an independent multi-university research program for reliable, self-aware, fault adaptive behavior in real-time embedded systems (RTES). Key elements of the architecture, algorithm, performance, and engineered reliability are presented.

关键词： Embedded systems

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Augmented Reality Based Brain Tumor 3D Visualization

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Procedia Computer Science 2017年 113卷 400-407页

作者： Qian Shan Thomas E. Doyle Reza Samavi Mona Al-Rei Department of Computing and Software McMaster University 1280 Main St. W Hamilton ON L8S 4L8 Canada Department of Electrical and Computer Engineering School of Biomedical Engineering McMaster University 1280 Main St. W Hamilton ON L8S 4L8 Canada eHealth Graduate Program McMaster University 1280 Main St. W Hamilton ON L8S 4L8 Canada

In this paper we present an augmented reality system for mobile devices that facilitates 3D brain tumor visualization in real time. The system uses facial features to track the subject in the scene. The system performs camera calibration based on the face size of the subject, instead of the common approach of using a number of chessboard images to calibrate the camera every time the application is installed on a new device. Camera 3D pose estimation is performed by finding its position and orientation based on a set of 3D points and their corresponding 2D projections. According to the estimated camera pose, a reconstructed brain tumor model is displayed at the same location as the subject’s real anatomy. The results of our experiment show the system was successful in performing the brain tumor augmentation in real time with a reprojection accuracy of 97%.

关键词： Augmented reality 3D visualization Tumor visualization Markerless tracking Mobile device

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Alteration in circulating metabolites during and after heat stress in the conscious rat: Potential biomarkers of exposure and organ-specific injury

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BMC Physiology 2014年第1期14卷 14页

作者： Ippolito, Danielle L. Lewis, John A. Yu, Chenggang Leon, Lisa R. Stallings, Jonathan D. United States Army Center for Environmental Health Research Environmental Health Program Bldg. 568 Doughten Drive Frederick 21702-5010 MD United States Biotechnology High Performance Computing Software Applications Institute Frederick 21702-5010 MD United States Thermal Mountain Medicine Division US Army Research Institute of Environmental Medicine Natick 01760-5007 MA United States

Background: Heat illness is a debilitating and potentially life-threatening condition. Limited data are available to identify individuals with heat illness at greatest risk for organ damage. We recently described the transcriptomic and proteomic responses to heat injury and recovery in multiple organs in an in vivo model of conscious rats heated to a maximum core temperature of 41.8°C (T_c,Max). In this study, we examined changes in plasma metabolic networks at T_c,Max, 24, or 48 hours after the heat stress stimulus. Results: Circulating metabolites were identified by gas chromatography/mass spectrometry and liquid chromatography/tandem mass spectrometry. Bioinformatics analysis of the metabolomic data corroborated proteomics and transcriptomics data in the tissue at the pathway level, supporting modulations in metabolic networks including cell death or catabolism (pyrimidine and purine degradation, acetylation, sulfation, redox alterations and glutathione metabolism, and the urea cycle/creatinine metabolism), energetics (stasis in glycolysis and tricarboxylic acid cycle, ß-oxidation), cholesterol and nitric oxide metabolism, and bile acids. Hierarchical clustering identified 15 biochemicals that differentiated animals with histopathological evidence of cardiac injury at 48 hours from uninjured animals. The metabolic networks perturbed in the plasma corroborated the tissue proteomics and transcriptomics pathway data, supporting a model of irreversible cell death and decrements in energetics as key indicators of cardiac damage in response to heat stress. Conclusions: Integrating plasma metabolomics with tissue proteomics and transcriptomics supports a diagnostic approach to assessing individual susceptibility to organ injury and predicting recovery after heat stress. © 2014 Ippolito et al.

关键词： Energetics Heat stress Metabolic networks Metabolomics Systems biology

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Perspectives on risk prioritization of data center vulnerabilities using rank aggregation and multi-objective optimization

arXiv

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arXiv 2022年

作者： Grisci, Bruno Iochins Kuhn, Gabriela Colombelli, Felipe Matter, Vítor Kehl Lima, Leomar Heinen, Karine Pegoraro, Mauricio Borges, Marcio Rigo, Sandro José Barbosa, Jorge Luis Victória da Rosa Righi, Rodrigo da Costa, Cristiano André de Oliveira Ramos, Gabriel Software Innovation Laboratory - Softwarelab Graduate Program in Applied Computing Universidade do Vale do Rio dos Sinos Av. Unisinos 950 RS São Leopoldo93022-750 Brazil Institute of Informatics Federal University of Rio Grande do Sul Av. Bento Gonçalves 9500 RS Porto Alegre91501-970 Brazil Dell Technologies Brazil Av. Industrial Belgraf 400 Eldorado do Sul RS 92990-000 Brazil

Nowadays, data has become an invaluable asset to entities and companies, and keeping it secure represents a major challenge. Data centers are responsible for storing data provided by software applications. Nevertheless, the number of vulnerabilities has been increasing every day. Managing such vulnerabilities is essential for building a reliable and secure network environment. Releasing patches to fix security flaws in software is a common practice to handle these vulnerabilities. However, prioritization becomes crucial for organizations with an increasing number of vulnerabilities since time and resources to fix them are usually limited. This review intends to present a survey of vulnerability ranking techniques and promote a discussion on how multi-objective optimization could benefit the management of vulnerabilities risk prioritization. The state-of-the-art approaches for risk prioritization were reviewed, intending to develop an effective model for ranking vulnerabilities in data centers. The main contribution of this work is to point out multi-objective optimization as a not commonly explored but promising strategy to prioritize vulnerabilities, enabling better time management and increasing security. Copyright © 2022, The Authors. All rights reserved.

关键词： Multiobjective optimization

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Building a Winning Business Case for Standards Adoption

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IEEE Engineering Management Review 2020年第1期48卷 14-17页

作者： Bishop, David David Bishop (Senior Member IEEE) received the Bachelor of Computer Engineering degree from the Georgia Institute of Technology Atlanta GA USA and the M.B.A. degree with a concentration in IT management and a doctorate degree in business administration from Georgia State University Atlanta GA USA. He is a Technologist Consultant Researcher Entrepreneur and Instructor with more than 25 years of experience in telecommunications transportation government and utility industries. He is the author of Metagility: Managing Agile Development for Competitive Advantage Elizabeth's Song The Big Brother's Guides and numerous other books and articles. He is a frequent contributor to Ieee's Engineering Management Review and an inventor of several U.S. patents. He is the CEO and Founder of Agile Worx LLC a firm that provides program and project management software tools training and consulting services. He is a member and Committee Chair for the International Electrotechnical Commission (IEC) based in Geneva Switzerland a member of ANSI and the Association for Computing Machinery. David is also a Research Associate with the Center for Engaged Business Research Georgia State University and the Founding Chair for the Atlanta chapter of the IEEE Technology and Engineering Management Society.

In a recent issue of Ieee Engineering Management Review, we explored the problem of building a winning business case and the elements that can differentiate an 'average' business case from a 'winning' one. For this second installment, we will show how these winning elements were applied in practice. To make it even more interesting, we will illustrate how this can be accomplished with arguably one of the most difficult cases to make: adoption of technical standards. Our stakeholder is a large power utility. © 1973-2011 IEEE.

关键词： Task analysis Acceleration

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Fluctuation free matrix representation based random data partitioning through HDMR

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AIP Conference Proceedings 2012年第1期1504卷

作者： M. Alper Tunga Metin Demiralp Bahçeşehir University Faculty of Engineering Department of Software Engineering Beşiktaş 34349 İstanbul Turkey İstanbul Technical University Informatics Institute Computational Science and Engineering Program Group for Science and Methods of Computing Maslak 34469 İstanbul Turkey

High Dimensional Model Representation (HDMR) method does not have the random data partitioning capability because of its nature. This paper focuses on how we can bring the random data partitioning feature to the HDMR method by virtue of the fluctuation free approximation method for the multivariate interpolation problems. The main aim of this work is to construct the universal fluctuation free matrix and to determine the best eigenvalues and the corresponding eigenvectors needed in our new method for partitioning the given multivariate random data through the HDMR method.

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Using Machine Learning to Study the Effects of Genetic Predisposition on Brain Aging in the UK Biobank

Using Machine Learning to Study the Effects of Genetic Predi...

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IEEE International Symposium on Biomedical Imaging

作者： Karen Ardila Emily Munro Fernando Vega Aashka Mohite Charlotte Curtis Amanda V. Tyndall M. Ethan MacDonald Department of Electronic and Automation Biomedical Engineering Universidad Autónoma de Manizales Manizales Colombia Department of Biomedical Engineering University of Calgary Calgary Canada Department of Electrical & Software Engineering University of Calgary Calgary Canada Department of Radiology University of Calgary Calgary Canada Hotchkiss Brain Institute University of Calgary Calgary Canada Mitacs Globalink Research Internship Program Canada Department of Chemical Engineering University of Calgary Calgary Canada Department of Mathematics and Computing Mount Royal University Calgary Canada Department of Medical Genetics University of Calgary Calgary Canada

The influence of genetic predisposition on changes in brain morphology during aging remains largely unknown. This study explores the effects of genetic predisposition on three key brain regions: total brain volume (TBV), lateral ventricular volume (LVV), and total hippocampal volume (THV). The brain age gap estimate (BrainAGE) biomarker is used as an input to a genome-wide association study to determine which single nucleotide polymorphisms (SNPs) and genes are associated with accelerated brain aging. Six independent significant SNPs were found to contribute to accelerated morphological changes: TBV had associations on chromosome 17 linked with brain aging, and the total THV had independent significant associations in the APOC1 and TOMM40 gene regions related to neurodegeneration. Lastly, LVV presented a possible novel discovery in the gene NUAK1, known to play a role in cellular senescence. This study provides a framework to uncover complex associations between brain aging physiology and genetics.

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AAAI 2008 workshop reports

AAAI 2008 workshop reports

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作者： Anand, Sarabjot Singh Bunescu, Razvan Carvcdho, Vitor Chomicki, Jan Conitzer, Vincent Cox, Michael T. Dignum, Virginia Dodds, Zachary Dredze, Mark Furcy, David Gabrilovich, Evgeniy Göker, Mehmet H. Guesgen, Hans Hirsh, Haym Jannach, Dietmar Junker, Ulrich Ketter, Wolfgang Kobsa, Alfred Koenig, Sven Lau, Tessa Lewis, Lundy Matson, Eric Metzler, Ted Mihalcea, Rada Mobasher, Bamshad Pineau, Joelle Poupart, Pascal Raja, Anita Ruml, Wheeler Sadeh, Norman Shani, Guy Shapiro, Daniel Smith, Trey Taylor, Matthew E. Wagstaff, Kiri Walsh, William Zhou, Rong Department of Computer Science University of Warwick United Kingdom School of Electrical Engineering and Computer Science Ohio University United States Microsoft Live Labs United States computer science and engineering University at Buffalo United States Computer science and economics Duke University United States Intelligent Computing group of BBN Technologies Utrecht University Netherlands Department of Computer science Harvey Mudd College United States University of Pennsylvania United States University of Wisconsin United States Yahoo Research PricewaterhouseCoopers Center for Advanced Research United States Department of Computer science School of Engineering and Advanced Technology Massey University New Zealand Departent of Computer science Rutgers University United States Department of Computer Science Dortmund University of Technology. Germany ILOG Rotterdam School of Management Erasmus University Netherlands Donald Bren School of Information and Computer Sciences University of California Irvine United States Depatrment of Computer science University of Southern California United States IBM Almaden Research Center United States Department of Computer Information Technology Southern New Hampshire University United States Computer and Information Technology Program College of Technology Purdue University United States Hughes Program for Religion and Science Dialogue Oklahoma City University United States Department of Computer Science and Engineering University of North Texas United States School of Computing DePaul University United States Department of Computer Science McGill University Canada School of Computer Science University of Waterloo Canada Department of Software and Information Systems University of North Carolina Charlotte United States University of New Hampshire United States Microsoft Research Institute for the Study of Learning and Expertise Applied Reactivity Inc. United States NASA Ames Research Center Carnegie Mellon University West

AAAI was pleased to present the AAAI-08 Workshop program, held Sunday and Monday, July 13-14, in Chicago, Illinois, USA. The program included the following 15 workshops: Advancements in POMDP Solvers;AI Education Workshop Colloquium;Coordination, Organizations, Institutions, and Norms in Agent Systems, Enhanced Messaging;Human Implications of Human-Robot Interaction;Intelligent Techniques for Web Personalization and Recommender Systems;Metareasoning: Thinking about Thinking;Multidisciplinary Workshop on Advances in Preference Handling;Search in Artificial Intelligence and Robotics;Spatial and Temporal Reasoning;Trading Agent Design and Analysis;Transfer Learning for Complex Tasks;What Went Wrong and Why: Lessons from AI Research and Applications;and Wikipedia and Artificial Intelligence: An Evolving Synergy. Copyright © 2009, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Human robot interaction

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