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Ernst Denert Award for software engineering 2022 1

1000年

作者： Eric Bodden Michael Felderer Wilhelm Hasselbring Paula Herber Heiko Koziolek Carola Lilienthal Florian Matthes Lutz Prechelt Bernhard Rumpe Ina Schaefer

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A standard simulation environment: a review of preliminary requirements 94

A standard simulation environment: a review of preliminary r...

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Simulation Winter Conference

作者： M.A.F. Wagner S. Sevinc O. Tanir P.L. Haigh J.D. Arthur R.E. Nance H.D. Schwetman SysTech Software Solutions Annandale VA USA Knowledge Systems Group Basser University of Sydney Australia Quality Engineering and Research (QER) Group Longueuil QUE Canada High Performance Software Inc. Dayton OH USA Systems Research Center Department of Computer Science Virginia Polytechnic Institute and State University Blacksburg VA USA Mesquite Software Inc. Austin TX USA

ISBN: (纸本)9780780321090

The concept of a simulation environment combines different aspects of the simulation process into one complete powerful tool. The environment should provide the necessary state-of-the-art advances and concepts that a modeler may require during the simulation development and execution process. The "environment" requirements must address the end user needs while minimizing the necessity of learning a new language. The requirements must specify the useful features, independent of different platforms and implementation languages. Hence the opportunity exists for standardization of environments. The paper opens a discussion on challenges and rewards awaiting the simulation community with the advent of a standard environment.

关键词： Power system modeling Computational modeling Computer simulation Standardization knowledge based systems Australia knowledge engineering software performance Drives Computer science

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Construction of the Corpus of Spontaneous Japanese and annotation techniques

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Journal of the National Institute of Information and Communications Technology 2007年第3期54卷 5-14页

作者： Uchimoto, Kiyotaka Isahara, Hitoshi Takanashi, Katsuya Takeuchi, Kazuhiro Nobata, Chikashi Morimoto, Ikuyo Yamada, Atsushi Computational Linguistic Group Knowledge Creating Communication Research Center Academic Center for Computing and Media Studies Kyoto University School of Computer Science University of Manchester Advanced Software Technology and Mechatronics Research Institute of Kyoto Dept. of Engineering Informatics Osaka Elmectro-Communication University School of Low and Politics Kwansei Gakuin University

This paper describes annotations for the Corpus of Spontaneous Japanese. The information we annotated to the corpus includes morphemes, clause units, dependency structures, summaries, and discourse structures. They are integrated in the form of XML. Morphological information was semi-automatically annotated to the transcribed text by reducing the human labor cost within the framework of morphological annotation that we proposed. Next, clause unites were detected based on the morphological information as basic units for our annotation. Then, dependency structures, summaries, discourse structures were annotated based on the clause units.

关键词： Information technology

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C2MS: Dynamic Monitoring and Management of Cloud Infrastructures

C2MS: Dynamic Monitoring and Management of Cloud Infrastruct...

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IEEE International Conference on Cloud Computing Technology and Science (CloudCom)

作者： Gary A. McGilvary Josep Rius Íñigo Goiri Francesc Solsona Adam Barker Malcolm Atkinson Edinburgh Data-Intensive Research Group The University of Edinburgh ICG Software Industrial Polygon Torrefarrera Spain Dept. of Computer Science Rutgers University Dept. of Computer Science and Industrial Engineering Univrsity of Lleida School of Computer Science University of St Andrews

Server clustering is a common design principle employed by many organisations who require high availability, scalability and easier management of their infrastructure. Servers are typically clustered according to the service they provide whether it be the application(s) installed, the role of the server or server accessibility for example. In order to optimize performance, manage load and maintain availability, servers may migrate from one cluster group to another making it difficult for server monitoring tools to continuously monitor these dynamically changing groups. Server monitoring tools are usually statically configured and with any change of group membership requires manual reconfiguration, an unreasonable task to undertake on large-scale cloud infrastructures. In this paper we present the Cloudlet Control and Management System (C2MS), a system for monitoring and controlling dynamic groups of physical or virtual servers within cloud infrastructures. The C2MS extends Ganglia - an open source scalable system performance monitoring tool - by allowing system administrators to define, monitor and modify server groups without the need for server reconfiguration. In turn administrators can easily monitor group and individual server metrics on large-scale dynamic cloud infrastructures where roles of servers may change frequently. Furthermore, we complement group monitoring with a control element allowing administrator-specified actions to be performed over servers within service groups as well as introduce further customized monitoring metrics. This paper outlines the design, implementation and evaluation of the C2MS.

关键词： Servers Monitoring Temperature measurement Clouds Temperature sensors Educational institutions

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Process Support and knowledge Representation in Health Care 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Richard Lenz Silvia Miksch Mor Peleg Manfred Reichert David Riaño Annette Teije

ISBN: (数字)9783642364389

ISBN: (纸本)9783642364372

This book constitutes thoroughly refereed revised selected papers from the BPM 2012 Joint Workshop on Process-Oriented Information Systems and knowledge Representation in Health Care, ProHealth 2012/KR4HC 2012, held in Tallinn, Estonia, in September 2012. The 9 papers presented were carefully reviewed and selected from 19 submissions. In addition the book contains 1 keynote paper and 2 invited contributions. The papers are organized in topical sections named: guidelines and summarization; archetypes and cooperation; and process mining and temporal analysis.

关键词： Artificial Intelligence Information Systems Applications (incl. Internet) Information Storage and Retrieval Database Management User Interfaces and Human Computer Interaction Computer Communication Networks

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DETECTING CRITICAL LEAST ASSOCIATION RULES IN MEDICAL DATABASES

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International Journal of Modern Physics: Conference Series 2012年第9期ijmpcs卷 464-479页

作者： ZAILANI ABDULLAH TUTUT HERAWAN MUSTAFA MAT DERIS Department of Computer Science Universiti Malaysia Terengganu Mengabang Telipot Kuala Terengganu 21030 Terengganu Malaysia Database and Knowledge Management Research Group Faculty of Computer System and Software Engineering Universiti Malaysia Pahang Lebuhraya Tun Razak Gambang 26300 Kuantan Pahang Malaysia Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Parit Raja 86400 Batu Pahat Johor Malaysia

Least association rules are corresponded to the rarity or irregularity relationship among itemset in database. Mining these rules is very difficult and rarely focused since it always involves with infrequent and exceptional cases. In certain medical data, detecting these rules is very critical and most valuable. However, mathematical formulation and evaluation of the new proposed measurement are not really impressive. Therefore, in this paper we applied our novel measurement called Critical Relative Support (CRS) to mine the critical least association rules from medical dataset. We also employed our scalable algorithm called Significant Least Pattern Growth algorithm (SLP-Growth) to mine the respective association rules. Experiment with two benchmarked medical datasets, Breast Cancer and Cardiac Single Proton Emission Computed Tomography (SPECT) Images proves that CRS can be used to detect to the pertinent rules and thus verify its scalability.

关键词： Critical least association rules medial data

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Reports of the AAAI 2009 spring symposia

Reports of the AAAI 2009 spring symposia

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作者： Bao, Jie Bojars, Uldis Choudhury, Tanzeem Ding, Li Greaves, Mark Kapoor, Ashish Louchart, Sandy Mehta, Manish Nebel, Bernhard Nirenburg, Sergei Oates, Tim Roberts, David L. Sanfilippo, Antonio Stojanovic, Nenad Stubbs, Kristen Thomaz, Andrea L. Tsui, Katherine Woelfl, Stefan Tetherless World Constellation Rensselaer Polytechnic Institute United States Social Software Unit of DERI Galway Ireland Computer Science Department Dartmouth College United States Knowledge Systems at Vulcan Inc United States Adaptive Systems and Interaction Group Microsoft Research Redmond United States School for Mathematics and Computer Sciences Heriot-Watt University United Kingdom School ot Interactive Computing Georgia Institute of Technology United States Department of Computer Science University of Freiburg Germany Computer Science and Electrical Engineering Department University of Maryland Baltimore County United States Pacific Northwest National Laboratory Richland WA United States University of Karlsruhe Germany IRobot Corporation United States University of Massachusetts Lowell United States

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, was pleased to present the 2009 Spring Symposium Series, held Monday through Wednesday, March 23-25, 2009, at Stanford University. The titles of the nine symposia were Agents That Learn from Human Teachers, Benchmarking of Qualitative Spatial and Temporal Reasoning Systems, Experimental Design for Real- World Systems, Human Behavior Modeling, Intelligent Event Processing, Intelligent Narrative Technologies II, Learning by Reading and Learning to Read, Social Semantic Web: Where Web 2.0 Meets Web 3.0, and Technosocial Predictive Analytics. The goal of the Agents That Learn from Human Teachers symposium was to investigate how we can enable software and robotics agents to leam from real-time interaction with an everyday human partner. The aim of the Benchmarking of Qualitative Spatial and Temporal Reasoning Systems symposium was to initiate the development of a problem repository in the field of qualitative spatial and temporal reasoning and identify a graded set of challenges for future midterm and long-term research. The Experimental Design symposium discussed the challenges of evaluating AI systems. The Human Behavior Modeling symposium explored reasoning methods for understanding various aspects of human behavior, especially in the context of designing intelligent systems that interact with humans. The Intelligent Event Processing symposium discussed the need for more Al-based approaches in event pro-cessing and defined a kind of research agenda for the field, coined as intelligent complex event processing (iCEP). The Intelligent Narrative Technologies IIAAAI symposium discussed innovations, progress, and novel techniques in the research domain. The Learning by Reading and Learning to Read symposium explored two aspects of making natural language texts semantically accessible to, and processable by, machines. The Social Semantic

关键词： Benchmarking

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The redefinition of supportability and its role as a systems engineering tool

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NAVAL ENGINEERS JOURNAL 1999年第3期111卷 269-277页

作者： Blackwell, P Hausner, E Paul Blackwell:graduated in May 1985 from Michigan Technological University with a bachelor of science degree in electrical engineering. In Octover 1986 Paul took a position in inertial navigation engineering at the Naval took a position in inertial navigation engineering at the Naval Aviation Depot. Five years later he move to the Mission Software group where he worked developing tactical navigation software. W. Erich Hausner:is currently the Project Engineer—Producibility and Supportability Research. Erich's primary focus has been producibility and supportability research and life cycle cost analyses for various aircraft and space programs. He integrates producibility and supportability domain experts within systems engineering/design leads research and development in advanced producibility and supportability concepts and works with producibility and supportability engineers to define design. requirements. He developed the Knowledge-Aided Producibility/Supportability Analysis Technique (KPAT/KSAT). The International Society of Logistics awarded him with the prestigious Field Award for Concurrent Engineering and the Best Technical Paper—Acquisition and Support. He is a member of the Office of Naval Research—Best Manufacturing Practices—Producibility Task Force. He majored in physics at the New York Institute of Technology.

Reliability Centered Maintenance (RCM) is described as the cornerstone of time NAVAIR, NAVSEA, and SPAWAR Affordable Readiness Initiatives. However, many technical issues, which result in a significant impact to the Fleet's Readiness and Operations and Support Costs, are irrelevant to RCM analyses and are therefore overlooked. In addition, reliability and maintainability, parameters more suitable as a "figure of merit" in a laboratory environment, are used with fervor to analyze field data. This further compounds the ambiguity and diminishes the effectiveness of the RCM recommendations on readiness and cost In other words, using RCM "we are potentially stepping over dollars to save pennies." Supportability is traditionally thought of as a logistics metric related to the operational availability of a system. This paper redefines Supportability, describes the comprehensive knowledge-Aided Supportability Analysis Technique (KSAT), and discusses how it can enhance the traditional metrics.

关键词： Decision support systems

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Collaborative tools and processes to support software engineering shift work

British Telecom technology journal

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British Telecom technology journal 1997年第3期15卷 189-198页

作者： Gorton, I. Hawryszkiewycz, I. Ragoonaden, K. Sheffield Hallam University United Kingdom CSIRO Australia Software Engineering Research Group CSIRO Transarc Corporation Sydney NSW Australia Department of Computing Sciences University of Technology Sydney NSW Australia Computer Supported Cooperative Work Ger. Natl. Computer Research Center Res. Inst. of Appl. Knowledge Proc. University of Ulm Germany University of Technology Sydney NSW Australia University of Canberra Australia University of Maryland College Park MD United States Telecom Australia Australia MIT United States University of Adelaide Australia UMIST United Kingdom City University London United Kingdom BT Laboratories United Kingdom Software Technology Division BT Asia Pacific Regional MIS Unit Sydney NSW Australia GWSE

This paper describes the construction of and early experiences with a software engineering support environment for projects using globally distributed teams. The goals of the project are twofold. Firstly, it aims to construct a pragmatic solution to the problems experienced by widely geographically dispersed groups which collaborate on software development projects. Secondly, it aims to experiment with processes which facilitate software shift work through exploitation of time differences between collaborating groups. The construction of the support environment, known as GWSE (Global Working in software engineering) system, is presented, including its architecture and integration with existing workflow, document and project management tools. The use of the GWSE system in a trial development project is then described, including an initial quantitative analysis of the collaboration overheads experienced.

关键词： Computer aided software engineering

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Application of a machine learning model for early prediction of in-hospital cardiac arrests: Retrospective observational cohort study

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Medicina intensiva 2024年第2期49卷 88-95页

作者： L Socias Crespí L Gutiérrez Madroñal M Fiorella Sarubbo M Borges-Sa A Serrano García D López Ramos C Pruenza Garcia-Hinojosa E Martin Garijo Intensive Care Department Son Llàtzer University Hospital Crta. Manacor Km 4 07198 Palma Spain Department of Medicine Faculty of Medicine University of the Balearic Islands Crta. Valldemossa Km. 7.5 Palma Spain Group of Critic Patient Health Research Institute of the Balearic Islands (IdISBa) 07198 Palma Spain. Electronic address: lsocias@hsll.es. Research Unit Son Llàtzer University Hospital Crta. Manacor Km 4 07198 Palma Spain. Research Unit Son Llàtzer University Hospital Crta. Manacor Km 4 07198 Palma Spain Department of Biology Faculty of Science University of the Balearic Islands Crta. Valldemossa Km. 7.5 Palma Spain. Department of Medicine Faculty of Medicine University of the Balearic Islands Crta. Valldemossa Km. 7.5 Palma Spain. Knowledge Engineering Institute Universidad Autónoma de Madrid Madrid Spain.

OBJECTIVE:To describe the results of the application of a Machine Learning (ML) model to predict in-hospital cardiac arrests (ICA) 24 hours in advance in the hospital wards. DESIGN:Retrospective observational cohort study. SETTING:Hospital Wards. PATIENTS:Data were extracted from the hospital's Electronic Health Record (EHR). The resulting database contained a total of 750 records corresponding to 620 different patients (370 patients with ICA and 250 control), between may 2009 and december 2021. INTERVENTIONS:No. MAIN VARIABLES OF INTEREST:As predictors of ICA, a set of 28 variables including personal history, vital signs and laboratory data was employed. MODELS:For the early prediction of ICA, predictive models based on the following ML algorithms and using the mentioned variables, were developed and compared: K Nearest Neighbours, Support Vector Machine, Multilayer Perceptron, Random Forest, Gradient Boosting and Custom Ensemble of Gradient Boosting estimators (CEGB). EXPERIMENTS:Model training and evaluation was carried out using cross validation. Among metrics of performance, accuracy, specificity, sensitivity and AUC were estimated. RESULTS:The best performance was provided by the CEGB model, which obtained an AUC = 0.90, a specificity = 0.84 and a sensitivity = 0.81. The main variables with influence to predict ICA were level of consciousness, haemoglobin, glucose, urea, blood pressure, heart rate, creatinine, age and hypertension, among others. CONCLUSIONS:The use of ML models could be of great support in the early detection of ICA, as the case of the CEGB model endorsed, which enabled good predictions of ICA.

关键词： Artificial intelligence Big Data Critical care Diagnosis Heart arrest In-hospital cardiac arrest intensive Care Unit Machine learning Prevention Prognosis

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