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Measuring productivity of software projects: A data envelopment analysis approach

DECISION SCIENCES 1996年第1期27卷 57-80页

作者： Mahmood, MA Pettingell, KJ Shaskevich, AI Information and Decision Sciences University of Texas–El Paso El Paso TX 79968 E-mail: mmahmood@mail.utep.edu Information and Decision Sciences University of Texas–El Paso El Paso TX 79968 950 Camino Del Rex Las Cruces NM 88001 [?]1Mo Adam Mahmood is a professor of information systems and Ellis and Susan Mayfield Endowed Professor in Business Administration at the University of Texas at El Paso. He received his Ph.D. in management information system from Texas Tech University. His research interests include software engineering information technology in support of superior organizational shategic and ecxlIKlmic perfonnamethe strategic manager's perspectives on information technology and infamation technology for national and inkmatid competitiveness. Dr. Mahtnd has published in Decision SciencesMIS Quarterly Joumal of Management Information SystemsEuropean Joud of Information Systems INFOR-Canadian' Journal of Operation Research and Information Processing and Information and Management among others. He has also edited and published a book in the information technology investment and performance area. He is cmntly serving as editor of the Journal of End-User Computing. He is also serving as guest editor associate editor member of the editorial review board or referee for a number of information systems journals. In addition he has presented research papers served as both a reviewer and discussant chaired sessions and tracks and participated in program committees of several regional national and international conferences.

Current economic conditions are forcing information system departments to focus simultaneously on decreasing costs while increasing software productivity. Improving software productivity is becoming critical because software costs of large in-house software companies have been increasing rapidly. For many organizations, however, measuring software productivity has been a difficult task. Using Data Envelopment Analysis (DEA), this research study investigates the productivity of 78 commercial system projects. The results of this study have practical implications for software project managers undertaking software development. The results showed that the DEA technology can be successfully used to identify efficient and inefficient software projects. Furthermore, within the inefficient group, DEA can also identify factors that affect software productivity in a positive or negative manner, allowing managers to take corrective actions. Based on the findings of this study, the manuscript also provides some practical guidelines for managers to follow in software development.

关键词： Data Envelopment Analysis Information systems implementation systems development methodologies

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Bitcoin’s future carbon footprint

arXiv

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arXiv 2020年

作者： Qin, Shize Klaaßen, Lena Gallersdörfer, Ulrich Stoll, Christian Zhang, Da Institute of Energy Environment and Economy Tsinghua University Beijing100084 China TUM School of Management Technical University of Munich Munich Germany TUM Software Engineering for Business Information Systems Department of Informatics Technical University of Munich Munich Germany MIT Center for Energy and Environmental Policy Research Massachusetts Institute of Technology CambridgeMA United States TUM Center for Energy Markets TUM School of Management Technical University of Munich Munich Germany MIT Joint Program on the Science and Policy of Global Change CambridgeMA02139 United States

The carbon footprint of Bitcoin has drawn wide attention, but Bitcoin’s long-term impact on the climate remains uncertain. Here we present a framework to overcome uncertainties in previous estimates and project Bitcoin’s electricity consumption and carbon footprint in the long term. If we assume Bitcoin’s market capitalization grows in line with the one of gold, we find that the annual electricity consumption of Bitcoin may increase from 50 to 400 TWh between 2020 and 2100. The future carbon footprint of Bitcoin strongly depends on the decarbonization pathway of the electricity sector. If the electricity sector achieves carbon neutrality by 2050, Bitcoin’s carbon footprint has peaked already. However, in the business-as-usual scenario, emissions sum up to 2 gigatons until 2100, an amount comparable to 6% of global emissions in 2018. Therefore, we also discuss policy instruments to reduce Bitcoin’s future carbon footprint. Copyright © 2020, The Authors. All rights reserved.

关键词： Carbon footprint

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Annual business and news:: Beginning the 31st year of the Journal of Guidance, Control, and Dynamics

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2008年第1期31卷 1-1页

作者： Schmidt, George T. Aeronautics and Astronautics Massachusetts Institute of Technology (MIT) AIAA Institute of Electrical and Electronics Engineers Russian Federation Academy of Navigation and Motion Control Department of Mechanical and Aerospace Engineering and Engineering Mechanics University of Missouri-Rolla(UMR) Lockheed Electronics Company Center for Space Research University of Texas Austin United States Wright Laboratory Eglin Air Force Base UMR AIAA Guidance Navigation and Control Technical Committee American Automatic Control Council Lockheed Martin Aeronautics Company Palmdale CA United States C4ISR and Unmanned Air Vehicle (UAV) Programs for Air Vehicle Sciences and Systems Accreditation Board Engineering and Technology Inc./Aeronautical National Technical Committee on Guidance Navigation and Control Department of Mechanical and Aerospace Engineering University at Buffalo State University of New York (SUNY) AIAA Technical Committee on GN and C Air Vehicles Directorate Air Force Research Laboratory (AFRL) Wright-Patterson Air Force Base Space Access and Hypersonic Vehicle Guidance and Control Group Control Science Center of Excellence AFRL AIAA Technical Committee on Guidance Navigation and Control Department of Mechanical and Aeronautical Engineering University of California (UC) Davis United States Boeing Company Modernized Flight Control System for the Apache Longbow AIAA Institute of Electrical and Electronics Engineers AHS Jet Propulsion Laboratory California Institute of Technology Boeing Company Flight Sciences and Advanced Design Group Guidance Navigation and Control (GN and C) Systems Engineer Distributed Space Systems NASA Goddard Space Flight Center (GSFC) AIAA GN and C Technical Committee Department of Aerospace Engineering and Engineering Mechanics University of Texas Austin United States Institute of Navigation American Astronautical Society AIAA Guidance Navigation (GN and C) and Control Technical Committee Department of Aerospace Engineering Iowa State University Iowa

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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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The Joint Tactical Combat Training System system model

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NAVAL ENGINEERS JOURNAL 1997年第3期109卷 293-298页

作者： McCarthy, PJ Munkacsy, M Peter J. McCarthy:is an electrnics engineer at the Naval Air Wrfare Center Training Systems Division in Orlando Florida. He received a B.S. degree in electrical engineering from the University of Illinois at Urbana-Champaign in 1984 and an M.S.E. degree in electical engineering from the Unversity of Central Florida in 1991. He joined the Naval Air Warfare Center in 1985 and worked for seven years on submarine combat system trainingbefore moving to the Modeling and Simulation Development Branch. He is currently a member of the NavAir JTCTS team. Mark J. Munkacsy:is a principal engineer at Raytheon Electronic Systems in Portsmouth RI. He received a B.S. degreein After nuclear power and submarine training he served as weapons officer aboard the USS Boston fast-attack submarine. In 1984 he joined Raytheon and served as lead engineer for the development os submarine-launched Tomahawk fire-control software. He is currently the lead modelingand simulation engineer for the JTCTS program.

The Joint Tactical Combat Training System (JTCTS) is a joint Navy/Air Force program to provide enhanced tactical combat training from single-platform warfighting through integration of multi-platform coordinated combat training (surface, subsurface, and air). Key requirements of JTCTS include the use of the Global Positioning System to generate platform position information, simulated platforms and weapons, and a real-time radio datalink to transmit training data within 400 nm of a JTCTS core-capable site, using a distributed simulation architecture derived from distributed interactive simulations. Many design tradeoffs need to be made to implement this system. To enable the meaningful test and tradeoff of various design options, a software model of the JTCTS system was constructed. This discrete-event simulation was implemented entirely in software running on commercial workstations. The model allows the designers to test various software and hardware design implementations and measure their influence on the ''goodness'' of the exercise data. Based on platform attitude and relative position, datalink connectivity can be assessed and various message-passing algorithms tested. The effects of message latency and communications dropouts on dead-reckoning accuracy can be directly measured. Effects of aircraft antenna shading, atmospheric effects on radio frequency propagation, and others can be turned on or off depending on the needs of the particular test, and to support validation of the model. The engineering model was created during the project concept definition;it is being used today in a number of design studies. One, a datalink transmitter power tradeoff, is giving insight into the relationship between the accuracy of after-action reports and the heat dissipation of the datalink components. These simulated exercises are providing both the end-user and the design team with insight into subsystem and operational interactions usually not seen until system integrati

关键词： Naval warfare

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Self-Awareness for Autonomous systems

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PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems Computational modeling

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INNOVATIONS IN COMPUTER-AIDED-DESIGN OF MARINE TURBINES USING INTERACTIVE GRAPHICS

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NAVAL ENGINEERS JOURNAL 1980年第2期92卷 207-217页

作者： GINGRICH, JK WINTER, RL Mr. John K. Gingrich joined the General Electric Company after his graduation from Lafayette College in 1948. His early assignments were with the General Engineering Laboratory and the Knolls Atomic Power Laboratory in Schenectady. N. Y. He joined the Marine Turbine and Gear Department in 1968 as Manager Engineering Administration. and assumed his present assignment as Manager Engineering Resource Planning & Administration in 1976. Mr. Gingrich was instrumental in procuring the Interactive Graphics System for the Medium Steam Department. having headed up the Study Team and is now responsible for the Interactive Graphics Systems management including new procurements. He is a member of the American Institute of Design Drafting and is currently the Chairman of the Computer-Aided Drafting Committee in that organization. Mr. Reinhold L. Winter is a graduate of the General Electric Apprentice Program and Salem State College from which he received his B.S. degree in Business Administration. He has nineteen years experience with the General Electric Company including eight years in Business Systems and Programming two years in Computer Operations Management and six years in his present position as Manager Engineering Business Systems. He was a member of the original Study Team that investigated and selected the present Applicon Interactive Graphics (IAG) equipment and currently is responsible for the management of software and hardware support for the ZAG Facility.

This paper discusses the Interactive Graphics System used by the General Electric Company, Medium Steam Turbine Department (engineering & Manufacturing) for designing, drafting, and manufacturing applications. A brief overview of the hardware malting up the system is described, followed by a more detailed description of the actual applications. Two-dimensional applications described include a Heat Balance Analysis, Flow Diagrams, and Electrical Schematics. A more fruitful area for increased productivity gains is described in the three-dimensional or mechanical applications including turbine design & layout and bucket design. coordination of the design with manufacturing for numerical control tape generation is described through CAM and Plate Frame Cutting applications. Finally, a short review of the engineering design work using Interactive Graphics is discussed. Productivity gains of 2.6 to 1 are being realized, and the overall savings to the Medium Steam Department are outlined.

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SHIPBOARD DAMAGED STABILITY ASSESSMENT - THE FLOODING CASUALTY CONTROL software

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NAVAL ENGINEERS JOURNAL 1993年第3期105卷 152-166页

作者： ZAHN, PB ROSBOROUGH, J CARLSTROM, R Peter B. Zahn:is a section chief in the Naval Architecture Department at Advanced Marine Enterprises. He is responsible for software development and special trials support. He has led the Flooding Casualty Control Software (FCCS) development effort since joining AME in 1989. He is also responsible for the material handling strikedown and stowage (MHS&S) software development program as well as special trials support for the ACVLAP and T-AGOS 19 programs. Prior to joining AME Mr. Zahn spent nine years with various companies of the ARCTEC Group. His experience includes field trials in venues from the Caribbean to the Bering Sea as well as model tests and engineering design and development efforts. Mr. Zahn received his B.S. in naval architecture and marine engineering from Webb Institute in 1980 and has published various papers on pollution prevention offshore systems and icebreaker design and performance. He is a member of ASNE and SNAME. John Rosborough:has been a naval architect for the Naval Sea Systems Command (NavSea) for the past 15 years. He is currently assigned to the Hydrodynamics Division with responsibility for aircraft carrier stability evaluations and as a task leader for computer-aided ship design development. In the Stability Division he was previously responsible for stability analyses on various amphibious ships SWATHs and foreign ships. He manages the upgrade and augmentation of SHCP at NavSea and is the Navy's technical point of contact for evaluating shipboard stability software and transitioning technology to the fleet. Mr. Rosborough received his B.S. in naval architecture and marine engineering from the University of Michigan in 1977. He is a member of USNI and the Association of Scientists and Engineers at NavSea. Richard Carlstrom:is a naval architect with Advanced Marine Enterprises. He has been responsible for software development in support of a variety of major programs including FCCS and SHCP and is a specialist in stability evaluations for complex ships such as CVs CVNs

The Flooding Casualty Control software (FCCS) was developed under the auspices of the Naval Sea systems Command (NavSea) and is currently being deployed on a variety of ships in the neets of both the U.S. Navy and the U.S. Coast Guard. The primary objective of FCCS is to enable damage control personnel to identify critical stability conditions, especially when related to the loss of reserve buoyancy due to battle damage and the destabilizing effects of large quantities of firefighting water, in a timely manner. FCCS was initially deploved in 1990. It utilizes the standard algorithms of the Ship Hull Characteristics program (SHCP). The user interface was designed to allow quick familiarity for shipboard users, primarily the damage control assistant (DCA) and his staff. Intact stability evaluations include the effects of topside icing, high winds, personnel crowding, heavy lifts over the side, high speed turns, and towing. FCCS also supports ballasting analysis for amphibious ships as well as providing bottom reaction and beached stability data for grounding incidents. Bv providing a tool for the ''fuel king'' and DCA to generate the required daily updates on the current ship load and liquids status, FCCS is assured of an accurate baseline in the event of damage. The design allows the evaluation of the ultimate ship stability status for a damage event using simple compartmentation and flooding status inputs. Evaluation of the adequacy of resulting stabilitv, as well as identification of such critical stability parameters as off center loading, margin line immersion, and negative GM, are accomplished by the program. Guidance is provided for the user to initiate appropriate flooding related damage control activities. Initially fitted on USS Oliver Hazard Perry Class frigates, FCCS databases have been for the USCG Hamilton class high endurance cutters, USS Arleigh Burke class Aegis destroyers, and a variety of other U.S. Navy and U.S. Coast Guard ship classes. The progra

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Accelerating Real-Time Imaging for Radiotherapy: Leveraging Multi-GPU Training with PyTorch

Accelerating Real-Time Imaging for Radiotherapy: Leveraging ...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Ruth Obe Brandt Kaufmann Kaelen Baird Sam Kadel Yasmin Soltani Mostafa Cham Matthias K. Gobbert Carlos A. Barajas Zhuoran Jiang Vijay R. Sharma Lei Ren Stephen W. Peterson Jerimy C. PoIf Dept. of Computer Science and of Software Engineering U. of Houston-Clear Lake USA Dept. of Mathematics and Statistics U. of San Francisco USA Dept. of Computer Science and of Mathematics Skidmore College USA Dept. of Computer Science and of Psychology Mount Holyoke College USA Dept. of Biomedical Engineering U. of Houston USA Dept. of Information Systems U. of Maryland Baltimore County Dept. of Mathematics and Statistics U. of Maryland Baltimore County Medical Physics Graduate Program Duke University USA Dept. of Radiation Oncology U. of Maryland School of Medicine USA Department of Radiation Oncology U. of Maryland School of Medicine USA Dept. of Physics U. of Cape Town South Africa H3D Inc. USA

Proton beam therapy is an advanced form of cancer radiotherapy that uses high-energy proton beams to deliver precise and targeted radiation to tumors. This helps to mit-igate unnecessary radiation exposure in healthy tissues. Real-time imaging of prompt gamma rays with Compton cameras has been suggested to improve therapy efficacy. However, the camera's non-zero time resolution leads to incorrect interaction classifications and noisy images that are insufficient for accurately assessing proton delivery in patients. To address the challenges posed by the Compton camera's image quality, machine learning techniques are employed to classify and refine the generated data. These machine-learning techniques include recurrent and feedforward neural networks. A PyTorch model was designed to improve the data captured by the Compton camera. This decision was driven by PyTorch's flexibility, powerful capabilities in handling sequential data, and enhanced G PU usage. This accelerates the model's computations on large-scale radiotherapy data. Through hyperparameter tuning, the validation accuracy of our PyTorch model has been improved from an initial 7 % to over 60 %. Moreover, the PyTorch Distributed Data Parallelism strategy was used to train the RNN models on multiple G PU s, which significantly reduced the training time with a minor impact on model accuracy.

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PARALLEL AND DISTRIBUTED TLM COMPUTATION WITH SIGNAL-PROCESSING FOR ELECTROMAGNETIC-FIELD MODELING

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INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS 1995年第3-4期8卷 169-185页

作者： SO, PPM ESWARAPPA, C HOEFER, WJR NSERC/MPR Teltech Research Chair in RF Engineering Department of Electrical and Computer Engineering University of Victoria Victoria British Columbia V8W 3P6 Canada Poman So received his B.Sc. degree in computer science and physics from the University of Toronto Toronto Onatario Canada in 1985. He obtained his B.A. Sc. and M.A.Sc. degrees in electrical engineering (summa cum laude) from the University of Ottawa Ottawa Ontario Canada in 1987 and 1989 respectively. Mr So was a research engineer in the University of Ottawa from January 1989 to October 1991 his research interests included CAD techniques of microwave circuits and numerical methods for electromagnetic wave modelling. He specialized in the development of electromagnetic engineering CAD software and successfully implemented a number of electromagnetic wave simulators based on the two-dimensional and three-dimensional transmission-line matrix methods. From August 1990 to February 1991 he accompanied Professor W. J. R. Hoefer to Rome Italy and Sophia Antiopolas France. During that time he implemented a parallel version of the 3D-TLM simulator for the CM-2 Connection Machine using C-Star and X Windows Library. He is a research engineer and a Ph.D. student at the University of Victoria Victoria British Columbia Canada. He ported the 2D- and 3D-TLM simulators to DECmpp 1200 massively parallel computer using MPL C and C++. He also combined OSA90/hope a commercially available microwave CAD program with a 2D-TLM simulation module for geometry optimization using the Datapipe technique of OSA90/hope. Recently he has developed a distributed client-server computing technique for the TLM method this technique could accelerate the TLM simulation by more than an order of magnitude. Channabasappa Eswarappa received the M.Tech. degree in electrical engineering from the Indian Institute of Technology Kanpur India in 1983 and Ph. D. degree from the University of Ottawa Canada in 1990. He worked as an Assistant Executive Engineer and later as

This paper describes the implementation of transmission-line matrix (TLM) method algorithms on a massively parallel computer (DECmpp 12000), the technique of distributed computing in the UNIX environment, and the combination of TLM analysis with Prony's method as well as with autoregressive moving average (ARMA) digital signal processing for electromagnetic field modelling. By combining these advanced computation techniques, typical electromagnetic field modelling of microwave structures by TLM analysis can be accelerated by a few orders of magnitude.

关键词： Mathematical models

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