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ROLE OF SIMULATION IN RAPID PROTOTYPING FOR CONCEPT DEVELOPMENT

NAVAL ENGINEERS JOURNAL 1991年第3期103卷 204-211页

作者： KING, JF BARTON, DE J. Fred King:is the manager of the Advanced Technology Department for Unisys in Reston Virginia. He earned his Ph.D. in mathematics from the University of Houston in 1977. He has been principal investigator of research projects in knowledge engineering pattern recognition and heuristic problem-solving. Efforts include the development of a multi-temporal multispectral classifier for identifying graincrops using LANDSAT satellite imagery data for NASA. Also as a member of the research team for a NCI study with Baylor College of Medicine and NASA he helped develop techniques for detection of carcinoma using multispectral microphotometer scans of lung tissue. He established and became technical director of the AI Laboratory for Ford Aerospace where he developed expert scheduling modeling and knowledge acquisition systems for NASA. Since joining Unisys in 1985 he has led the development of object-oriented programming environments blackboard architectures data fusion techniques using neural networks and intelligent data base systems. Douglas E. Barton:is manager of Logistics Information Systems for Unisys in Reston Virginia. He earned his B.A. degree in computer science from the College of William and Mary in 1978 and did postgraduate work in London as a Drapers Company scholar. Since joining Unisys in 1981 his work has concentrated on program management and software engineering of large scale data base management systems and design and implementation of knowledge-based systems in planning and logistics. As chairman of the Logistics Data Subcommittee of the National Security Industrial Association (NSIA) he led an industry initiative which examined concepts in knowledge-based systems in military logistics. His responsibilities also include evaluation development and tailoring of software engineering standards and procedures for data base and knowledge-based systems. He is currently program manager of the Navigation Information Management System which provides support to the Fleet Ballistic Missile Progr

A valuable technique during concept development is rapid prototyping of software for key design components. This approach is particularly useful when the optimum design approach is not readily apparent or several known alternatives need to be rapidly evaluated. A problem inherent in rapid prototyping is the lack of a "target system" with which to interface. Some alternatives are to develop test driver libraries, integrate the prototype with an existing working simulator, or build one for the specific problem. This paper presents a unique approach to concept development using rapid prototyping for concept development and scenario-based simulation for concept verification. The rapid prototyping environment, derived from artificial intelligence technology, is based on a blackboard architecture. The rapid prototype simulation capability is provided through an object-oriented modeling environment. It is shown how both simulation and blackboard technologies are used collectively to rapidly gain insight into a tenacious problem. A specific example will be discussed where this approach was used to evolve the logic of a mission controller for an autonomous underwater vehicle.

关键词： Military engineering

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Application of factor analysis method to support the users acceptance model of ERP systems implementation

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Journal of Physics: Conference Series 2021年第1期1836卷

作者： W Sardjono J Sudirwan W Priatna G R Putra Information Systems Management Department BINUS Graduate Program -Master of Information Systems Management Bina Nusantara University Jakarta Indonesia – 11480 School of Information Systems Department BINUS Undergraduate Program Bina Nusantara University Jakarta Indonesia 11480 Informatics Engineering Engineering Bhayangkara University Jakarta Raya Indonesia Computer Science Study Program Faculty of Mathematics & Natural Sciences Pakuan University Bogor Indonesia

An e-Commerce company has been using an Enterprise Resource Planning (ERP) system for several years, but is still constrained in its implementation, this is reflected in the number of issue/change request tickets submitted by users who have not been able to reach ideal conditions. To overcome this problem, we need an appropriate reference model, the ERP system user acceptance model in companies. The study conducted factors that influence the level of acceptance of SAP ERP users in the XYZ group to then determine a model that is able to explain practically the level of ERP system user acceptance, which in turn can produce concrete proposals to increase ERP system user acceptance. Research is quantitative descriptive using factor analysis and regression analysis methods. The research method uses a questionnaire with a total of 107 valid respondents coming from 8 company names under the XYZ group in 6 Southeast Asian countries. The conclusion of the study is that there are 24 indicators and 4 factors that influence user acceptance of the SAP ERP system. These four factors are the low contribution of the ERP system, the quality of ERP systems and data, the development of ERP systems, and also the low quality of ERP system supporters. It is hoped that by optimizing the value of the 4 factors, the XYZ group can increase user acceptance of the SAP ERP system so that the system can provide benefits expected by the company to be competitive advantage.

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Fog computing in medical internet-of-things: Architecture, implementation, and applications

arXiv

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arXiv 2017年

作者： Dubey, Harishchandra Monteiro, Admir Constant, Nicholas Abtahi, Mohammadreza Borthakur, Debanjan Mahler, Leslie Sun, Yan Yang, Qing Akbar, Umer Mankodiya, Kunal Department of Electrical Computer and Biomedical Engineering University of Rhode Island RI-02881 United States Department of Communicative Disorders University of Rhode Island RI-02881 United States Wearable Biosensing Lab University of Rhode Island RI-02881 United States Movement Disorders Program Rhode Island Hospital RI-02903 United States Center for Robust Speech Systems University of Texas DallasTX75080 United States

In the era when the market segment of Internet of Things (IoT) tops the chart in various business reports, it is apparently envisioned that the field of medicine expects to gain a large benefit from the explosion of wearables and internet-connected sensors that surround us to acquire and communicate unprecedented data on symptoms, medication, food intake, and daily-life activities impacting one's health and wellness. However, IoT-driven healthcare would have to overcome many barriers, such as: 1) There is an increasing demand for data storage on cloud servers where the analysis of the medical big data becomes increasingly complex;2) The data, when communicated, are vulnerable to security and privacy issues;3) The communication of the continuously collected data is not only costly but also energy hungry;4) Operating and maintaining the sensors directly from the cloud servers are non-trial tasks. This book chapter defined Fog Computing in the context of medical IoT. Conceptually, Fog Computing is a serviceoriented intermediate layer in IoT, providing the interfaces between the sensors and cloud servers for facilitating connectivity, data transfer, and queryable local database. The centerpiece of Fog computing is a low-power, intelligent, wireless, embedded computing node that carries out signal conditioning and data analytics on raw data collected from wearables or other medical sensors and offers efficient means to serve telehealth interventions. We implemented and tested an fog computing system using the Intel Edison and Raspberry Pi that allows acquisition, computing, storage and communication of the various medical data such as pathological speech data of individuals with speech disorders, Phonocardiogram (PCG) signal for heart rate estimation, and Electrocardiogram (ECG)-based Q, R, S detection. The book chapter ends with experiments and results showing how fog computing could lessen the obstacles of existing cloud-driven medical IoT solutions and enhance the ove

关键词： Internet of things

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Towards Robust and Scalable Dispatch Modeling of Long-Duration Energy Storage

arXiv

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arXiv 2024年

作者： Guerra, Omar J. Dalvi, Sourabh Thatte, Amogh A. Cowiestoll, Brady Jorgenson, Jennie Hodge, Bri-Mathias National Renewable Energy Laboratory 15013 Denver West Parkway GoldenCO80401 United States Colorado School of Mines Advanced Energy Systems Graduate Program 1500 Illinois Street GoldenCO80401 United States Renewable and Sustainable Energy Institute University of Colorado BoulderCO80309 United States Department of Electrical Computer & Energy Engineering University of Colorado BoulderCO80309 United States

Energy storage technologies, including short-duration, long-duration, and seasonal storage, are seen as technologies that can facilitate the integration of larger shares of variable renewable energy, such as wind and solar photovoltaics, in power systems. However, despite recent advances in the techno-economic modeling of energy storage (particularly for short-duration applications), the operation and economics of long-duration energy storage are still incomplete in power systems modeling platforms. For instance, existing modeling approaches for long-duration storage are often based either on an oversimplified representation of power system operations or limited representation of storage technologies, e.g., evaluation of only a single application. This manuscript presents an overview of the challenges of modeling long-duration energy storage technologies, as well as a discussion regarding the capabilities and limitations of existing approaches. We used two test power systems with high shares of both solar photovoltaics- and wind (70% - 90% annual variable renewable energy shares) to assess long-duration energy storage dispatch approaches. Our results estimate that better dispatch modeling of long-duration energy storage could increase the associated operational value by 4% - 14% and increase the standard capacity credit by 14% - 34%. Thus, a better long-duration energy storage dispatch could represent significant cost saving opportunities for electric utilities and system operators. In addition, existing long-duration dispatch modeling approaches were tested in terms of both improved system value (e.g., based on production cost and standard capacity credit) and scalability (e.g., based on central processing unit time and peak memory usage). Both copper plate and nodal representations of the power system were considered. Although the end volume target dispatch approach, i.e., based on mid-term scheduling, showed promising performance in terms of both improved system

关键词： Scalability

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Exploring the effect of image enhancement techniques on COVID‐19 detection using chest X‐rays images

arXiv

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arXiv 2020年

作者： Rahman, Tawsifur Khandakar, Amith Qiblawey, Yazan Tahir, Anas Kiranyaz, Serkan Kashem, Saad Bin Abul Islam, Mohammad Tariqul Maadeed, Somaya Al Zughaier, Susu M. Khan, Muhammad Salman Chowdhury, Muhammad E.H. Department of Biomedical Physics & Technology University of Dhaka Dhaka 1000 Bangladesh Department of Electrical Engineering Qatar University Doha2713 Qatar Faculty of Robotics and Advanced Computing Qatar Armed Forces‐Academic Bridge Program Qatar Foundation Doha24404 Qatar Dept. of Electrical Electronics and Systems Engineering Universiti Kebangsaan Malaysia BangiSelangor43600 Malaysia Department of Computer Science and Engineering Qatar University Doha2713 Qatar Department of Basic Medical Sciences College of Medicine Biomedical and Pharmaceutical Research Unit QU Health Qatar University Doha2713 Qatar University of Engineering and Technology Peshawar Pakistan

The use of computer-aided diagnosis in the reliable and fast detection of corona virus disease (COVID-19) has become a necessity to prevent the spread of the virus during the pandemic to ease the burden on the medical infrastructure. Chest X-ray (CXR) imaging has several advantages over other imaging techniques as it is cheap, easily accessible, fast and portable. CXR images are sometimes of poor quality and so image enhancement techniques can help the machine learning models to extract valuable discriminating features from the image. Numerous works have been reported on COVID-19 detection from smaller set of original X-ray images. However, the effect of image enhancement in COVID-19 detection was not reported in the literature. This paper explores the effect of various popular image enhancement techniques and states the © 2020, CC BY.

关键词： Image enhancement

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Ecology, Spatial Structure, and Selection Pressure Induce Strong Signatures in Phylogenetic Structure

arXiv

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arXiv 2024年

作者： Moreno, Matthew Andres Rodriguez-Papa, Santiago Dolson, Emily Department of Ecology and Evolutionary Biology University of Michigan Ann Arbor United States Center for the Study of Complex Systems University of Michigan Ann Arbor United States Michigan Institute for Data Science University of Michigan Ann Arbor United States Department of Computer Science and Engineering Michigan State University East Lansing United States Program in Ecology Evolution and Behavior Michigan State University East Lansing United States

Evolutionary dynamics are shaped by a variety of fundamental, generic drivers, including spatial structure, ecology, and selection pressure. These drivers impact the trajectory of evolution, and have been hypothesized to influence phylogenetic structure. For instance, they can help explain natural history, steer behavior of contemporary evolving populations, and influence efficacy of application-oriented evolutionary optimization. Likewise, in inquiry-oriented artificial life systems, these drivers constitute key building blocks for open-ended evolution. Here, we set out to assess (1) if spatial structure, ecology, and selection pressure leave detectable signatures in phylogenetic structure, (2) the extent, in particular, to which ecology can be detected and discerned in the presence of spatial structure, and (3) the extent to which these phylogenetic signatures generalize across evolutionary systems. To this end, we analyze phylogenies generated by manipulating spatial structure, ecology, and selection pressure within three computational models of varied scope and sophistication. We find that selection pressure, spatial structure, and ecology have characteristic effects on phylogenetic metrics, although these effects are complex and not always intuitive. Signatures have some consistency across systems when using equivalent taxonomic unit definitions (e.g., individual, genotype, species). Further, we find that sufficiently strong ecology can be detected in the presence of spatial structure. We also find that, while low-resolution phylogenetic reconstructions can bias some phylogenetic metrics, high-resolution reconstructions recapitulate them faithfully. Although our results suggest potential for evolutionary inference of spatial structure, ecology, and selection pressure through phylogenetic analysis, further methods development is needed to distinguish these drivers' phylometric signatures from each other and to appropriately normalize phylogenetic metrics. With s

关键词： Abiotic

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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 ...

引用

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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A Parametric QoE Video Quality Estimator for Wireless Networks

A Parametric QoE Video Quality Estimator for Wireless Networ...

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Institute of Electrical and Electronics Engineers Globecom Workshops

作者： E. Cerqueira Augusto Neto M. Curado A. Riker R. Immich H. Barros E. Aguiar A. Abelem Federal University of Para (UFPA) Federal University of Ceara Department of Informatics Engineering (DETI) Fortaleza-CE Institute of Telecommunications Aveiro University of Coimbra Department of Informatics Engineering (DEI) Federal University of Rio Grande do Norte Post Graduation Program in Computer Systems (PPgSC)

ISBN: (纸本)9781467349420

The development of real-time quality estimator schemes for emerging Internet videos with different content types remains a significant challenge and is crucial for the success of wireless multimedia systems. However, currently in-service assessment schemes fail in capturing subjective aspects of multimedia content related to the user perception. Therefore, this paper proposes an on-the-fly parametric video quality estimator approach (called MultiQoE) for real-time video streaming applications. Experiments in a Wireless Mesh Network (WMN) scenario were carried out to show the accuracy, benefit, and impact of MultiQoE compared to widely used Quality of Experience (QoE) subjective, objective and parametric methods.

关键词： Quality of Experience Video Streaming Wireless Mesh Networks Service Assessment

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Estimation of the main air pollutants from different biomasses under combustion atmospheres by artificial neural networks

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Chemosphere 2024年 352卷 141484页

作者： Monteiro, Thalyssa Oliveira Alves, Pedro Augusto Araújo da Silva de Almeida Nava Barradas Filho, Alex Oliveira Villa-Vélez, Harvey Alexander Cruz, Glauber Postgraduate Program in Mechanical Engineering (PPGMEC) Department of Mechanics and Materials Federal Institute of Education Science and Technology of Maranhão (IFMA) Maranhão São Luís Brazil Postgraduate Program in Computer Science and Computational Mathematics (PPG-CCMC) Department of Computer Science University of São Paulo (USP) São Carlos São Paulo Brazil Data Analysis and Artificial Intelligence Laboratory (DARTi) Department of Computational Engineering Federal University of Maranhão (UFMA) Maranhão São Luís Brazil Department of Chemical Engineering Federal University of Maranhão (UFMA) Maranhão São Luís Brazil Processes and Thermal Systems Laboratory (LPSisTer) Department of Mechanical Engineering Federal University of Maranhão (UFMA) Maranhão São Luís Brazil

The production of biofuels to be used as bioenergy under combustion processes generates some gaseous emissions (CO, CO2, NOx, SOx, and other pollutants), affecting living organisms and requiring careful assessments. H... 详细信息

The production of biofuels to be used as bioenergy under combustion processes generates some gaseous emissions (CO, CO₂, NO_x, SO_x, and other pollutants), affecting living organisms and requiring careful assessments. However, obtaining such information experimentally for data evaluation is costly and time-consuming and its in situ obtaining for regional biomasses (e.g., those from Northeast Brazil (NEB) is still a major challenge. This paper reports on the application of artificial neural networks (ANNs) for the prediction of the main air pollutants (CO, CO₂, NO, and SO₂) produced during the direct biomass combustion (N₂/O₂:80/20%) with the use of ultimate analysis (carbon, hydrogen, nitrogen, sulfur, and oxygen). 116 worldwide biomasses were used as input data, which is a relevant alternative to overcome the lack of experimental resources in NEB and obtain such information. Cross-validation was conducted with k-fold to optimize the ANNs and performance was analyzed with the use of statistical errors for accuracy assessments. The results showed an acceptable statistical performance for all architectures of ANNs, with 0.001–12.41% MAPE, 0.001–5.82 mg Nm⁻³ MAE, and 0.03–52.30 mg Nm⁻³ RMSE, highlighting the high precision of the emissions studied. On average, the differences between predicted and real values for CO, CO₂, NO, and SO₂ emissions from NEB biomasses were approximately 0.01%, 10⁻⁶%, 0.14%, and 0.05%, respectively. Pearson coefficient provided consistent results of concentration of the ultimate analysis in relation to the emissions studied and effectiveness of the test set in the developed models. © 2024 Elsevier Ltd

关键词： Brazilian northeastern Environmental statistics Evaluation metrics Gaseous emissions Predictive models Thermoconversion

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SHIPBOARD MAIN BOILER AND FEED PUMP CONTROL-SYSTEM ONLINE ALIGNMENT VERIFICATION

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NAVAL ENGINEERS JOURNAL 1982年第6期94卷 39-46页

作者： BANHAM, JW ADAM, DJ James W. Banham:holds positions both as Director of the Machinery Automation Systems Department of the Naval Ship Systems Engineering Station and as Assistant Chairman of the Mechanical and Industrial Engineering Department of Drexel University's Evening College where he holds the rank of Adjunct Associate Professor. He is the author of a text on Numerical Methods Applications in Engineering. In addition to numerous technical papers he is also the author of the ISA film on Boiler Feedwater Control Systems. A registered professional engineer in the state of Pennsylvania Mr. Banham is co-author of a forthcoming handbook on preparing for the Professional Engineering Examination in mechanical engineering. Mr. Banham holds a bachelor of science degree in mechanical engineering from the Pennsylvania State University his graduate studies were taken at the University of Pennsylvania. He is currently a member of the American Society for Engineering Education and the Instrument Society of America. He served as a member of the ISA Education Committee from 1964 through 1973 and as a member of the ISA Power Plant Dynamics Committee since 1969. His service on the latter committee includes terms as Executive Secretary Vice-Chairman and Chairman. Among other honors Mr. Banham was the winner of the Naval Ship Engineering Center's first Technical Achievement Award (1963) Technical Publication Award (1974) and Equal Employment Opportunity Award (1978). He was also the recipient of Drexel University's Laura S. Campbell Award for Excellence in Teaching (1978). He has taught undergraduate courses in classical control theory numerical methods computer programming systems design and analysis and instrumentation. He also teaches systems theory and computer science in an EIT Review and heat transfer in a PE Review conducted by the Drexel University Department of Continuing Professional Education. Mr. David J. Adam:is a Project Engineer in the Naval Sea Systems Command (PMS301) Steam Propulsion Plant Improvement Program where he i

One of the most serious problems encountered in Naval steam plants following World War II was the unreliable performance of boiler and main feedpump pneumatic control systems. In addition to control component and system design deficiencies, these control systems suffered from inadequate methods to measure and adjust system alignment. This paper describes the development of a set of procedures for on-line alignment verification (OLV) of pneumatic main boiler and feedpump control systems. The procedures are designed for use by N avy control system technicians and, in addition to on-line alignment verification, provide guidance for troubleshooting and for performing system alignment. Procedure static checks measure steady state steaming performance and OLV procedure dynamic checks measure the ability of the boiler and control systems to respond to load changes. The paper describes typical control system characteristics that influence OLV procedure content and the supporting analysis that was used to establish alignment criteria ranges that satisfy both steady state and transient performance requirements. Also described is the alignment criteria tolerance analysis along with the steps involved in a typical OLV check procedure development. Descriptions of the various OLV checks, troubleshooting procedures and alignment procedures are provided. Typical shipboard implementation requirements are described and experience to date with the procedures is provided along with a status report on OLV procedure implementations.

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