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Identification of hand motion using background subtraction method and extraction of image binary with backpropagation neural network on skeleton model

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Journal of Physics: Conference Series 2018年第1期978卷 012020-012020页

作者： Fauziah Wibowo, E P Madenda, S Hustinawati Information Technology Doctoral Programme in Gunadarma University Lecturer in Faculty of Informatic and Communication Technology Nasional University Indonesia Microelectronic & Images Processing Studies Gunadarma University Professor in Gunadarma University Indonesia Head Laboratory of Application and Programming Gunadarma University

Capturing and recording motion in human is mostly done with the aim for sports, health, animation films, criminality, and robotic applications. In this study combined background subtraction and back propagation neural network. This purpose to produce, find similarity movement. The acquisition process using 8 MP resolution camera MP4 format, duration 48 seconds, 30frame/rate. video extracted produced 1444 pieces and results hand motion identification process. Phase of image processing performed is segmentation process, feature extraction, identification. Segmentation using bakground subtraction, extracted feature basically used to distinguish between one object to another object. Feature extraction performed by using motion based morfology analysis based on 7 invariant moment producing four different classes motion: no object, hand down, hand-to-side and hands-up. Identification process used to recognize of hand movement using seven inputs. Testing and training with a variety of parameters tested, it appears that architecture provides the highest accuracy in one hundred hidden neural network. The architecture is used propagate the input value of the system implementation process into the user interface. The result of the identification of the type of the human movement has been clone to produce the highest acuracy of 98.5447%. The training process is done to get the best results.

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Molecular dynamics for very large systems on massively parallel computers: The MPSim program

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Journal of Computational Chemistry 1998年第4期18卷

作者： Kian‐Tat Lim Sharon Brunett Mihail Iotov Richard B. McClurg Nagarajan Vaidehi Siddharth Dasgupta Stephen Taylor William A. Goddard Materials and Process Simulation Center Beckman Institute (139‐74) Division of Chemistry and Chemical Engineering Pasadena California 91125 Scalable Concurrent Programming Laboratory California Institute of Technology Pasadena California 91125

We describe the implementation of the cell multipole method (CMM) in a complete molecular dynamics (MD) simulation program (MPSim) for massively parallel supercomputers. Tests are made of how the program scales with size (linearly) and with number of CPUs (nearly linearly) in applications involving up to 10 7 particles and up to 500 CPUs. Applications include estimating the surface tension of Ar and calculating the structure of rhinovirus 14 without requiring icosahedral symmetry. © 1997 by John Wiley & Sons, Inc.

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Quality of life during the Pandemic: A cross sectional study about Attitude, Individual perspective and behavior change affecting general population in daily life 6

Quality of life during the Pandemic: A cross sectional study...

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6th Smart Cities Symposium, SCS 2022

作者： Khatoon, Fahmida Kumar, Manish Khalid, Ayesha Akbar Alshammari, Amal Daher Khan, Farida Alshammari, Rashid D. Balouch, Zahid Verma, Deepmala Mishra, Pradeep Abotaleb, Mostafa Makarovskikh, Tatiana El-Kenawy, El-Sayed M. Dutta, P.K. Marques, Joao Alexandre Biochemistry Department College of Medicine University of Hail Saudi Arabia Department of Zoology Narain College Shikohabad India Queen Elizabeth the Queen Mother Hospital East Kent NHS Foundation Trust Margate United Kingdom Dept. of Public Health Community Medicine in College of Medicine Princess Nourah Bint Abdul Rahman University Saudi Arabia Sulaiman Al-Rajhi University Saudi Arabia Department of Community Medicine Community Medicine Hail University Saudi Arabia United Medical College Jinnah University Pakistan Department of Zoology SS Jain Subodh Autonomous College Raj Jaipur India J.N.K.V.V. College of Agriculture M.P. Powarkheda India Department of System Programming South Ural State University Chelyabinsk454080 Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Mansoura Egypt School of Engineering and Technology Amity University West Bengal Kolkata India Laboratory of Applied Neurosciences - LAN/USJ University of Saint Joseph China

ISBN: (纸本)9781839538544

Quality of life in general population before and during pandemic is topic need to be address by researcher in terms of mobility, self-care, usual activities, pain/discomfort and anxiety/depression. The study was carried out among Saudi population. Data were collected from general population using questionnaire during the period from 22 August 2021 to 10th January 2022. As a result, total 214 participants have included in this study. Among them prevalent age group include 40 years (n= 63, 29.4%) shadowed by the age group 25-35 (n= 61, 28.5%) while above 60 years group were least frequent (n= 1, 0.5%). On questioning the applicants whether they were satisfied with their health and how would they rate their quality of life, their answers were as follows: yes, or satisfied (n= 86, 40.2%), very Satisfied (n= 102, 47.7%) Dissatisfied (n= 11, 5.1%) and neither satisfied nor dissatisfied (n= 15, 7%). Due to pandemic, they were rate quality of life very good (n= 94, 43.9%), good (n= 63, 29.4 %) poor (n= 5, 2.3 %) and neither good and nor poor (n= 52, 24.3 %). During pandemic 96 participants feel no change in their weight but 110 participants respond that there is increase in coffee intake during the pandemic. Similarly increased in smoking habits and decrease rate in social activities (n=119,41.4%). The psychosomatic well-being of people has been interrupted by disturbing their social activities during pandemic. © 2022 IET Conference Proceedings. All rights reserved.

关键词： SARS

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SUMMA: scalable universal matrix multiplication algorithm

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Concurrency and Computation: Practice and Experience 1998年第4期9卷

作者： R. A. Van De Geijn J. Watts Department of Computer Sciences The University of Texas at Austin Taylor Hall 2.124 Austin TX 78712-1188 USA Scalable Concurrent Programming Laboratory California Institute of Technology Pasadena CA 91125 USA

In the paper we give a straightforward, highly efficient, scalable implementation of common matrix multiplication operations. The algorithms are much simpler than previously published methods, yield better performance, and require less work space. MPI implementations are given, as are performance results on the Intel Paragon system. © 1997 by John Wiley & Sons, Ltd.

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Uvl: Feature Modelling with the Universal Variability Language

SSRN

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SSRN 2024年

作者： Benavides, David Sundermann, Chico Feichtinger, Kevin Galindo, José A. Rabiser, Rick Thüm, Thomas Department of Computer Languages and Systems Universidad de Sevilla Av. Reina Mercedes Seville41012 Spain Institute of Software Engineering and Programming Languages University of Ulm Albert-Einstein-Allee 11 Ulm89069 Germany CRC 1608 KASTEL – Dependability of Software-intensive Systems Karlsruhe Institute of Technology Am Fasanengarten 5 Karlsruhe76131 Germany Christian Doppler Laboratory VaSiCS LIT CPS Lab Johannes Kepler University Linz Altenberger Straße 69 Linz4040 Austria

Feature modelling is a cornerstone of software product line engineering, providing a means to represent software variability through features and their relationships. Since its inception in 1990, feature modelling has evolved through various extensions, and after three decades of development, there is a growing consensus on the need for a standardised feature modelling language. Despite multiple endeavours to standardise variability modelling and the creation of various textual languages, researchers and practitioners continue to use their own approaches, impeding effective model sharing. In 2018, a collaborative initiative was launched by a group of researchers to develop a novel textual language for representing feature models. This paper introduces the outcome of this effort: the Universal Variability Language (\UVL), which is designed to be human-readable and serves as a pivot language for diverse software engineering tools. The development of \UVL drew upon community feedback and leveraged established literature in the field of variability modelling. The language is structured into three levels -Boolean, Arithmetic, and Type- and allows for language extensions to introduce additional constructs enhancing its expressiveness. \UVL is integrated into various existing software tools, such as FeatureIDE and FLAMA, and is maintained by a consortium of institutions. © 2024, The Authors. All rights reserved.

关键词： Modeling languages

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Eigenvalue tunneling and decay of quenched random network

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Physical Review E 2016年第6期94卷 062313-062313页

作者： V. Avetisov M. Hovhannisyan A. Gorsky S. Nechaev M. Tamm O. Valba N. N. Semenov Institute of Chemical Physics of the Russian Academy of Sciences 119991 Moscow Russia Department of Applied Mathematics National Research University Higher School of Economics 101000 Moscow Russia Chair of Programming and Information Technologies Yerevan State University Yerevan Armenia Institute of Information Transmission Problems Russian Academy of Sciences Moscow Russia Moscow Institute of Physics and Technology Dolgoprudny 141700 Russia Poncelet Laboratory Centre National de la Recherche Scientifique (UMI2615) Independent University of Moscow Moscow Russia P. N. Lebedev Physical Institute Russian Academy of Sciences 119991 Moscow Russia Physics Department Moscow State University 119992 Moscow Russia

We consider the canonical ensemble of N-vertex Erdős-Rényi (ER) random topological graphs with quenched vertex degree, and with fugacity μ for each closed triple of bonds. We claim complete defragmentation of large-N graphs into the collection of [p−1] almost full subgraphs (cliques) above critical fugacity, μc, where p is the ER bond formation probability. Evolution of the spectral density, ρ(λ), of the adjacency matrix with increasing μ leads to the formation of a multizonal support for μ>μc. Eigenvalue tunneling from the central zone to the side one means formation of a new clique in the defragmentation process. The adjacency matrix of the network ground state has a block-diagonal form, where the number of vertices in blocks fluctuates around the mean value Np. The spectral density of the whole network in this regime has triangular shape. We interpret the phenomena from the viewpoint of the conventional random matrix model and speculate about possible physical applications.

关键词： Clustering Collective behavior in networks Critical phenomena Evolving networks Network evolution Network phase transitions

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Concurrent simulation of neutral flow in the GEC reference cell

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Concurrency and Computation: Practice and Experience 2000年第1期12卷

作者： Marc Rieffel Mikhail Ivanov Sadasivan Shankar Stephen Taylor Scalable Concurrent Programming Laboratory -120 CST Syracuse University Syracuse NY 13244 U.S.A. Institute for Theoretical and Applied Mechanics Russian Academy of Sciences Siberian Branch Russia Technology CAD Department Intel Corporation RN 2-40 2200 Mission College Blvd Santa Clara CA 95054 U.S.A.

This paper describes computational techniques for concurrent Direct Simulation Monte Carlo (DSMC) of neutral flow inside three-dimensional plasma reactors. These techniques are designed to reduce the overall time to obtain realistic three-dimensional results. A simulation problem is first defined by automatically generating a tetrahedral grid. This grid is statically partitioned in order to achieve scalable memory utilization. Parallel algorithms allow high-performance multicomputer architectures to be leveraged to reduce simulation time. Adaptive gridding techniques are employed to maintain the desired accuracy in the presence of dynamic flow variations. Load balancing algorithms, based on heat diffusion, are used to maximize efficiency. Finally, automatic granularity control is used to ensure appropriate granularity for load balancing and for maximum processor utilization. Simulation results are presented for a simulation of the GEC reference cell in a flow configuration of industrial relevance. Performance results are presented for large-scale multicomputers, symmetric multiprocessors and networks of PCs. Copyright © 2000 John Wiley & Sons, Ltd.

关键词： DSMC concurrent programming load balancing granularity control parallel processing plasma simulation

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Quality of life during the pandemic: a cross sectional study about attitude, individual perspective and behavior change affecting general population in daily life

Quality of life during the pandemic: a cross sectional study...

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6th Smart Cities Symposium (SCS 2022)

作者： F. Khatoon M. Kumar A. A. Khalid A. D. Alshammari F. Khan R. D. Alshammari Z. Balouch D. Verma P. Mishra M. Abotaleb T. Makarovskikh E. M. El-kenawy P. K. Dutta J. A. Marques Biochemistry Department College of Medicine University of Hail Hail Saudi Arabia Department of Zoology Narain College Narain College Shikohabad India Queen Elizabeth the Queen Mother Hospital East Kent NHS Foundation Trust Margate Dept. of Public Health/Community Medicine in College of Medicine Princess Nourah Bint Abdul Rahman University Sulaiman Al-Rajhi University Department of Community Medicine Hail university United Medical College Jinnah University SS Jain Subodh Autonomous College Department of Zoology Jaipur (Raj) Jaipur India J.N.K.V.V. College of Agriculture Powarkheda India Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Mansoura Egypt School of Engineering and Technology Amity University Kolkata Kolkata India Laboratory of Applied Neurosciences - LAN/USJ University of Saint Joseph West Hartford China

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ROLE OF SIMULATION IN RAPID PROTOTYPING FOR CONCEPT DEVELOPMENT

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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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Scientific Data Lake for High Luminosity LHC project and other data-intensive particle and astro-particle physics experiments

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Journal of Physics: Conference Series 2020年第1期1690卷

作者： A Alekseev A Kiryanov A Klimentov T Korchuganova V Mitsyn D Oleynik A Smirnov S Smirnov A Zarochentsev Compiler Technology Department Ivannikov Institute for System Programming of the RAS Moscow 109004 Russia Cloud technologies and Big Data analytics laboratory Plekhanov Russian University of Economics Moscow 117997 Russia ATLAS group Universidad Andres Bello Santiago 7550196 Chile Department of computing resources and technologies NRC 'Kurchatov Institute' - PNPI 188300 Gatchina Russia Physics Department Brookhaven National Laboratory Upton NY 11973 USA Laboratory of Information Technologies Joint Institute for Nuclear Research Dubna 141980 Russia Institute of Nuclear Physics and Engineering National Research Nuclear University MEPhI Moscow 115409 Russia Laboratory of Ultra-High Energy Physics Saint Petersburg State University Saint Petersburg 198504 Russia

The next phase of LHC Operations – High Luminosity LHC (HL-LHC), which is aimed at ten-fold increase in the luminosity of proton-proton collisions at the energy of 14 TeV, is expected to start operation in 2027-2028 and will deliver an unprecedented scientific data volume of multi-exabyte scale. This amount of data has to be stored and the corresponding storage system should ensure fast and reliable data delivery for processing by scientific groups distributed all over the world. The present LHC computing and data processing model will not be able to provide the required infrastructure growth even taking into account the expected hardware technology evolution. To address this challenge the new state-of-the-art computing infrastructure technologies are now being developed and are presented here. The possibilities of application of the HL-LHC distributed data handling technique for other particle and astro-particle physics experiments dealing with large-scale data volumes like DUNE, LSST, Belle-II, JUNO, SKAO etc. are also discussed.

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