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Journal articles on the topic 'Space-based computing'

Author: Grafiati

Published: 4 June 2021

Last updated: 13 February 2022

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1

Khalfi, Mohammed Fethi, and Sidi Mohamed Benslimane. "Meta Model Context Based Space for Ubiquitous Computing." International Journal of Advanced Pervasive and Ubiquitous Computing 7, no. 2 (April 2015): 51–66. http://dx.doi.org/10.4018/ijapuc.2015040105.

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Pervasive computing is a paradigm that focuses on the availability of computer resources anytime anywhere for any application and supports integration of computing services into everyday life. Context awareness is the core feature of pervasive computing. High-level context awareness can be enhanced by situation awareness that represents the ability to detect and reason about the real-life situations. In this paper, in order to deal with the problem in context-aware modeling in pervasive computing environments, the authors present a comprehensive and integrated approach for context modeling. They first propose a Meta model context based on ontology for Pervasive Computing aiming firstly to overcome the limitations of the existing ontologies, and secondly extend its capabilities by adding new environmental aspects. They divide the context model into Meta Ontology level and Domain-specific Ontology level according to the abstraction hierarchy. The Meta Ontology is the high abstract level which extracting the basic elements of the context knowledge. The Domain-specific Ontology is the lower abstract lever which focusing on different domains knowledge, directed by the Meta Ontology. The advantage is that it can provide a flexible modeling mechanism for multiple applications of context-aware pervasive computing. A case study of HealthCare domain is given to illustrate the practicality of the authors' Model.

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Esposito, S., C. Albanese, M. Alderighi, F. Casini, L. Giganti, M. L. Esposti, C. Monteleone, and M. Violante. "COTS-Based High-Performance Computing for Space Applications." IEEE Transactions on Nuclear Science 62, no. 6 (December 2015): 2687–94. http://dx.doi.org/10.1109/tns.2015.2492824.

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3

Vyurkov, V., S. Filippov, and L. Gorelik. "Quantum computing based on space states without charge transfer." Physics Letters A 374, no. 33 (July 2010): 3285–91. http://dx.doi.org/10.1016/j.physleta.2010.06.023.

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4

Cristea, Valentin, Ciprian Dobre, Alexandru Costan, and Florin Pop. "Middleware and architectures for space-based and situated computing." International Journal of Space-Based and Situated Computing 1, no. 1 (2011): 43. http://dx.doi.org/10.1504/ijssc.2011.039106.

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Chen, Yong, Huang Xu, Guanlin Chen, Huajian Pang, and Wujian Yang. "A parking space allocation algorithm based on distributed computing." International Journal of Sensor Networks 33, no. 4 (2020): 250. http://dx.doi.org/10.1504/ijsnet.2020.10031354.

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Chen, Guanlin, Huajian Pang, Huang Xu, Wujian Yang, and Yong Chen. "A parking space allocation algorithm based on distributed computing." International Journal of Sensor Networks 33, no. 4 (2020): 250. http://dx.doi.org/10.1504/ijsnet.2020.109196.

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7

Innocenti, Maria Elena, Alec Johnson, Stefano Markidis, Jorge Amaya, Jan Deca, Vyacheslav Olshevsky, and Giovanni Lapenta. "Progress towards physics-based space weather forecasting with exascale computing." Advances in Engineering Software 111 (September 2017): 3–17. http://dx.doi.org/10.1016/j.advengsoft.2016.06.011.

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8

Huang, Bin Wen, and Jie Yu Li. "A Teaching Resources Platform Based on Cloud Computing Technology." Applied Mechanics and Materials 687-691 (November 2014): 3074–77. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.3074.

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This paper gives a teaching resources platform that is a comprehensive feature rich, convenient use, strong interactivity based on cloud computing technology. Platform includes various cloud functions and cloud spaces such as identity authentication function, single sign-on function, resources upload/download function, resources collection function, resource integration function, instant communication function, teacher resource cloud space, student resources cloud space, theme resources cloud space, department resources cloud space and schools resources cloud space. Compared with available technology, we can build an no capacity constraints cloud platform for storage and sharing of teaching resources based on the cloud computing technology, this teaching resources cloud platform is an open, interactive public service platform of educational resources.

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Gunter, Brian C., and Daan C. Maessen. "Space-Based Distributed Computing Using a Networked Constellation of Small Satellites." Journal of Spacecraft and Rockets 50, no. 5 (September 2013): 1086–95. http://dx.doi.org/10.2514/1.a32384.

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Liu, Hongbing, Gengyi Liu, Xuewen Ma, and Daohua Liu. "Training dictionary by granular computing with L∞-norm for patch granule–based image denoising." Journal of Algorithms & Computational Technology 12, no. 2 (March 2, 2018): 136–46. http://dx.doi.org/10.1177/1748301818761131.

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Considering the objects by different granularity reflects the recognition common law of people, granular computing embodies the transformation between different granularity spaces. We present the image denoising algorithm by using the dictionary trained by granular computing with L∞-norm, which realizes three transformations, (1) the transformation from image space to patch granule space, (2) the transformation between granule spaces with different granularities, and (3) the transformation from patch granule space to image space. We demonstrate that the granular computing with L∞-norm achieved the comparable peak signal to noise ratio (PSNR) measure compared with BM3D and patch group prior based denoising for eight natural images.

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Pei, Ao Qiu, Min Yang, and Yan Bin Tang. "The Research Based on Security Model and Cloud Computing Strategy." Advanced Materials Research 846-847 (November 2013): 1600–1603. http://dx.doi.org/10.4028/www.scientific.net/amr.846-847.1600.

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Cloud computing based on a large number of distributed computer gathers a wide variety of computing resources data and builds huge virtual resources space and provides information technology resources for the majority of computer users through the Internet. Security issues is one of the core elements which constrains the depth development of cloud computing. It also is the hot issue of research in this field. This paper first analyzes the architecture and threat signatures of cloud computing system and data application model based on the data of cloud computing and data security threat characteristics. It builds a data security implementation model under cloud computing. Based on this, it builds information security model of cloud computing strategy and analyzes configuration program of the model in the cloud computing.

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Bruhn, Fredrik C., Nandinbaatar Tsog, Fabian Kunkel, Oskar Flordal, and Ian Troxel. "Enabling radiation tolerant heterogeneous GPU-based onboard data processing in space." CEAS Space Journal 12, no. 4 (June 15, 2020): 551–64. http://dx.doi.org/10.1007/s12567-020-00321-9.

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Abstract The last decade has seen a dramatic increase in small satellite missions for commercial, public, and government intelligence applications. Given the rapid commercialization of constellation-driven services in Earth Observation, situational domain awareness, communications including machine-to-machine interface, exploration etc., small satellites represent an enabling technology for a large growth market generating truly Big Data. Examples of modern sensors that can generate very large amounts of data are optical sensing, hyperspectral, Synthetic Aperture Radar (SAR), and Infrared imaging. Traditional handling and downloading of Big Data from space requires a large onboard mass storage and high bandwidth downlink with a trend towards optical links. Many missions and applications can benefit significantly from onboard cloud computing similarly to Earth-based cloud services. Hence, enabling space systems to provide near real-time data and enable low latency distribution of critical and time sensitive information to users. In addition, the downlink capability can be more effectively utilized by applying more onboard processing to reduce the data and create high value information products. This paper discusses current implementations and roadmap for leveraging high performance computing tools and methods on small satellites with radiation tolerant hardware. This includes runtime analysis with benchmarks of convolutional neural networks and matrix multiplications using industry standard tools (e.g., TensorFlow and PlaidML). In addition, a ½ CubeSat volume unit (0.5U) (10 × 10 × 5 cm3) cloud computing solution, called SpaceCloud™ iX5100 based on AMD 28 nm APU technology is presented as an example of heterogeneous computer solution. An evaluation of the AMD 14 nm Ryzen APU is presented as a candidate for future advanced onboard processing for space vehicles.

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Hu, Xingchen, Witold Pedrycz, and Xianmin Wang. "Fuzzy classifiers with information granules in feature space and logic-based computing." Pattern Recognition 80 (August 2018): 156–67. http://dx.doi.org/10.1016/j.patcog.2018.03.011.

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Kaddouri, Ali, Mustapha Guezouri, and Nader Mbarek. "A new proposed cloud computing based architecture for space ground data systems." International Journal of Communication Networks and Distributed Systems 20, no. 2 (2018): 244. http://dx.doi.org/10.1504/ijcnds.2018.089772.

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Mbarek, Nader, Ali Kaddouri, and Mustapha Guezouri. "A new proposed cloud computing based architecture for space ground data systems." International Journal of Communication Networks and Distributed Systems 20, no. 2 (2018): 244. http://dx.doi.org/10.1504/ijcnds.2018.10010390.

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Cheng, Xiongwen, Feng Lyu, Wei Quan, Conghao Zhou, Hongli He, Weisen Shi, and Xuemin Shen. "Space/Aerial-Assisted Computing Offloading for IoT Applications: A Learning-Based Approach." IEEE Journal on Selected Areas in Communications 37, no. 5 (May 2019): 1117–29. http://dx.doi.org/10.1109/jsac.2019.2906789.

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17

Wang, An, and Bing Gui. "ITS Platform Research Based on Cloud Computing." Applied Mechanics and Materials 496-500 (January 2014): 2117–20. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.2117.

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Intelligent transportation system (ITS) is a new informationization, intelligent, and socialization type of modern traffic system. Development of cloud computing technology will bring new space of development for the development Of ITS, and the combination will be the future development trend. The paper discusses the application of cloud computing technology in the field of intelligent traffic, puts forward ITS platform based on cloud computing in order to solve problems that how to share mass traffic information.

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18

Ryan, Nathan C., Nicolás Sirolli, Nils-Peter Skoruppa, and Gonzalo Tornaría. "Computing Jacobi forms." LMS Journal of Computation and Mathematics 19, A (2016): 205–19. http://dx.doi.org/10.1112/s1461157016000346.

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We describe an implementation for computing holomorphic and skew-holomorphic Jacobi forms of integral weight and scalar index on the full modular group. This implementation is based on formulas derived by one of the authors which express Jacobi forms in terms of modular symbols of elliptic modular forms. Since this method allows a Jacobi eigenform to be generated directly from a given modular eigensymbol without reference to the whole ambient space of Jacobi forms, it makes it possible to compute Jacobi Hecke eigenforms of large index. We illustrate our method with several examples.

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19

Zhang, Chi Jun, and Wang Sheng Liu. "Research on VR-Based Experiment Space for Complex Electromagnetic Environment." Advanced Materials Research 403-408 (November 2011): 2923–26. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.2923.

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Virtual Reality technology is a hot research field in simulation of complex electromagnetic and its practical environment in the condition of information and high technology war. The paper discussed the main framework of spatial electromagnetic environment computing and simulating, presented realizing method and key arithmetic designing based on Virtual Reality Modeling Language. The work is evidently valuable for quantitative examinations, evaluation, and analysis of complex electromagnetic environment function, diversification, and effect on human beings, electronic units.

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Wang, Jiang Xiong, Jun Wen, and Fu Xia Zhang. "The Rainstorm Space and Time Characteristic Analysis Based on GIS." Applied Mechanics and Materials 71-78 (July 2011): 2712–15. http://dx.doi.org/10.4028/www.scientific.net/amm.71-78.2712.

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Base on the theory of rainstorm and flood, concept of spatial image and geographical, the elementary and computing technique foundation of gis. In experimental plot data quite complete situation, Summary science reasonable, both accurate and highly effective rainstorm flood space and time structure evolution rule research technique, And key discussion and research spatial data pretreatment and quality analysis, space and time structure differentiation analysis, spatial reckoning analysis, spatial pattern analysis and spatial autocorrelation analysis in rainstorm flood space and time structure evolution research concrete application.

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S Pathak, Shantanu, and D. Rajeswara Rao. "Reservoir Computing for Healthcare Analytics." International Journal of Engineering & Technology 7, no. 2.32 (May 31, 2018): 240. http://dx.doi.org/10.14419/ijet.v7i2.32.15576.

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In this data age tools for sophisticated generation and handling of data are at epitome of usage. Data varying in both space and time poses a breed of challenges. Challenges they possess for forecasting can be well handled by Reservoir computing based neural networks. Challenges like class imbalance, missing values, locality effect are discussed here. Additionally, popular statistical techniques for forecasting such data are discussed. Results show how Reservoir Computing based technique outper-forms traditional neural networks.

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22

Fang, Gang, Jiale Wang, and Hong Ying. "A Novel Model for Mining Frequent Patterns Based on Embedded Granular Computing." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 26, no. 05 (September 28, 2018): 741–69. http://dx.doi.org/10.1142/s0218488518500344.

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For mining frequent patterns, it is very expensive for the Apriori mining model to read the database repeatedly, and a highly condensed data structure made the FP-growth mining model cost larger memory. In order to avoid the disadvantages of these data mining model, this paper proposes a novel data mining model for discovering frequent patterns, called a data mining model based on embedded granular computing, which is different from the Apriori model and the FP-growth model. The data mining model adopts efficiently dividing and conquering from granular computing, which can construct adaptively different hierarchical granules. To form the data mining model, an embedded granular computing model is proposed in this paper. The granular computing model is used in discovering frequent patterns, on the one hand, it avoids reading the database repeatedly via constructing the extended information granule, and lessen the calculated amount of support; on the other hand, it reduces the memory requirements by the attribute granule, where the search space can compress the memory space of data structure that make the method of generating the candidate become simple relatively; and it can divide the overlarge computing task into several easy operations via the attribute granule, namely, the embedded granular computing model could short the size of the search space from a super state to several sub-states. All experimental results show that the data mining model based on embedded granular computing is more reasonable and efficient than these classical models for mining frequent patterns under these different types of datasets. Otherwise, an extra discussion describes the performance trend of the model by a group of experiments.

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23

Kolařík, Filip, and Bořek Patzák. "IMPLEMENTATION OF 3D VOF TRACKING ALGORITHM BASED ON BINARY SPACE-PARTITIONING." Acta Polytechnica 57, no. 2 (May 2, 2017): 105. http://dx.doi.org/10.14311/ap.2017.57.0105.

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The paper focuses on modelling free surface flow. The interface is modelled using the Volume-Of-Fluid method, where the advection of volume fractions is treated by a purely geometrical method. The novelty of the work lies in the way that it incorporates Binary Space-Partitioning trees for computing the intersections of polyhedra. Volume-conserving properties and shape-preserving properties are presented on two benchmarks and on a simulation of the famous broken dam problem.

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Huang, Bin Wen, and Yuan Jiao. "Study on the Construction of Teaching Resources Platform Based on Cloud Space." Applied Mechanics and Materials 678 (October 2014): 663–65. http://dx.doi.org/10.4028/www.scientific.net/amm.678.663.

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With the rapid development of cloud computing technology and application, the construction of teaching resources platform based on cloud space has become a development trend and direction of the education informatization, this paper presents the existing problems in teaching resources platform and the ideas and methods about how to construct teaching resources platform based on cloud space

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25

Pei, Zhi Li, Qing Hu Wang, Jie Lian, and Bin Wu. "A MSTP DNA Computing Model Based on Genetic Algorithm and Incompletion-Molecule Commixed Encoding Strategy." Applied Mechanics and Materials 411-414 (September 2013): 2056–61. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.2056.

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Artificial intelligence based on the genetic algorithm and DNA computing based on the biological intelligence is two kinds of important intelligent computing model, Graph theory and combinatorial optimization problem is a hotspot of research on intelligent computing. This paper designs a coding space optimized by using genetic algorithm, and by using DNA computing to solve Minimum Spanning Tree Problem calculation model. Because MSTP (Minimum Spanning Tree Problem) refer to Weight, IMCE (Incompletion-Molecule Commixed Encoding) is used in vertex, edges and weights encoding. The calculation process of the MSTP solution has been detailed described detailed.

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Ilango, S. Sudhakar, and V. Seenivasagam. "Wavelet Based Image Compression Using Soft Computing Techniques." Applied Mechanics and Materials 573 (June 2014): 477–82. http://dx.doi.org/10.4028/www.scientific.net/amm.573.477.

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The Wavelet Transform is a multi-resolution transform, that is, it allows a form of time–frequency analysis (or translation–scale in wavelet speak). When using the Fourier transform the result is a very precise analysis of the frequencies contained in the signal, but no information on when those frequencies occurred. The wavelet based image compression algorithms are used widely compared with other conventional compression algorithms. The wavelet coding based on the coefficient selection and sub band level. In this paper we have used two wavelets such as spherical and geometric wavelets. The spherical representation is a hierarchical description of how total energy gets distributed within each wavelet sub band.In the proposed method, we used fuzzy quantization technique for coefficient selection in the spherical wavelet. The other scheme introduces binary space partitioning scheme and geometric wavelet, where the existing pruning method of binary space partitioning is replaced by the genetic algorithm. We had another experiment with geometric wavelet with Artificial Bee Colony (ABC) algorithm. The experimental results for all the three methods are discussed in this paper. The advantages of these methods are the improved PSNR values at high and medium bit rates.

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Lentaris, George, Konstantinos Maragos, Ioannis Stratakos, Lazaros Papadopoulos, Odysseas Papanikolaou, Dimitrios Soudris, Manolis Lourakis, Xenophon Zabulis, David Gonzalez-Arjona, and Gianluca Furano. "High-Performance Embedded Computing in Space: Evaluation of Platforms for Vision-Based Navigation." Journal of Aerospace Information Systems 15, no. 4 (April 2018): 178–92. http://dx.doi.org/10.2514/1.i010555.

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Bose, Amartya, and Nancy Makri. "Coherent State-Based Path Integral Methodology for Computing the Wigner Phase Space Distribution." Journal of Physical Chemistry A 123, no. 19 (April 15, 2019): 4284–94. http://dx.doi.org/10.1021/acs.jpca.9b00758.

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Andreeva, Julia, Dimitrios Christidis, Alessandro Di Girolamo, and Oliver Keeble. "WLCG space accounting in the SRM-less world." EPJ Web of Conferences 214 (2019): 04021. http://dx.doi.org/10.1051/epjconf/201921404021.

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The WLCG computing infrastructure provides distributed storage capacity hosted at the geographically dispersed computing sites. In order to effectively organize storage and processing of the LHC data, the LHC experiments require a reliable and complete overview of the storage capacity in terms of the occupied and free space, the storage shares allocated to different computing activities, and the possibility to detect “dark” data that occupies space while being unknown to the experiment's file catalogue. The task of the WLCG space accounting activity is to provide such an overview and to assist LHC experiments and WLCG operations to manage storage space and to understand future requirements. Several space accounting solutions which have been developed by the LHC experiments are currently based on Storage Resource Manager (SRM). In the coming years SRM becomes an optional service for sites which do not provide tape storage. Moreover, already now some of the storage implementations do not provide an SRM interface. Therefore, the next generation of the space accounting systems should not be based on SRM. In order to enable possibility for exposing storage topology and space accounting information the Storage Resource Reporting proposal has been agreed between LHC experiments, sites and storage providers. This contribution describes the WLCG storage resource accounting system which is being developed based on Storage Resource Reporting proposal.

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Xu, Rongxu, Wenquan Jin, and Dohyeun Kim. "Environment Optimization Scheme Based on Edge Computing Using PSO for Efficient Thermal Comfort Control in Resident Space." Actuators 10, no. 9 (September 17, 2021): 241. http://dx.doi.org/10.3390/act10090241.

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With the fast development of infrastructure and communication technology, the Internet of Things (IoT) has become a promising field. Ongoing research is looking at the smart home environment as the most promising sector that adopts IoT and cloud computing to improve resident live experiences. The IoT and cloud-dependent smart home services related to recent researches have security, bandwidth issues, and a lack of concerning thermal comfort of residents. In this paper, we propose an environment optimization scheme based on edge computing using Particle Swarm Optimization (PSO) for efficient thermal comfort control in resident space to overcome the aforementioned limitations of researches on smart homes. The comfort level of a resident in a smart home is evaluated by Predicted Mean Vote (PMV) that represents the thermal response of occupants. The PSO algorithm combined with PMV to improve the accuracy of the optimization results for efficient thermal comfort control in a smart home environment. We integrate IoT with edge computing to upgrade the capabilities of IoT nodes in computing power, storage space, and reliable connectivity. We use EdgeX as an edge computing platform to develop a thermal comfort considering PMV-based optimization engine with a PSO algorithm to generate the resident’s friendly environment parameters and rules engine to detects the environmental change of the smart home in real-time to maintain the indoor environment thermal comfortable. For evaluating our proposed system that maintenance resident environment with thermal comfort index based on PSO optimization scheme in smart homes, we conduct the comparison between the real data with optimized data, and measure the execution times of optimization function. From the experimental results, when our proposed system is applied, it satisfies thermal comfort and consumes energy more stably.

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Liu, Rongsheng, Minfang Peng, and Xianghui Xiao. "Ultra-Short-Term Wind Power Prediction Based on Multivariate Phase Space Reconstruction and Multivariate Linear Regression." Energies 11, no. 10 (October 15, 2018): 2763. http://dx.doi.org/10.3390/en11102763.

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In order to improve the accuracy of wind power prediction (WPP), we propose a WPP based on multivariate phase space reconstruction (MPSR) and multivariate linear regression (MLR). Firstly, the multivariate time series (TS) are constructed through reasonable selection of wind power and weather factors, which are closely associated with wind power. Secondly, the phase space of the multivariate time series is reconstructed based on the chaos theory and C-C method. Thirdly, an auto regression model for multivariate phase space is created by regarding phase variables as state variables, and the very-short-term wind power is predicted by using a multi-linear regression algorithm. Finally, a parallel algorithm based on map/reduce is presented to improve computing speed. A cloud computing platform, Hadoop consisting of five nodes, is established as a matter of convenience, followed by the prediction of wind power of a wind farm in the Hunan province of China. The experimental results show that the model based on MPSR and MLR is more accurate than both the continuous method and the simple approximation method, and the parallel algorithm based on map/reduce effectively accelerates the computing speed.

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Li, Bingzheng, Jinchen Xu, and Zijing Liu. "SW-LZMA: Parallel Implementation of LZMA Based on SW26010 Many-Core Processor." Wireless Communications and Mobile Computing 2021 (September 18, 2021): 1–10. http://dx.doi.org/10.1155/2021/4486494.

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With the development of high-performance computing and big data applications, the scale of data transmitted, stored, and processed by high-performance computing cluster systems is increasing explosively. Efficient compression of large-scale data and reducing the space required for data storage and transmission is one of the keys to improving the performance of high-performance computing cluster systems. In this paper, we present SW-LZMA, a parallel design and optimization of LZMA based on the Sunway 26010 heterogeneous many-core processor. Combined with the characteristics of SW26010 processors, we analyse the storage space requirements, memory access characteristics, and hotspot functions of the LZMA algorithm and implement the thread-level parallelism of the LZMA algorithm based on Athread interface. Furthermore, we make a fine-grained layout of LDM address space to achieve DMA double buffer cyclic sliding window algorithm, which optimizes the performance of SW-LZMA. The experimental results show that compared with the serial baseline implementation of LZMA, the parallel LZMA algorithm obtains a maximum speedup ratio of 4.1 times using the Silesia corpus benchmark, while on the large-scale data set, speedup is 5.3 times.

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Schneegass, Stefan, Thomas Olsson, Sven Mayer, and Kristof van Laerhoven. "Mobile Interactions Augmented by Wearable Computing." International Journal of Mobile Human Computer Interaction 8, no. 4 (October 2016): 104–14. http://dx.doi.org/10.4018/ijmhci.2016100106.

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Wearable computing has a huge potential to shape the way we interact with mobile devices in the future. Interaction with mobile devices is still mainly limited to visual output and tactile finger-based input. Despite the visions of next-generation mobile interaction, the hand-held form factor hinders new interaction techniques becoming commonplace. In contrast, wearable devices and sensors are intended for more continuous and close-to-body use. This makes it possible to design novel wearable-augmented mobile interaction methods – both explicit and implicit. For example, the EEG signal from a wearable breast strap could be used to identify user status and change the device state accordingly (implicit) and the optical tracking with a head-mounted camera could be used to recognize gestural input (explicit). In this paper, the authors outline the design space for how the existing and envisioned wearable devices and sensors could augment mobile interaction techniques. Based on designs and discussions in a recently organized workshop on the topic as well as other related work, the authors present an overview of this design space and highlight some use cases that underline the potential therein.

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Li, Dong, and Dong Yun Yi. "Preliminary Orbit Determination for GEO Objects Using Space-Based Optical Observations." Advanced Materials Research 457-458 (January 2012): 728–33. http://dx.doi.org/10.4028/www.scientific.net/amr.457-458.728.

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Preliminary orbit determination for geosynchronous Earth orbit (GEO) using two short arcs of space-based optical observations plays a key role in the space-based space surveillance systems. The concept of attributable is introduced to represent the information in a short arc of observations. Using two-body integrals, the polynomial equations for distance and radial velocity between the surveillance satellite and the GEO object at two epochs are constructed. By variables transformation, multiple solutions of these equations are obtained. By covariance analysis, a penalty function is given to select the practical solutions for computing preliminary orbits. The simulation results show this algorithm can successfully obtain preliminary orbits with certain accuracy.

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Fan, Yu Cheng, Yi Feng Chiang, and Ching Min Lee. "Three Dimensional Vision Conversion Based on Cloud Computing." Applied Mechanics and Materials 284-287 (January 2013): 3492–96. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.3492.

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In this paper, we propose a three dimensional vision conversion based on cloud computing. Three dimensional video and image system become an important technology in consumer electronics field in latest decade. There are numerous three dimensional video and image formats for different 3D products. However, the three dimensional vision contents that are manufactured by different standards are difficult to exchange without complete three dimensional vision converters. Therefore, how to perform the three dimensional vision format converters to interchange different kinds of three dimension vision becomes an important research topic in academic and industry. Nevertheless, three dimensional vision processor and converter have high computing complexity. It is hard to perform whole three dimensional vision converter according to all kinds of international standards in client machine and portable device. At the same time, three dimensional visions often require a large number of storage spaces. It is also very difficult to record all kinds of three dimensional visions in local device. The above problem should be solved adopting different concepts. Therefore, we proposed cloud computing concept that establishes a complete three dimensional vision converter in cloud computing server and storage space in three dimensional vision clouds. The customer access the three dimensional vision rely on three dimensional vision cloud. The approach methodology solves the problems of computing complexity and storage space of tradition three dimensional vision converters and storage. The presented intact framework of three dimensional vision converters also provides a solution of related research in this paper.

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A. J., Umbarkar, and Joshi M. S. "REVIEW OF PARALLEL GENETIC ALGORITHM BASED ON COMPUTING PARADIGM AND DIVERSITY IN SEARCH SPACE." ICTACT Journal on Soft Computing 03, no. 04 (July 1, 2013): 615–22. http://dx.doi.org/10.21917/ijsc.2013.0089.

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Arakawa, Ren, Naoya Onizawa, Jean-Philippe Diguet, and Takahiro Hanyu. "Multi-Context TCAM-Based Selective Computing: Design Space Exploration for a Low-Power NN." IEEE Transactions on Circuits and Systems I: Regular Papers 68, no. 1 (January 2021): 67–76. http://dx.doi.org/10.1109/tcsi.2020.3030104.

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B.S, Mrs Sunitha, and Dr Anir Ban Basu. "Review of Role Based Access Control Method for Securing User Space in Cloud Computing." International Journal of Computer Trends and Technology 14, no. 1 (August 25, 2014): 22–25. http://dx.doi.org/10.14445/22312803/ijctt-v14p106.

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Hong, Chung-Pyo, Cheong-Ghil Kim, and Shin-Dug Kim. "An Effective Personalized Service Provision Scheme Based on Virtual Space for Ubiquitous Computing Environment." Wireless Personal Communications 73, no. 2 (June 11, 2013): 275–88. http://dx.doi.org/10.1007/s11277-013-1236-3.

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Terzo, Olivier, Lorenzo Mossucca, Manuela Cucca, and Riccardo Notarpietro. "Data intensive scientific analysis with grid computing." International Journal of Applied Mathematics and Computer Science 21, no. 2 (June 1, 2011): 219–28. http://dx.doi.org/10.2478/v10006-011-0016-z.

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Data intensive scientific analysis with grid computing At the end of September 2009, a new Italian GPS receiver for radio occultation was launched from the Satish Dhawan Space Center (Sriharikota, India) on the Indian Remote Sensing OCEANSAT-2 satellite. The Italian Space Agency has established a set of Italian universities and research centers to implement the overall processing radio occultation chain. After a brief description of the adopted algorithms, which can be used to characterize the temperature, pressure and humidity, the contribution will focus on a method for automatic processing these data, based on the use of a distributed architecture. This paper aims at being a possible application of grid computing for scientific research.

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Dai, Zhe Min, De Sheng Li, and Hu Xie. "The Analysis for Evaluation of Ceramic Tile’s Color Difference Based on CIELAB Color Space." Advanced Materials Research 490-495 (March 2012): 3726–32. http://dx.doi.org/10.4028/www.scientific.net/amr.490-495.3726.

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The color difference is one of the important evaluation index in ceramic tiles quality evaluation. So a good color difference evaluation index selecting has a great influence to the ceramic tile’s quality testing. In this paper, by computing and analyzing different color difference evaluation index, it is shown that CIE2000 formula is robust and feasible in ceramic tiles quality evaluation.

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Dunn, J. Michael, Tobias J. Hagge, Lawrence S. Moss, and Zhenghan Wang. "Quantum logic as motivated by quantum computing." Journal of Symbolic Logic 70, no. 2 (June 2005): 353–59. http://dx.doi.org/10.2178/jsl/1120224716.

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§1. Introduction. Our understanding of Nature comes in layers, so should the development of logic. Classic logic is an indispensable part of our knowledge, and its interactions with computer science have recently dramatically changed our life. A new layer of logic has been developing ever since the discovery of quantum mechanics. G. D. Birkhoff and von Neumann introduced quantum logic in a seminal paper in 1936 [1]. But the definition of quantum logic varies among authors (see [2]). How to capture the logic structure inherent in quantum mechanics is very interesting and challenging. Given the close connection between classical logic and theoretical computer science as exemplified by the coincidence of computable functions through Turing machines, recursive function theory, and λ-calculus, we are interested in how to gain some insights about quantum logic from quantum computing. In this note we make some observations about quantum logic as motivated by quantum computing (see [5]) and hope more people will explore this connection.The quantum logic as envisioned by Birkhoff and von Neumann is based on the lattice of closed subspaces of a Hilbert space, usually an infinite dimensional one. The quantum logic of a fixed Hilbert space ℍ in this note is the variety of all the true equations with finitely many variables using the connectives meet, join and negation. Quantum computing is theoretically based on quantum systems with finite dimensional Hilbert spaces, especially the states space of a qubit ℂ2. (Actually the qubit is merely a convenience.

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Zhou, Li. "Cloud Computing Research Vehicle Traffic Information Service System Based on Network." Applied Mechanics and Materials 727-728 (January 2015): 944–47. http://dx.doi.org/10.4028/www.scientific.net/amm.727-728.944.

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In vehicle network under the cloud computing environment model of traffic information service system construction as the goal, the use of cloud computing technology and service oriented software architecture is divided into thought, differentiation and security mechanism from the service account, complete vehicle based on cloud computing network traffic information service system of the letter of the architecture design, function design, software structure design. Based on the geographical space cloud services, cloud services based car networking function, constructing high performance, scalable, supporting differentiated information service system. The research results show that: cloud computing car network traffic information service collaborative system can greatly improve the level of intelligent, personalized information service based on traffic, the user required service supply pertinence increased significantly； system can provide traffic information service more safe and reliable for vehicle network users of the service coordination, which helps to guarantee Intelligent Transportation and efficient operation.

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Huang, Xuepeng. "Ant Colony Optimization Algorithm Model Based on the Continuous Space." International Journal of Online Engineering (iJOE) 12, no. 12 (December 25, 2016): 27. http://dx.doi.org/10.3991/ijoe.v12i12.6451.

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Ant colony algorithm is a heuristic algorithm which is fit for solving complicated combination optimization.It showed great advantage on solving combinatorial optimization problem since it was proposed. The algorithm uses distributed parallel computing and positive feedback mechanism, and is easy to combine with other algorithms.This ant colony algorithm has already been widespread used in the field of discrete space optimization, however, is has been rarely used for continuous space optimization question.On the basis of basic ant colony algorithm principles and mathematical model, this paper proposes an ant colony algorithm for solving continuous space optimization question.Comparing with the ant colony algorithm, the new algorithm improves the algorithm in aspects of ant colony initialization, information density function, distribution algorithms, direction of ant colonymotion, and so on. The new algorithm uses multiple optimization strategy, such as polynomial time reduction and branching factor, and improves the ant colony algorithm effectively.

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Jagadeesan, J., Arpan Sarkar, Sanchay Mishra, and Sarthak Pandita. "Smart Parking System Using Batch Algorithms Cloud Computing and Internet of Things." Journal of Computational and Theoretical Nanoscience 17, no. 4 (April 1, 2020): 1646–52. http://dx.doi.org/10.1166/jctn.2020.8417.

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Innovative smart parking system works on sensor based IOT technology and cloud computing data collection to direct the driver to the particular parking spot. This paper implements an agile algorithm that improves the efficiency of the present cloud-based parking system and builds a network architecture based on the IOT technology. This paper introduces a system that helps users find a parking space at the least cost based on new efficiency constraints to calculate the user parking cost by considering the dimensions and the total number of free spaces in each car park. This cost will be used to offer a solution of finding an available parking space upon a request by the user and a solution of suggesting a new car park if the current car park is full. The simulation results convey that the algorithm helps improve the stability of successful parking and minimizes the user waiting time at the same time avoiding congestion. We also successfully implemented the algorithm virtually. Existing systems implement first come first serve algorithms to allocate parking space to cars which arrive to parking space, hence wasting a lot of space at the time costing efficiency to the parking lot. The proposed algorithm first sorts the cars based on their size, hence efficiently using the space available and balancing load at the parking side. Also separating the parking space for both large and small cars can help improve the parking congestion and price per space utility factor. The algorithm uses batch algorithms knowingly used in operating systems to arrange tasks and processes in an effective manner. It divides the cars into small and large categories alike the processes in operating systems, which helps to deal with the cars better. The whole system is also backed by low power IOT hardware like Arduino® Uno, NodeMCU® ESP8266, ZigBee networks and cloud computing solutions like Google© Firebase® and Thing Speak®.

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Heydari, B., and M. Aajami. "Providing a New Model for Discovering Cloud Services Based on Ontology." Engineering, Technology & Applied Science Research 7, no. 6 (December 18, 2017): 2268–72. http://dx.doi.org/10.48084/etasr.1577.

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Due to its efficient, flexible, and dynamic substructure in information technology and service quality parameters estimation, cloud computing has become one of the most important issues in computer world. Discovering cloud services has been posed as a fundamental issue in reaching out high efficiency. In order to do one’s own operations in cloud space, any user needs to request several various services either simultaneously or according to a working routine. These services can be presented by different cloud producers or different decision-making policies. Therefore, service management is one of the important and challenging issues in cloud computing. With the advent of semantic web and practical services accordingly in cloud computing space, access to different kinds of applications has become possible. Ontology is the core of semantic web and can be used to ease the process of discovering services. A new model based on ontology has been proposed in this paper. The results indicate that the proposed model has explored cloud services based on user search results in lesser time compared to other models.

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Yun, Deok-Won, and Won-Cheol Lee. "Intelligent Dynamic Spectrum Resource Management Based on Sensing Data in Space-Time and Frequency Domain." Sensors 21, no. 16 (August 4, 2021): 5261. http://dx.doi.org/10.3390/s21165261.

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Edge computing offers a promising paradigm for implementing the industrial Internet of things (IIoT) by offloading intensive computing tasks from resource constrained machine type devices to powerful edge servers. However, efficient spectrum resource management is required to meet the quality of service requirements of various applications, taking into account the limited spectrum resources, batteries, and the characteristics of available spectrum fluctuations. Therefore, this study proposes intelligent dynamic spectrum resource management consisting of learning engines that select optimal backup channels based on history data, reasoning engines that infer idle channels based on backup channel lists, and transmission parameter optimization engines based genetic algorithm using interference analysis in time, space and frequency domains. The performance of the proposed intelligent dynamic spectrum resource management was evaluated in terms of the spectrum efficiency, number of spectrum handoff, latency, energy consumption, and link maintenance probability according to the backup channel selection technique and the number of IoT devices and the use of transmission parameters optimized for each traffic environment. The results demonstrate that the proposed method is superior to existing spectrum resource management functions.

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VALENCIANO, J., and M. A. J. CHAPLAIN. "COMPUTING HIGHLY ACCURATE SOLUTIONS OF A TUMOUR ANGIOGENESIS MODEL." Mathematical Models and Methods in Applied Sciences 13, no. 05 (May 2003): 747–66. http://dx.doi.org/10.1142/s0218202503002702.

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In this paper we describe and implement a numerical method which provides highly accurate solutions of a generic two-dimensional model for the formation of capillary networks as a partial process in tumour angiogenesis. The model includes effects due to diffusion, chemotaxis, haptotaxis and cell proliferation. The governing partial differential equation is a diffusion-advection-reaction equation of parabolic type. In order to achieve high accuracy in space, we use a semi-discretisation based on the spectral element method. The resulting system of stiff ordinary differential equations is advanced forward in time using one-step explicit higher order time integrators based on Taylor series expansions. The high accuracy in space is monitored by a residual based a posteriori error indicator while the high accuracy in time is guaranteed by the local and global truncation errors of the higher order Taylor series method.

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Taghipour, Hassan, Mahdi Rezaei, and Heydar Ali Esmaili. "Solving the 0/1 Knapsack Problem by a Biomolecular DNA Computer." Advances in Bioinformatics 2013 (February 18, 2013): 1–6. http://dx.doi.org/10.1155/2013/341419.

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Solving some mathematical problems such as NP-complete problems by conventional silicon-based computers is problematic and takes so long time. DNA computing is an alternative method of computing which uses DNA molecules for computing purposes. DNA computers have massive degrees of parallel processing capability. The massive parallel processing characteristic of DNA computers is of particular interest in solving NP-complete and hard combinatorial problems. NP-complete problems such as knapsack problem and other hard combinatorial problems can be easily solved by DNA computers in a very short period of time comparing to conventional silicon-based computers. Sticker-based DNA computing is one of the methods of DNA computing. In this paper, the sticker based DNA computing was used for solving the 0/1 knapsack problem. At first, a biomolecular solution space was constructed by using appropriate DNA memory complexes. Then, by the application of a sticker-based parallel algorithm using biological operations, knapsack problem was resolved in polynomial time.

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Gui, Z., Y. Wang, Z. Cui, D. Peng, J. Wu, Z. Ma, S. Luo, and H. Wu. "DEVELOPING APACHE SPARK BASED RIPLEY’S K FUNCTIONS FOR ACCELERATING SPATIOTEMPORAL POINT PATTERN ANALYSIS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2020 (August 25, 2020): 545–52. http://dx.doi.org/10.5194/isprs-archives-xliii-b4-2020-545-2020.

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Abstract. Ripley’s K functions are powerful tools for studying the spatial arrangement or spatiotemporal distribution characteristics of geographic phenomena and events in spatial analysis and has been used in many fields. However, the K functions are compute-intensive for point-wise distance comparisons, edge correction and simulations for significance test. Although parallel computing technologies have been adopted to accelerate K functions, previous works haven’t extended the optimization from space to space-time dimension. This study presents an acceleration method for K functions upon state-of-the-art distributed computing framework Apache Spark, and four optimization strategies are leveraged to simplify calculation procedures and accelerate distributed computing respectively, including 1) spatiotemporal indexing based on R-tree with Sort-Tile-Recursive (STR) algorithm for reducing distance comparison when retrieving potential spatiotemporally neighbouring points; 2) Hash-Table-based caching for spatiotemporal edge correction weights reuse and reducing repetitive computation; 3) Spatiotemporal partitioning using KDB-tree as well as cylinder intersection redundancy strategy for decreasing ghost buffer redundancy in partitions and supporting near-balanced distributed processing; 4) Customized serialization of spatiotemporal objects and indexes for lowering the overhead of data transmission. Experiments verify the effectiveness and time efficiency of the proposed optimization strategies, and also evaluate the overall performance and scalability. Based on the proposed methods, a web-based visual analytics framework has been developed and publicly shared through GitHub, and four types of the distributed K functions are implemented, including space, space-time, local and cross K functions, which demonstrates its value on promoting geographical and socioeconomic studies.

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