scholarly journals A Space-Interconnection Algorithm for Satellite Constellation Based on Spatial Grid Model

2020 ◽  
Vol 12 (13) ◽  
pp. 2131
Author(s):  
Shuang Li ◽  
Kaihua Hou ◽  
Chengqi Cheng ◽  
Shizhong Li ◽  
Bo Chen
Keyword(s):  
Computational Efficiency ◽  
Large Scale ◽  
Rapid Development ◽  
Satellite Constellations ◽  
Integrated Networks ◽  
Grid Model ◽  
Emergency Rescue ◽  
Efficient Calculation ◽  
Spatial Grid ◽  
Increasing Demand

With the rapid development of large-scale satellite constellations and the increasing demand for rapid communication and emergency rescue using global satellite-based Internet, there have been new requirements for efficient algorithms for inter-communication between satellites. As the constellations of low-orbit satellites become larger, the complexities of real-time inter-satellite calculation and path planning are becoming more complicated and are increasing geometrically. To address the bottlenecks in large-scale node space computing, we introduced a global space grid. Based on this grid, an efficient calculation method of spatial inter-connection between satellite constellations is proposed, according to the concept of “storage for computing” and the high computational efficiency of the spatial grid model. This strategy includes the following parts: (1) the introduction of the GeoSOT-3D global grid model into aerospace and the construction of the aerospace grid indexing BigTable; (2) a set of algorithms for satellite visibility analysis according to the visible grid look-up table and the secondary grid index; and (3) planning inter-satellite routing by querying the grid’s inherent visibility. The idea at the basis of this method is to employ the “space for time” concept to convert the high-dimensional floating operations into one-dimensional matching operations by querying the inherent “visible” attribute of the grid. In our study, we simulated thousands of satellites, discretized their trajectories into grids, and pre-calculated the visibility between grid cells to plan the routing path for the ground data transmission. The theoretical analysis and experimental verification show that the algorithm is feasible and efficient, and it can significantly improve the computational efficiency of inter-satellite connection. We hope that the method can be used in emergency communications, disaster warning, and maritime rescue, and can contribute to the next generation of satellite internet and “satellite-ground” integrated networks.

scholarly journals Possibilities of Biogas in Urban Context

2020 ◽  
Vol 15 (3) ◽  
pp. 191-199
Author(s):  
Srijana Koirala
Keyword(s):  
Energy Demand ◽  
Alternative Energy ◽  
Large Scale ◽  
Solid Waste Management ◽  
Positive Impact ◽  
Rapid Development ◽  
Developed Countries ◽  
Urban Context ◽  
Energy Demands ◽  
Increasing Demand

Increasing population and rapid development in the planet earth have resulted in increasing demand of energy sources. Developed countries have adopted renewable sources in their policy for a sustainable future but, developing countries like Nepal are still lagging behind. Petroleum gas is used by all the city dwellers which is imported from neighboring countries and is not sustainable for a long term. Rapid urban growth has brought solid waste management and energy demand as a great challenge. Production of energy through biogas can help in management of bio-degradable waste as well as fulfill energy demands. This paper highlights study of large-scale biogas plant in and outside Nepal and explains how they have helped in managing waste, fulfilling energy demands and made positive impact in the community. This paper also suggests on possibilities of biogas as an alternative energy in developing scenario of Nepal.

scholarly journals Large-scale traffic flow simulation based on intelligent PSO

2022 ◽  
Vol 355 ◽  
pp. 02010
Author(s):  
Zeyu Liu ◽  
Gongping Yang
Keyword(s):  
Traffic Flow ◽  
Waiting Time ◽  
Large Scale ◽  
Road Traffic ◽  
Rapid Development ◽  
Flow Simulation ◽  
Urban Traffic ◽  
The Real ◽  
Urban Road ◽  
Grid Model

With the rapid development of urban traffic, a large number of vehicles in cities not only bring convenience to people, but also bring a series of traffic problems, including traffic congestion and high traffic accident rates. Driving speed and waiting time of vehicles are two important factors of traffic problems. To simulate the real urban road traffic flow, a one-dimensional traffic flow grid model was proposed, which considered the nearest and next neighbour car at the same time, and connected the front and rear neighbour cars to optimize the traffic flow. The experiment results showed that our traffic flow grid model can simulate the real urban road traffic flow. In addition, we tried to optimize the urban traffic network model and improved the traffic speed of vehicles and reduced the waiting time.

scholarly journals High-Rate Transition Metal-based Cathode Materials for Battery-Supercapacitor Hybrid Devices

2021 ◽  
Author(s):  
Cong Wang ◽  
Zehao Song ◽  
Pei Shi ◽  
Lin Lv ◽  
Houzhao Wan ◽  
...  
Keyword(s):  
Large Scale ◽  
Rapid Development ◽  
Electronic Devices ◽  
High Rate ◽  
Specific Power ◽  
Energy Storage Devices ◽  
Storage Devices ◽  
Electrochemical Devices ◽  
Hybrid Devices ◽  
Scale Grid

With the rapid development of portable electronic devices, electric vehicles and large-scale grid energy storage devices, it needs to reinforce specific energy and specific power of related electrochemical devices meeting...

scholarly journals High-Throughput Phenotyping Methods for Breeding Drought-Tolerant Crops

2021 ◽  
Vol 22 (15) ◽  
pp. 8266
Author(s):  
Minsu Kim ◽  
Chaewon Lee ◽  
Subin Hong ◽  
Song Lim Kim ◽  
Jeong-Ho Baek ◽  
...  
Keyword(s):  
Drought Stress ◽  
High Throughput ◽  
Large Scale ◽  
Crop Yields ◽  
Plant Traits ◽  
Rapid Development ◽  
Plant Responses ◽  
Phenotypic Data ◽  
Agricultural Technologies ◽  
High Throughput Phenotyping

Drought is a main factor limiting crop yields. Modern agricultural technologies such as irrigation systems, ground mulching, and rainwater storage can prevent drought, but these are only temporary solutions. Understanding the physiological, biochemical, and molecular reactions of plants to drought stress is therefore urgent. The recent rapid development of genomics tools has led to an increasing interest in phenomics, i.e., the study of phenotypic plant traits. Among phenomic strategies, high-throughput phenotyping (HTP) is attracting increasing attention as a way to address the bottlenecks of genomic and phenomic studies. HTP provides researchers a non-destructive and non-invasive method yet accurate in analyzing large-scale phenotypic data. This review describes plant responses to drought stress and introduces HTP methods that can detect changes in plant phenotypes in response to drought.

Strategies to manage stream flow to benefit people and nature: a non-government conservation organisation's perspective

2004 ◽  
Vol 49 (7) ◽  
pp. 89-95
Author(s):  
J. Pittock ◽  
R. Holland
Keyword(s):  
Stream Flow ◽  
Large Scale ◽  
River Basins ◽  
River Basin Management ◽  
Freshwater Biodiversity ◽  
Flow Management ◽  
Stream Flows ◽  
Freshwater Management ◽  
Increasing Demand ◽  
The Impact

More than for any other biome, freshwater biodiversity is increasingly imperiled, particularly due to poor stream flow management and increasing demand for water diversions. The adoption by the world's governments of targets to extend water services to the poor and at the same time to conserve biodiversity increase the need to better direct investments in freshwater management. In this paper WWF draws on examples from its work to identify areas where investment can be focused to assure efficient water use and improve stream flow management, namely:• Prioritize and target those river basins and sub-catchments that are most critical for conservation of freshwater biodiversity to maintain stream flows;• Link strategic field, policy and market interventions at different scales in river basins to maximize the impact of interventions;• Implement the World Commission on Dams guidelines to minimize investment in large scale and costly infrastructure projects;• Apply market mechanisms and incentives for more sustainable production of the world's most water consuming crops;• Enhance statutory river basin management organizations to draw on their regulatory and financial powers;• Implement international agreements, such as the Convention on Wetlands;• Integrate environment and development policies.

scholarly journals Renormalization group theory of molecular dynamics

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Daiji Ichishima ◽  
Yuya Matsumura
Keyword(s):  
Molecular Dynamics ◽  
Renormalization Group ◽  
Critical Exponent ◽  
Computational Efficiency ◽  
Large Scale ◽  
Dissipative Particle Dynamics ◽  
Computational Cost ◽  
Coarse Graining ◽  
Spatial Dimension ◽  
Deborah Number

AbstractLarge scale computation by molecular dynamics (MD) method is often challenging or even impractical due to its computational cost, in spite of its wide applications in a variety of fields. Although the recent advancement in parallel computing and introduction of coarse-graining methods have enabled large scale calculations, macroscopic analyses are still not realizable. Here, we present renormalized molecular dynamics (RMD), a renormalization group of MD in thermal equilibrium derived by using the Migdal–Kadanoff approximation. The RMD method improves the computational efficiency drastically while retaining the advantage of MD. The computational efficiency is improved by a factor of $$2^{n(D+1)}$$ 2 n ( D + 1 ) over conventional MD where D is the spatial dimension and n is the number of applied renormalization transforms. We verify RMD by conducting two simulations; melting of an aluminum slab and collision of aluminum spheres. Both problems show that the expectation values of physical quantities are in good agreement after the renormalization, whereas the consumption time is reduced as expected. To observe behavior of RMD near the critical point, the critical exponent of the Lennard-Jones potential is extracted by calculating specific heat on the mesoscale. The critical exponent is obtained as $$\nu =0.63\pm 0.01$$ ν = 0.63 ± 0.01 . In addition, the renormalization group of dissipative particle dynamics (DPD) is derived. Renormalized DPD is equivalent to RMD in isothermal systems under the condition such that Deborah number $$De\ll 1$$ D e ≪ 1 .

scholarly journals Cloud-based intelligent self-diagnosis and department recommendation service using Chinese medical BERT

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Junshu Wang ◽  
Guoming Zhang ◽  
Wei Wang ◽  
Ka Zhang ◽  
Yehua Sheng
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Medical Service ◽  
Rapid Development ◽  
Medical Knowledge ◽  
Language Models ◽  
Computing Environment ◽  
Computing Power ◽  
Cloud Computing Environment ◽  
Proposed Model

AbstractWith the rapid development of hospital informatization and Internet medical service in recent years, most hospitals have launched online hospital appointment registration systems to remove patient queues and improve the efficiency of medical services. However, most of the patients lack professional medical knowledge and have no idea of how to choose department when registering. To instruct the patients to seek medical care and register effectively, we proposed CIDRS, an intelligent self-diagnosis and department recommendation framework based on Chinese medical Bidirectional Encoder Representations from Transformers (BERT) in the cloud computing environment. We also established a Chinese BERT model (CHMBERT) trained on a large-scale Chinese medical text corpus. This model was used to optimize self-diagnosis and department recommendation tasks. To solve the limited computing power of terminals, we deployed the proposed framework in a cloud computing environment based on container and micro-service technologies. Real-world medical datasets from hospitals were used in the experiments, and results showed that the proposed model was superior to the traditional deep learning models and other pre-trained language models in terms of performance.

scholarly journals The Development of Disaster Nursing in China-from the Spirit of Nightingale to COVID-19

2020 ◽  
pp. 1-15
Author(s):  
DI Zhang ◽  
Liyan Zhang ◽  
Aihua Gong
Keyword(s):  
Emergency Response ◽  
Nursing Staff ◽  
Rapid Development ◽  
Theoretical Development ◽  
Emergency Rescue ◽  
Chinese Model ◽  
Practice Models ◽  
The World ◽  
National Disaster

Abstract As an emerging discipline, disaster nursing is very important in disaster emergency management, but there are few mature practice models and theoretical discussions. In particular, the contribution of nursing staff in disaster emergency has not yet received widespread attention and recognition. After more than ten years of rapid development, China’s disaster nursing has gradually formed a Chinese model and Chinese experience. During the global fight against COVID-19, this article takes the nursing work in disaster emergency rescue as the perspective and briefly describes the development process of disaster nursing in China to introduce the practice and theoretical development of disaster nursing in China to nursing workers around the world. By analyzing the role of Chinese nurses in national disaster emergency response, it provides a reference for global disaster nursing talent capacity building. By sharing the Nightingale spirit of Chinese nurses in disaster emergency, we will show people all over the world the professional value of disaster nursing practitioners and pay tribute to the nursing staff engaged in disaster emergency work.

scholarly journals Large-Scale Linear RankSVM

2014 ◽  
Vol 26 (4) ◽  
pp. 781-817 ◽  
Author(s):  
Ching-Pei Lee ◽  
Chih-Jen Lin
Keyword(s):  
Decision Trees ◽  
Computational Efficiency ◽  
Efficient Algorithm ◽  
Large Scale ◽  
Learning To Rank ◽  
Gradient Boosting ◽  
Baseline Model ◽  
Nonlinear Methods ◽  
Advantages And Disadvantages ◽  
Linear Ranksvm

Linear rankSVM is one of the widely used methods for learning to rank. Although its performance may be inferior to nonlinear methods such as kernel rankSVM and gradient boosting decision trees, linear rankSVM is useful to quickly produce a baseline model. Furthermore, following its recent development for classification, linear rankSVM may give competitive performance for large and sparse data. A great deal of works have studied linear rankSVM. The focus is on the computational efficiency when the number of preference pairs is large. In this letter, we systematically study existing works, discuss their advantages and disadvantages, and propose an efficient algorithm. We discuss different implementation issues and extensions with detailed experiments. Finally, we develop a robust linear rankSVM tool for public use.

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