Reasoning Method Based on Intervals with Symmetric Truncated Normal Density

Error parameters are inevitable in systems. In formal verification, previous reasoning methods seldom considered the probability information of errors. In this article, errors are described as symmetric truncated normal intervals consisting of the intervals and symmetric truncated normal probability density. Furthermore, we also rigorously prove lemmas and a theorem to partially simplify the calculation process of truncated normal intervals and independently verify the formulas of variance and expectation of symmetric truncated interval given by some scholars. The mathematical derivation process or verification codes are provided for most of the key formulas in this article. Hence, we propose a new reasoning method that combines the probability information of errors with the previous statistical reasoning methods. Finally, an engineering example of the reasoning verification of train acceleration is provided. After simulating the large-scale cases, it is shown that the simulation results are consistent with the theoretical reasoning results. This method needs more calculation, while it is more effective in detecting non-error’s fault factors than other error reasoning methods.

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SOCIAL PROJECT AS A PLATFORM FOR THE IMPLEMENTATION OF PROFESSIONAL SKILLS OF FUTURE INFORMATICS TEACHERS

Informatics and Education ◽

10.32517/0234-0453-2019-34-5-16-22 ◽

2019 ◽

pp. 16-22

Author(s):

E. V. Klimenko ◽

N. S. Buslova

Keyword(s):

Large Scale ◽

Modern Society ◽

Professional Competencies ◽

Future Teachers ◽

Professional Skills ◽

Knowledge And Skills ◽

Theoretical Reasoning ◽

Social Project ◽

The University

The article is devoted to the consideration of ways to solve one of the actual problems in theory and methodology of training and upbringing — the problem of developing professional skills of future informatics teacher. As a way to adapt students to the profession, the possibility of their involvement in social designing was chosen. Participation in social projects contributes to the approbation and introduction of new forms and methods in teaching informatics. Expanding the experience of future teachers in carrying out large-scale events contributes to the formation of a socially adapted personality competitive in modern society. The potential of a social project in consolidating the knowledge and skills obtained during the theoretical training at the university is indicated. In the article, theoretical reasoning is accompanied by examples of real social projects and activities aimed at the formation of professional competencies of future informatics teachers.

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Design and Evaluation of Large-Scale IoT-Enabled Healthcare Architecture

Applied Sciences ◽

10.3390/app11083623 ◽

2021 ◽

Vol 11 (8) ◽

pp. 3623

Author(s):

Omar Said ◽

Amr Tolba

Keyword(s):

Packet Loss ◽

Large Scale ◽

Performance Metrics ◽

Medical System ◽

Healthcare Data ◽

High Altitude Platforms ◽

Wide Range ◽

Simulation Results ◽

Healthcare Architecture ◽

The Internet Of Things

Employment of the Internet of Things (IoT) technology in the healthcare field can contribute to recruiting heterogeneous medical devices and creating smart cooperation between them. This cooperation leads to an increase in the efficiency of the entire medical system, thus accelerating the diagnosis and curing of patients, in general, and rescuing critical cases in particular. In this paper, a large-scale IoT-enabled healthcare architecture is proposed. To achieve a wide range of communication between healthcare devices, not only are Internet coverage tools utilized but also satellites and high-altitude platforms (HAPs). In addition, the clustering idea is applied in the proposed architecture to facilitate its management. Moreover, healthcare data are prioritized into several levels of importance. Finally, NS3 is used to measure the performance of the proposed IoT-enabled healthcare architecture. The performance metrics are delay, energy consumption, packet loss, coverage tool usage, throughput, percentage of served users, and percentage of each exchanged data type. The simulation results demonstrate that the proposed IoT-enabled healthcare architecture outperforms the traditional healthcare architecture.

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The Flexible Operation of Coal Power and Its Renewable Integration Potential in China

Sustainability ◽

10.3390/su11164424 ◽

2019 ◽

Vol 11 (16) ◽

pp. 4424 ◽

Cited By ~ 2

Author(s):

Chunning Na ◽

Huan Pan ◽

Yuhong Zhu ◽

Jiahai Yuan ◽

Lixia Ding ◽

...

Keyword(s):

Renewable Energy ◽

Power Systems ◽

Power System ◽

Large Scale ◽

Renewable Integration ◽

Flexible Resources ◽

Feasible Option ◽

Coal Power ◽

Simulation Results ◽

Flexible Operation

At present time, China’s power systems face significant challenges in integrating large-scale renewable energy and reducing the curtailed renewable energy. In order to avoid the curtailment of renewable energy, the power systems need significant flexibility requirements in China. In regions where coal is still heavily relied upon for generating electricity, the flexible operations of coal power units will be the most feasible option to face these challenges. The study first focused on the reasons why the flexible operation of existing coal power units would potentially promote the integration of renewable energy in China and then reviewed the impacts on the performance levels of the units. A simple flexibility operation model was constructed to estimate the integration potential with the existing coal power units under several different scenarios. This study’s simulation results revealed that the existing retrofitted coal power units could provide flexibility in the promotion of the integration of renewable energy in a certain extent. However, the integration potential increment of 20% of the rated power for the coal power units was found to be lower than that of 30% of the rated power. Therefore, by considering the performance impacts of the coal power units with low performances in load operations, it was considered to not be economical for those units to operate at lower than 30% of the rated power. It was believed that once the capacity share of the renewable energy had achieved a continuously growing trend, the existing coal power units would fail to meet the flexibility requirements. Therefore, it was recommended in this study that other flexible resources should be deployed in the power systems for the purpose of reducing the curtailment of renewable energy. Furthermore, based on this study’s obtained evidence, in order to realize a power system with high proportions of renewable energy, China should strive to establish a power system with adequate flexible resources in the future.

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Control method for the stable operation of distributed inverters following the introduction of large-scale renewable energy to a remote island grid

Clean Energy ◽

10.1093/ce/zkab004 ◽

2021 ◽

Vol 5 (2) ◽

pp. 196-207

Author(s):

Shoichi Sato ◽

Yasuhiro Noro

Keyword(s):

Renewable Energy ◽

Large Scale ◽

Control Method ◽

Synchronous Generator ◽

Stable Operation ◽

Battery Energy Storage Systems ◽

Simulation Results ◽

Battery Energy ◽

Systems Simulation ◽

Different Characteristics

Abstract The introduction of large-scale renewable energy requires a control system that can operate multiple distributed inverters in a stable way. This study proposes an inverter control method that uses information corresponding to the inertia of the synchronous generator to coordinate the operation of battery energy storage systems. Simulation results for a system with multiple inverters applying the control method are presented. Various faults such as line-to-line short circuits and three-phase line-to-ground faults were simulated. Two fault points with different characteristics were compared. The voltage, frequency and active power quickly returned to their steady-state values after the fault was eliminated. From the obtained simulation results, it was verified that our control method can be operated stably against various faults.

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Large-scale Structure and Turbulence Transport in the Young Solar Wind – Comparison of Parker Solar Probe Observations with a Global 3D Reynolds-averaged MHD Model

10.5194/egusphere-egu21-12726 ◽

2021 ◽

Author(s):

Rohit Chhiber ◽

Arcadi Usmanov ◽

William Matthaeus ◽

Melvyn Goldstein ◽

Riddhi Bandyopadhyay

Keyword(s):

Solar Wind ◽

Large Scale ◽

Transport Equations ◽

Turbulence Energy ◽

Reynolds Stresses ◽

Mean Flow ◽

Coulomb Collisions ◽

Flow Equations ◽

Simulation Results ◽

Turbulence Transport

<div>Simulation results from a global magnetohydrodynamic model of the solar corona and the solar wind are compared with Parker Solar Probe's (PSP) observations during its first several orbits. The fully three-dimensional model (Usmanov et al., 2018, ApJ, 865, 25) is based on Reynolds-averaged mean-flow equations coupled with turbulence transport equations. The model accounts for effects of electron heat conduction, Coulomb collisions, Reynolds stresses, and heating of protons and electrons via nonlinear turbulent cascade. Turbulence transport equations for turbulence energy, cross helicity, and correlation length are solved concurrently with the mean-flow equations. We specify boundary conditions at the coronal base using solar synoptic magnetograms and calculate plasma, magnetic field, and turbulence parameters along the PSP trajectory. We also accumulate data from all orbits considered, to obtain the trends observed as a function of heliocentric distance. Comparison of simulation results with PSP data show general agreement. Finally, we generate synthetic fluctuations constrained by the local rms turbulence amplitude given by the model, and compare properties of this synthetic turbulence with PSP observations.</div>

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Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

10.5194/hess-2016-620 ◽

2017 ◽

Cited By ~ 1

Author(s):

Cherry May R. Mateo ◽

Dai Yamazaki ◽

Hyungjun Kim ◽

Adisorn Champathong ◽

Jai Vaze ◽

...

Keyword(s):

Spatial Resolution ◽

Large Scale ◽

Flood Hazard ◽

Regional Scale ◽

Global Scale ◽

Test Case ◽

Efficiency Coefficient ◽

Computational Power ◽

Extreme Flood ◽

Simulation Results

Abstract. Global-scale River Models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representation of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash–Sutcliffe Efficiency coefficient decreased by more than 35 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions in finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings are universal and can be extended to global-scale simulations. These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

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Improving COVID-19 Testing Efficiency using Guided Agglomerative Sampling

10.1101/2020.04.13.039792 ◽

2020 ◽

Author(s):

Fayyaz Minhas ◽

Dimitris Grammatopoulos ◽

Lawrence Young ◽

Imran Amin ◽

David Snead ◽

...

Keyword(s):

Large Scale ◽

Resource Constraints ◽

Large Population ◽

Sampling Strategy ◽

Population Surveillance ◽

Large Scale Testing ◽

Scale Population ◽

Simulation Results ◽

The Given ◽

Test Outcomes

AbstractOne of the challenges in the current COVID-19 crisis is the time and cost of performing tests especially for large-scale population surveillance. Since, the probability of testing positive in large population studies is expected to be small (<15%), therefore, most of the test outcomes will be negative. Here, we propose the use of agglomerative sampling which can prune out multiple negative cases in a single test by intelligently combining samples from different individuals. The proposed scheme builds on the assumption that samples from the population may not be independent of each other. Our simulation results show that the proposed sampling strategy can significantly increase testing capacity under resource constraints: on average, a saving of ~40% tests can be expected assuming a positive test probability of 10% across the given samples. The proposed scheme can also be used in conjunction with heuristic or Machine Learning guided clustering for improving the efficiency of large-scale testing further. The code for generating the simulation results for this work is available here: https://github.com/foxtrotmike/AS.

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Traffic Fuzzy Controller's Improvement Based on Self-Adaptive Optimal Algorithm

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.562-564.1414 ◽

2012 ◽

Vol 562-564 ◽

pp. 1414-1417

Author(s):

Zhi Yi Xu ◽

Da Lu Guan ◽

Ai Long Fan

Keyword(s):

Mathematical Model ◽

Large Scale ◽

Fuzzy Controller ◽

Optimal Algorithm ◽

Signal Control ◽

Traffic Signal Control ◽

Time Varying ◽

Large Scale Systems ◽

Simulation Results ◽

Self Adaptive

The transport system is a nonlinear, time-varying, lagging large-scale systems. Fuzzy control does not need to build a precise mathematical model, can be easily integrated people's thinking and experience, and is suitable for applications in the traffic signal control system. Here,a self-adaptive optimal algorithm was used to improve the traditional fuzzy controller. Simulation results show that the improved system has higher availability.

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Reply to “Comments on ‘Incorporating the Effects of Moisture into a Dynamical Parameter: Moist Vorticity and Moist Divergence’”

Weather and Forecasting ◽

10.1175/waf-d-16-0111.1 ◽

2016 ◽

Vol 31 (4) ◽

pp. 1397-1405

Author(s):

Weihong Qian ◽

Ning Jiang ◽

Jun Du

Keyword(s):

Large Scale ◽

Value Added ◽

Heavy Rain ◽

Heavy Precipitation ◽

Small Scale ◽

Precipitation Efficiency ◽

Long Duration ◽

Advection Term ◽

Rain Events ◽

Mathematical Derivation

Abstract Mathematical derivation, meteorological justification, and comparison to model direct precipitation forecasts are the three main concerns recently raised by Schultz and Spengler about moist divergence (MD) and moist vorticity (MV), which were introduced in earlier work by Qian et al. That previous work demonstrated that MD (MV) can in principle be derived mathematically with a value-added empirical modification. MD (MV) has a solid meteorological basis. It combines ascent motion and high moisture: the two elements necessary for rainfall. However, precipitation efficiency is not considered in MD (MV). Given the omission of an advection term in the mathematical derivation and the lack of precipitation efficiency, MD (MV) might be suitable mainly for heavy rain events with large areal coverage and long duration caused by large-scale quasi-stationary weather systems, but not for local intense heavy rain events caused by small-scale convection. In addition, MD (MV) is not capable of describing precipitation intensity. MD (MV) worked reasonably well in predicting heavy rain locations from short to medium ranges as compared with the ECMWF model precipitation forecasts. MD (MV) was generally worse than (though sometimes similar to) the model heavy rain forecast at shorter ranges (about a week) but became comparable or even better at longer ranges (around 10 days). It should be reiterated that MD (MV) is not intended to be a primary tool for predicting heavy rain areas, especially in the short range, but is a useful parameter for calibrating model heavy precipitation forecasts, as stated in the original paper.

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Thermal Transport in Nanocrystalline Materials

Heat Transfer: Volume 1 ◽

10.1115/ht2005-72776 ◽

2005 ◽

Author(s):

Zhanrong Zhong ◽

Xinwei Wang

Keyword(s):

Thermal Conductivity ◽

Specific Heat ◽

Thermal Transport ◽

Nanocrystalline Materials ◽

Large Scale ◽

Md Simulation ◽

Fundamental Physics ◽

Grain Sizes ◽

Simulation Results ◽

Thermal Phenomena

In this work, thermal transport in nanocrystalline materials is studied using large-scale equilibrium molecular dynamics (MD) simulation. Nanocrystalline materials with different grain sizes are studied to explore how and to what extent the size of nanograins affects the thermal conductivity and specific heat. Substantial thermal conductivity reduction is observed and the reduction is stronger for nanocrystalline materials with smaller grains. On the other hand, the specific heat of nanocrystalline materials shows little change with the grain size. The simulation results are compared with the thermal transport in individual nanograins based on MD simulation. Further discussions are provided to explain the fundamental physics behind the observed thermal phenomena in this work.

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