scholarly journals An Ml-Based Memory Leak Detection Scheme for Network Devices

2021 ◽  
Author(s):  
Minghui Wang ◽  
Jiangxuan Xie ◽  
Xinan Yang ◽  
Xiangqiao Ao
Keyword(s):  
Large Scale ◽  
Leak Detection ◽  
Normal Operation ◽  
Computationally Efficient ◽  
Memory Leak ◽  
Detection Scheme ◽  
Software Failure ◽  
The Stability ◽  
Common Memory ◽  
The Impact

The network is very important to the normal operation of all aspects of society and economy, and the memory leak of network device is a software failure that seriously damages the stability of the system. Some common memory checking tools are not suitable for network devices that are running online, so the operation staff can only constantly monitor the memory usage and infer from experience, which has been proved to be inefficient and unreliable. In this paper we proposed a novel memory leak detection method for network devices based on Machine learning. It first eliminates the impact of large-scale resource table entries on the memory utilization. Then, by analyzing its monotonicity and computing the correlation coefficient with the memory leak sequence sets pre constructed by simulation, the memory leak fault can be found in time. The simulation experiments show that the scheme is computationally efficient and the precision rate is close to 100%, it works well in the actual network environment, and has excellent performance.

scholarly journals Australian agricultural scale and corporate agroholdings: environmental and climatic impacts

2017 ◽  
Vol 20 (2) ◽  
pp. 187-190 ◽  
Author(s):  
Bradley Plunkett ◽  
Andrew Duff ◽  
Ross Kingwell ◽  
David Feldman
Keyword(s):  
Large Scale ◽  
Climatic Variability ◽  
Institutional Setting ◽  
Corporate Ownership ◽  
Family Structures ◽  
Climatic Impacts ◽  
The Stability ◽  
Average Size ◽  
The Impact ◽  
Concentrate Production

The average size of Australian farms in scale and revenue are the globe’s largest. This scale is a result, in part, of low average rural population densities; development patterns in broadacre production; low levels of effective public policy transfers; a stable and suitable institutional setting suitable for corporate and other large scale investment; and low yields. It is also a factor of the natural variability of the country’s climatic systems which have contributed to the scale of extensive northern cattle production; this variability has implications for the pattern of ownership of broadacre and extensive production. Corporate ownership, tends to concentrate production aggregations at sufficient scale to offset its additional overheads in areas of relative climatic stability and to replicate these agroholding aggregations spatially to protect the stability of revenue flows. Family structures are more dominant in areas of greater climatic variability. Of interest is the impact that any increasing climatic variability (versus rapid changes in technology) may have upon this pattern.

A Predictive Energy Landscape Model of Metamorphic Protein Conformational Specificity

2021 ◽  
Author(s):  
James O. Wrabl ◽  
Keila Voortman-Sheetz ◽  
Vincent J. Hilser
Keyword(s):  
Amino Acid ◽  
Structure Prediction ◽  
Large Scale ◽  
Energy Landscape ◽  
Thermodynamic Approach ◽  
High Identity ◽  
Denatured State ◽  
Metamorphic Protein ◽  
The Stability ◽  
The Impact

'Metamorphic' proteins challenge state-of-the-art structure prediction methods reliant on amino acid similarity. Unfortunately, this obviates a more effective thermodynamic approach necessary to properly evaluate the impact of amino acid changes on the stability of two different folds. A vital capability of such a thermodynamic approach would be the quantification of the free energy differences between 1) the energy landscape minima of each native fold, and 2) each fold and the denatured state. Here we develop an energetic framework for conformational specificity, based on an ensemble description of protein thermodynamics. This energetic framework was able to successfully recapitulate the structures of high-identity engineered sequences experimentally shown to adopt either Streptococcus protein GA or GB folds, demonstrating that this approach indeed reflected the energetic determinants of fold. Residue-level decomposition of the conformational specificity suggested several testable hypotheses, notably among them that fold-switching could be affected by local de-stabilization of the populated fold at positions sensitive to equilibrium perturbation. Since this ensemble-based compatibility framework is applicable to any structure and any sequence, it may be practically useful for the future targeted design, or large-scale proteomic detection, of novel metamorphic proteins.

scholarly journals The impact of secondary ice production on Arctic stratocumulus

2020 ◽  
Vol 20 (3) ◽  
pp. 1301-1316
Author(s):  
Georgia Sotiropoulou ◽  
Sylvia Sullivan ◽  
Julien Savre ◽  
Gary Lloyd ◽  
Thomas Lachlan-Cope ◽  
...  
Keyword(s):  
Large Scale ◽  
Cloud Condensation Nuclei ◽  
The Arctic ◽  
Computationally Efficient ◽  
Eddy Simulation ◽  
Scale Models ◽  
Break Up ◽  
Ice Production ◽  
Low Sensitivity ◽  
The Impact

Abstract. In situ measurements of Arctic clouds frequently show that ice crystal number concentrations (ICNCs) are much higher than the number of available ice-nucleating particles (INPs), suggesting that secondary ice production (SIP) may be active. Here we use a Lagrangian parcel model (LPM) and a large-eddy simulation (LES) to investigate the impact of three SIP mechanisms (rime splintering, break-up from ice–ice collisions and drop shattering) on a summer Arctic stratocumulus case observed during the Aerosol-Cloud Coupling And Climate Interactions in the Arctic (ACCACIA) campaign. Primary ice alone cannot explain the observed ICNCs, and drop shattering is ineffective in the examined conditions. Only the combination of both rime splintering (RS) and collisional break-up (BR) can explain the observed ICNCs, since both of these mechanisms are weak when activated alone. In contrast to RS, BR is currently not represented in large-scale models; however our results indicate that this may also be a critical ice-multiplication mechanism. In general, low sensitivity of the ICNCs to the assumed INP, to the cloud condensation nuclei (CCN) conditions and also to the choice of BR parameterization is found. Finally, we show that a simplified treatment of SIP, using a LPM constrained by a LES and/or observations, provides a realistic yet computationally efficient way to study SIP effects on clouds. This method can eventually serve as a way to parameterize SIP processes in large-scale models.

Method of Image Matching for Seabed Sonar Images Based on Regions of Interest

2014 ◽  
Vol 532 ◽  
pp. 126-129
Author(s):  
Zhi Gang Zhang ◽  
Hong Yu Bian ◽  
Hui Xu ◽  
Zi Qi Song
Keyword(s):  
Target Detection ◽  
Image Matching ◽  
Large Scale ◽  
Regions Of Interest ◽  
Matching Method ◽  
Aspect Angle ◽  
Sonar Images ◽  
The Stability ◽  
Imaging Sonar ◽  
The Impact

One of the most effective instruments for target detection in turbid waters is imaging sonar. However, the aspect angle of imaging sonar is usually small and that is a sacrifice for high detection precision. To make imaging sonar practical in large scale target detection with wide aspect angle, investigating image matching methods for continuous sonar frames is of great importance. A novel image matching method using local features of SIFT is described in this paper, which mainly focuses on the problem of weak echo signals and the following sonar images mismatch. The correspondence between objects and cast shadow regions is employed to extract regions of interest. Besides, status parameters of underwater vehicle are used to approximate the image transformation. Image segmentation methods are involved to decrease the size of the feature extracting regions and reduce the impact of non-target seabed areas, which improves the stability of this sonar image matching method significantly.

Evaluating the Effects of Transportation—Land-Use Policies on Housing Values and Household Welfare

1980 ◽  
Vol 12 (7) ◽  
pp. 747-764 ◽  
Author(s):  
A Anas
Keyword(s):  
Simulation Model ◽  
Discrete Choice ◽  
Transportation Planning ◽  
Large Scale ◽  
Travel Demand ◽  
Choice Theory ◽  
Property Values ◽  
Computationally Efficient ◽  
Demand Prediction ◽  
The Impact

In a previous article published in this journal (Anas, 1979a), a simulation model developed by the author was used to examine the impact of transit investment on property values in an urban transportation corridor that had a completely centralized employment distribution. The present paper examines the effect of rail-transit investment in the context of various scenarios which deal with urban employment decentralization, housing distribution, transportation pricing, and income composition. From these simulations it appears that under a variety of assumptions regarding urban change the taxation of short-run differential changes in property values caused by transit investment can raise only a small portion of the cost of typical transit investments. The distinctive feature of the simulation model is that it is consistent with the discrete-choice theory of travel demand currently used in transportation planning and travel-demand prediction. But whereas the state of the art in transportation planning ignores the simultaneity of transportation changes and price changes in the housing market, the model developed here is a first attempt to deal with these effects by incorporating discrete-choice theory into a Walrasian market-equilibration procedure. In addition to being a theoretical alternative to the classical bid-rent model, still made use of by urban economists, the new approach is computationally efficient and suitable for large-scale simulation.

scholarly journals Resilient Supply Chain Management Model

2021 ◽  
Vol 93 ◽  
pp. 03005
Author(s):  
Oleg Larin ◽  
Dmitry Tarasov ◽  
Leonid Mirotin ◽  
Vladimir Rublev ◽  
Denis Kapski
Keyword(s):  
Supply Chain ◽  
Material Flow ◽  
Operating Costs ◽  
Normal Operation ◽  
Work Processes ◽  
Response Models ◽  
The Stability ◽  
High Level ◽  
Material Flow Control ◽  
The Impact

The strategy for the development of the supply chain should ensure a high level of fault tolerance of all links when exposed to adverse factors. The article analyzes the impact on the stability of the supply chain of two types of influences: failure and disruption. The low stability of the supply chain appears in the stoppage of work in case of any disruptions and failures. With moderate stability, disruptions do not give up a significant impact on the operation of the supply chain, and failures lead to an increase in operating costs to maintain the stability of work processes. With a high level of stability, failures can cause disruptions in the operations of individual links. In case of disruptions, response models are applied based on the control of process parameters, the subsequent analysis of the causes of disruptions and the development of measures to restore the normal operation of the links in the supply chain. Effective disruption response involves the use of proactive response models. For this, it is necessary to ensure flexibility and transparency of processes in all links of the supply chain based on digital services for material flow control and mining of big data.

scholarly journals Investigating the impact of atmospheric stability on thunderstorm outflow winds and turbulence

2018 ◽  
Vol 3 (1) ◽  
pp. 203-219 ◽  
Author(s):  
Patrick Hawbecker ◽  
Sukanta Basu ◽  
Lance Manuel
Keyword(s):  
Large Scale ◽  
Atmospheric Stability ◽  
Temperature Inversion ◽  
Ring Vortex ◽  
Large Eddy Simulation Model ◽  
Eddy Simulation ◽  
Large Scale Flow ◽  
The Stability ◽  
Thunderstorm Outflow ◽  
The Impact

Abstract. Downburst events initialized at various hours during the evening transition (ET) period are simulated to determine the effects of ambient stability on the outflow of downburst winds. The simulations are performed using a pseudo-spectral large eddy simulation model at high resolution to capture both the large-scale flow and turbulence characteristics of downburst winds. First, a simulation of the ET is performed to generate realistic initial and boundary conditions for the subsequent downburst simulations. At each hour in the ET, an ensemble of downburst simulations is initialized separately from the ET simulation in which an elevated cooling source within the model domain generates negatively buoyant air to mimic downburst formation. The simulations show that while the stability regime changes, the ensemble mean of the peak wind speed remains fairly constant (between 35 and 38 m s−1) and occurs at the lowest model level for each simulation. However, there is a slight increase in intensity and decrease in the spread of the maximum outflow winds as stability increases as well as an increase in the duration over which these strongest winds persist. This appears to be due to the enhanced maintenance of the ring vortex that results from the low-level temperature inversion, increased ambient shear, and a lack of turbulence within the stable cases. Coherent turbulent kinetic energy and wavelet spectral analysis generally show increased energy in the convective cases and that energy increases across all scales as the downburst passes.

scholarly journals From giant clumps to clouds – I. The impact of gas fraction evolution on the stability of galactic discs

2021 ◽  
Vol 508 (1) ◽  
pp. 352-370
Author(s):  
Florent Renaud ◽  
Alessandro B Romeo ◽  
Oscar Agertz
Keyword(s):  
Large Scale ◽  
Molecular Gas ◽  
Stellar Component ◽  
Main Driver ◽  
Spiral Structures ◽  
The Stability ◽  
Stability Regime ◽  
The Impact ◽  
Gas Fractions ◽  
Disc Galaxies

ABSTRACT The morphology of gas-rich disc galaxies at redshift $\sim 1\!-\!3$ is dominated by a few massive clumps. The process of formation or assembly of these clumps and their relation to molecular clouds in contemporary spiral galaxies are still unknown. Using simulations of isolated disc galaxies, we study how the structure of the interstellar medium and the stability regime of the discs change when varying the gas fraction. In all galaxies, the stellar component is the main driver of instabilities. However, the molecular gas plays a non-negligible role in the interclump medium of gas-rich cases, and thus in the assembly of the massive clumps. At scales smaller than a few 100 pc, the Toomre-like disc instabilities are replaced by another regime, especially in the gas-rich galaxies. We find that galaxies at low gas fraction (10 per cent) stand apart from discs with more gas, which all share similar properties in virtually all aspects we explore. For gas fractions below $\approx 20{{\ \rm per\ cent}}$, the clump-scale regime of instabilities disappears, leaving only the large-scale disc-driven regime. Associating the change of gas fraction to the cosmic evolution of galaxies, this transition marks the end of the clumpy phase of disc galaxies, and allows for the onset of spiral structures, as commonly found in the local Universe.

scholarly journals Transmission Dynamics of Resistant Bacteria in a Predator-Prey System

2015 ◽  
Vol 2015 ◽  
pp. 1-12
Author(s):  
Xubin Gao ◽  
Qiuhui Pan ◽  
Mingfeng He
Keyword(s):  
Human Health ◽  
Large Scale ◽  
Equilibrium Points ◽  
Predation Rate ◽  
Resistant Bacteria ◽  
Mathematical Methods ◽  
Predator Prey ◽  
Prey System ◽  
The Stability ◽  
The Impact

This paper discusses the impact on human health caused by the addition of antibiotics in the feed of food animals. We use the established transmission rule of resistant bacteria and combine it with a predator-prey system to determine a differential equations model. The equations have three steady equilibrium points corresponding to three population dynamics states under the influence of resistant bacteria. In order to quantitatively analyze the stability of the equilibrium points, we focused on the basic reproduction numbers. Then, both the local and global stability of the equilibrium points were quantitatively analyzed by using essential mathematical methods. Numerical results are provided to relate our model properties to some interesting biological cases. Finally, we discuss the effect of the two main parameters of the model, the proportion of antibiotics added to feed and the predation rate, and estimate the human health impacts related to the amount of feed antibiotics used. We further propose an approach for the prevention of the large-scale spread of resistant bacteria and illustrate the necessity of controlling the amount of in-feed antibiotics used.

On Leak Detection of Pipelines Using Computational Pipeline Monitoring

2008 ◽  
Author(s):  
Kamal A. F. Moustafa ◽  
Gamal M. Nawara ◽  
Hesham Elawady ◽  
Mohsen Fouad
Keyword(s):  
Mathematical Model ◽  
Leak Detection ◽  
Normal Operation ◽  
Pipeline System ◽  
Computational Pipeline ◽  
State Variables ◽  
Monitoring Method ◽  
Detection Scheme ◽  
Pipeline Systems ◽  
Pipeline Monitoring

The unintentional release of fluid from pipelines is considered as a leak. Leaks contribute to the environmental pollution, promote corrosion and equipment failures and produce instabilities in the pipeline operation and control. There is a need, therefore, to develop an effective leak diagnosis scheme in pipeline systems that can detect the occurrence of any leak in the system. One objective of this paper is to develop a mathematical model that accounts for the behavior of pressure and flow-rate profiles in pipeline systems with multi leaks. Such a mathematical model is needed to better understand the dynamic behavior of the pipeline and its characteristics and for the detection the leaks. The paper also involves computer simulation of pipeline conditions using the developed mathematical model. A leak detection scheme is developed that is based on a computational pipeline monitoring method. This method evaluates the mismatch between the actual variables and those of the healthy pipeline system. The pipeline conditions during normal operation were simulated and the system state variables were computed in real time based on simulated measurements collected at few selected locations along the pipeline. The underlying pipeline variables are estimated by applying Kalman filtering technique.

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