active monitoring
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Noha G. Elnagar ◽  
Ghada F. Elkabbany ◽  
Amr A. Al-Awamry ◽  
Mohamed B. Abdelhalim

<span lang="EN-US">Load balancing is crucial to ensure scalability, reliability, minimize response time, and processing time and maximize resource utilization in cloud computing. However, the load fluctuation accompanied with the distribution of a huge number of requests among a set of virtual machines (VMs) is challenging and needs effective and practical load balancers. In this work, a two listed throttled load balancer (TLT-LB) algorithm is proposed and further simulated using the CloudAnalyst simulator. The TLT-LB algorithm is based on the modification of the conventional TLB algorithm to improve the distribution of the tasks between different VMs. The performance of the TLT-LB algorithm compared to the TLB, round robin (RR), and active monitoring load balancer (AMLB) algorithms has been evaluated using two different configurations. Interestingly, the TLT-LB significantly balances the load between the VMs by reducing the loading gap between the heaviest loaded and the lightest loaded VMs to be 6.45% compared to 68.55% for the TLB and AMLB algorithms. Furthermore, the TLT-LB algorithm considerably reduces the average response time and processing time compared to the TLB, RR, and AMLB algorithms.</span>

Florian Mertes ◽  
Stefan Röttger ◽  
Annette Röttger

In this work, a novel approach for the standardization of low-level 222Rn emanation is presented. The technique is based on the integration of a 222Rn source, directly, with an α-particle detector, which allows the residual 222Rn to be continuously monitored. Preparation of the device entails thermal physical vapor deposition of 226RaCl2 directly onto the surface of a commercially available ion implanted Si-diode detector, resulting in a thin-layer geometry. This enables continuous collection of well resolved α-particle spectra of the nuclei, decaying within the deposited layer, with a detection efficiency of approximately 0.5 in a quasi 2π geometry. The continuously sampled α-particle spectra are used to derive the emanation by statistical inversion. It is possible to achieve this with high temporal resolution due to the small background and the high counting efficiency of the presented technique. The emanation derived in this way exhibits a dependence on the relative humidity of up to 15% in the range from 20% rH to 90% rH. Traceability to the SI is provided by employing defined solid-angle α-particle spectrometry to characterize the counting efficiency of the modified detectors. The presented technique is demonstrated to apply to a range covering the release of at least 1 to 210 222Rn atoms per second, and it results in SI-traceable emanation values with a combined standard uncertainty not exceeding 2%. This provides a pathway for the realization of reference atmospheres covering typical environmental 222Rn levels and thus drastically improves the realization and the dissemination of the derived unit of the activity concentration concerning 222Rn in air.

L.G. Akhmetzyanova ◽  
B.M. Usmanov ◽  
R.S. Kuz’min ◽  
A.M. Gafurov ◽  
V.V. Sirotkin ◽  

Assessment of the current residual capacity is a fundamentally important task, the solution of which is demonstrated on a landfill located in the Republic of Tatarstan. To solve the task, the modern methods of high-precision three-dimensional reconstruction were used based on the survey from an unmanned aircraft DJI Phantom 4, equipped with a global satellite navigation system (GNSS) receiver. As a result of combining the project data and data from field surveys into one coordinate system and elevations and reconstruction of designed underground and ground parts of landfill calculation, the difference of models and the residual capacity of the landfill becomes possible. Based on the materials considered as of July 2020, the residual capacity of the studied landfill is 41.2 % of the project capacity, which allows us to continue to operate this landfill. The proposed approach allows for rapid and high-quality active monitoring of the engineered facility. Photogrammetric processing of the results of low-altitude aerial photography makes it possible to obtain objective data on the current actual state of the landfills, to carry out competent and valid management of the landfill functioning. Significant, this will extend the landfill's lifetime, minimize the adverse effects on the environment and predict the yield to the project capacity much more accurately.

Yuliia O. Danylevska ◽  
Tetiana A. Sokur ◽  
Oleksandr M. Bodnaruk ◽  
Andrii V. Shevchuk ◽  
Oleksiy V. Stratiy

The aim of the article was to conduct a comparative legal analysis of the features and problems of criminal prosecution of legal entities for environmental crimes. The research objectives were fulfilled through modern methods of cognition. The leading practical method was the method of observation. The study allowed to form a conceptual understanding of theoretical ideas about environmental crimes of legal entities in Ukraine. Currently, Ukraine is trying to focus in its legislative innovations on the implementation of progressive approaches to the introduction of a comprehensive institution of criminal law measures regarding the liability of these entities. Relevant legal mechanisms and comments identified in the practice of the European Union and substantiated by scholars, can be implemented in the legislation of Ukraine. Amendments to the rules governing the procedure for effective prevention of environmental crimes by legal entities are proposed. It seems reasonable to introduce an active monitoring analysis of anthropogenic activities of companies, and the creation of special units to identify relevant violations. The mechanisms for implementing the set of preventive and monitoring measures outlined in the article, set the background for further scientific research.

Georgina Dominique ◽  
Wayne G. Brisbane ◽  
Robert E. Reiter

Abstract Purpose We present an overview of the literature regarding the use of MRI in active surveillance of prostate cancer. Methods Both MEDLINE® and Cochrane Library were queried up to May 2020 for studies of men on active surveillance with MRI and later confirmatory biopsy. The terms studied were ‘prostate cancer’ as the anchor followed by two of the following: active surveillance, surveillance, active monitoring, MRI, NMR, magnetic resonance imaging,  MRI, and multiparametric MRI. Studies were excluded if pathologic reclassification (GG1 →  ≥ GG2) and PI-RADS or equivalent was not reported. Results Within active surveillance, baseline MRI is effective for identifying clinically significant prostate cancer and thus associated with fewer reclassification events. A positive initial MRI (≥ PI-RADS 3) with GG1 identified at biopsy has a positive predictive value (PPV) of 35–40% for reclassification by 3 years. MRI possessed a stronger negative predictive value, with a negative MRI (≤ PI-RADS 2) yielding a negative predictive value of up to 85% at 3 years. Surveillance MRI, obtained after initial biopsy, yielded a PPV of 11–65% and NPV of 85–95% for reclassification. Conclusion MRI is useful for initial risk stratification of prostate cancer in men on active surveillance, especially if MRI is negative when imaging is obtained during surveillance. While useful, MRI cannot replace biopsy and further research is necessary to fully integrate MRI into active surveillance.

2021 ◽  
Vol 2131 (3) ◽  
pp. 032032
A V Valyaev ◽  
E A Lukina ◽  
Y S Fedosenko

Abstract The problem of determination of threshold values of changes in stability characteristics of a river displacement ship is studied. A model and a data preparation scheme are being developed for the algorithmic implementation of the construction of curves of threshold values of lateral stability characteristics until the moment corresponding to the command given by the ship’s captain to bring life-saving appliances to a state of readiness or to use them. For the case of flooding of two adjacent hull compartments of a three-deck river passenger motor ship under the action of an external static inclining moment, illustrating data of calculations of hydrostatic characteristics and ship trim are presented, and an ensemble of diagrams of its static stability with threshold values is built. The results of the studies performed are intended for the software and hardware implementation of a digital system for active monitoring of the ship’s hull condition, predicting the development of a dangerous situation, supporting decision-making by the captain of a river vessel on the use of standard rescue equipment in the event of the threat of the ship being flooded and overturned.

Georgina Wilkins ◽  
Fernando Zanghelini ◽  
Kieran Brooks ◽  
Oladapo Ogunbayo

IntroductionEarly identification of innovative medicines is crucial for timely health technology assessment (HTA) and efficient patient access. The National Institute for Health Research Innovation Observatory (NIHRIO) identifies, monitors and notifies key HTA stakeholders in England of ‘technologies’ (innovative medicines) within three to five years of regulatory approval. Increasing numbers of innovative medicines and significant uncertainties in clinical and regulatory pathways are major challenges in the monitoring and notification process. An active monitoring framework using pre-defined predictive criteria has previously been developed. This framework provides a standardized and consistent process, but is highly resource-intensive, requiring manual review of individual records.MethodsUsing the previous active monitoring framework, a scoring matrix was calculated and used to prioritize individual technologies using available data in the NIHRIO database: estimated regulatory timelines, regulatory awards/designations, innovative medicine type (for example gene therapies) and clinical trial phase, completion dates and results. A threshold for automatic and manual reviewing of technologies was developed and tested by NIHRIO analysts.ResultsThe scoring system identified approximately ninety percent of technologies meeting the threshold for semi-automated reviewing. The review period for these technologies are set automatically according to predefined criteria depending on data availability. The review periods are updated automatically until the record reaches the threshold that triggers manual reviewing. The remaining ten percent had estimated regulatory timelines necessitating the need for manual reviewing and early engagement with companies to verify regulatory timelines and/or notify HTA stakeholders.ConclusionsPreliminary analysis indicates that each technology is routinely and automatically updated. The semi-automatic updating represents a significant improvement in the efficiency of the monitoring of the large volume of technologies on the NIHRIO database. Ongoing work is being undertaken to further refine, pilot and test the system.This project is funded by the NIHR [(HSRIC-2016-10009)/Innovation Observatory]. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7867
Yanjie Guo ◽  
Zhaoyi Xu ◽  
Joseph Saleh

In this study, a novel collaborative method is developed to optimize hybrid sensor networks (HSN) for environmental monitoring and anomaly search tasks. A weighted Gaussian coverage method hs been designed for static sensor allocation, and the Active Monitoring and Anomaly Search System method is adapted to mobile sensor path planning. To validate the network performance, a simulation environment has been developed for fire search and detection with dynamic temperature field and non-uniform fire probability distribution. The performance metrics adopted are the detection time lag, source localization uncertainty, and state estimation error. Computational experiments are conducted to evaluate the performance of HSNs. The results demonstrate that the optimal collaborative deployment strategy allocates static sensors at high-risk locations and directs mobile sensors to patrol the remaining low-risk areas. The results also identify the conditions under which HSNs significantly outperform either only static or only mobile sensor networks in terms of the monitoring performance metrics.

S. Ya. Davydov ◽  
R. A. Apakashev ◽  
N. G. Valiev ◽  
A. A. Kutenev ◽  
N. A. Evseev


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