scholarly journals Estimating Transmission Potential of H5N1 Viruses Among Humans in Egypt Using Phylogeny, Genetic Distance and Sampling Time Interval

2019 ◽  
Vol 10 ◽  
Author(s):  
Wessam Mohamed ◽  
Kimihito Ito ◽  
Ryosuke Omori
Keyword(s):  
Genetic Distance ◽  
Sampling Time ◽  
Time Interval ◽  
Transmission Potential ◽  
Sampling Time Interval

scholarly journals Application of Multistep Inversion Method for Online Monitoring Aerosol Particle Size Distribution and Aerosol Concentration

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Zhenzong He ◽  
Liang Xu ◽  
Junkui Mao ◽  
Xingsi Han ◽  
Biao Zhang
Keyword(s):  
Particle Size ◽  
Standard Deviation ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Sampling Time ◽  
Aerosol Concentration ◽  
Inversion Method ◽  
Time Interval ◽  
Aerosol Particle Size ◽  
Sampling Time Interval

Aerosol concentration in the flow is usually time varying, and aerosol particle size distribution (PSD) is considered to be unchanged, which increases the difficulty of the measurement of aerosol PSD and concentration online. To solve these problems, a kind of multistep inversion method based on the angular light-scattering (ALS) signals is proposed. First, the aerosol PSD is estimated using shuffled frog-leaping algorithms (SFLAs) from relative ALS signals. Then, with aerosol PSD as priori information, the aerosol concentration is obtained by the Kalman filter (KF) algorithm, widely used in the real-time control system of industrial facilities for its ability of fast predictions. The result reveals that the performance of the improved SFLA is better than that of the original SFLA in solving the aerosol PSD. Moreover, in studying the aerosol concentration, more accurate results can be obtained with larger standard deviation of process noise or smaller standard deviation of measurement noise, while decreasing sampling time interval can improve the accuracy of retrieval results and reduce time delay to a certain degree. So, to improve retrieval accuracy, the noise should be controlled, and appropriate sampling time interval should be selected. All the numerical simulations confirm that the methodology provides effective and reliable results in real-time estimating.

Effects of sampling time interval on the image offsets of the observed points for Moon-based earth observations

2020 ◽  
Vol 42 (6) ◽  
pp. 2258-2268
Author(s):  
Hanlin Ye ◽  
Wei Zheng ◽  
Huadong Guo ◽  
Guang Liu ◽  
Mingyuan wang ◽  
...  
Keyword(s):  
Sampling Time ◽  
Time Interval ◽  
Earth Observations ◽  
Sampling Time Interval

scholarly journals Accuracy of Broiler Activity Index as Affected by Sampling Time Interval

Animals ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 1102
Author(s):  
Xiao Yang ◽  
Yang Zhao ◽  
George T. Tabler
Keyword(s):  
Activity Index ◽  
Sampling Time ◽  
Time Interval ◽  
Short Time Interval ◽  
Time Intervals ◽  
Commercial Housing ◽  
Computational Resources ◽  
Short Time ◽  
Top View ◽  
Sampling Time Interval

Different time intervals between consecutive images have been used to determine broiler activity index (AI). However, the accuracy of broiler AI as affected by sampling time interval remains to be explored. The objective of this study was to investigate the effect of the sampling time interval (0.04, 0.2, 1, 10, 60, and 300 s) on the accuracy of broiler AI at different bird ages (1–7 weeks), locations (feeder, drinker, and open areas) and times of day (06:00–07:00 h, 12:00–13:00 h, and 18:00–19:00 h). A ceiling-mounted camera was used to capture top-view videos for broiler AI calculations. The results show that the sampling time interval of 0.04 s yielded the highest broiler AI because more bird motion details were captured at this short time interval. The broiler AIs at longer time intervals were 1–99% of that determined at the 0.04-s interval. The broiler AI at 0.2-s interval showed an acceptable accuracy with 80% less computational resources. Broiler AI decreased as birds aged but increased after week 4 at the drinker area. Broiler AI was the highest at the open area for weeks 1–4 and at the feeder and drinker areas for weeks 5–7. It is concluded that the accuracy of broiler AI was significantly affected by sampling time intervals. Broiler AI in commercial housing showed both temporal and spatial variations.

scholarly journals A Fine-Grained Horizontal Scaling Method for Container-Based Cloud

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Chunmao Jiang ◽  
Peng Wu
Keyword(s):  
Sampling Time ◽  
Time Interval ◽  
Data Sampling ◽  
Scaling Method ◽  
Scheduling Policies ◽  
Fine Grained ◽  
The Third ◽  
Cpu Utilization ◽  
Elastic Scaling ◽  
Container Orchestration

The container scaling mechanism, or elastic scaling, means the cluster can be dynamically adjusted based on the workload. As a typical container orchestration tool in cloud computing, Horizontal Pod Autoscaler (HPA) automatically adjusts the number of pods in a replication controller, deployment, replication set, or stateful set based on observed CPU utilization. There are several concerns with the current HPA technology. The first concern is that it can easily lead to untimely scaling and insufficient scaling for burst traffic. The second is that the antijitter mechanism of HPA may cause an inadequate number of onetime scale-outs and, thus, the inability to satisfy subsequent service requests. The third concern is that the fixed data sampling time means that the time interval for data reporting is the same for average and high loads, leading to untimely and insufficient scaling at high load times. In this study, we propose a Double Threshold Horizontal Pod Autoscaler (DHPA) algorithm, which fine-grained divides the scale of events into three categories: scale-out, no scale, and scale-in. And then, on the scaling strength, we also employ two thresholds that are further subdivided into no scaling (antijitter), regular scaling, and fast scaling for each of the three cases. The DHPA algorithm determines the scaling strategy using the average of the growth rates of CPU utilization, and thus, different scheduling policies are adopted. We compare the DHPA with the HPA algorithm under different loads, including low, medium, and high. The experiments show that the DHPA algorithm has better antijitter and antiload characteristics in container increase and reduction while ensuring service and cluster security.

Suitability of Redesigned Digital Control Systems Having an Interval Plant via an Evolutionary Approach

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Chen-Chien Hsu ◽  
Tsung-Chi Lu
Keyword(s):  
Control System ◽  
Continuous Time ◽  
Digital Control ◽  
Sampling Time ◽  
Digital System ◽  
Time Interval ◽  
Digital Control System ◽  
Worst Case ◽  
Signal Energy ◽  
Sampling Times

In this paper, a quantitative index is proposed to address the performance evaluation and design issues in the digital redesign of continuous-time interval systems. From the perspective of signal energy, a worst-case energy resemblance index (WERI), defined as the ratio of the worst-case continuous signal energy (WCSE) of the continuous-time interval system over the worst-case discrete sequence energy (WDSE) of the redesigned digital system, is established for evaluating the closeness of the system performance between the redesigned digital control system and its continuous-time counterpart. Based on the WERI, performance of the redesigned digital systems can be evaluated for different discretization methods at different sampling times. It is found that no discretization method outperforms the others for all sampling times. Because of serious nonlinearities and nonconvexity involved, the determination of WCSE and WDSE is first formulated as an optimization problem and subsequently solved via an evolutionary algorithm. To guarantee stability of the redesigned digital system, the largest sampling time allowed is also evolutionarily determined to establish a sampling-time constraint under which robust Schur stability of the redesigned digital system can be ensured. For design purposes, sampling time required can be determined according to the user-specified WERI, which serves as a performance specification for fine tuning the performance of the redesigned digital control system.

scholarly journals STUDI DINAMIKA SENYAWA FOSFAT DALAM KUALITAS AIR SUNGAI CILIWUNG HULU KOTA BOGOR

2018 ◽  
Vol 8 (1) ◽  
pp. 43
Author(s):  
RTM Sutamihardja ◽  
Mia Azizah ◽  
Yunita Hardini
Keyword(s):  
Water Quality ◽  
River Water ◽  
Environmental Problem ◽  
Nitrate Concentration ◽  
Threshold Level ◽  
Quality Standard ◽  
Time Interval ◽  
Quality Water ◽  
Sampling Time Interval

Study of Dynamics of Phosphate in the Water Quality in Bogor of Upstream Ciliwung RiverCiliwung River has existed and become an important part of the community since ancient period. Since 2009, the Ciliwung River has been polluted condition from upstream. One of the pollutant that could decrease the quality of river water was phosphate. Excessive phosphate level in water bodies caused nutrient enrichment conditions (eutrophication). The presence of nitrate supporting phosphate also caused algae blooming, one of the environmental problem. The research was conducted to determine the dynamics of the phosphate compound of Ciliwung River whether the pollution was reduced, same, or worse. The research included sampling of river water at three points of Katulampa, Pasar Bogor, and Warung Jambu River with sampling time interval of 8 hours in a day for 3 weeks in a row. The data of phosphate and nitrate concentration were measured and compared to the results in PP No.82 year 2001. The total of phosphate in Ciliwung river water has exceeded threshold level in accordance with the environmental quality standard of PP. 82 year 2001, and has been indicated to be in eutrophication condition.Keywords: Ciliwung River, Water Quality, Water Pollution, Phosphate.ABSTRAKSungai Ciliwung telah ada dan menjadi bagian penting masyarakat sejak zaman purba. Namun seiring dengan berlalunya waktu dan perkembangan pesat, sejak tahun 2009 Sungai Ciliwung telah tercemar dari hulu. Salah satu polutan yang bisa menurunkan kualitas air sungai adalah fosfat. Keberadaan fosfat yang berlebihan di badan air dapat menyebabkan kondisi pengayaan nutrisi (eutrofikasi), dan dengan dukungan nitrat dapat menyebabkan algae blooming yang menjadi salah satu masalah lingkungan. Penelitian ini dilakukan untuk mengetahui dinamika senyawa fosfat Sungai Ciliwung apakah pencemarannya berkurang, sama, atau lebih buruk. Ruang lingkup penelitian meliputi pengambilan sampel air sungai pada tiga titik Katulampa, Pasar Bogor, dan Warung Jambu dengan interval waktu sampling 8 jam dalam sehari, dan dilakukan setiap minggu selama 3 minggu berturut-turut. Kemudian dilakukan analisis sampel di laboratorium, serta interpretasi data dengan membandingkan hasilnya terhadap PP No.82 tahun 2001. Nilai total fosfat di air sungai Ciliwung Hulu tidak memenuhi standar kualitas lingkungan PP. 82 tahun 2001, dan diindikasikan berada dalam kondisi eutrofikasi.Kata kunci: Sungai Ciliwung, Kualitas Air, Polusi Air, Fosfat.

Encoder-Less Synchronized Averaging Using Order Tracking and Interpolation

2004 ◽  
Author(s):  
George T. Tzeng
Keyword(s):  
Signal To Noise Ratio ◽  
Processing Technique ◽  
Time Interval ◽  
Signal Processing Technique ◽  
Rotating Speed ◽  
Order Tracking ◽  
Useful Signal ◽  
Significant Difference ◽  
Band Pass ◽  
Sampling Time Interval

Synchronized averaging is a very useful signal processing technique, in particular, for condition monitoring of rotating machinery. It enhances the signal to noise ratio by attenuating noises that are not repeated from one rotation to the next. Its use, however, is limited due to the costly hardware needed to trigger the sampling at exactly the same angular positions rotation after rotation. This paper describes an improved order tracking technique which employs a Kalman filter to track the instantaneous rotating speed of machinery and an interpolation technique to resample data obtained under constant sampling time interval into data sampled at constant angular increments. Experiments were conducted to validate the proposed algorithm. Comparing the synchronized average obtained by the order tracking algorithm with the true average using encoder triggering, no significant difference can be seen until 3x of meshing frequency. Since the technique only requires band-pass filtered vibration and a once-per-revolution index signal, it is much simpler compared to the existing technique which requires complex and cumbersome hardware to track the rotating speed.

Comparison of two methods for optimizing existing groundwater monitoring networks: application to the Bacchiglione Basin, Italy

2020 ◽  
Author(s):  
Andrea Sottani ◽  
Mara Meggiorin ◽  
Luís Ribeiro ◽  
Andrea Rinaldo
Keyword(s):  
Time Series ◽  
Correlation Coefficient ◽  
Groundwater Monitoring ◽  
Clustering Algorithm ◽  
Distance Measure ◽  
Pearson Correlation ◽  
Sampling Time ◽  
Time Interval ◽  
Monitoring Networks ◽  
Simple Method

<p>In the presence of a groundwater monitoring network (GMN) of sensors aimed at measuring the hydraulic head in a given domain, the statistical analysis of time series not only provides insight into the general aquifer behaviour, but it can also return parameters useful to optimize and enhance the GMN’s efficiency.</p><p>Several methods to design new GMNs are available, but few of them are useful for optimizing existing networks. This study compares two methods in order to define pros and cons of their applicability and effectiveness.</p><p>They are carried out for the case study of the alluvial basin of the Bacchiglione river, near Vicenza (Veneto, Italy). The existing network comprises 92 groundwater data-loggers, installed in wells screening mostly the unconfined aquifer.</p><p>The first simple method, here proposed, is based on the Pearson correlation coefficient and the microscale parameter, which shows the time interval in which data are perfectly correlated. The coefficients were calculated between detrended time series. Firstly, based on the correlation coefficient threshold of 0.95, areas of intercorrelated couples are defined. They are characterized by similar hydrological behaviour, therefore it is sufficient to constantly monitor only one location in each area, while other interesting correlated points can be measured manually at longer sampling time. The microscale can be used to estimate this sampling time in order to see the water table trend (between 7 and 78 days in this domain), even if shorter oscillations are obviously missed and some peaks could remain unseen. This way, extra sensors can be moved to other critical areas, in order to improve the system knowledge.</p><p>The second method defines the seasonal Mann Kendall (sMK) test for detecting monotonic trends, that are used into Principal Component Analysis (PCA). Finally, a Hierarchical Clustering Analysis is carried out to group sensors with similar factors of the PCA. This method is more articulated than the previous one and entails some informed choices to be made about the distance measure and the clustering algorithm. Thanks to the sMK test and the PCA, a high insight of the system is achieved, however the clustering result may strongly variate depending on the expert’s knowledge and expectation.</p><p>The two proposed statistical analyses of hydrogeological data provide integrative decision support to improve representativeness and effectiveness of monitoring networks aimed at both qualitative and quantitative groundwater control.</p>

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