EFFECTS OF SAMPLING FREQUENCY IN SEWAGE QUALITY SURVEY ON ESTIMATION ACCURACY OF SEWAGE CONCENTRATION: A CASE STUDY OF HUE

2019 ◽  
Vol 75 (7) ◽  
pp. III_245-III_253
Author(s):  
Ryuichi WATANABE ◽  
Hidenori HARADA ◽  
Shigeo FUJII ◽  
Hidenari YASUI
Keyword(s):  
Sampling Frequency ◽  
Estimation Accuracy

A Review on Enhanced Stability Analyses of Soil Slopes Using Statistical Design

2018 ◽  
pp. 446-481
Author(s):  
Srđan Kostić
Keyword(s):  
Slope Stability ◽  
External Validation ◽  
Statistical Design ◽  
Estimation Accuracy ◽  
Rupture Surface ◽  
Stability Of Slopes ◽  
Mathematical Expressions ◽  
Grid Search Method ◽  
Homogeneous Soil

This chapter deals with the application of experimental design in slope stability analysis. In particular, focus of the present chapter is on the application of Box-Behnken statistical design for assessment of stability of slopes in homogeneous soil (general case), for estimation of slope stability in clay-marl deposits at the edge of Neogene basins (case study) and for the extension of grid search method for locating the critical rupture surface. Extensive statistical analysis, internal and external validation imply high estimation accuracy and reliability of developed mathematical expressions for slope safety factor and for parameters of location of critical rupture surface. Main advantages and limitations of the proposed approach are thoroughly discussed with suggestions for main directions of further research.

scholarly journals Complexity Effective Sampling Frequency Offset Estimation Method for OFDM-Based HomePlug Green PHY Systems

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 544
Author(s):  
Yong-An Jung ◽  
Young-Hwan You
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Estimation Method ◽  
Frequency Offset ◽  
Sampling Frequency ◽  
Estimation Accuracy ◽  
Computationally Efficient ◽  
Pilot Symbols ◽  
Sampling Frequency Offset ◽  
Efficient Sampling ◽  
Estimation Scheme

The HomePlug Green PHY (HomePlug GP) specification provides an attractive solution to enable smart grid power line communication (PLC) applications by using robust orthogonal frequency division multiplexing (ROBO) mode. This paper proposes a computationally efficient sampling frequency offset (SFO) estimation technique in the HomePlug GP system without relying on pilot symbols. For this purpose, the proposed estimation scheme utilizes the redundant information contained within the repeat coding in the HomePlug GP ROBO mode, thus eliminating the need of dedicated pilots. Computer simulations are conducted to assess the performance of the proposed SFO estimation scheme and to compare it with the conventional decision-directed (DD) estimation schemes. Simulations indicate that the repeat coded ROBO signals are effectively used for the proposed estimation scheme, which provides an affordable estimation accuracy while reducing the complexity compared to the conventional DD estimation schemes.

scholarly journals Estimating Fire Background Temperature at a Geostationary Scale—An Evaluation of Contextual Methods for AHI-8

2018 ◽  
Vol 10 (9) ◽  
pp. 1368 ◽  
Author(s):  
Bryan Hally ◽  
Luke Wallace ◽  
Karin Reinke ◽  
Simon Jones ◽  
Chermelle Engel ◽  
...  
Keyword(s):  
Contextual Information ◽  
Window Size ◽  
Fire Detection ◽  
Estimation Accuracy ◽  
Significant Deterioration ◽  
Temperature Estimation ◽  
Landscape Characteristics ◽  
Detection And Attribution ◽  
Background Temperature

An integral part of any remotely sensed fire detection and attribution method is an estimation of the target pixel’s background temperature. This temperature cannot be measured directly independent of fire radiation, so indirect methods must be used to create an estimate of this background value. The most commonly used method of background temperature estimation is through derivation from the surrounding obscuration-free pixels available in the same image, in a contextual estimation process. This method of contextual estimation performs well in cloud-free conditions and in areas with homogeneous landscape characteristics, but increasingly complex sets of rules are required when contextual coverage is not optimal. The effects of alterations to the search radius and sample size on the accuracy of contextually derived brightness temperature are heretofore unexplored. This study makes use of imagery from the AHI-8 geostationary satellite to examine contextual estimators for deriving background temperature, at a range of contextual window sizes and percentages of valid contextual information. Results show that while contextual estimation provides accurate temperatures for pixels with no contextual obscuration, significant deterioration of results occurs when even a small portion of the target pixel’s surroundings are obscured. To maintain the temperature estimation accuracy, the use of no less than 65% of a target pixel’s total contextual coverage is recommended. The study also examines the use of expanding window sizes and their effect on temperature estimation. Results show that the accuracy of temperature estimation decreases significantly when expanding the examined window, with a 50% increase in temperature variability when using a larger window size than 5 × 5 pixels, whilst generally providing limited gains in the total number of temperature estimates (between 0.4%–4.4% of all pixels examined). The work also presents a number of case study regions taken from the AHI-8 disk in more depth, and examines the causes of excess temperature variation over a range of topographic and land cover conditions.

scholarly journals Low-Cost, High-Frequency, Data Acquisition System for Condition Monitoring of Rotating Machinery through Vibration Analysis-Case Study

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3493
Author(s):  
César Ricardo Soto-Ocampo ◽  
José Manuel Mera ◽  
Juan David Cano-Moreno ◽  
José Luis Garcia-Bernardo
Keyword(s):  
Data Acquisition ◽  
Condition Monitoring ◽  
Vibration Analysis ◽  
Low Cost ◽  
Data Acquisition System ◽  
Sampling Frequency ◽  
Rotating Machinery ◽  
Acquisition System ◽  
Raspberry Pi

Data acquisition is a crucial stage in the execution of condition monitoring (CM) of rotating machinery, by means of vibration analysis. However, the major challenge in the execution of this technique lies in the features of the recording equipment (accuracy, resolution, sampling frequency and number of channels) and the cost they represent. The present work proposes a low-cost data acquisition system, based on Raspberry-Pi, with a high sampling frequency capacity in the recording of up to three channels. To demonstrate the effectiveness of the proposed data acquisition system, a case study is presented in which the vibrations registered in a bearing are analyzed for four degrees of failure.

Failure Probability of Thermally Stable Diamond Composite Tips for Cutting Rock Segments

2018 ◽  
Vol 936 ◽  
pp. 192-197 ◽  
Author(s):  
Yong Sun ◽  
Xing Sheng Li
Keyword(s):  
Failure Probability ◽  
Rock Cutting ◽  
Estimation Accuracy ◽  
Segment Length ◽  
High Wear Resistance ◽  
Failure Behavior ◽  
Thermally Stable ◽  
Diamond Composite ◽  
The Impact

Thermally Stable Diamond Composite (TSDC) tips have attracted a great attention of rock cutting industry due to the higher thermal stability and high wear resistance of TSDC. To make the TSDC tipped picks practical for real application, it is important to understand the failure behavior of the TSDC tips for rock cutting. One of the failure characters of TSDC tips is random failures. In this paper, a method is proposed to calculate the failure probability of TSDC tips for cutting individual rock segments. This method enables to link the segment length to the failure probability of the tip for cutting the segment. A numerical case study is presented to validate the method. The method can effectively reduce the impact of the number of segments on failure probability estimation accuracy.

An Approach to Determining Applicability Domains for QSAR Group Contribution Models: An Analysis of SRC KOWWIN

2005 ◽  
Vol 33 (5) ◽  
pp. 461-470 ◽  
Author(s):  
Nina Nikolova-Jeliazkova ◽  
Joanna Jaworska
Keyword(s):  
Principal Component ◽  
Qsar Model ◽  
Operational Definition ◽  
Group Contribution ◽  
Applicability Domain ◽  
Estimation Accuracy ◽  
Processing Step ◽  
Water Partition Coefficient ◽  
Component Rotation

QSAR model predictions are most reliable if they come from the model's applicability domain. The Setubal Workshop report provides a conceptual guidance for defining a (Q)SAR applicability domain. However, an operational definition is necessary for applying this guidance in practice. It should also permit the design of an automatic (computerised) procedure for determining a model's applicability domain. This paper attempts to address this need for models that use a large number of descriptors (for example, group contribution-based models). The high dimensionality of these models imposes specific computational restrictions on estimating the interpolation region. The Syracuse Research Corporation KOWWIN model for prediction of the n-octanol/water partition coefficient is analysed as a case study. This is a linear regression model that uses 508 fragment counts and correction factors as descriptors, and is based on the group contribution approach. We conclude that the applicability domain estimation by descriptor ranges, combined with Principal Component rotation as a data pre-processing step, is an acceptable compromise between estimation accuracy and the amount of data in the training set.

A case study on the estimation accuracy of soil properties and fertilizer rates for different soil-sampling grids

2012 ◽  
Vol 176 (1) ◽  
pp. 57-68 ◽  
Author(s):  
Michał Stępień ◽  
Dariusz Gozdowski ◽  
Stanisław Samborski
Keyword(s):  
Soil Properties ◽  
Soil Sampling ◽  
Estimation Accuracy ◽  
Fertilizer Rates
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