scholarly journals Optimization of Indoor Bluetooth Ranging Model Based on RSSI

2021 ◽  
Vol 5 (3) ◽  
Author(s):  
Demei Peng ◽  
◽  
Liangfu Peng ◽  
Yingying Yang ◽  
◽  
...  
Keyword(s):  
Least Squares Method ◽  
Absolute Error ◽  
Line Of Sight ◽  
Average Error ◽  
Indoor Environments ◽  
Maximum Absolute Error ◽  
Filtering Method ◽  
Multipath Effects ◽  
Received Signal Strength Indication ◽  
Ranging Model

Because the received signal strength indication (RSSI) ranging technology has problems with line-of-sight and multipath effects in indoor environments, the actual received RSSI value is unstable. In order to reduce the influence of RSSI value volatility on ranging accuracy, according to the fluctuation characteristics of the signal itself, a combined filtering method of Gaussian, median and mean is proposed to process the collected RSSI values, and the least squares method is used to fit and optimize the ranging parameter. Experiments show that using the RSSI intensity value processed by the combined filtering method to establish a model to achieve ranging, the maximum absolute error is about 2 m, and the absolute average error is about 0.763 m. The accuracy of the ranging has been significantly improved, and the ranging model has been optimized.

scholarly journals Inner Wall Temperature Distribution Measurement of The Ladle Based on Cavity Effective Emissivity Correction

2021 ◽  
Author(s):  
Jun Liu ◽  
Yanhui Huang ◽  
Ying Ci ◽  
Jiangxiong Fang ◽  
Feng Yang ◽  
...  
Keyword(s):  
Wall Temperature ◽  
Monte Carlo Model ◽  
Absolute Error ◽  
Average Error ◽  
Material Surface ◽  
Laser Sensor ◽  
Effective Emissivity ◽  
Maximum Absolute Error ◽  
Rotating Platform ◽  
High Measurement

Abstract Inner wall temperature of ladle is closely related to the quality of steelmaking and control of steel-making tapping temperature. This article adopts a rotating platform to drive an infrared temperature sensor and a laser sensor to scan the temperature field distribution of the ladle inner wall at the hot repair station, where the scanning laser sensor obtains coordinates of each measured point. Because of measuring errors of infrared thermal radiation caused by emissivity uncertainty of the ladle inner wall surface, this article proposes a method for temperature measurement based on Monte Carlo model for effective emissivity correction of each measured point. In the model, we consider the ladle and fire baffle as a cavity. By calculation of the model, the effect of distance from the fire baffle to the ladle and the material surface emissivity of the ladle inner wall on the effective emissivity of the cavity are obtained. After that, the effective emissivity of each measured point is determined. Then the scanning temperature of each measured point is corrected to real temperature. By field measuring test and verification contrast, the results show that: the maximum absolute error of the method in this article is 4.7℃, the minimum error is 0.6℃, and the average error is less than 2.8℃. The method in this article achieves high measurement accuracy and contributes to the control of metallurgical process based on temperature information.

Low-Power High-Accuracy Fixed-Width Radix-8 Booth Multiplier Using Probabilistic Estimation Technique

2017 ◽  
Vol 26 (05) ◽  
pp. 1750079 ◽  
Author(s):  
Saroja S. Bhusare ◽  
V. S. Kanchana Bhaaskaran
Keyword(s):  
Mean Square Error ◽  
Absolute Error ◽  
Average Error ◽  
Mean Square ◽  
Estimation Technique ◽  
Maximum Absolute Error ◽  
Theoretical Computation ◽  
Probabilistic Estimation ◽  
Booth Multiplier ◽  
The Mean

In many Multimedia and DSP applications, the fixed-width multipliers are used to avoid infinite growth in the word size. Fixed-width multiplier produces an [Formula: see text]-bit product with two [Formula: see text]-bit inputs. This paper presents probabilistic estimation technique applied for the fixed-width radix-8 Booth multiplier for the generation of the compensation bias circuit. The probabilistic estimation circuit for the fixed-width radix-8 Booth multiplier is derived systematically from theoretical computation in preference to time-consuming exhaustive simulations. Results show that the radix-8 direct truncated multiplier reduces the maximum absolute error by 33%, the average error by 22% and the mean square error by 39% for a 12-bit multiplier compared with the radix-4 direct truncated multiplier. Results also demonstrate that, with the probabilistic estimation technique applied to the fixed-width radix-8 Booth multiplier, there is a reduction of 25% in the maximum absolute error, 13.4% reduction in the average error, and 25.13% reduction in the mean square error have been realized compared with the existing fixed-width radix-4 Booth multiplier with probabilistic estimation technique. Standard EDA design tools are used for simulations.

EXPRESS: Baseline Correction Based on a Search Algorithm from Artificial Intelligence

2020 ◽  
pp. 000370282097751
Author(s):  
Xin Wang ◽  
Xia Chen
Keyword(s):  
Artificial Intelligence ◽  
Objective Function ◽  
Least Squares ◽  
Least Squares Method ◽  
Search Algorithm ◽  
Absolute Error ◽  
Search Problem ◽  
Baseline Correction ◽  
Current Spectrum ◽  
Data Points

Many spectra have a polynomial-like baseline. Iterative polynomial fitting (IPF) is one of the most popular methods for baseline correction of these spectra. However, the baseline estimated by IPF may have substantially error when the spectrum contains significantly strong peaks or have strong peaks located at the endpoints. First, IPF uses temporary baseline estimated from the current spectrum to identify peak data points. If the current spectrum contains strong peaks, then the temporary baseline substantially deviates from the true baseline. Some good baseline data points of the spectrum might be mistakenly identified as peak data points and are artificially re-assigned with a low value. Second, if a strong peak is located at the endpoint of the spectrum, then the endpoint region of the estimated baseline might have significant error due to overfitting. This study proposes a search algorithm-based baseline correction method (SA) that aims to compress sample the raw spectrum to a dataset with small number of data points and then convert the peak removal process into solving a search problem in artificial intelligence (AI) to minimize an objective function by deleting peak data points. First, the raw spectrum is smoothened out by the moving average method to reduce noise and then divided into dozens of unequally spaced sections on the basis of Chebyshev nodes. Finally, the minimal points of each section are collected to form a dataset for peak removal through search algorithm. SA selects the mean absolute error (MAE) as the objective function because of its sensitivity to overfitting and rapid calculation. The baseline correction performance of SA is compared with those of three baseline correction methods: Lieber and Mahadevan–Jansen method, adaptive iteratively reweighted penalized least squares method, and improved asymmetric least squares method. Simulated and real FTIR and Raman spectra with polynomial-like baselines are employed in the experiments. Results show that for these spectra, the baseline estimated by SA has fewer error than those by the three other methods.

Error Compensation Techniques for Fixed-Width Array Multiplier Design — A Technical Survey

2016 ◽  
Vol 26 (03) ◽  
pp. 1730003 ◽  
Author(s):  
S. Balamurugan ◽  
P. S. Mallick
Keyword(s):  
Error Compensation ◽  
Absolute Error ◽  
Mean Square ◽  
Maximum Absolute Error ◽  
Comprehensive Review ◽  
Related Research ◽  
Error Formula ◽  
Error Metrics ◽  
Array Multiplier ◽  
Future Work

This paper provides a comprehensive review of various error compensation techniques for fixed-width multiplier design along with its applications. In this paper, we have studied different error compensation circuits and their complexities in the fixed-width multipliers. Further, we present the experimental results of error metrics, including normalized maximum absolute error [Formula: see text], normalized mean error [Formula: see text] and normalized mean-square error [Formula: see text] to evaluate the accuracy of fixed-width multipliers. This survey is intended to serve as a suitable guideline and reference for future work in fixed-width multiplier design and its related research.

scholarly journals Evaluation of Mekong River commission operational flood forecasts, 2000–2012

2014 ◽  
Vol 18 (7) ◽  
pp. 2645-2656 ◽  
Author(s):  
T. C. Pagano
Keyword(s):  
Protective Action ◽  
Absolute Error ◽  
Probability Of Detection ◽  
Mekong River ◽  
Average Error ◽  
Wet Season ◽  
Phnom Penh ◽  
Mekong River Commission ◽  
Flood Level ◽  
Skill Scores

Abstract. This study created a 13-year historical archive of operational flood forecasts issued by the Regional Flood Management and Mitigation Center (RFMMC) of the Mekong River Commission. The RFMMC issues 1- to 5-day daily deterministic river height forecasts for 22 locations throughout the wet season (June–October). When these forecasts reach near flood level, government agencies and the public are encouraged to take protective action against damages. When measured by standard skill scores, the forecasts perform exceptionally well (e.g., 1 day-ahead Nash–Sutcliffe > 0.99) although much of this apparent skill is due to the strong seasonal cycle and the narrow natural range of variability at certain locations. Five-day forecasts upstream of Phnom Penh typically have 0.8 m error standard deviation, whereas below Phnom Penh the error is typically 0.3 m. The coefficients of persistence for 1-day forecasts are typically 0.4–0.8 and 5-day forecasts are typically 0.1–0.7. RFMMC uses a series of benchmarks to define a metric of percentage satisfactory forecasts. As the benchmarks were derived based on the average error, certain locations and lead times consistently appear less satisfactory than others. Instead, different benchmarks were proposed and derived based on the 70th percentile of absolute error over the 13-year period. There are no obvious trends in the percentage of satisfactory forecasts from 2002 to 2012, regardless of the benchmark chosen. Finally, when evaluated from a categorical "crossing above/not-crossing above flood level" perspective, the forecasts have a moderate probability of detection (48% at 1 day ahead, 31% at 5 days ahead) and false alarm rate (13% at 1 day ahead, 74% at 5 days ahead).

Precise Ranging Technology Application Research Based on IEEE802.15.4a

2014 ◽  
Vol 631-632 ◽  
pp. 558-562
Author(s):  
Zi Hui Wei ◽  
Zheng He Feng ◽  
Zhi Feng Wang ◽  
Duan Bo Cai
Keyword(s):  
Spread Spectrum ◽  
Wide Band ◽  
Impulse Radio ◽  
Line Of Sight ◽  
Test Results ◽  
Application Research ◽  
Technology Application ◽  
Accuracy Test ◽  
Chirp Spread Spectrum ◽  
Received Signal Strength Indication

To solve the poor location accuracy of wireless sensor networks using Received Signal Strength Indication (RSSI) ranging. Time Of Flight (TOF) ranging is used to ensure the accuracy based on two optional physical layer of Impulse Radio-Ultra Wide-Band (IR-UWB) and Chirp Spread Spectrum (CSS) in IEEE802.15.4a. In this paper, we designed ranging module utilizing CSS and UWB. In the Line Of Sight (LOS) and None Line Of Sight (NLOS) environments ranging accuracy test is implemented, the test results show that the IR-UWB ranging technology can achieve higher ranging accuracy and better multipath resistance compared to CSS.

scholarly journals Least Squares Estimations for the General Linear Model Parameters with Epsilon Skew Normal Error Term

2020 ◽  
pp. 636-645
Author(s):  
Hussain Karim Nashoor ◽  
Ebtisam Karim Abdulah
Keyword(s):  
Least Squares ◽  
Linear Model ◽  
Least Squares Method ◽  
General Linear Model ◽  
Ordinary Least Squares ◽  
Skewed Distribution ◽  
General Linear ◽  
Average Error ◽  
Model Parameters ◽  
Skew Normal

Examination of skewness makes academics more aware of the importance of accurate statistical analysis. Undoubtedly, most phenomena contain a certain percentage of skewness which resulted to the appearance of what is -called "asymmetry" and, consequently, the importance of the skew normal family . The epsilon skew normal distribution ESN (μ, σ, ε) is one of the probability distributions which provide a more flexible model because the skewness parameter provides the possibility to fluctuate from normal to skewed distribution. Theoretically, the estimation of linear regression model parameters, with an average error value that is not zero, is considered a major challenge due to having difficulties, as no explicit formula to calculate these estimates can be obtained. Practically, values for these estimates can be obtained only by referring to numerical methods. This research paper is dedicated to estimate parameters of the Epsilon Skew Normal General Linear Model (ESNGLM) using an adaptive least squares method, as along with the employment of the ordinary least squares method for estimating parameters of the General Linear Model (GLM). In addition, the coefficient of determination was used as a criterion to compare the models’ preference. These methods were applied to real data represented by dollar exchange rates. The Matlab software was applied in this work and the results showed that the ESNGLM represents a satisfactory model. 

scholarly journals A Device to Measure a Smoker’s Puffing Topography and Real-Time Puff-By-Puff “Tar” Delivery

2014 ◽  
Vol 26 (2) ◽  
Author(s):  
Sandra J. Slayford ◽  
Barrie E. Frost
Keyword(s):  
Real Time ◽  
Light Emitting Diode ◽  
Absolute Error ◽  
Average Error ◽  
Light Emitting ◽  
Light Obscuration ◽  
Test Study ◽  
Added Benefit ◽  
Volume Characteristics ◽  
The Relationship

AbstractA device for measuring the flow, duration and volume characteristics of human puffing behaviour when smoking cigarettes is described. Cigarettes are smoked through a holder comprising a measured pressure drop across a critical orifice. The holder also contains a Light Emitting Diode (LED) and photodetector that measures light obscuration in order to estimate nicotine-free dry particulate matter (NFDPM, “tar”) delivery. All data are recorded on a puff-by-puff basis and displayed in real time. These NFDPM estimates are known as optical “tar” (OT), and are derived from the calibration of the OT measurement versus gravimetric NFDPM yields of cigarettes under a range of smoking regimes. In a test study, puff volumes from 20-80 mL were recorded to ± 6.0% of a pre-set volume, with an absolute error of 4.7 mL for an 80 mL volume drawn on a lit cigarette, and an average error of less than 2.0 mL across the range 20-80 mL. The relationship between NFDPM and OT was linear (R2 = 0.99) and accurate to ± 1.3 mg per cigarette over the range 1-23 mg per cigarette. The device provides an alternative to the widely used part filter methodology for estimating mouth level exposure with an added benefit that no further laboratory smoking replication or analysis is required. When used in conjunction with the part filter methodology, the puffing behaviour recorded can explain anomalies in the data while providing a second independent estimate.

Spatial Dynamic Analysis of a Mangeove Patch Based on Unmanned Aerial Vehicle: A Case Study in Pear Bay in Guangxi, China

2021 ◽  
Author(s):  
Xin Lin ◽  
Chungan Li ◽  
Mei Zhou ◽  
Wenhai Liang ◽  
Biao Li
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Spatial Dynamics ◽  
Absolute Error ◽  
Maximum Error ◽  
Canopy Height ◽  
Accurate Information ◽  
Maximum Absolute Error ◽  
Patch Area ◽  
Maximum Increase ◽  
Aerial Vehicle

Abstract This study investigated the short-term spatial variability of an mangrove patch, located in the Pearl Bay in Guangxi, China. Unmanned aerial vehicle (UAV) imagery covering the period from March 2015 to October 2017 were used and the following models were developed: two annual ultra-high resolution spatial resolution digital orthophoto maps (DOMs), two digital elevation models (DEMs), two digital surface models (DSMs), two canopy height models (CHMs), and a canopy height difference model (d-CHM). Using these models, the spatial dynamics of the extent and canopy height of the patch were analyzed. The resolution of the DOMs was 0.1 m, with an average geometrical error of 0.17 m and a maximum error of 0.44 m. The resolutions of DEMs, DSMs, CHMs, d-CHM were all 1 m. The average elevation errors of CHM in 2015 and 2017 were 0.002 m and -0.001 m, respectively, with maximum absolute errors of 0.034 m and 0.030 m, respectively. The average elevation error of d-CHM was -0.003 m and the maximum absolute error was 0.036 m, and the data quality were rated as good. From 2015 to 2017, the area of the mangrove patch increased from 8.16 ha to 8.79 ha, with an average annual increase of 3.7%. Specifically, the areas of expansion, shrinkage, and maximum seaward expansion were 6356 m2, 19 m2, and 24 m, respectively. The driving factor for the variability was natural processes. Stand canopy height exhibited a particular trend of decrease from northwest to southeast (horizontal; parallel to the seawall) and from the land to the sea (vertically; perpendicular to the seawall). From 2015 to 2017, 88.2% of the patch area showed increased canopy height, with an average increase of 0.78 m and a maximum increase of 3.2 m. In contrast, 11.8% of the patch area showed decreased canopy height with a maximum decrease of 3.1 m. The main reason for the decrease in canopy height was the death of trees caused by serious insect plagues. On the other hand, the reason for the increase in height could be attributed to the natural growth of mangrove trees, but further studies are required to verify the cause. UAV remote sensing has an incomparable advantage over traditional methods in that it provides extremely detailed and highly accurate information for in-depth study of the spatial evolution of mangrove patches, which would significantly contribute towards the protection and management of mangroves.

scholarly journals Method of Measuring Liquid Water Mass Fraction of Snow by Alcohol Solution

1986 ◽  
Vol 32 (112) ◽  
pp. 538-539 ◽  
Author(s):  
D. Fisk
Keyword(s):  
Liquid Water ◽  
Water Mass ◽  
Field Measurements ◽  
Absolute Error ◽  
Liquid Water Content ◽  
Snow Sample ◽  
Maximum Absolute Error ◽  
Water Fraction ◽  
Single Operator ◽  
Temperature Depression

Abstracta method of making field measurements of the liquid water fraction of snow has been developed in which a snow sample is dissolved in methanol to produce a temperature depression. The depression is linearly related to the liquid water content of the snow sample. a single operator can perform four to five measurements per hour with a maximum absolute error of 1.0%.

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