scholarly journals Identification of Daily Activites and Environments Based on the AdaBoost Method Using Mobile Device Data: A Systematic Review

Electronics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 192 ◽  
Author(s):  
José M. Ferreira ◽  
Ivan Miguel Pires ◽  
Gonçalo Marques ◽  
Nuno M. Garcia ◽  
Eftim Zdravevski ◽  
...  
Keyword(s):  
Systematic Review ◽  
Standard Deviation ◽  
Mobile Devices ◽  
Magnetic Sensors ◽  
Daily Activities ◽  
Motion Sensors ◽  
Accurate Identification ◽  
Absolute Deviation ◽  
Environment Recognition ◽  
The Mean

Using the AdaBoost method may increase the accuracy and reliability of a framework for daily activities and environment recognition. Mobile devices have several types of sensors, including motion, magnetic, and location sensors, that allow accurate identification of daily activities and environment. This paper focuses on the review of the studies that use the AdaBoost method with the sensors available in mobile devices. This research identified the research works written in English about the recognition of daily activities and environment recognition using the AdaBoost method with the data obtained from the sensors available in mobile devices that were published between 2012 and 2018. Thus, 13 studies were selected and analysed from 151 identified records in the searched databases. The results proved the reliability of the method for daily activities and environment recognition, highlighting the use of several features, including the mean, standard deviation, pitch, roll, azimuth, and median absolute deviation of the signal of motion sensors, and the mean of the signal of magnetic sensors. When reported, the analysed studies presented an accuracy higher than 80% in recognition of daily activities and environments with the Adaboost method.

scholarly journals Robust Confidence Intervals for PM2.5 Concentration Measurements in the Ecuadorian Park La Carolina

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 654 ◽  
Author(s):  
Wilmar Hernandez ◽  
Alfredo Mendez ◽  
Rasa Zalakeviciute ◽  
Angela Maria Diaz-Marquez
Keyword(s):  
Air Pollution ◽  
Standard Deviation ◽  
Confidence Intervals ◽  
Quality Index ◽  
Urban Park ◽  
Absolute Deviation ◽  
The Mean ◽  
Concentration Measurements ◽  
Pm2.5 Concentration

In this article, robust confidence intervals for PM2.5 (particles with size less than or equal to 2.5   μ m ) concentration measurements performed in La Carolina Park, Quito, Ecuador, have been built. Different techniques have been applied for the construction of the confidence intervals, and routes around the park and through the middle of it have been used to build the confidence intervals and classify this urban park in accordance with categories established by the Quito air quality index. These intervals have been based on the following estimators: the mean and standard deviation, median and median absolute deviation, median and semi interquartile range, a -trimmed mean and Winsorized standard error of order a , location and scale estimators based on the Andrew’s wave, biweight location and scale estimators, and estimators based on the bootstrap- t method. The results of the classification of the park and its surrounding streets showed that, in terms of air pollution by PM2.5, the park is not at caution levels. The results of the classification of the routes that were followed through the park and its surrounding streets showed that, in terms of air pollution by PM2.5, these routes are at either desirable, acceptable or caution levels. Therefore, this urban park is actually removing or attenuating unwanted PM2.5 concentration measurements.

Cleaning of Matched License Plate Data

2002 ◽  
Vol 1804 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Stephen D. Clark ◽  
S. Grant-Muller ◽  
Haibo Chen
Keyword(s):  
Standard Deviation ◽  
Road Traffic ◽  
Statistical Test ◽  
License Plate ◽  
Mean Absolute Deviation ◽  
Test Results ◽  
Absolute Deviation ◽  
Traffic Conditions ◽  
The Third ◽  
The Mean

Three methods for identifying outlying journey time observations collected as part of a motorway license plate matching exercise are presented. Each method is examined to ensure that it is comprehensible to transport practitioners, is able to correctly classify outliers, and is efficient in its application. The first method is a crude method based on percentiles. The second uses a mean absolute deviation test. The third method is a modification of a traditional z- or t-statistical test. Results from each method and combinations of methods are compared. The preferred method is judged to be the third method alone, which uses the median rather than the mean as its measure of location and the inter-quartile range rather than the standard deviation as its measure of variability. This method is seen to be robust to both the outliers themselves and the presence of incident conditions. The effectiveness of the method is demonstrated under a number of typical and atypical road traffic conditions. In particular, the method is applied to a different section of motorway and is shown to still produce useful results.

Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median

2013 ◽  
Vol 49 (4) ◽  
pp. 764-766 ◽  
Author(s):  
Christophe Leys ◽  
Christophe Ley ◽  
Olivier Klein ◽  
Philippe Bernard ◽  
Laurent Licata
Keyword(s):  
Standard Deviation ◽  
Absolute Deviation ◽  
The Mean

scholarly journals Properties of the Standard Deviation that are Rarely Mentioned in Classrooms

2016 ◽  
Vol 38 (3) ◽  
Author(s):  
Mohammad Fraiwan Al-Saleh ◽  
Adil Eltayeb Yousif
Keyword(s):  
Standard Deviation ◽  
Coefficient Of Variation ◽  
Sample Variance ◽  
Mean Absolute Deviation ◽  
Hidden Information ◽  
Absolute Deviation ◽  
Sample Mean ◽  
The Mean ◽  
Vague Concept ◽  
Chebyshev's Inequality

Unlike the mean, the standard deviation ¾ is a vague concept. In this paper, several properties of ¾ are highlighted. These properties include the minimum and the maximum of ¾, its relationship to the mean absolute deviation and the range of the data, its role in Chebyshev’s inequality and the coefficient of variation. The hidden information in the formula itself is extracted. The confusion about the denominator of the sample variance being n ¡ 1 is also addressed. Some properties of the sample mean and varianceof normal data are carefully explained. Pointing out these and other properties in classrooms may have significant effects on the understanding and the retention of the concept.

scholarly journals PROPOSTA DI UNA FUNZIONE UTILITÀ DIPENDENTE DALL’UTILITÀ ATTESA E DALLA DISPERSIONE DELLE UTILITÀ

2014 ◽  
Author(s):  
Vittorio B. Frosini
Keyword(s):  
Standard Deviation ◽  
Expected Utility ◽  
Dispersion Measure ◽  
Risk Averse ◽  
Mean Absolute Deviation ◽  
Summary Statistic ◽  
Absolute Deviation ◽  
The Mean ◽  
Condition C ◽  
Substitution Axiom

The author develops the properties and implications of a proposal, concerning a summary statistic of the random prospect of utilities. Following a suggestion of Maurice Allais, such a statistic is increasing with expected utility, and decreasing – for most people, who are risk averse – with the mean absolute deviation of utilities; a parameter multiplying this dispersion measure allows for risk averse or risk prone behaviour, according to its sign, and also for more or less departure from a certain prospect. It is demonstrated that this statistic (a) satisfies the first stochastic dominance, (b) satisfies the independence condition, (c) satisfies the so called “problem of probabilistic insurance”, (d) resolves the paradoxes of Allais, Ellsberg and Kahneman-Tversky (paradox of the substitution axiom), (e) the mean absolute deviation from the mean cannot be replaced by the standard deviation.

scholarly journals MAD saccade: statistically robust saccade threshold estimation

2019 ◽  
Author(s):  
Benjamin Voloh ◽  
Marcus Watson ◽  
Seth König ◽  
Thilo Womelsdorf
Keyword(s):  
Standard Deviation ◽  
Marked Improvement ◽  
Common Method ◽  
Robust Estimator ◽  
Classification Algorithms ◽  
Threshold Estimation ◽  
False Negatives ◽  
Absolute Deviation ◽  
The Mean ◽  
Modified Algorithm

Saccade detection is a critical step in the analysis of gaze data. A common method for saccade detection is to use a simple threshold for velocity or acceleration values, which is typically estimated from the data using the mean and standard deviation. However, this method has the downside of being influenced by the very signal it is trying to detect, the outlying velocities or accelerations that occur during saccades. We propose instead to use the median absolute deviation (MAD), a robust estimator of the standard deviation that is not influenced by outliers. We modify an algorithm proposed by Nyström and colleagues, and quantify saccade detection performance in both simulated and human data. Our modified algorithm shows a significant and marked improvement in saccade detection, showing both more true positives and less false negatives. We conclude that robust estimators can be widely adopted in other common, automatic gaze classification algorithms due to their ease of implementation.

scholarly journals Is The Timed-Up and Go Test Feasible in Mobile Devices? A Systematic Review

Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 528 ◽  
Author(s):  
Vasco Ponciano ◽  
Ivan Miguel Pires ◽  
Fernando Reinaldo Ribeiro ◽  
Gonçalo Marques ◽  
Nuno M. Garcia ◽  
...  
Keyword(s):  
Systematic Review ◽  
Older Adults ◽  
Mobile Devices ◽  
Inertial Sensors ◽  
Dynamic Balance ◽  
Well Being ◽  
State Transitions ◽  
Motion Sensors ◽  
Timed Up And Go ◽  
Test Execution

The number of older adults is increasing worldwide, and it is expected that by 2050 over 2 billion individuals will be more than 60 years old. Older adults are exposed to numerous pathological problems such as Parkinson’s disease, amyotrophic lateral sclerosis, post-stroke, and orthopedic disturbances. Several physiotherapy methods that involve measurement of movements, such as the Timed-Up and Go test, can be done to support efficient and effective evaluation of pathological symptoms and promotion of health and well-being. In this systematic review, the authors aim to determine how the inertial sensors embedded in mobile devices are employed for the measurement of the different parameters involved in the Timed-Up and Go test. The main contribution of this paper consists of the identification of the different studies that utilize the sensors available in mobile devices for the measurement of the results of the Timed-Up and Go test. The results show that mobile devices embedded motion sensors can be used for these types of studies and the most commonly used sensors are the magnetometer, accelerometer, and gyroscope available in off-the-shelf smartphones. The features analyzed in this paper are categorized as quantitative, quantitative + statistic, dynamic balance, gait properties, state transitions, and raw statistics. These features utilize the accelerometer and gyroscope sensors and facilitate recognition of daily activities, accidents such as falling, some diseases, as well as the measurement of the subject’s performance during the test execution.

Use of Trimmed Duplicates Derived from Laboratory Data To Estimate Standard Deviation

1994 ◽  
Vol 77 (6) ◽  
pp. 1660-1663
Author(s):  
Richard L Johnson ◽  
George W Latimer ◽  
Cliff Spiegelman
Keyword(s):  
Standard Deviation ◽  
Normal Distribution ◽  
Laboratory Data ◽  
Interquartile Range ◽  
Mean Absolute Deviation ◽  
Robust Estimators ◽  
Absolute Deviation ◽  
Mean Squared Errors ◽  
The Mean ◽  
Estimate Standard Deviation

Abstract Improved standard deviation estimates from possibly biased duplicate measurements can be derived from appropriately trimmed plots of standard deviation estimates using pairs of replicates vs the quantiles of a half-normal distribution. Simulated studies show that these estimates exhibit generally lower mean-squared errors and biases than do more standard robust estimators of location—¾ times the interquartile range and 3/2 times the mean absolute deviation from the median.

scholarly journals EMPIRICAL COMPARISON OF RELATIVE PRECISION OF GEOMETRIC MEASURE OF VARIATION ABOUT THE MEAN AND STANDARD DEVIATION

2021 ◽  
Author(s):  
Benedict Troon
Keyword(s):  
Standard Deviation ◽  
Mean Squared Error ◽  
Mean Deviation ◽  
Efficiency Coefficient ◽  
Average Deviation ◽  
Statistical Tool ◽  
Absolute Deviation ◽  
Geometric Measure ◽  
Measures Of Dispersion ◽  
The Mean

Measure of dispersion is an important statistical tool used to illustrate the distribution of datasets.The use of this measure has allowed researchers to define the distribution of various datasets especially the measures of dispersion from the mean. Researchers have been able to develop measures of dispersion from the mean such as mean deviation, mean absolute deviation, variance and standard deviation. Studies have shown that standard deviation is currently the most efficient measure of variation about the mean and the most popularly used measure of variation about the mean around the world because of its fewer shortcomings. However, studies have also established that standard deviation is not 100% efficient because the measure is affected by outlier in thedatasets and it also assumes symmetry of datasets when estimating the average deviation about the mean a factor that makes it to be responsive to skewed datasets hence giving results which are biased for such datasets. The aim of this study is to make a comparative analysis of the precision of the geometric measure of variation and standard deviation in estimating the average variationabout the mean for various datasets. The study used paired t-test to test the difference in estimates given by the two measures and four measures of efficiency (coefficient of variation, relative efficiency, mean squared error and bias) to assess the efficiency of the measure. The results determined that the estimates of geometric measure were significantly smaller than those of standard deviation and that the geometric measure was more efficient in estimating the average deviation for geometric, skewed and peaked datasets. In conclusion, the geometric measure was not affected by outliers and skewed datasets, hence it was more precise than standard deviation.

scholarly journals Recognition of Activities of Daily Living and Environments Using Acoustic Sensors Embedded on Mobile Devices

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1499 ◽  
Author(s):  
Ivan Miguel Pires ◽  
Gonçalo Marques ◽  
Nuno M. Garcia ◽  
Nuno Pombo ◽  
Francisco Flórez-Revuelta ◽  
...  
Keyword(s):  
Neural Networks ◽  
Activities Of Daily Living ◽  
Mobile Devices ◽  
Daily Living ◽  
Feedforward Neural Networks ◽  
Magnetic Sensors ◽  
Acoustic Sensors ◽  
Environment Recognition ◽  
The One ◽  
Classification Procedures

The identification of Activities of Daily Living (ADL) is intrinsic with the user’s environment recognition. This detection can be executed through standard sensors present in every-day mobile devices. On the one hand, the main proposal is to recognize users’ environment and standing activities. On the other hand, these features are included in a framework for the ADL and environment identification. Therefore, this paper is divided into two parts—firstly, acoustic sensors are used for the collection of data towards the recognition of the environment and, secondly, the information of the environment recognized is fused with the information gathered by motion and magnetic sensors. The environment and ADL recognition are performed by pattern recognition techniques that aim for the development of a system, including data collection, processing, fusion and classification procedures. These classification techniques include distinctive types of Artificial Neural Networks (ANN), analyzing various implementations of ANN and choosing the most suitable for further inclusion in the following different stages of the developed system. The results present 85.89% accuracy using Deep Neural Networks (DNN) with normalized data for the ADL recognition and 86.50% accuracy using Feedforward Neural Networks (FNN) with non-normalized data for environment recognition. Furthermore, the tests conducted present 100% accuracy for standing activities recognition using DNN with normalized data, which is the most suited for the intended purpose.

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