The Statistical Meaning of Kurtosis and Its New Application to Identification of Persons Based on Seismic Signals

Liang, Zhiqiang; Wei, Jianming; Zhao, Junyu; Liu, Haitao; Li, Baoqing; Shen, Jie; Zheng, Chunlei

doi:10.3390/s8085106

Cited by 39 publications

(20 citation statements)

References 11 publications

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“…Afterwards, the signals can be classified using artificial intelligence methods. For example, spectral analysis for discriminating between seismic events caused by animal's footsteps, cadence [78] (the interval between events (footsteps)) and kurtosis [87] (degree of peakedness of a distribution) are used for footstep detection. In the domain of human sensing, seismic waves have been used to detect presence of humans [88,89], tracking and bearing estimation [90].…”

Section: Technologies For Eulerian Approachmentioning

confidence: 99%

Sensing Solutions for Collecting Spatio-Temporal Data for Wildlife Monitoring Applications: A Review

Baratchi

Meratnia

Havinga

et al. 2013

Sensors

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Movement ecology is a field which places movement as a basis for understanding animal behavior. To realize this concept, ecologists rely on data collection technologies providing spatio-temporal data in order to analyze movement. Recently, wireless sensor networks have offered new opportunities for data collection from remote places through multi-hop communication and collaborative capability of the nodes. Several technologies can be used in such networks for sensing purposes and for collecting spatio-temporal data from animals. In this paper, we investigate and review technological solutions which can be used for collecting data for wildlife monitoring. Our aim is to provide an overview of different sensing technologies used for wildlife monitoring and to review their capabilities in terms of data they provide for modeling movement behavior of animals.

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Section: Technologies For Eulerian Approachmentioning

confidence: 99%

Sensing Solutions for Collecting Spatio-Temporal Data for Wildlife Monitoring Applications: A Review

Baratchi

Meratnia

Havinga

et al. 2013

Sensors

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“…It is perhaps helpful to visualise in terms of the dispersion of the Z 2 distribution about 1 (Moors, 1986) and is a measure of the shape of the distribution tails; high kurtosis represents strong central tendency, and lower values represent heavy tails (Balanda & MacGillivray, 1988). Accordingly, some commentators also frame kurtosis in terms of the 'shoulder' size of a distribution (Liang et al, 2008). Student (Student, 1927) used the images in Figure 1 as a novel way of visualising kurtosis.…”

Section: Introductionmentioning

confidence: 99%

A simple method for optimising transformation of non-parametric data: an illustration by reference to cortisol assays

Clark

Osborne

Gallagher

et al. 2016

Hum. Psychopharmacol Clin Exp

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Neuroendocrine data are typically positively skewed and rarely conform to the expectations of a Gaussian distribution. This can be a problem when attempting to analyse results within the framework of the general linear model, which relies on assumptions that residuals in the data are normally distributed. One frequently used method for handling violations of this assumption is to transform variables to bring residuals into closer alignment with assumptions (as residuals are not directly manipulated). This is often attempted through ad hoc traditional transformations such as square root, log and inverse. However, Box and Cox (Box & Cox, ) observed that these are all special cases of power transformations and proposed a more flexible method of transformation for researchers to optimise alignment with assumptions. The goal of this paper is to demonstrate the benefits of the infinitely flexible Box-Cox transformation on neuroendocrine data using syntax in spss. When applied to positively skewed data typical of neuroendocrine data, the majority (~2/3) of cases were brought into strict alignment with Gaussian distribution (i.e. a non-significant Shapiro-Wilks test). Those unable to meet this challenge showed substantial improvement in distributional properties. The biggest challenge was distributions with a high ratio of kurtosis to skewness. We discuss how these cases might be handled, and we highlight some of the broader issues associated with transformation. Copyright © 2016 John Wiley & Sons, Ltd.

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“…Çalışmalarında insan adımının anlık kuvvetler sonucu sinyal oluşturduğunu ve bu özelliği sayesinde diğer sinyal kaynaklarından ayırt edilebileceğini söylemişlerdir. Kurtosisin istatiksel anlamını inceleyen yazarlar, makalelerinde insan tespitinde kurtosis kullanımı hakkında detaylar vermişlerdir [14]. Kurtosisin incelenmesiyle hedef tespit etkinliğinin araştırılması için gerçekleştirilen bir diğer çalışmada, Jin ve ark.…”

Section: Gi̇ri̇ş (Introduction)unclassified

Zemi̇n Ti̇treşi̇mleri̇ Ölçümü Ve Anali̇zi̇ İle İnsan Hedefleri̇n Tespi̇ti̇

Ermiş¹,

Yurttadur²,

Karaçay³

2015

Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi

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ÖZETHareket halindeki insanlar zemin üzerinde birbirlerini takip eden darbeler şeklinde zorlamalar oluştururlar. Darbeler sonucu zeminde bir takım düzensizlikler oluşur ve bu düzensizlikler sonucu oluşan titreşimler darbe kaynağından sismik dalgalar şeklinde yayılırlar. Zeminde oluşan bu titreşimlerinin ölçülmesi ve analizi ile insanların varlığının algılanması ve tespiti mümkündür. Bu çalışmada hedef tespiti amacıyla sismik sinyaller toplanmış ve belirli zaman aralıklarına bölünerek incelenmiştir. Bu sinyallerin ölçülebilmesi için bir deney altyapısı kurulmuş ve belirlenen ölçüm senaryoları dâhilinde bir takım deneyler gerçekleştirilmiştir. Test sonuçları zaman ve frekans tanım bölgelerinde analiz edilmiştir. Kullanılan analiz yöntemleri ile insan adımı karakteristiği çıkarılmış, adım kaynaklı darbelerin zeminde oluşturduğu zorlamalar incelenmiş ve farklı yürüyüş stillerinde bir insanın oluşturduğu sismik sinyal bileşenleri tespit edilebilmiştir. Elde edilen sonuçlar, titreşim analizi ile hedef tespiti ve tanımlaması yapılabileceğini ortaya koymaktadır. Anahtar Kelimeler: Sismik sinyaller, izinsiz girişlerin tespiti, titreşim analizi HUMAN INTRUDER DETECTION BY MEASURING AND ANALYSING GROUND VIBRATIONS ABSTRACTPeople moving on a ground generate a consecutive impact which excites the ground and vibrations spread as seismic waves expanding from the source. Seismic level vibrations could be used to detect human intruders. In this study, ground vibrations are acquired and analyzed by dividing the time history into windowed segments. In order to collect vibration signal an experimental setup is formed and different scenarios are tested. Then, test results are analyzed in time and frequency domain. Tests are exposed the walking characteristics of human as well as ground vibrations propagation components. Results show that human intrusion can be identified by ground vibration measurement and analysis.

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The Statistical Meaning of Kurtosis and Its New Application to Identification of Persons Based on Seismic Signals

Cited by 39 publications

References 11 publications

Sensing Solutions for Collecting Spatio-Temporal Data for Wildlife Monitoring Applications: A Review

Sensing Solutions for Collecting Spatio-Temporal Data for Wildlife Monitoring Applications: A Review

A simple method for optimising transformation of non-parametric data: an illustration by reference to cortisol assays

Zemi̇n Ti̇treşi̇mleri̇ Ölçümü Ve Anali̇zi̇ İle İnsan Hedefleri̇n Tespi̇ti̇

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