scholarly journals Presentation of Coupling Analysis Techniques of Maximum and Minimum Values Between N Sets of Data Using Matrix [µ][MKN]

2021 ◽  
Vol 6 (4) ◽  
pp. 1127-1136
Author(s):  
K. N. Makris ◽  
I. Vonta
Keyword(s):  
Time Series ◽  
Indirect Method ◽  
Direct Method ◽  
Time Dependent ◽  
Data Sets ◽  
Data Display ◽  
Coupling Analysis ◽  
Time Points ◽  
Analysis Techniques ◽  
Coupling Techniques

This paper deals with the presentation and study of alternative coupling techniques for maximum and minimum values between data sets, namely the problem which is examined in this work is the possible appearance of maximum or minimum values between data sets in the same or neighboring time points. The data can be time-dependent (time series) or non-time-dependent. In this work, the analysis is focused on time series and novel indices are defined in order to measure whether the values of N sets of data display in terms of time, the maximum or minimum values at the same instances or at very close instances. For this purpose, two methods will be compared, one direct method and one indirect method. The indirect method is based on Matrices of dimensionless indicators which are denoted by [μ][MKN], and the direct method is based on a variance-type measure which is denoted by [V][MKN].

scholarly journals On Similarity Measures for Stochastic and Statistical Modeling

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 840
Author(s):  
Konstantinos Makris ◽  
Ilia Vonta ◽  
Alex Karagrigoriou
Keyword(s):  
Time Series ◽  
Statistical Modeling ◽  
Similarity Measures ◽  
Epidemiological Data ◽  
Time Dependent ◽  
Dependent Data ◽  
Data Sets ◽  
Data Set ◽  
Time Points ◽  
Statistical Functions

In this work, our goal is to present and discuss similarity techniques for ordered observations between time series and non-time dependent data. The purpose of the study was to measure whether ordered observations of data sets are displayed at or close to, the same time points for the case of time series and with the same or similar frequencies for the case of non-time dependent data sets. A simultaneous time pairing and comparison can be achieved effectively via indices, advanced indices and the associated index matrices based on statistical functions of ordered observations. Hence, in this work we review some previously defined standard indices and propose new advanced dimensionless indices and the associated index matrices which are both easily interpreted and provide efficient comparison of the series involved. Furthermore, the proposed methodology allows the analysis of data with different units of measurement as the indices presented are dimensionless. The applicability of the proposed methodology is explored through an epidemiological data set on influenza-like-illness (ILI). We finally provide a thorough discussion on all parameters involved in the proposed indices for practical purposes along with examples.

Spike detection using a multiresolution entropy based method

2018 ◽  
Vol 63 (4) ◽  
pp. 361-376 ◽  
Author(s):  
Sajjad Farashi
Keyword(s):  
Time Series ◽  
Sliding Window ◽  
Entropy Method ◽  
Time Dependent ◽  
Final Decision ◽  
Data Sets ◽  
Decision Threshold ◽  
Spike Detection ◽  
Neural Data ◽  
Window Approach

Abstract Correct interpretation of neural mechanisms depends on the accurate detection of neuronal activities, which become visible as spikes in the electrical activity of neurons. In the present work, a novel entropy based method is proposed for spike detection which employs the fact that transient spike events change the entropy level of the neural time series. In this regard, the time-dependent entropy method can be used for detecting spike times, where the entropy of a selected segment of a neural time series, using a sliding window approach, is calculated and the time of the events are highlighted by sharp peaks in the output of the time-dependent entropy method. It is shown that the length of the sliding window determines the resolution of the time series in entropy space, therefore, the calculation is performed with a different window length for obtaining a multiresolution transform. The final decision threshold for detecting spike events is applied to the point-wise product of the time dependent entropy calculations with different resolutions. The proposed detection method has been assessed using several simulated and real neural data sets. The results show that the proposed method detects spikes in their exact times while compared with other traditional methods, relatively lower false alarm rate is obtained.

scholarly journals محاولات المدرس لتعزيز دوافع الطالبات في مهارة الكلام بالمدرسة الفتيان التعليمي أتشية

2021 ◽  
Vol 10 (3) ◽  
pp. 436
Author(s):  
Feni Zumara ◽  
Qusaiyen Qusaiyen ◽  
Fajriah Fajriah
Keyword(s):  
Data Collection ◽  
Qualitative Method ◽  
Direct Method ◽  
Arabic Language ◽  
Data Display ◽  
Analysis Techniques ◽  
Data Collection And Analysis ◽  
Collection Data ◽  
Speaking Skill ◽  
A Direct Method

This research aims to see and find out the efforts that made by the teacher of Al-Fityan School Aceh to motivate students in speaking skill. The research method used is descriptive qualitative method. The researcher used the theory of Miles and Huberman as the way of data collection and analysis techniques. There are four stages of the techniques, they are: data collection, data reduction, data presentation(data display) andconclusion drawing/verification. The results of this research is the researcher found that the teacher tried to motivate the students in several ways, including: (1) The method that used by the teacher of Al-Fityan School Aceh is a direct method (thariqah mubasyarah) where the method is using Arabic language directly in daily activity without using mother tounge. 2) The use of learning method such as mumarasah takallum al-lughah arabiyyah and expression of language habituation program. (3) The use of media such as picture (shurah), poster (lauhah), and video..

An example of spectrum imaging used for comparison of EELS quantitative analysis techniques on Al-Li

1991 ◽  
Vol 49 ◽  
pp. 726-727
Author(s):  
John A. Hunt
Keyword(s):  
Quantitative Analysis ◽  
Large Data ◽  
Difference Spectrum ◽  
Large Data Sets ◽  
Foil Thickness ◽  
Data Sets ◽  
Analysis Techniques ◽  
Spectrum Imaging ◽  
Normal Spectrum ◽  
Electron Energy Loss

Spectrum-imaging is a useful technique for comparing different processing methods on very large data sets which are identical for each method. This paper is concerned with comparing methods of electron energy-loss spectroscopy (EELS) quantitative analysis on the Al-Li system. The spectrum-image analyzed here was obtained from an Al-10at%Li foil aged to produce δ' precipitates that can span the foil thickness. Two 1024 channel EELS spectra offset in energy by 1 eV were recorded and stored at each pixel in the 80x80 spectrum-image (25 Mbytes). An energy range of 39-89eV (20 channels/eV) are represented. During processing the spectra are either subtracted to create an artifact corrected difference spectrum, or the energy offset is numerically removed and the spectra are added to create a normal spectrum. The spectrum-images are processed into 2D floating-point images using methods and software described in [1].

THE IMPLEMENTATION OF RADIN INTEN II’S NATIONALISM RESISTANCE VALUES WITHIN LOCAL HISTORY LEARNING

Ta dib ◽  
2020 ◽  
Vol 23 (2) ◽  
pp. 145
Author(s):  
Surandi Surandi ◽  
Supardi Supardi ◽  
Johan Setiawan
Keyword(s):  
Data Collection ◽  
Learning Process ◽  
Local History ◽  
Data Display ◽  
Analysis Techniques ◽  
Learning Plan ◽  
History Learning ◽  
Collection Data ◽  
Students Attitudes

Abstract: The purposes of this study are to find out: (1) the implementation of Radin Inten II’s resistance nationalism values in the learning process; (2) the obstacles experienced by teachers when implementing Radin Inten II’s resistance nationalism values in the learning process; (3) the efforts made by teachers in overcoming obstacles during the implementation of Radin Inten II’s nationalism values in the learning process. This study used qualitative approach with the type of case study conducted at SMAN 1 Kalianda. Data collection techniques consisted of observation, interviews, and documentary studies. Data analysis techniques used the model of Miles & Huberman consisting of data collection, data reduction, data display, and conclusion. The results show: (1) the implementation of Radin Inten II’s nationalism resistance values in the process of learning local history was carried out by compiling a syllabus and implementing learning plan (RPP) by incorporating local history into Indonesian historical material which was consisted of planning, implementation, and evaluation, (2) the obstacles experienced by teachers included: the ability of teachers during learning process, students’ attitudes, and time constraints, (3) the efforts made by the teacher were taking the initiative to instill the values of nationalism in the resistance of Radin Inten II’s, applying various models, strategies, methods and singing a national song before learning. Abstrak: Tujuan penelitian ini adalah untuk mengetahui: (1) implementasi nilai-nilai nasionalisme perlawanan Radin Inten II dalam proses pembelajaran, (2) kendala yang dialami oleh guru saat implementasi nilai-nilai nasionalisme perlawanan Radin Inten II dalam proses pembelajaran, (3) upaya yang dilakukan guru dalam mengatasi kendala yang dihadapi saat implementasi nilai-nilai nasionalisme perlawanan Radin Inten II dalam proses pembelajaran. Penelitian ini menggunakan pendekatan kualitatif dengan jenis studi kasus di SMAN 1 Kalianda. Teknik pengumpulan data terdiri dari observasi, wawancara, dan dokumentasi. Teknik analisis data menggunakan model Miles & Huberman yang terdiri dari pengumpulan data, reduksi data, penyajian data, dan penarikan kesimpulan. Hasil penelitian menunjukkan: (1) implementasi nilai-nilai nasionalisme perlawanan Radin Inten II dalam proses pembelajaran sejarah lokal dilakukan dengan menyusun silabus dan rencana pelaksana pembelajaran (RPP) dengan memasukkan sejarah lokal kedalam materi sejarah Indonesia yang terdiri dari perencanaan, pelaksanaan, dan evaluasi, (2) kendala yang dialami oleh guru diantaranya: kemampuan guru dalam proses pembelajaran, sikap siswa, dan adanya keterbatasan waktu, (3) upaya yang dilakukan oleh guru yaitu berinisiatif menanamkan nilai-nilai nasionalisme dalam perlawanan Radin Inten II, menerapkan berbagai model, strategi, metode dan menyanyikan lagu nasional sebelum pembelajaran.

scholarly journals Interpretation of the Chemical and Physical Time-Series Retrieved from Sentik Glacier, Ladakh Himalaya, India

1984 ◽  
Vol 30 (104) ◽  
pp. 66-76 ◽  
Author(s):  
Paul A. Mayewski ◽  
W. Berry Lyons ◽  
N. Ahmad ◽  
Gordon Smith ◽  
M. Pourchet
Keyword(s):  
Time Series ◽  
Chemical Species ◽  
Data Sets ◽  
Reactive Iron ◽  
Physical Time ◽  
Ladakh Himalaya ◽  
Data Density ◽  
Mass Circulation ◽  
The Himalaya ◽  
Analysis Of Time Series

AbstractSpectral analysis of time series of a c. 17 ± 0.3 year core, calibrated for total ß activity recovered from Sentik Glacier (4908m) Ladakh, Himalaya, yields several recognizable periodicities including subannual, annual, and multi-annual. The time-series, include both chemical data (chloride, sodium, reactive iron, reactive silicate, reactive phosphate, ammonium, δD, δ(18O) and pH) and physical data (density, debris and ice-band locations, and microparticles in size grades 0.50 to 12.70 μm). Source areas for chemical species investigated and general air-mass circulation defined from chemical and physical time-series are discussed to demonstrate the potential of such studies in the development of paleometeorological data sets from remote high-alpine glacierized sites such as the Himalaya.

scholarly journals An edge-cloud collaboration architecture for pattern anomaly detection of time series in wireless sensor networks

2021 ◽  
Author(s):  
Cong Gao ◽  
Ping Yang ◽  
Yanping Chen ◽  
Zhongmin Wang ◽  
Yue Wang
Keyword(s):  
Time Series ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Anomaly Detection ◽  
Estimation Method ◽  
Feature Representation ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Data Sets ◽  
Edge Node

AbstractWith large deployment of wireless sensor networks, anomaly detection for sensor data is becoming increasingly important in various fields. As a vital data form of sensor data, time series has three main types of anomaly: point anomaly, pattern anomaly, and sequence anomaly. In production environments, the analysis of pattern anomaly is the most rewarding one. However, the traditional processing model cloud computing is crippled in front of large amount of widely distributed data. This paper presents an edge-cloud collaboration architecture for pattern anomaly detection of time series. A task migration algorithm is developed to alleviate the problem of backlogged detection tasks at edge node. Besides, the detection tasks related to long-term correlation and short-term correlation in time series are allocated to cloud and edge node, respectively. A multi-dimensional feature representation scheme is devised to conduct efficient dimension reduction. Two key components of the feature representation trend identification and feature point extraction are elaborated. Based on the result of feature representation, pattern anomaly detection is performed with an improved kernel density estimation method. Finally, extensive experiments are conducted with synthetic data sets and real-world data sets.

scholarly journals A Hypothesis Test for the Goodness-of-Fit of the Marginal Distribution of a Time Series with Application to Stablecoin Data

2021 ◽  
Vol 5 (1) ◽  
pp. 10
Author(s):  
Mark Levene
Keyword(s):  
Time Series ◽  
Goodness Of Fit ◽  
Marginal Distribution ◽  
Hypothesis Test ◽  
Data Sets ◽  
Test Statistic ◽  
Sample Test ◽  
Kolmogorov Smirnov ◽  
Heavy Tailed ◽  
Jensen Shannon Divergence

A bootstrap-based hypothesis test of the goodness-of-fit for the marginal distribution of a time series is presented. Two metrics, the empirical survival Jensen–Shannon divergence (ESJS) and the Kolmogorov–Smirnov two-sample test statistic (KS2), are compared on four data sets—three stablecoin time series and a Bitcoin time series. We demonstrate that, after applying first-order differencing, all the data sets fit heavy-tailed α-stable distributions with 1<α<2 at the 95% confidence level. Moreover, ESJS is more powerful than KS2 on these data sets, since the widths of the derived confidence intervals for KS2 are, proportionately, much larger than those of ESJS.

scholarly journals Onboard Radio Frequency Interference as the Origin of Inter-Satellite Biases for Microwave Humidity Sounders

2019 ◽  
Vol 11 (7) ◽  
pp. 866 ◽  
Author(s):  
Imke Hans ◽  
Martin Burgdorf ◽  
Stefan A. Buehler
Keyword(s):  
Time Series ◽  
Radio Frequency ◽  
Time Dependent ◽  
Radio Frequency Interference ◽  
Climate Variables ◽  
Compelling Evidence ◽  
Climate Data ◽  
The Earth ◽  
Correction Scheme

Understanding the causes of inter-satellite biases in climate data records from observations of the Earth is crucial for constructing a consistent time series of the essential climate variables. In this article, we analyse the strong scan- and time-dependent biases observed for the microwave humidity sounders on board the NOAA-16 and NOAA-19 satellites. We find compelling evidence that radio frequency interference (RFI) is the cause of the biases. We also devise a correction scheme for the raw count signals for the instruments to mitigate the effect of RFI. Our results show that the RFI-corrected, recalibrated data exhibit distinctly reduced biases and provide consistent time series.

scholarly journals Three-dimensional deformation time series of glacier motion from multiple-aperture DInSAR observation

2019 ◽  
Vol 93 (12) ◽  
pp. 2651-2660 ◽  
Author(s):  
Sergey Samsonov
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Ground Deformation ◽  
Three Dimensional ◽  
Data Sets ◽  
Ice Flow ◽  
The North ◽  
Glacier Ice ◽  
Deformation Component ◽  
3D Deformation

AbstractThe previously presented Multidimensional Small Baseline Subset (MSBAS-2D) technique computes two-dimensional (2D), east and vertical, ground deformation time series from two or more ascending and descending Differential Interferometric Synthetic Aperture Radar (DInSAR) data sets by assuming that the contribution of the north deformation component is negligible. DInSAR data sets can be acquired with different temporal and spatial resolutions, viewing geometries and wavelengths. The MSBAS-2D technique has previously been used for mapping deformation due to mining, urban development, carbon sequestration, permafrost aggradation and pingo growth, and volcanic activities. In the case of glacier ice flow, the north deformation component is often too large to be negligible. Historically, the surface-parallel flow (SPF) constraint was used to compute the static three-dimensional (3D) velocity field at various glaciers. A novel MSBAS-3D technique has been developed for computing 3D deformation time series where the SPF constraint is utilized. This technique is used for mapping 3D deformation at the Barnes Ice Cap, Baffin Island, Nunavut, Canada, during January–March 2015, and the MSBAS-2D and MSBAS-3D solutions are compared. The MSBAS-3D technique can be used for studying glacier ice flow at other glaciers and other surface deformation processes with large north deformation component, such as landslides. The software implementation of MSBAS-3D technique can be downloaded from http://insar.ca/.

Sign in / Sign up

Export Citation Format

Share Document