scholarly journals Sentinel-1 Data Processing for Detecting and Monitoring of Ground Instabilities in the Rocky Coast of Central Asturias (N Spain)

2021 ◽  
Vol 13 (16) ◽  
pp. 3076
Author(s):  
José Cuervas-Mons ◽  
María José Domínguez-Cuesta ◽  
Félix Mateos Redondo ◽  
Anna Barra ◽  
Oriol Monserrat ◽  
...  
Keyword(s):  
Time Series ◽  
Local Study ◽  
Deformation Velocity ◽  
Unsupervised Approach ◽  
Coastal Retreat ◽  
Dataset Analysis ◽  
Rocky Coast ◽  
Comparison Of The Results ◽  
The University ◽  
Professional Tool

The cliff coastline of the central region of Asturias (N Spain) is severely affected by terrain instabilities, causing considerable damage to properties and infrastructures every year. In this study, we applied the A-DInSAR technique based on Sentinel-1 imagery to map and monitor active slopes in an emblematic rocky area of the Asturian coast: the Peñas Cape. The A-DInSAR dataset analysis has been focused at regional and local scales. For the local scale assessment, six areas were selected based on previous work and the landslide database of the Principality of Asturias region (BAPA-Base de datos de Argayos del Principado de Asturias), created by the University of Oviedo. The processing of the data has been performed using two independent sets of processing tools: the PSIG software tools, a professional tool and, the GEP service, an unsupervised platform. The dataset consisted of 113 SAR IW-SLC images acquired by the Sentinel-1 A/B satellites between January 2018 and February 2020. LOS mean deformation velocity maps (mm year−1) and deformation time series (mm) were obtained by PSIG and GEP software, allowing coastal areas with landslide incidence and other terrain movements to be distinguished. Deformation motion has been estimated from PSIG VLOS rates to be from −17.1 to 37.4 mm year−1 and GEP VLOS rates from −23.0–38.3 mm year−1. According to deformation time series (mm), the minimum and maximum accumulated displacements are −68.5–78.8 and −48.8–77.0 mm by means of PSIG and GEP, respectively. These ground motions could be associated with coastal instabilities related to marine activity and coastal retreat, both at regional and local study scales. The main contributions of this work are: (1) the demonstration of the potential of A-DInSAR techniques to evaluate coastal instabilities in a coastal retreat context and (2) the comparison of the results provided by the two sets of tools, which allowed the ground motion to be assessed by using an unsupervised approach vs. a contrasted one (robust software). This study increases the knowledge about coastal instabilities and other ground movements along the rocky coast and cliffs of Central Asturias. As a conclusion for the future, we believe that this work highlights the evaluated methods as significant tools to support the management of coastal territories with jagged and rocky coastlines.

Perceptions, Attitudes and Use of Pharmacy Customers to Medicine Labels

2021 ◽  
pp. 58-70
Author(s):  
Eman Elmahjoubi ◽  
Mufida Yamane
Keyword(s):  
Structured Interview ◽  
University Hospital ◽  
High Rate ◽  
Foreign Languages ◽  
Local Study ◽  
The Public ◽  
Interview Technique ◽  
Written Information ◽  
Awareness Programs ◽  
The University

Background. The safe use of medicines largely relies on consumers reading the labeling and packaging carefully and accurately, and being able to comprehend and act on the information presented. We aimed to conduct local study on consumers’ perceptions, attitudes and use of written drug information. Methods. A survey included 200 adults of the public in 13 community pharmacies and one main hospital (the University Hospital) in Tripoli city of Libya, using a structured interview technique. Results. The results showed that 73% of participants read drug labels with variation from always (39.72 %) to rarely (10.95%). About 42.46% of pharmacy customers read the Patients Package Inserts (PPIs) routinely, however; 53.42% of them faced difficulties in understanding the labelling. Foreign languages and small font sizes of written information were the most barriers to participants` comprehensibility (44.69 %, 34%) respectively. The findings indicated that 59 % of the respondents were used to obtain information from pharmacists. Despite the relatively high rate of reading to drug labels among pharmacy customers; more than half of them were unable to interpret information correctly. Conclusion. The study demonstrated the need for the implementation of educational and awareness programs for patients by pharmacists to improve the health literacy of medication labels. Steps must be taken to ensure that medicines in Libyan market are supplied with bilingual and non-technical language labels.

An Efficient Method for Forecasting Using Fuzzy Time Series

2017 ◽  
pp. 287-304 ◽  
Author(s):  
Pritpal Singh
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Weather Forecasting ◽  
Small Error ◽  
Fuzzy Time Series ◽  
Series Data ◽  
Data Sets ◽  
Proposed Model ◽  
Temperature Forecasting ◽  
The University

Forecasting using fuzzy time series has been applied in several areas including forecasting university enrollments, sales, road accidents, financial forecasting, weather forecasting, etc. Recently, many researchers have paid attention to apply fuzzy time series in time series forecasting problems. In this paper, we present a new model to forecast the enrollments in the University of Alabama and the daily average temperature in Taipei, based on one-factor fuzzy time series. In this model, a new frequency based clustering technique is employed for partitioning the time series data sets into different intervals. For defuzzification function, two new principles are also incorporated in this model. In case of enrollments as well daily temperature forecasting, proposed model exhibits very small error rate.

scholarly journals Mapping deciduous forests by using time series of filtered MODIS NDVI and neural networks

CERNE ◽  
2010 ◽  
Vol 16 (2) ◽  
pp. 123-130 ◽  
Author(s):  
Thomaz Chaves de Andrade Oliveira ◽  
Luis Marcelo Tavares de Carvalho ◽  
Luciano Teixeira de Oliveira ◽  
Adriana Zanella Martinhago ◽  
Fausto Weimar Acerbi Júnior ◽  
...  
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Vegetation Indices ◽  
Deciduous Forests ◽  
Modis Ndvi ◽  
Minas Gerais State ◽  
Ndvi Time Series ◽  
Multi Temporal ◽  
Comparison Of The Results ◽  
Filtering Techniques

Multi-temporal images are now of standard use in remote sensing of vegetation during monitoring and classification. Temporal vegetation signatures (i. e., vegetation indices as functions of time) generated, poses many challenges, primarily due to signal to noise-related issues. This study investigates which methods generate the most appropriate smoothed curves of vegetation signatures on MODIS NDVI time series. The filtering techniques compared were the HANTS algorithm which is based on Fourier analyses and Wavelet temporal algorithm which uses the wavelet analysis to generate the smoothed curves. The study was conducted in four different regions of the Minas Gerais State. The smoothed data were used as input data vectors for vegetation classification by means of artificial neural networks for comparison purpose. A comparison of the results was ultimately discussed in this work showing encouraging results and similarity between the two filtering techniques used.

scholarly journals High-Order Fuzzy Time Series Model Based on Generalized Fuzzy Logical Relationship

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Wangren Qiu ◽  
Xiaodong Liu ◽  
Hailin Li
Keyword(s):  
Time Series ◽  
Stock Exchange ◽  
Composite Index ◽  
High Order ◽  
Fuzzy Time Series ◽  
Time Series Models ◽  
Logical Relationship ◽  
Proposed Model ◽  
The University ◽  
Fuzzy Logical

In view of techniques for constructing high-order fuzzy time series models, there are three methods which are based on advanced algorithms, computational methods, and grouping the fuzzy logical relationships, respectively. The last kind model has been widely applied and researched for the reason that it is easy to be understood by the decision makers. To improve the fuzzy time series forecasting model, this paper presents a novel high-order fuzzy time series models denoted asGTS(M,N)on the basis of generalized fuzzy logical relationships. Firstly, the paper introduces some concepts of the generalized fuzzy logical relationship and an operation for combining the generalized relationships. Then, the proposed model is implemented in forecasting enrollments of the University of Alabama. As an example of in-depth research, the proposed approach is also applied to forecast the close price of Shanghai Stock Exchange Composite Index. Finally, the effects of the number of orders and hierarchies of fuzzy logical relationships on the forecasting results are discussed.

The Use of Single-subject Time-series Designs in Adapted Physical Activity

1984 ◽  
Vol 1 (1) ◽  
pp. 19-29 ◽  
Author(s):  
E.J. Watkinson ◽  
D.L. Wasson
Keyword(s):  
Physical Activity ◽  
Time Series ◽  
Instructional Program ◽  
Single Subject ◽  
Adapted Physical Activity ◽  
Mentally Handicapped ◽  
Instructional Programs ◽  
University Of Alberta ◽  
Reversal Design ◽  
The University

The individualized nature of instructional programs for the mentally handicapped often makes group designs inappropriate in adapted physical activity research. Single-subject time-series designs are suitable for use in investigating the acquisition, maintenance, and generalization of motor skills when the research involves small numbers of subjects. These designs require the collection of data before, and during or after treatment. Three single-subject time-series designs are described and illustrated with data from studies in the PREP Play Program, an instructional program for young mentally handicapped children at the University of Alberta. The simple time-series design has severe limitations for use as a research tool, but is appropriate for use by teachers or practitioners who are monitoring previously tested treatments in physical activity programs. The repeated time-series or reversal design can be used to investigate the maintenance or generalization of effects after treatments are withdrawn. The multiplebaseline design is recommended for researchers or practitioners who wish to assess the effects of instructional programs on different subjects or different dependent variables.

scholarly journals Study of Systematic Bias in Measuring Surface Deformation with SAR Interferometry

2020 ◽  
Author(s):  
Homa Ansari ◽  
Francesco De Zan ◽  
Alessandro Parizzi
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Sar Interferometry ◽  
Systematic Bias ◽  
Earth Surface ◽  
Phase Component ◽  
Measuring Surface ◽  
Deformation Velocity ◽  
Temporal Decorrelation ◽  
Efficient Processing

<div>This paper investigates the presence of a new interferometric signal in multilooked Synthetic Aperture Radar (SAR) interferograms which cannot be attributed to atmospheric or earth surface topography changes. The observed signal is short-lived and decays with temporal baseline; however, it is distinct from the stochastic noise usually attributed to temporal decorrelation. The presence of such fading signal introduces a systematic phase component, particularly in short temporal baseline interferograms. If unattended, it biases the estimation of Earth surface deformation from SAR time series. <br></div><div>The contribution of the mentioned phase component is quantitatively assessed. For short temporal baseline interferograms, we quantify the phase contribution to be in the regime of 5 rad at C-band. The biasing impact on deformation signal retrieval is further evaluated. As an example, exploiting a subset of short temporal baseline interferograms which connects each acquisition with the successive 5 in the time series, a significant bias of -6.5 mm/yr is observed in the estimation of deformation velocity from a four-year Sentinel-1 data stack. A practical solution for mitigation of this physical fading signal is further discussed; special attention is paid to the efficient processing of Big Data from modern SAR missions such as Sentinel-1 and NISAR. Adopting the proposed solution, the deformation bias is shown to decrease to -0.24 mm/yr for the Sentinel-1 time series.</div>Based on these analyses, we put forward our recommendations for efficient and accurate deformation signal retrieval from large stacks of multilooked interferograms.

scholarly journals ỨNG DỤNG ĐẠI SỐ GIA TỬ TRONG DỰ BÁO CHUỖI THỜI GIAN MỜ

2016 ◽  
Vol 54 (2) ◽  
pp. 161
Author(s):  
Nguyễn Cát Hồ ◽  
Nguyễn Công Điều ◽  
Vũ Như Lân
Keyword(s):  
Time Series ◽  
Time Series Forecasting ◽  
Fuzzy Time Series ◽  
Fuzzy Approach ◽  
University Of Alabama ◽  
Simple Arithmetic ◽  
Proposed Model ◽  
Improving Accuracy ◽  
The University ◽  
And Control

Fuzzy time series given by Song & Chissom (1993) in magazine "Fuzzy Sets and   Systems" has been widely studied for forecasting purposes. However, the accuracy of forecasts based on the concept of fuzzy approach of Song & Chissom is not high because of such depends on many factors. Chen (1996) proposed an efficient fuzzy time series model which consists of simple arithmetic calculations only. After that, this has been widely studied for improving accuracy of forecasting in many applications to get better results. The hedge algebras developed by Nguyen and Wechler (1990) was completely different from the fuzzy approach. Here the hedge algebras was used to model  linguistic domains and variables and their semantic structure is obtained. Instead of performing fuzzification and defuzzification, more simple methods are adopted, termed as semantization and desemantization, respectively. The hedge algebras based fuzzy system is a new topic, which was first applied to fuzzy control 2008 [16]. Hedge algebras applications for some specific problems in the field of information technology and control has a number of important results and confirm advantages of this approach in comparing with fuzzy approach. In continuilty of hedge algebras applications, this paper is mainly focused on the field of  fuzzy time series forecasting under hedge algebras approach. In this paper, we present a new approach using hedge algebras to provide a computational model, which is completely different from the fuzzy approach for fuzzy time series forecasting. The experimental results of forecasting enrollments of students of the University of Alabama show that the model of fuzzy time series based on hedge algebras is better than many existing models. We can see that the proposed model gains higher forecasting accuracy than the original model presented by Song and Chissom (1993b), Chen (1996, 2002), or Lee (2009), Qiu (2011), Egrioglu (2012), Ozdemir ( 2012) and Uslu (2013).

scholarly journals A nonparametric framework for water consumption data cleansing: an application to a smart water network in Naples (Italy)

2020 ◽  
Vol 22 (4) ◽  
pp. 666-680 ◽  
Author(s):  
Roberta Padulano ◽  
Giuseppe Del Giudice
Keyword(s):  
Time Series ◽  
Water Consumption ◽  
Remote Monitoring ◽  
Prior Information ◽  
Water Network ◽  
Smart Water ◽  
Consumption Data ◽  
Large Databases ◽  
Unsupervised Approach ◽  
Water Uses

Abstract Remote monitoring and collection of water consumption has gained pivotal importance in the field of demand understanding, modelling and prediction. However, most of the analyses that can be performed on such databases could be jeopardized by inconsistencies due to technological or behavioural issues causing significant amounts of missing or anomalous values. In the present paper, a nonparametric, unsupervised approach is presented to investigate the reliability of a consumption database, applied to the dataset of a district metering area in Naples (Italy) and focused on the detection of suspicious amounts of zero or outlying data. Results showed that the methodology is effective in identifying criticalities both in terms of unreliable time series, namely time series having huge amounts of invalid data, and in terms of unreliable data, namely data values suspiciously different from some suitable central parameters, irrespective of the source causing the anomaly. As such, the proposed approach is suitable for large databases when no prior information is known about the underlying probability distribution of data, and it can also be coupled with other nonparametric, pattern-based methods in order to guarantee that the database to be analysed is homogeneous in terms of water uses.

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