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Open access

Janusz Bogusz, Anna Klos, Marta Gruszczynska and Maciej Gruszczynski

Abstract

In the modern geodesy the role of the permanent station is growing constantly. The proper treatment of the time series from such station lead to the determination of the reliable velocities. In this paper we focused on some pre-analysis as well as analysis issues, which have to be performed upon the time series of the North, East and Up components and showed the best, in our opinion, methods of determination of periodicities (by means of Singular Spectrum Analysis) and spatio-temporal correlations (Principal Component Analysis), that still exist in the time series despite modelling. Finally, the velocities of the selected European permanent stations with the associated errors determined following power-law assumption in the stochastic part is presented.

Open access

Time Series Approach To Athletes Motor Potential

Time series approach to motor potential

Adam Maszczyk, Robert Roczniok, Przemysław Pietraszewski, Arkadiusz Stanula, Adam Zając and Artur Gołaś

Abstract

Introduction. The aim of this study was to determine the dynamics of changes in selected motor abilities of javelin throwers and to determine predictors of javelin throw distances. Material and methods. Research material included the results obtained from a group of 60 competitors from the Silesia Region of Poland, aged 14 - 15 years. In order to answer the research question, the following statistical analysis were employed: Pearson's linear correlation coefficients, vectors R0 and R1, time series analysis, distributed lag analysis and Almon distributed lag analysis and coefficient of concordance φ2 Results. The correlation analyzes allowed for a selection of two variables for further analyses: specific strength of arms and trunk (SSAT) and specific strength of shoulders girdle and trunk (SSGT). Calculated indexes revealed that the level of SSAT showed a constant upward tendency (+15%). The highest rise in SSAT level was recorded in the 4th and 5th quarter (+9%). The level of SSGT showed an upward tendency nearly (+6%). In this case, the highest rise was observed in the 7th and 8th quarter (+4.5%). Conclusions. The standardized regression analysis revealed that the variable of specific power of arms and trunk (SOBT) is the most important predictor for javelin throw distance with a full approach run.

Open access

Dorota Latos, Bogdan Kolanowski, Wojciech Pachelski and Ryszard Sołoducha

Abstract

Real time monitoring of engineering structures in case of an emergency of disaster requires collection of a large amount of data to be processed by specific analytical techniques. A quick and accurate assessment of the state of the object is crucial for a probable rescue action. One of the more significant evaluation methods of large sets of data, either collected during a specified interval of time or permanently, is the time series analysis. In this paper presented is a search algorithm for those time series elements which deviate from their values expected during monitoring. Quick and proper detection of observations indicating anomalous behavior of the structure allows to take a variety of preventive actions. In the algorithm, the mathematical formulae used provide maximal sensitivity to detect even minimal changes in the object’s behavior. The sensitivity analyses were conducted for the algorithm of moving average as well as for the Douglas-Peucker algorithm used in generalization of linear objects in GIS. In addition to determining the size of deviations from the average it was used the so-called Hausdorff distance. The carried out simulation and verification of laboratory survey data showed that the approach provides sufficient sensitivity for automatic real time analysis of large amount of data obtained from different and various sensors (total stations, leveling, camera, radar).

Open access

Wiesław Miczulski and Łukasz Sobolewski

Influence of the GMDH Neural Network Data Preparation Method on UTC(PL) Correction Prediction Results

The article presents results of the influence of the GMDH (Group Method of Data Handling) neural network input data preparation method on the results of predicting corrections for the Polish timescale UTC(PL). Prediction of corrections was carried out using two methods, time series analysis and regression. As appropriate to these methods, the input data was prepared based on two time series, ts1 and ts2. The implemented research concerned the designation of the prediction errors on certain days of the forecast and the influence of the quantity of data on the prediction error. The obtained results indicate that in the case of the GMDH neural network the best quality of forecasting for UTC(PL) can be obtained using the time-series analysis method. The prediction errors obtained did not exceed the value of ± 8 ns, which confirms the possibility of maintaining the Polish timescale at a high level of compliance with the UTC.

Open access

Jerzy Parysek and Lidia Mierzejewska

Trajectories of the demographic development of Poland after 1989

One of the major problems of contemporary Poland is its increasingly difficult and complicated demographic situation. This makes the identification of demographic trends of the recent years an important research task. The article presents an assessment of Poland's demographic situation after 1989, i.e. after the change of the country's socio-political system, using the graphic method of trajectories. It is one of the possible, though less popular, methods of studying time series, offering a new perspective on various processes, here demographic ones. The article has two aims: cognitive and methodological.

Open access

Arnis Kirshners and Yuri Kornienko

Time-Series Data Mining for E-Service Application Analysis

This paper provides application analysis of e-services available on the joint state and municipal e-service portal www.latvija.lv. The research is performed using a combination of time series analysis and data mining techniques. Time series analysis has enabled the determination of the count of clusters that represent services classification by application frequency. Meta-information is processed using data pre-processing methods and the values obtained are then discretised. The methods combinations examined in the paper are tested experimentally on the limited data amount available. The data describe the existing e-service requests by months. The clusters obtained are then added to the initial meta-information available when planning and developing services. E-service membership in the formed data set is determined using inductive classification trees. These algorithms represent knowledge in the form of classification trees through analysing feature values and cyclically split training instances into classes. As a result, based on the analysis conducted, recommendations for e-service developers and implementers are elaborated and basic parameters for successful introduction and application of e-services are determined.

Open access

Aleksandrs Dahs

Abstract

In recent decades, scientific literature on demographic research is increasing attention on spatial data analysis. It is considered a useful and reliable analysis methodology in evaluating complex regional development processes. However, due to its complexity and reliance on properly captured and quantified spatial relations, it remains a difficult topic for many scholars and practitioners. In Latvia, spatial demographic analysis may prove useful, providing opportunities for uncovering new dimensions of long-term regional demographic and economic development issues. Here, the author analyses spatial distribution aspects of key demographic indicators in Latvia’s municipalities, the associated socio-economic factors and their impact. The implications of the identified spatial processes and dependencies for regional development policy and aid are discussed, including possible lessons learned from or shared with the EU Eastern Partnership countries facing similar challenges.

Open access

Anabella Ferral, Velia Solis, Alejandro Frery, Alejandro Orueta, Ines Bernasconi, Javier Bresciano and Carlos M. Scavuzzo

Abstract

In this work we present novel results concerning water quality changes in an eutrophic water body connected with an artificial aeration system installed in it. Sixty one in-situ and laboratory measurements of biogeochemical variables were recorded monthly between October 2008 and June 2011 to evaluate temporal and spatial changes in San Roque reservoir (Argentina). t-Student mean difference tests, carried out over the whole period, showed with 95% confidence that a monitoring point located at the centre of the water body is representative of the chemical behaviour of the reservoir. Thermal stratification was observed in all sampling sites in the summer, but the frequency of these episodes was markedly lower in bubbling zones. Mean chlorophyll-a concentrations were 58.9 μg·dm−3 and 117.0 μg·dm−3 in the absence and in the presence of thermocline respectively. According to the t-Student test, this difference was significant, with p < 0.001. Phosphate release from sediments was corroborated under hypoxia conditions. ANOVA one way analysis did not show significant spatial differences for any variable. Mean normalize spatial index (MENSI) was developed to compare data from different regions affected by high temporal variability. It proved to be useful to quantify spatial differences. Structure analysis of temporal series was used to scrutinize both chemical and spatial association successfully. Three chemically different zones were determined in the reservoir. This study demonstrated that spatial comparisons by means of marginal statistics may not be an adequate method when high temporal variation is present. In such a case, temporal structure analysis has to be considered.

Open access

J. Kowal, J. Dańko and J. Stojek

Abstract

The article presents examples of vibration signals analysis derived from the research of prototype reclaimer REGMAS. After the division of the time-frequency analysis methods of measuring signals, their non-parametric and parametric models were estimated. At the end of the article the summary and conclusions were set.

Open access

Yaşar Tonta

Abstract

Purpose

One of the main indicators of scientific production is the number of papers published in scholarly journals. Turkey ranks 18th place in the world based on the number of scholarly publications. The objective of this paper is to find out if the monetary support program initiated in 1993 by the Turkish Scientific and Technological Research Council (TÜBİTAK) to incentivize researchers and increase the number, impact, and quality of international publications has been effective in doing so.

Design/methodology/approach

We analyzed some 390,000 publications with Turkish affiliations listed in the Web of Science (WoS) database between 1976 and 2015 along with about 157,000 supported ones between 1997 and 2015. We used the interrupted time series (ITS) analysis technique (also known as “quasi-experimental time series analysis” or “intervention analysis”) to test if TÜBİTAK’s support program helped increase the number of publications. We defined ARIMA (1,1,0) model for ITS data and observed the impact of TÜBİTAK’s support program in 1994, 1997, and 2003 (after one, four and 10 years of its start, respectively). The majority of publications (93%) were full papers (articles), which were used as the experimental group while other types of contributions functioned as the control group. We also carried out a multiple regression analysis.

Findings

TÜBİTAK’s support program has had negligible effect on the increase of the number of papers with Turkish affiliations. Yet, the number of other types of contributions continued to increase even though they were not well supported, suggesting that TÜBİTAK’s support program is probably not the main factor causing the increase in the number of papers with Turkish affiliations.

Research limitations

Interrupted time series analysis shows if the “intervention” has had any significant effect on the dependent variable but it does not explain what caused the increase in the number of papers if it was not the intervention. Moreover, except the “intervention”, other “event(s)” that might affect the time series data (e.g., increase in the number of research personnel over the years) should not occur during the period of analysis, a prerequisite that is beyond the control of the researcher.

Practical implications

TÜBİTAK’s “cash-for-publication” program did not seem to have direct impact on the increase of the number of papers published by Turkish authors, suggesting that small amounts of payments are not much of an incentive for authors to publish more. It might perhaps be a better strategy to concentrate limited resources on a few high impact projects rather than to disperse them to thousands of authors as “micropayments.”

Originality/value

Based on 25 years’ worth of payments data, this is perhaps one of the first large-scale studies showing that “cash-for-publication” policies or “piece rates” paid to researchers tend to have little or no effect on the increase of researchers’ productivity. The main finding of this paper has some implications for countries wherein publication subsidies are used as an incentive to increase the number and quality of papers published in international journals. They should be prepared to consider reviewing their existing support programs (based usually on bibliometric measures such as journal impact factors) and revising their reward policies.