Meslek Yüksek Okulu

Permanent URI for this communityhttps://hdl.handle.net/20.500.12416/285

Browse

Now showing 1 - 20 of 22

Citation - WoS: 10
Citation - Scopus: 16
The Causal Relationship Between Foreign Debt and Economic Growth: Evidence From Commonwealth Independent States
(Sage Publications india Pvt Ltd, 2021) Yasar, Nermin
This study investigates the relationship between external borrowing and eco-nomic growth in the Commonwealth Independent States during the period 1995-2018. Autoregressive distributed lag (ARDL) model is employed to determine the co-integration relationship among the series and then vector error correction model (VECM) is used to analyse the causality between external debt and income.The obtained results suggest that there is a negative long-term unidirectional causal relationship running from external debt to GDP presenting a strong evidence of existence of debt overhang hypothesis.The possible reasons for this unidirectional causal relationship can be explained by poor management of provided financial resources and incomplete governance in economic transition process along with structural rigidities and immature institutions in these countries which, in the long term, resulted in insufficient capital charged to service external debt.The policymakers in these post-Soviet countries should not use foreign loans to capitalise the deficits in the economies; instead, they should be more determined in employing these funds in the areas that will create national value-added production and, thus, future income.
Citation - WoS: 2
Citation - Scopus: 4
Comparative Performance Analysis of Filtering Methods for Removing Baseline Wander Noise From an Ecg Signal
(World Scientific Publ Co Pte Ltd, 2024) Ozaydin, Selma; Ahmad, Imteyaz
ECG signals play a vital role in the diagnosis of cardiovascular conditions. However, they often suffer from the effects of various noise sources, including baseline wandering, respiratory artifact noise, power line interference and electrode motion artifacts. To overcome these challenges, it is imperative to implement low-frequency signal noise reduction strategies. Such strategies aim to significantly improve the quality of ECG signals, thus promoting more accurate and reliable diagnosis of cardiovascular disorders. This paper conducts a comparative analysis to assess the effectiveness of commonly used filtering and wavelet techniques in reducing Baseline Wander (BW) noise within ECG signals generated by the influence of breathing or electrode movements. It is common to observe the selection and evaluation of only one particular technique in the existing literature. In contrast, this study aims to provide a comprehensive comparative analysis, providing insight into the performance and relative merits of different techniques. Our research uses both filtering and Discrete Wavelet Transform (DWT) techniques in baseline noise removal. In this context, a reference point is established utilizing noise-free signals and a meticulous investigation of the wavelet-based approach that most effectively eliminates the resulting noise is provided. Subsequently, we assess the reference input and output signal via Signal-to-Noise Ratio (SNR) and Kolmogorov-Smirnov statistical test measurements. The most important contribution of this work to the scientific community resides in the comprehensive examination of IIR/FIR-based and wavelet method-based filtering methods capable of yielding the highest SNR levels across various ECG signals with various types of BW noise. Additionally, the effectiveness of the Chebychev-II filter in BW noise removal is highlighted. Our study was conducted using the MATLAB platform and code command lines were shared to facilitate the reproduction of our study by other researchers. It is considered that this study will be an important reference in the selection of effective techniques for removing BW noise within ECG signals.
Citation - Scopus: 7
The Convergence of Electricity Prices for European Union Countries
(Springer International Publishing, 2020) Telatar, M.E.; Yaşar, N.
The goal of achieving a single European market for electricity has been one of the main objectives for European countries since the “Single European Act” of 1988. The main purpose of this study is to examine whether the aim of unified electricity market has been achieved in terms of the convergence of electricity prices. Β-Convergence and s-convergence tests, are applied for 12 European Union states electricity price data through the period of 2003-2017. For this reason, along with conventional applied techniques, recently improved unit root tests are implemented for both linear and nonlinear data generating processes. The results suggest that convergence did not occur for most of the considered countries. © Springer Nature Switzerland AG 2020.
Citation - Scopus: 2
Design of a Voice Activity Detection Algorithm Based on Logarithmic Signal Energy
(Institute of Electrical and Electronics Engineers Inc., 2022) Ozaydin, S.
This article presents a new method for calculating the signal energies of speech segments in voice activity detection algorithms. In the study, the μ-law signal compression method is adapted to calculate short-term signal energies. A simple voice activity detection (VAD) algorithm is designed to demonstrate the effectiveness of the proposed method. The same VAD algorithm was also run with two different conventional energy calculation formulas and the performance of each VAD was evaluated using time-domain short-time energy features. The G729 standard VAD algorithm was also used for performance comparison. During the test of the analyzed detectors, many kinds of input speech signals with various types of background environmental noise, such as restaurants, vehicles, and streets, were tested. Using the new energy calculation method, the VAD detector has improved detection accuracy compared to VAD detectors based on the other two energy methods and was able to effectively identify voice-active regions even in noisy conditions at low SNR levels. The results revealed that the VAD detector designed with the proposed new energy calculation formula outperforms traditional energy-based voice activity detection methods and provides noticeable increases in detection rate even under adverse conditions. © 2022 IEEE.
Ecg Signal Denoising With Scilab
(Ismail Saritas, 2023) Ahmad, I.; Özaydın, Selma; Ozaydin, S.; Çankaya Meslek Yüksekokulu
This paper presents a study on de-noising electrocardiogram (ECG) signals using Scilab, an open-source software package known for its signal processing capabilities. ECG signals are often contaminated by various noise sources, which can reduce the accurate diagnosis and monitoring of heart health. In this work, digital signal processing methods such as Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) filters are used to effectively suppress noise while preserving the essential features of the ECG waveform. We explore main noise sources that commonly affect ECG recordings, such as baseline wandering noise, power-line interference, and muscle artifacts, and discuss their respective challenges. The de-noising methods has been extensively evaluated and demonstrated its ability to improve signal quality and diagnostic accuracy by eliminating noise artifacts. The results highlight Scilab's potential for de-noising ECG signals and its importance in improving patient care and biomedical signal processing applications. The efficacy of the de-noising methods is thoroughly evaluated through comparative analyses with other commonly used de-noising approaches. Experimental results demonstrate its superiority in preserving the QRS complex while efficiently eliminating noise artifacts, leading to more accurate and reliable diagnostic information. In conclusion, this paper presents a comprehensive study on de-noising ECG signals using Scilab, offering a valuable contribution to the field of biomedical signal processing. Researchers and practitioners in the domain of ECG signal processing can benefit from the insights and techniques presented herein to advance their studies and further applications. © 2023, Ismail Saritas. All rights reserved.
Citation - WoS: 12
Citation - Scopus: 12
The Effects of Inflation Uncertainty on Interest Rates: a Nonlinear Approach
(Routledge Journals, Taylor & Francis Ltd, 2010) Hasanov, Muebariz; Omay, Tolga
In this article, we investigate the effects of inflation variability on short-term interest rates within a nonlinear smooth transition regression framework. The test results suggest that only the conditional mean of the inflation is a nonlinear process whereas the conditional variance is time variant but linear. Using the square root of conditional variance as a proxy for inflation risk, we estimate Fisher equation augmented with inflation risk. Although the estimated Fisher equations suggest that inflation risk reduces short-term interest rates, we find that the effects of inflation risk on interest rates are regime-dependent. Particularly, we find that the negative effects of inflation variability on nominal rates are greater in low-inflationary regimes when compared to high-inflationary regimes. On the other hand, it is found that both inflation and inflation uncertainty raise the expected inflation effect.
Citation - WoS: 31
Citation - Scopus: 36
The Endogenous and Non-Linear Relationship Between Terrorism and Economic Performance: Turkish Evidence
(Taylor & Francis Ltd, 2009) Arin, K. Peren; Omay, Tolga; Araz-Takay, Bahar
This paper investigates the macroeconomic effects of terror by using a novel data set from Turkey for the period of 1987:1 to 2004:4. This research contributes to the literature by controlling for the possible non-linear and endogenous relationship between political conflict and economic activity. Empirical evidence from both linear and non-linear models confirms that terrorism has a large significant negative impact on economic activity. Finally, the results from the non-linear model show that the impact of terrorism on the aggregate economy is more severe during expansionary periods, and that the impact of economic activity on terrorism is significant only in recessionary periods.
Citation - WoS: 7
Citation - Scopus: 8
Firm Survival in Times of Crisis: Do Innovation and Financing Constraints Matter? Insights From the Covid-19 Pandemic
(Routledge Journals, Taylor & Francis Ltd, 2023) Ozsuca, Ekin Ayse
Utilizing survey data collected over three rounds, this paper investigates the impact of pre-COVID innovation performance, innovation type, sources of knowledge, and the moderating role of financial constraints on survival following the outbreak of COVID-19. The findings pinpoint a strong and positive link between firm survival and innovation, especially process innovation, confirming the ability of innovators to adapt to new conditions as a determinant of survival. Moreover, relying on internal knowledge is found to increase the chance of survival and adaptability to times of crisis. The results further indicate that access to finance strengthens the positive impact of innovation on firm survival/adaptation.
A Graphical Speech Analysis Teaching Tool
(Institute of Electrical and Electronics Engineers Inc., 2022) Ozaydin, S.
The widespread use of digital speech processing in today's technologies causes many electronics and computer engineering students to need a basic background in these subjects. The paper describes a toolbox designed to support undergraduate or graduate level courses on speech processing. The proposed educational toolbox is designed as a virtual lab for basic operations in digital speech processing-based courses. This graphical user interface (GUI) based speech analysis algorithm is built with six main function modules, which are signal input, noise addition, up-sampling/down-sampling, time domain feature analysis, pitch detection and frequency domain analysis. The toolbox involves different operations for measuring important speech feature parameters such as pitch, energy, zero-crossing ratio, FFT and power spectrum of an input speech signal. The toolbox has also been developed to easily manipulate and add some other possible speech processing methods. It is thought that the tool will make it easier for students to understand the methods that form the basis of digital speech processing, increase the interest in the lesson with its visual outputs, and allow new methods to be added easily when desired thanks to its simple and modular structure. The main aim of this paper to show how such a tool facilitates students understanding of technical concepts introduced in speech courses. © 2022 IEEE.
Citation - WoS: 2
Citation - Scopus: 2
Mobbing Used Against Teachers by School Administrators: Examples of Case
(Hacettepe Univ, 2023) Okdem, Meltem
Mobbing means psychological violence, siege, harassment, inconvenience or annoyance. Mobbing against a teacher in schools can also negatively affect other teachers and create negativities in their performance. Also, this costs society a lot. It is crucial for teachers raising young people who are our future to work peacefully in their workplace both for themselves and for students. The purpose of this study was to assess mobbing behaviors, which are used by school principals against teachers and are submitted to the court. The study chose the "qualitative" research method. The study reached the mobbing cases opened by teachers against school principals on (www.LegalBank.com). The study investigated the mobbing cases by giving keywords without date restriction. Since the study investigated the court decisions to determine the mobbing behaviors used by school principals against teachers, it used the "document review" method and reached 15 cases between 2010 and 2020 within this scope. As a result of the study the school principals most displayed behaviors in the category of "attacks against professional career" of the teachers. Eight of the cases were attacks against professional career. Then the study reached six mobbing cases against communication. However, the study encountered no behaviors related to "attacks against social relations". In order to prevent these behaviors, we can recommend the following: Awareness should be raised in teachers concerning psychological harassment/intimidation in schools, seminars should be organized for them to protect from such behaviors via in-service training applications, awareness should be raised in teachers concerning their legal rights, the crime of administrators applying mobbing should be registered and they should not be allowed to get promotion and should be suspended for a certain period of time.
Citation - WoS: 20
Citation - Scopus: 23
Nonlinearities in Emerging Stock Markets: Evidence From Europe's Two Largest Emerging Markets
(Routledge Journals, Taylor & Francis Ltd, 2008) Omay, Tolga; Hasanov, Muebariz
Recent developments in time series analysis allow proper modelling of nonlinearities in economic and financial variables. A growing body of research was dedicated to investigation of potential nonlinearities in conditional mean of many economic and financial variables, mainly concentrating in developed economies. However, nonlinearities in financial variables in developing economies have not been fully examined yet. In this article we investigate potential nonlinearity and cyclical behaviour of stock returns in Europe's two largest emerging stock markets, mainly in the Greek and Turkish stock markets. Specifically, we use STAR family models, which allow to model nonlinearities in the conditional mean, for modelling monthly returns on stock exchange indices of the Athens Stock Exchange and Istanbul Stock Exchange. Although we find no nonlinearity in conditional variance, we do find strong evidence in favour of nonlinear adjustment of stock returns. It is found that allowing for nonlinearity in conditional mean results in a superior model and provides good out-of-sample forecasts, which contradicts to efficient market hypothesis.
Citation - WoS: 28
Citation - Scopus: 30
On Fractional Filtering Versus Conventional Filtering in Economics
(Elsevier, 2010) Baleanu, Dumitru; Nigmatullin, Raoul R.; Omay, Tolga
In this study, we compare the Hodrick-Prescott Filter technique with the Fractional filtering technique that has recently started to be used in various applied sciences like physics, engineering, and biology. We apply these filtering techniques to quarterly GDP data from Turkey for the period 1988:1-2003:2. The filtered series are analyzed using Minimum Square Error (MSE) and real life evidence. In the second part of the study, we use simulated data to analyze the statistical properties of the aforementioned filtering techniques. (C) 2009 Elsevier B.V. All rights reserved.
Citation - WoS: 68
Citation - Scopus: 86
Re-Examining the Threshold Effects in the Inflation-Growth Nexus With Cross-Sectionally Dependent Non-Linear Panel: Evidence From Six Industrialized Economies
(Elsevier Science Bv, 2010) Omay, Tolga; Kan, Elif Oeznur
This paper analyzes the empirical relationship between inflation and output growth using a novel panel data estimation technique, Panel Smooth Transition Regression (PSTR) model, which takes account of the non-linearities in the data. By using a panel data set for 6 industrialized countries that enable us to control for unobserved heterogeneity at both country and time levels, we find that there exists a statistically significant negative relationship between inflation and growth for the inflation rates above the critical threshold level of 2.52%, which is endogenously determined. Furthermore, we also control cross-section dependency by using the CD test modified to non-linear context and remedy cross-section dependency with Seemingly Unrelated Regression Equations through Generalized Least Squares (SURE-GLS) and newly proposed Common Correlated Effects (CCE) estimation techniques. We find that these methods change the critical threshold value slightly. The estimated threshold values from these estimation methods are 3.18% and 2.42%, respectively. (C) 2010 Elsevier B.V. All rights reserved.
Citation - Scopus: 28
The Relationship Between Energy Consumption and Economic Growth: Evidence From Different Income Country Groups
(Econjournals, 2017) Yaşar, N.
This study analyses the relationship between energy consumption and economic growth for 119 countries during the period of 1970-2015, classified into four groups regarding to the World Bank income ranking. The main motivation of this study is to analyze whether the causal relationship differs between different income groups of countries. For this purpose, panel auto regressive distributed lag boundary approach and Granger causality test were used. The results of the study indicate that the causal relationship between energy use and economic growth differs depending on which income group country belongs to. We conclude that the feedback hypothesis is supported for upper-middle income group in the long run and high-income group, while conservation hypothesis is supported for upper-middle income group in the short run and lower-middle income group in the long run. Finally, neutrality hypothesis is supported for low and lower middle-income groups in the short run. © 2017, Econjournals. All rights reserved.
Citation - Scopus: 5
The Relationship Between Foreign Direct Investment and Co 2 Emissions Across a Panel of Countries
(Springer International Publishing, 2018) Yaşar, N.; Telatar, M.E.
This paper analyses the relationship between foreign direct investment inflows and pollution emissions for 139 countries during the period of 1970-2015 and the countries are classified into four groups regarding to the World Bank income ranking. The main motivation of this study is to analyse, whether the causal relationship differs between different income groups. For this purpose, panel ARDL (Auto Regressive Distributed Lag) boundary approach and Granger causality test are used. The results of the study indicate that the causal relationship between FDI (Foreign Direct Investment) and CO 2 emissions differs depending on which income group country belongs to. We conclude that, while there is not statistically significant short-run causality relationship running from FDI to CO 2 emission for high income, upper middle income and low income group countries, the pollution haven hypothesis is supported for lower middle income group countries. © Springer International Publishing AG, part of Springer Nature 2018.
Citation - WoS: 20
Citation - Scopus: 23
The Relationship Between Inflation, Output Growth, and Their Uncertainties: Evidence From Selected Cee Countries
(M E Sharpe inc, 2011) Omay, Tolga; Hasanov, Mubariz
In this paper, we examine causal relationships between inflation rate, output growth rate, inflation uncertainty, and output uncertainty for ten Central and Eastern European transition countries. For this purpose, we estimate a bivariate GARCH model that includes output growth and inflation rates for each country. Then we use conditional standard deviations of inflation and output to proxy nominal and real uncertainty, respectively, and perform Granger causality tests. Our results suggest that inflation rate induces uncertainty about both inflation rate and output growth rate, which is detrimental to real economic activity. At the same time, we find that output growth rate reduces macroeconomic uncertainty in some countries. In addition, we also examine and discuss causal relationships between the remaining variables.
Citation - Scopus: 3
A Relationship Marketing Strategy in Brand Communication: Influencer Marketing Strategy
(IGI Global, 2019) Dursun, T.; Ôzsaçmaci, B.
Influencer marketing increases brand awareness by generating appropriate content to attract the attention of consumers in a virtual environment in accordance with the brand texture. This chapter explores research to determine importance of influencer marketing in the brand communication area, which is based on relationship marketing. Authors mainly focus on influencer marketing and its connection with relationship marketing. They describe the constituent parts of the topics and illustrate them with the case studies and statistical facts. The authors strongly claim influencer marketing shares similar variables with relationship marketing and their basic keywords are related. © 2020 by IGI Global.
Citation - Scopus: 9
Speech Denoising With Maximal Overlap Discrete Wavelet Transform
(Institute of Electrical and Electronics Engineers Inc., 2022) Ozaydin, S.; Alak, I.K.
In this paper, the effectiveness of the maximum overlapping discrete wavelet transform (MODWT) method on denoising the speech signal is tested and examined. Ensuring the intelligibility of the speech signal in noisy environments by separating it from the noise is a widely researched topic today. On the other hand, being able to recover the original speech from the noisy signal with minimal distortion is a challenge due to the difficulties in removing the background noise. Numerous factors in environmental noise environments can interfere with the signal. In this study, the performance of some discrete wavelets transform methods is experimentally analyzed using different wavelet filters. The analysis program was carried out in the MATLAB environment. As the input noise speech signal, speech sounds containing different environmental background noises (train, car, station, plane, etc.) were analyzed. During the tests, these noisy input signals were filtered out from the speech signal by wavelet analysis. The input noisy speech signal is decomposed into wavelet coefficients with different thresholding methods. The reconstructed speech was compared by measuring the signal-to-noise ratio (SNR) values between the noisy input signal and the smoothed output signals. The scientific contributions of the study include a detailed comparative analysis of the performances of various wavelet methods against different background environmental noises. © 2022 IEEE.
Citation - Scopus: 1
Stationarity Properties of Renewable Energy Consumption in the Commonwealth of Independent States
(Econjournals, 2020) Yasar, N.
This study investigates the stochastic properties of renewable energy consumption series across 11 Commonwealth of Independent States countries through the period of 1990-2015. For this purpose, along with traditional stationarity analysis recently improved unit root techniques which allows for nonlinear adjustments in the data generating process are used in this paper. Based on our findings we may conclude that, consideration of nonlinearity in regression process causes to more frequent non rejection of the null hypothesis of stationarity. It implies that ignoring possible nonlinearities in time series regression process may lead to some misleading results. Hereby, fluctuations in global energy supply and trade systems influence renewable energy consumption in nonlinear pattern and policy-makers should take it into consideration in terms of proper energy policy implication. © 2019, Econjournals. All rights reserved.
Stochastic Pattern of Health Care Spending: Evidence From Nonlinear Panel Data Analysis
(Better Advances Press, 2021) Yasar, N.
This paper analyses the stochastic pattern of health care spending for 188 countries around the world which are categorized into four groups based on the World Bank income categories. The main motivation of this ar-ticle is to evaluate whether the stochastic features of total health care expenditure varies if decomposed into private and public health care consumption. To achieve this goal, in addition to conventional empirical methods, latterly de-veloped panel stationarity approaches are employed for both linear and nonlinear regression processes. Our results demonstrate that allowing for cross-section dependency between series and nonlinearity in the estimation process may lead to more often rejection of the null hypothesis of unit root for all series in panel data set. © 2021 Better Advances Press. All rights reserved.

Browse

Browsing Meslek Yüksek Okulu by Publication Index "Scopus"