Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Citation - WoS: 204Citation - Scopus: 234The Relationship Between Economic Growth and Electricity Consumption From Renewable and Non-Renewable Sources: A Study of Turkey(Pergamon-Elsevier Science Ltd, 2015-12) Dogan, EyupThe main objective of this study is to analyze the short and long run estimates as well as the causality relationships between economic growth (GR), electricity consumption from renewable sources (RELC) and electricity consumption from non-renewable sources (NRELC) for Turkey in a multivariate model wherein capital (K) and labor (L) are included as additional variables. Using the autoregressive distributed lag (ARDL) approach to cointegration, the Johansen cointegration test and the Gregory-Hansen cointegration test with structural break, we show that GR, RELC, NRELC, K and L are cointegrated. Although NRELC has a long run positive effect on GR, the long run estimate of RELC is negative but insignificant at 5% level of significance. The Granger causality test based on the vector error correction model reveals the evidence of neutrality hypothesis between RELC and GR, and between NRELC and GR in Turkey in the short run. In addition, the Granger causality runs from RELC, NRELC, K and L to GR as well as from GR, RELC, K and L to NRELC in the long run, which supports the existence of growth hypothesis between RELC and GR, and feedback hypothesis between NRELC and GR in the long run. It is advised that policy makers in the Turkish government should continue to reduce the share of electricity consumption from renewable sources and encourage the usage of electricity from non-renewable sources to have sustainable long run growth rates. It is also essential to promote the investment projects to increase the efficiency of electricity generation from non-renewable sources. (C) 2015 Elsevier Ltd. All rights reserved.Article Citation - WoS: 131Citation - Scopus: 135The Influence of Biomass Energy Consumption on CO2 Emissions: A Wavelet Coherence Approach(Springer Heidelberg, 2016-06-23) Bilgili, Faik; Ozturk, Ilhan; Kocak, Emrah; Bulut, Umit; Pamuk, Yalcin; Mugaloglu, Erhan; Baglitas, Hayriye H.In terms of today, one may argue, throughout observations from energy literature papers, that (i) one of the main contributors of the global warming is carbon dioxide emissions, (ii) the fossil fuel energy usage greatly contributes to the carbon dioxide emissions, and (iii) the simulations from energy models attract the attention of policy makers to renewable energy as alternative energy source to mitigate the carbon dioxide emissions. Although there appears to be intensive renewable energy works in the related literature regarding renewables' efficiency/impact on environmental quality, a researcher might still need to follow further studies to review the significance of renewables in the environment since (i) the existing seminal papers employ time series models and/or panel data models or some other statistical observation to detect the role of renewables in the environment and (ii) existing papers consider mostly aggregated renewable energy source rather than examining the major component(s) of aggregated renewables. This paper attempted to examine clearly the impact of biomass on carbon dioxide emissions in detail through time series and frequency analyses. Hence, the paper follows wavelet coherence analyses. The data covers the US monthly observations ranging from 1984:1 to 2015 for the variables of total energy carbon dioxide emissions, biomass energy consumption, coal consumption, petroleum consumption, and natural gas consumption. The paper thus, throughout wavelet coherence and wavelet partial coherence analyses, observes frequency properties as well as time series properties of relevant variables to reveal the possible significant influence of biomass usage on the emissions in the USA in both the short-term and the long-term cycles. The paper also reveals, finally, that the biomass consumption mitigates CO2 emissions in the long run cycles after the year 2005 in the USA.Article Citation - WoS: 356Citation - Scopus: 404The Impact of Trade Openness on Global Carbon Dioxide Emissions: Evidence From the Top Ten Emitters Among Developing Countries(Elsevier, 2016-08) Ertugrul, Hasan Murat; Cetin, Murat; Seker, Fahri; Dogan, EyupThis study aims to analyze the relationship between carbon dioxide (CO2) emissions, trade openness, real income and energy consumption in the top ten CO2 emitters among the developing countries; namely China, India, South Korea, Brazil, Mexico, Indonesia, South Africa, Turkey, Thailand and Malaysia over the period of 1971-2011. In addition, the possible presence of the EKC hypothesis is investigated for the analyzed countries. The Zivot-Andrews unit root test with structural break, the bounds testing for cointegration in the presence of structural break and the VECM Granger causality method are employed. The empirical results indicate that (i) the analyzed variables are co-integrated for Thailand, Turkey, India, Brazil, China, Indonesia and Korea, (ii) real income, energy consumption and trade openness are the main determinants of carbon emissions in the long run, (iii) there exists a number of causal relations between the analyzed variables, (iv) the EKC hypothesis is validated for Turkey, India, China and Korea. Robust policy implications can be derived from this study since the estimated models pass several diagnostic and stability tests. (C) 2016 Elsevier Ltd. All rights reserved.Article Citation - WoS: 31Citation - Scopus: 31Revisiting the Nexus Among Carbon Emissions, Energy Consumption and Total Factor Productivity in African Countries: New Evidence from Nonparametric Quantile Causality Approach(Elsevier Sci Ltd, 2020-03) Dogan, Eyup; Tzeremes, Panayiotis; Altinoz, BuketThis study aims to contribute to the existing thin body of nonlinear causality literature by applying the new hybrid nonparametric quantile causality approach. In this line, we investigate the non-linear nexus among total factor productivity, energy consumption and carbon emissions for seventeen African countries. From the results, it is remarkable that there are generally strong causalities between the variables in the middle lower, middle upper and middle quantiles. Hence, energy consumption, environmental pollution and total factor productivity are closely linked in African countries. In particular, bidirectional linkage is detected between total factor productivity and energy consumption for Angola, Benin, Botswana, Cote d'Ivoire, Kenya, Morocco, Egypt, Nigeria and Tunisia. Studying the relationship between total factor productivity and emissions again at the middle quantile bidirectional causal ordering is documented almost for all the countries. Lastly and regarding the linkage between energy consumption and carbon emissions, a strong bidirectional ordering between the two variables is confirmed for Angola, Benin, Cote d'Ivoire, Cameroon, Kenya, Morocco, Egypt, Mozambique, Nigeria, Senegal and Tunisia. We can notice that an increase in economic development is critical for these countries; a number of regulatory policies for environmental problems and energy consumption are required during this development.Article Citation - WoS: 63Citation - Scopus: 107Research Article Energy Consumption of On-Device Machine Learning Models for IoT Intrusion Detection(Elsevier, 2023-04) Tekin, Nazli; Acar, Abbas; Aris, Ahmet; Uluagac, A. Selcuk; Gungor, Vehbi CagriRecently, Smart Home Systems (SHSs) have gained enormous popularity with the rapid development of the Internet of Things (IoT) technologies. Besides offering many tangible benefits, SHSs are vulnerable to attacks that lead to security and privacy concerns for SHS users. Machine learning (ML)-based Intrusion Detection Systems (IDS) are proposed to address such concerns. Conventionally, ML models are trained and tested on computationally powerful platforms such as cloud services. Nevertheless, the data shared with the cloud is vulnerable to privacy attacks and causes latency, which decreases the performance of real-time applications like intrusion detection systems. Therefore, on-device ML models, in which the user data is kept locally, have emerged as promising solutions to ensure the security and privacy of the data for real-time applications. However, performing ML tasks requires high energy consumption. To the best of our knowledge, no study has been conducted to analyze the energy consumption of ML-based IDS. Therefore, in this paper, we perform a comparative analysis of on-device ML algorithms in terms of energy consumption for IoT intrusion detection applications. For a thorough analysis, we study the training and inference phases separately. For training, we compare the cloud computing-based ML, edge computing-based ML, and IoT device-based ML approaches. For the inference, we evaluate the TinyML approach to run the ML algorithms on tiny IoT devices such as Micro Controller Units (MCUs). Comparative performance evaluations show that deploying the Decision Tree (DT) algorithm on-device gives better results in terms of training time, inference time, and power consumption.Article Citation - WoS: 41Citation - Scopus: 43Re-Estimating the Interconnectedness Between the Demand of Energy Consumption, Income, and Sustainability Indices(Springer Heidelberg, 2019-07-10) Ozcan, Burcu; Tzeremes, Panayiotis; Dogan, EyupIn this study, we analyze the time-varying causality linkages between energy consumption, economic growth, and environmental degradation in 33 Organization for Economic Co-operation and Development countries, spanning the period 2000 to 2013. The curve causality approach provides evidence of a significant environmental Kuznets curve in 25 countries in the case of the ecological footprint and in 23 countries in the case of the Environmental Performance Index. However, out of them, only Italy, Slovakia, and South Korea have traditional environmental Kuznets curve, in the form of an inverted U-shaped curve. For the remaining countries, different forms of curves are valid. In particular, an N-shaped curve appears to be valid between income and environmental degradation for nearly half of the sample, i.e., for Austria, Belgium, Chile, Estonia, Finland, France, Germany, Hungary, Luxembourg, Netherlands, Sweden, Switzerland, New Zealand, Turkey, and the USA. Additionally, bidirectional causality relationships are confirmed among all covariates in most countries. In view of the results, some crucial policy implications would be suggested, such as sustainable development that aims to make a balance between economic growth and environmental protection.Article Citation - WoS: 298Citation - Scopus: 325Investigating the Impacts of Energy Consumption, Real GDP, Tourism and Trade on CO2 Emissions by Accounting for Cross-Sectional Dependence: A Panel Study of OECD Countries(Routledge Journals, Taylor & Francis Ltd, 2015-12-11) Dogan, Eyup; Seker, Fahri; Bulbul, SerapThe objective of this study is to analyse the long-run dynamic relationship of carbon dioxide emissions, real gross domestic product (GDP), the square of real GDP, energy consumption, trade and tourism under an Environmental Kuznets Curve (EKC) model for the Organization for Economic Co-operation and Development (OECD) member countries. Since we find the presence of cross-sectional dependence within the panel time-series data, we apply second-generation unit root tests, cointegration test and causality test which can deal with cross-sectional dependence problems. The cross-sectionally augmented Dickey-Fuller (CADF) and the cross-sectionally augmented Im-Pesaran-Shin (CIPS) unit root tests indicate that the analysed variables become stationary at their first differences. The Lagrange multiplier bootstrap panel cointegration test shows the existence of a long-run relationship between the analysed variables. The dynamic ordinary least squares (DOLS) estimation technique indicates that energy consumption and tourism contribute to the levels of gas emissions, while increases in trade lead to environmental improvements. In addition, the EKC hypothesis cannot be supported as the sign of coefficients on GDP and GDP(2) is negative and positive, respectively. Moreover, the Dumitrescu-Hurlin causality tests exploit a variety of causal relationship between the analysed variables. The OECD countries are suggested to invest in improving energy efficiency, regulate necessary environmental protection policies for tourism sector in specific and promote trading activities through several types of encouragement act.Article Citation - WoS: 54Citation - Scopus: 68FFRP: Dynamic Firefly Mating Optimization Inspired Energy Efficient Routing Protocol for Internet of Underwater Wireless Sensor Networks(IEEE-Inst Electrical Electronics Engineers Inc, 2020) Faheem, Muhammad; Butt, Rizwan Aslam; Raza, Basit; Alquhayz, Hani; Ashraf, Muhammad Waqar; Raza, Saleem; Bin Ngadi, Md Asri; Ngadi, Md. Asri BinEnergy-efficient and reliable data gathering using highly stable links in underwater wireless sensor networks (UWSNs) is challenging because of time and location-dependent communication characteristics of the acoustic channel. In this paper, we propose a novel dynamic firefly mating optimization inspired routing scheme called FFRP for the internet of UWSNs-based events monitoring applications. The proposed FFRP scheme during the events data gathering employs a self-learning based dynamic firefly mating optimization intelligence to find the highly stable and reliable routing paths to route packets around connectivity voids and shadow zones in UWSNs. The proposed scheme during conveying information minimizes the high energy consumption and latency issues by balancing the data traffic load evenly in a large-scale network. In additions, the data transmission over highly stable links between acoustic nodes increases the overall packets delivery ratio and network throughput in UWSNs. Several simulation experiments are carried out to verify the effectiveness of the proposed scheme against the existing schemes through NS2 and AquaSim 2.0 in UWSNs. The experimental outcomes show the better performance of the developed protocol in terms of high packets delivery ratio (PDR) and network throughput (NT) with low latency and energy consumption (EC) compared to existing routing protocols in UWSNs.Article Citation - WoS: 346Citation - Scopus: 388Exploring the Relationship Among CO2 Emissions, Real GDP, Energy Consumption and Tourism in the EU and Candidate Countries: Evidence From Panel Models Robust to Heterogeneity and Cross-Sectional Dependence(Pergamon-Elsevier Science Ltd, 2017-09) Dogan, Eyup; Aslan, AlperA major criticism to the existing energy-growth-environment literature, we notice, is the selection of methodology. Panel estimation techniques that fail to consider both heterogeneity and cross-sectional dependence across countries may cause forecasting errors. The other concern related to the literature is that only a small number of studies analyze the influence of tourism on CO2 emissions even though tourism sector has potential for affecting the environment. To fulfill the mentioned gaps in the literature, this study analyzes the relationship among carbon emissions, real income, energy consumption and tourism for a panel of the EU and candidate countries over the period 1995-2011 by using heterogeneous panel estimation techniques with cross-sectional dependence. Results from the CADF and the CIPS panel unit root tests show that the analyzed variables become stationary at their first-differences. The LM bootstrap panel cointegration test indicates the presence of a long run relationship among the analyzed variables. Results from the OLS with fixed effects, the FMOLS, the DOLS and the group-mean estimator reveal that energy consumption contributes to the level of emissions while real income and tourism mitigate CO2 emissions. The Emirmahmutoglu-Kose panel Granger causality test suggests that there is one-way causality running from tourism to carbon emissions, and two-way causality between CO2 emissions and energy consumption, and between real income and CO2 emissions. Policy implications are further discussed.Article Citation - WoS: 58Citation - Scopus: 67Analyzing the Tourism-Energy Nexus for the Top 10 Most-Visited Countries(MDPI, 2017-10-30) Isik, Cem; Dogan, Eyup; Ongan, Serdar; Dogan, EyüpBy using the Emirmahmutoglu-Kose bootstrap Granger non-causality method, this study explores the directions of causality among tourist arrivals, tourism receipts, energy consumption and economic growth for the top 10 most-visited countries (France, the USA, Spain, China, Italy, Turkey, Germany, the United Kingdom, Russia, and Mexico) in the world. This study finds a variety of causal directions between the pair of analyzed variables for each country and the panel. Since cross-sectional dependence exists across the top countries for the analyzed variables, the bootstrap Granger causality test that accounts for the mentioned issue in the estimation process presumably produces reliable and accurate outputs. Further results and policy implications are discussed in this empirical study.