WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://gcris.yasar.edu.tr/handle/123456789/11289

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Dynamic Automatic Forecaster Selection via Artificial Neural Network Based Emulation to Enable Massive Access for the Internet of Things
(ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD, 2022) Mert Nakip; Erdem Cakan; Volkan Rodoplu; Cuneyt Guzelis
The Massive Access Problem of the Internet of Things (IoT) occurs at the uplink Medium Access Control (MAC) layer when a massive number of IoT devices seek to transfer their data to an IoT gateway. Although recently proposed predictive access solutions that schedule the uplink traffic based on forecasts of IoT device traffic achieve high network performance these solutions depend heavily on the performance of forecasters. Hence the design and selection of forecasting schemes are key to enabling massive access for such predictive access solutions. To this end in this paper first we develop a framework that emulates the relationship between the IoT device class composition in the coverage area of an IoT gateway and the resulting network performance by virtue of an Artificial Neural Network (ANN). Second based on this framework we develop the Dynamic Automatic Forecaster Selection (DAFS) method which selects the best-performing forecasting scheme for predictive access in particular for Joint Forecasting-Scheduling (JFS) in a manner that adapts dynamically to a changing number of IoT devices in each device class in the coverage area. We evaluate the performance of DAFS via simulations and show that our method is able to achieve at least 80% of the best performance that can be attained for both throughput and energy consumption. Furthermore we demonstrate that DAFS is robust with respect to the selection of architectural parameters and has a reasonable computation time for real-time IoT applications. These results imply that DAFS holds the potential for practical implementation at IoT gateways in order to enable massive access under a dynamically changing composition of IoT devices.
Effects of Environment- Social- and Governance (ESG) Disclosures on ESG Scores: Investigating the Role of Corporate Governance for Publicly Traded Turkish Companies
(ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD, 2024) Tevfik Kartal; Dilvin Taskin; Muhammad Shahbaz; Serpil Kilic Depren; Ugur Korkut Pata
The world has experienced climate-related issues which increase the importance of ESG disclosures and corporate governance (CG) of companies which take place at the heart of economies. Therefore improving ESG disclosures and CG practices becomes significant to combat climate change at the company level. Considering that Turkiye restructured ESG disclosures in 2022 this study investigates the role of CG on the nexus between ESG scores of publicly traded companies (PTC) and ESG reports. So the study analyzes 102 PTC (full sample) 51 PTC in Borsa Istanbul Corporate Governance Index (in-sample) and the remaining 51 PTC (out-sample) using ESG disclosures of 2022 and applying novel super learner (SL) algorithm. Our results show that (i) SL has a higher prediction performance reaching similar to 94.3%, (ii) the environment (governance) layer has the highest (lowest) total relative importance (contribution) to ESG scores in all samples, (iii) C8 S6 and E5 are the most important ESG principles in the full sample in-sample and out-sample respectively, (iv) the contribution of each ESG principles to the total ESG scores varies by sample, (v) CG plays a smoothing role for the relative importance of each ESG principle while the relative importance in the out-sample shows much higher volatility. Overall the study reveals the non-linear contributions of ESG principles on ESG scores and suggests that PTC should prioritize highly important ESG principles consider the moderating role of CG on the link between ESG scores and ESG disclosures and use ESG disclosures as a strategic tool to develop ESG scores and disclosures.
How are energy transition and energy-related R&D investments effective in enabling decarbonization? Evidence from Nordic Countries by novel WLMC model
(ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD, 2024) Mustafa Tevfik Kartal; Muhammad Shahbaz; Dilvin Taskin; Serpil Kilic Depren; Fatih Ayhan
Public interest in climate change-related problems has been developing with the contribution of the recent energy crisis. Accordingly countries have been increasing their efforts to decarbonize economies. In this context energy transition and energy-related research and development (R&D) investments can be important strategic tools to be helpful to countries in the decarbonization of economies. Among all Nordic countries have come to the force because of their well-known position as green economies. Hence this study examines Nordic countries to investigate the impact of energy transition renewable energy R&D investments (RRD) energy efficiency R&D investments (EEF) on carbon dioxide (CO2) emissions by performing wavelet local multiple correlation (WLMC) model and using data from 2000/1 to 2021/12. The outcomes reveal that (i) based on bi-variate cases energy transition and RRD have a mixed impact on CO2 emissions in all countries across all frequencies, EEF has a declining impact on CO2 emissions in Norway (Sweden) at low and medium (very high) frequencies, (ii) according to four-variate cases all variables have a combined increasing impact on CO2 emissions, (iii) RRD is the most influential dominant factor in all countries excluding Norway where EEF is the pioneering one. Thus the reach proves the varying impacts of energy transition RRD and EEF investments on CO2 emissions. In line with the outcomes of the novel WLMC model various policy endeavors such as focusing on displacement between sub-types of R&D investments are argued to ensure the decarbonization of the economies.
Role of energy transition in easing energy security risk and decreasing CO2 emissions: Disaggregated level evidence from the USA by quantile-based models
(ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD, 2024) Tevfik Kartal; Dilvin Taskin; Muhammad Shahbaz; Dervis Kirikkaleli; Serpil Kilic Depren
Consistent with the increasing environmental interest the clean energy transition is highly critical to achieving decarbonization targets. Also energy security has become an important topic under the shadow of the energy crisis. Accordingly countries have been trying to stimulate clean energy use to preserve the environment and ensure energy security. So considering the leading role of economic size and volume of energy use the study examines the USA to define whether energy transition helps decrease energy security risk (ESR) and curb CO 2 emissions. So the study applies a disaggregated level analysis by performing quantile-based models for the period from 2001/Q1 through 2022/Q4. The results demonstrate that (i) the energy transition index decreases environmental ESR at higher quantiles and reliability ESR at lower and middle quantiles whereas it is not beneficial in declining economic and geopolitical ESR, (ii) energy transition curbs CO 2 emissions in building and transport sectors at lower quantiles whereas it does not help decrease CO 2 emissions in industrial and power sectors, (iii) energy transition is mostly ineffective on ESR whereas it is highly effective in curbing CO 2 emissions in all sectors except for transport across various quantiles as time passes, (iv) the results differ according to the aggregated and disaggregated levels, (v) the results are consistent across main and alternative models. Hence the study highlights the dominant effect of energy transition in curbing sectoral CO 2 emissions rather than easing ESR. Accordingly the study discusses various policy implications for the USA.
Citation - WoS: 74
Citation - Scopus: 76
The impact of geopolitical risk- institutional governance and green finance on attaining net-zero carbon emission
(ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD, 2024) Ahmed Imran Hunjra; Muhammad Azam; Peter Verhoeven; Dilvin Taskin; Jiapeng Dai; Verhoeven, Peter; Taskin, Dilvin; Hunjra, Ahmed Imran; Azam, Muhammad; Dai, Jiapeng
This research investigates the impact of geopolitical risk institutional governance and green finance on environmental outcomes specifically focusing on carbon emissions and ecological footprint. Utilizing the dynamic CS-ARDL method and aggregated mean group analysis on a panel dataset covering 21 nations from 2000 to 2021 our findings reveal that heightened geopolitical risk leads to both short and long run increases in carbon emissions and the ecological footprint. Our study finds both a direct as well as indirect connection between governance green finance and environmental outcomes in both the short and long run highlighting the nuanced impact of governance on the formulation of environmental policies and regulatory frameworks. The results emphasize the need for targeted strategies including focused investments and incentives for sustainable finance particularly in conflict-affected regions. Furthermore our research underscores the enduring impact of historical events such as wars on contemporary environmental indicators emphasizing the importance of proactive conflict prevention measures. Our research suggests that policymakers should adopt comprehensive strategies that prioritize emission reduction during short-run spikes in geopolitical risk while maintaining a steadfast commitment to long-run sustainability.

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