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    Energy Management in Organized Industrial Zones: Promoting the Green Energy Transition in Turkish Manufacturing Industry
    (Ieee, 2024) Ediger, Volkan S.; Kucuker, Mehmet Ali; Berk, Istemi; Inan, Ali; Uctug, Fehmi Gorkem; 0
    Organized Industrial Zones (OIZ), which gained legal status by Law 4562 of 2000, played a significant role in Turkish industrialization policies, particularly in improving Small and Medium-sized Enterprises (SMEs). The energy management (EM) within OIZs is essential for Turkiye's green transition and 2053 net-zero pathway. Following the publication of a directive on OIZ's electricity market activities in 2006, enterprises can purchase electricity directly from OIZ management. Moreover, the Energy Efficiency Law No. 5627 of 2007 required OIZs to establish an energy management unit (EMU) to serve the participants with less than 1000 tons of oil equivalent (toe) energy consumption. EMUs provide OIZ management with a unique opportunity to enhance sustainable energy transition by increasing renewable energy production and improving the energy efficiency of participating enterprises. The primary goal of this research is to evaluate the effectiveness of energy management units in OIZs in encouraging energy efficiency and green energy transition in the Turkish manufacturing industry. As a case study, we examine EM in the Adana Haci Sabanci Organized Industrial Zone (Adana OIZ), which ranks third among OIZs regarding electricity consumption. We analyze data on electricity infrastructures, roof-top PVs, invoice settlements/offsets, energy efficiency investments, and GHG emissions between 2017 and 2023. Our preliminary findings suggest that EMU in the Adana OIZ makes a very important contribution to the green transition of industrial establishments and that regulatory changes over the last decades have had positive effects. The share of renewable energy in the total energy mix increased from 1.6% to 21.4% over six years, and there has been a noteworthy enhancement in energy efficiency, reaching 27% in 22 companies evaluated. The main policy implication of our findings is that the role of regulatory bodies and efficient energy management in OIZs will be critical in achieving Turkiye's net zero target of 2053.
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    Securereg: Combining Nlp and Mlp for Enhanced Detection of Malicious Domain Name Registrations
    (Institute of Electrical and Electronics Engineers Inc., 2024) Ecevit, Mert İlhan; Dağ, Hasan; Dag,H.; Creutzburg,R.; 0
    The escalating landscape of cyber threats, charac-terized by the registration of thousands of new domains daily for lar ge-scale Inter net attacks such as spam, phishing, and drive-by downloads, underscor es the imperati ve for innovative detection methodologies. This paper introduces a cutting-edge approach for identifying suspicious domains at the onset of the registration process. The accompanying data pipeline generates crucial featur es by comparing new domains to register ed do-mains, emphasizing the crucial similarity score. The proposed system analyzes semantic and numerical attrib utes by leveraging a novel combination of Natural Language Processing (NLP) techniques, including a pretrained CANINE model and Multilayer Perceptr on (MLP) models, providing a robust solution for early threat detection. This integrated Pretrained NLP (CANINE) + MLP model showcases the outstanding perf ormance, surpassing both individual pretrained NLP models and standalone MLP models. With an PI score of 84.86% and an accuracy of 84.95%on the SecureReg dataset, it effecti vely detects malicious domain registrations. The finding demonstrate the effecti veness of the integrated appr oach and contrib ute to the ongoing efforts to develop proactive strategies to mitigate the risks associated with illicit online activities through the ear ly identificatio of suspicious domain registrations. © 2024 IEEE.