Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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  • Conference Object
    Citation - Scopus: 2
    Outage Probability Analysis of Triple-Hybrid Rf/Fso Communication System
    (Ieee, 2024) Bakirci, Emre Berker; Ahrazoglu, Evla Safahan; Altunbas, Ibrahim; Erdogan, Eylem
    Terahertz (THz) and free space optical (FSO) transmission techniques are considered as alternatives for radio frequency (RF) transmission to meet the requirements for the sixth generation and beyond wireless communication systems. However, these transmission techniques may experience high level of deterioration under different weather conditions. In this study, triple-hybrid RF/FSO/THz system is proposed to enhance the system performance. The results have shown that the proposed system has improved outage probability performance under wide range weather conditions compared to only RF, only FSO, and only THz systems as well as dual-hybrid systems (RF/FSO, RF/THz, and FSO/THz). Theoretical results are validated via computer simulations.
  • Conference Object
    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
    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.
  • Conference Object
    Improvements on a Multi-Task Bert Model
    (Ieee, 2024) Agrali, Mahmut; Tekir, Selma
    Pre-trained language models have introduced significant performance boosts in natural language processing. Fine-tuning of these models using downstream tasks' supervised data further improves the acquired results. In the fine-tuning process, combining the learning of tasks is an effective approach. This paper proposes a multi-task learning framework based on BERT. To accomplish the tasks of sentiment analysis, paraphrase detection, and semantic text similarity, we include linear layers, a Siamese network with cosine similarity, and convolutional layers to the appropriate places in the architecture. We conducted an ablation study using Stanford Sentiment Treebank (SST), Quora, and SemEval STS datasets for each task to test the framework and its components' effectiveness. The results demonstrate that the proposed multi-task framework improves the performance of BERT. The best results obtained for sentiment analysis, paraphrase detection, and semantic text similarity are accuracies of 0.534 and 0.697 and a Pearson correlation coefficient of 0.345.