Browsing by Author "Yucekaya,A."
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Conference Object Citation Count: 0Blockchain Technology In Loyalty Program Applications(Association for Computing Machinery, 2022) Bozkurt,H.I.; Gemici,S.; Yucekaya,A.; Hekimoglu,M.Loyalty programs provide income to the user as a result of their expenditures. It helps businesses if the customer ensures continuity. A loyalty program is based on the bilateral relationship between the customer and the business. It is important to be sure of the reliability of this bilateral relationship and to be able to follow it. Today, many companies are trying to incorporate Blockchain technology into their systems because they pay attention to reliability and transparency. In this study, a loyalty ecosystem based on Blockchain technology, which will include member businesses, change the shopping and reward experience, and encourage employees is explained. We propose an application named Decentralized Loyalty Token (DLOT) to be used by entities where the community is together and the spending potential is high such as restaurants, cafes, and e-commerce platforms that want to be included in this structure. Users will earn rewards while spending DLOT Tokens and can store and accumulate the rewards indefinitely or use them for any payment. In addition, users will be able to convert the loyalty Tokens into a digital value in other businesses included in Wallet. The details of the proposed Blockchain-based loyalty system are explained along with benefits to customers and entities. © 2022 ACM.Article Citation Count: 0An Overview of Electricity Consumption in Europe: Models for Prediction of the Electricity Usage for Heating and Cooling(Econjournals, 2024) Bilge, Ayşe Hümeyra; Aktunc,E.A.; Bilge,A.H.; Yucekaya,A.Although aggregate electricity consumption provides valuable information for market analysis, demand composition, including industrial, residential, illumination, and other uses, and special days, such as national or religious holidays and annual industrial shutdowns, differ for each country. This paper analyzes the hourly electricity consumption of European countries in the European Transmission System Operation for Electricity (ENTSO-E) grid from 2006 to 2018. We propose an outlier detection method to identify special days and a modulated Fourier Series Expansion model to determine the breakdown of industrial versus household consumption and heating versus cooling consumption. The proposed outlier detection method uses the time series for each hour and checks whether a day has more than a threshold number of hours with exceptional electricity consumption levels. The proposed demand prediction model has a 3% average error when electricity usage for heating is not dominant. It also allows country classification based on consumption patterns to efficiently manage regional or country-based electricity markets. © 2024, Econjournals. All rights reserved.