Yazar "Aydin, Ahmet Arif" seçeneğine göre listele

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    CAP-based Examination of Popular NoSQL Database Technologies in Streaming Data Processing
    (Ieee, 2019) Doguc, Tugba Beril; Aydin, Ahmet Arif
    Nowadays, when the Internet, software and hardware technologies develop rapidly, we are in a digital era where a wide range of resources generate data in different formats and 7/24. It is essential for organizations to quickly process data in near-real time and store it in a scalable form, especially without loss of data. In addition, the importance of streaming data processing due to the desire to get information quickly instantly increases. In this study, the popular NoSQL databases, which are prominent in streaming data processing, have been examined based on CAP's theorem. This work will help software developers in the selection and use of NoSQL databases for streaming data processing.
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    A Comparative Perspective on Technologies of Big Data Value Chain
    (Ieee-Inst Electrical Electronics Engineers Inc, 2023) Aydin, Ahmet Arif
    Data is one of the most valuable assets in the digital era because it may conceal hidden valuable insights. Diverse organizations in diverse domains overcome the challenges of the big data value chain by employing a wide range of technologies to meet their needs and achieve a variety of goals to support their decision-making. Due to the significance of data-oriented technologies, this paper presents a model of the big data value chain based on technologies used in the acquisition, storage, and analysis of data. The following are the paper's contributions: First, a model of the big data value chain is developed to illustrate a comprehensive representation of the big data value chain that depicts the relationships between the characteristics of big data and the technologies associated with each category. Second, in contrast to previous research, this paper presents an overview of technologies for each category of the big data value chain. The third contribution of this paper is to assist researchers and developers of data-intensive systems in selecting the appropriate technology for their specific application development use cases by providing examples of applications and use cases from prominent papers in a variety of fields and by describing the capabilities and stages of the technologies being presented so that the right technology is used at the right time in the big data collection, processing, storage, and analytics tasks.
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    Data modelling for large-scale social media analytics: design challenges and lessons learned
    (Inderscience Enterprises Ltd, 2020) Aydin, Ahmet Arif; Anderson, Kenneth M.
    We live in a world of big data; organisations collect, store, and analyse large volumes of data for various purposes. The five V's of big data introduce new challenges for developers to handle when performing data processing and analysis. Indeed, data modelling is one of the most challenging and critical aspects of big data because it determines how data will be structured and stored; these decisions then impact how that data can be processed and analysed. In this paper, we report on designing a data model for storing and analysing Twitter data in support of crisis informatics. In this work, we leverage the data model provided by columnar NoSQL data stores to design column families that can efficiently index, sort, store and analyse large Twitter datasets. In particular, our column families are designed to achieve efficient batch data processing. We evaluate these claims and discuss our future work.
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    A Novel Energy Consumption Prediction Model of Electric Buses Using Real-Time Big Data From Route, Environment, and Vehicle Parameters
    (Ieee-Inst Electrical Electronics Engineers Inc, 2023) Ekici, Yunus Emre; Akdag, Ozan; Aydin, Ahmet Arif; Karadag, Teoman
    Electric vehicles (EVs) have positive impacts on reducing oil dependence and exhaust emissions. However, the range problem of EVs is a factor that raises concerns for individual users and bus operators. For this reason, studies on increasing the range of the electric buses in public transportation is extremely important to ensure optimum operation. In this study, a novel energy consumption model, MTECM (Malatya Trolleybus Energy Consumption Model), is developed using the multi-parameter linear regression method. The real-time big data was collected on the field of Trolleybus vehicles, which have been operated for 8 years in Malatya / Turkiye. Firstly, by calculating the correlation of the parameters affecting this model, the parameters that are suitable for the purpose of our study are determined and regression analysis is performed on the original Trolleybus dataset. A total of 75.497.472 data are analyzed for this model. The RMSE (Root Mean Square Error) of MTECM is calculated as 0.29996. The trained model is applied to the 10 busiest routes in Malatya in terms of passenger density. The RMSE value on these routes is calculated between 0.30299 and 0.31421. Based on the results, with lower error rates, the proposed novel model is more efficient than other studies in the literature. In addition, energy consumption can be calculated for any route planned to establish an electric bus operation with MTECM. Therefore, according to the consumption obtained, the correct determination and selection of parameters that significantly affect the investment cost such as route, vehicle length, engine power, and battery capacity can be made.
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    Optimization of Proportional-Integral-Derivative Parameters for Speed Control of Squirrel-Cage Motors with Seahorse Optimization
    (Aves, 2024) Ekici, Yunus Emre; Akdag, Ozan; Aydin, Ahmet Arif; Karadag, Teoman
    The two different motion behaviors of seahorses in nature served as inspiration for the seahorse optimization (SHO) method, which is a new metaheuristic swarm intelligence-based approach to solving fundamental engineering problems. In this study, the propo rtion al-in tegra l-der ivati ve (PID) parameters for the simplified speed control of the manipulator joint using squirrel-cage induction motors were calculated with the SHO algorithm. As a result of these calculations, Kp, Ki, and Kd values were obtained as 0.0430, 0.00474, and 0.03254, respectively. Then, the time for the squirrel-cage motor to reach 50 rpm (revolutions per minute) and 90 rpm was calculated with the help of SHO. In PID + SHO operation, the squirrel-cage electric motor reached 50 rpm in 3 seconds and 90 rpm in 8 seconds. In this study, in which the SHO optimization method was used, it was calculated that the acceleration of the squirrel-cage motor and reaching the desired value gave 50% better results compared to the particle swarm optimization algorithm.
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    An Overview of Quality Attributes for Data Intensive Systems in Crisis Informatics
    (Ieee, 2017) Aydin, Ahmet Arif
    In today's digital world, we have been exposed by tremendous amounts of data generated by numerous sources and the developers of data intensive systems are confronted with the challenges of collecting, analyzing and storing large amounts of data. Dealing with those challenges and designing software systems provides demanded set of quality attributes require engaging with sophisticated approaches, developing clever techniques, and carefully making use of cutting edge technologies. In this paper, first, an outline of crisis informatics research and crisis management phases are introduced, next, an overview of quality attributes for data intensive systems is presented, last, a classification of frequently demanded quality attributes for crisis data intensive system is provided by taking into account crisis management phases and the type of data analytics performed.
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    Prominent quality attributes of crisis software systems: a literature review
    (Tubitak Scientific & Technological Research Council Turkey, 2020) Aydin, Ahmet Arif
    Developing software systems to meet user-demanded functionality is critical. Achieving the design goals by providing the needed functionality is a necessary task, and it is about figuring out a proper set of quality attributes and implementing each one by reflecting a complete set of quality attributes. This study presents popular quality attributes of crisis software systems by conducting a literature review. Each crisis software system has been studied by concentrating on crisis management phases where the system is used, design purposes, and the data processing style. The findings of this research shed light on the crisis software development process by presenting a quality attribute-oriented perspective, addressing design challenges, and recommending to developers remedies to handle challenges.