Browsing by Author "Kilinc, M"

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    Thermal, Chemical and Mechanical Properties of Regenerated Bacterial Cellulose Coated Cotton Fabric
    Kilinc, M; Ay, E; Kut, D
    Bacterial cellulose is a raw material that is used in many industrial areas such as textile due to its properties and an alternative to plant cellulose whose usage is increasing day by day. In this research, dissolved bacterial cellulose was used as a coating material. After the coating process, samples were immersed in three different coagulation baths to provide regeneration of the coated material. TGA, FTIR, SEM-EDX, air permeability, tensile test, thermal comfort (alambeta), and water vapor transmission (permetest) analyses were carried out to compare the mechanical, chemical, and thermal properties between raw fabric and treated fabrics. Because of chemical analysis, it was observed that the structures are similar to each other. In terms of thermal stability, it has been determined that the samples that have been coated are more durable than the raw fabric. The tensile test revealed that there was a decrease between 15.05% and 41,62% in the strength of coated materials. According to the results of air permeability, alambeta, and permetest, a decrease in air permeability values, an increase in relative water vapor permeability, and thermal conductivity values were observed with the increase of the remaining coating material in the fabric.
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    Feature selection for Turkish Crowdfunding projects with using filtering and wrapping methods
    Kilinc, M; Aydin, C
    Crowdfunding (CF) platforms host an increasing number of projects, where financial support from backers plays a vital role in project realization. Unfortunately, CF projects have experienced a downward trend in success rates. To address this issue, it is crucial to identify the factors that influence success by analyzing project characteristics. In our study, we collected project data from Turkey's Fongogo CF platform, performed feature selection, and rigorously tested the results. We employed various methods such as Pearson correlation, mutual information statistics, chi-square, Fisher's score from filtering methods, and recursive feature elimination from wrapper methods to understand feature relationships. We proposed a cross-validated recursive feature elimination method for feature selection. The identified success factors were classified using diverse machine learning algorithms, with the Gradient Boosting algorithm achieving the highest result of 84.28%. The results obtained with wrapper methods highlight the potential of utilizing features in decision support processes to enhance CF success.
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    Balancing performance and comfort in virtual reality: A study of FPS, latency, and batch values
    Geris, A; Cukurbasi, B; Kilinc, M; Teke, O
    This manuscript investigates the relationships among various performance metrics in a virtual reality (VR), namely frames per second (FPS), latency, batches, and the number of triangles (tris) and vertices (verts). The study aims to uncover correlations and directional associations between these metrics, shedding light on their impact on VR performance. The findings reveal a significant correlation between FPS and latency, albeit in opposite directions. Higher FPS values are associated with reduced latency, indicating that a smoother visual experience is accompanied by shorter delays in the VR. Conversely, lower FPS values are linked to increased latency, suggesting a potential degradation in overall system responsiveness. Additionally, a strong correlation is observed between latency and batches processed. This finding implies that latency has a direct impact on the system's ability to efficiently process and render objects within VR. Furthermore, a positive correlation is identified between the number of batches and the values of tris and verts. This relationship suggests that higher batch counts are associated with larger quantities of triangles and vertices, reflecting a more complex scene rendering process. Consequently, the performance of VR may be influenced by the density and intricacy of the virtual environments, as indicated by these metrics.