Yazar "Eren, Ezgi" seçeneğine göre listele

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    A DESIGN FOR PREVENTION OF VIOLATION OF DISABLED PARKING SPACES: DDPS (DETERRENT DISABLED PARKING SYSTEM)
    (2019) Katanalp, Burak Yiğit; Nennıoglu, A. Kemal; Özinal, Yağmur; Yıldırım, Zeynel Baran; Eren, Ezgi
    Limited public awareness and insufficient parking spaces result in the conscious orunconscious occupation of disabled parking by other drivers. According to the law ontraffic penalties, violation of disabled parking is punishable by a penalty and drivingreputation points. However, it is only possible to control and implement this law underideal conditions. This study describes in detail the Deterrent Disabled Parking System(DDPS), a distinctive design, planned in order to control disabled parking and to allowthe implementation of penal sanctions in case of violation and the algorithm for thesystem is presented. The design is modeled with Arduino UNO, ultrasonic distance sensor,Radio Frequency Identification (RFID), LCD screen and various connection elements. Theperformance of the system is tested with three different scenarios with a 76%measurement accuracy. The results are discussed and ways of improvement areindicated.
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    A review on bike-sharing: The factors affecting bike-sharing demand
    (Elsevier Ltd, 2020) Eren, Ezgi; Uz, Volkan Emre
    This paper aimed to address the need for a comprehensive review on the factors affecting bike-sharing demand to bridge the gaps by deepening the knowledge on weather, built environment and land use, public transportation, station level, socio-demographic effects, temporal factors, and safety. This article evaluates recent studies on station-based bike sharing in literature and seeks answers to two main research questions: First, how do the weather conditions, built environment and land use, public transportation, socio-demographic attributes, temporal factors, and safety affect the bike-sharing trip demand? Second, what are the most commonly used factors in literature affecting trip demand? For this purpose, an overview of the factors affecting trip demands has been established to evaluate the performance of Bike-Share Programs(BSPs) comprehensively. The results can provide reliable estimate for planners or decision-makers in understanding the key factors contributing to bike-sharing demand. The information obtained from this overview can also be a guideline for BSP planners, policymakers and researchers to improve the efficiency of BSPs. © 2019 Elsevier Ltd
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    Assessment of the Effects of Induction Heating Induced-Healing on the Fracture Properties of Very Thin Asphalt Concrete
    (Springer International Publishing Ag, 2024) Eren, Ezgi; Valentin, Jan; Ahmedzade, Perviz
    Self-healing by induction heating stands as a promising and sustainable technology for asphalt pavement maintenance applications. This study involves performing a series of test cycles, encompassing first SCB fracture testing on a waste steel fiber (WSF)-reinforced for an asphalt concrete for thin surface layers (BBTM) and asphalt concrete for binder layer (ACL), induction heating for healing, and subsequent second SCB fracture testing. The research aims to analyze how crack healing ability changes with a semi-circular bending (SCB) test before and after healing, considering the combination of BBTM and ACL with different WSF content. Based on the SCB test fractural parameters, the healing indexes (HI) are obtained through peak load (Fmax) and critical stress intensity factor (K-IC). Additionally, the fracture parameter results obtained based on the amount of WSF in the BBTMs and ACLs are consistent with the results of the indirect tension to cylindrical specimen (IT-CY) test. Consequently, it was emphasized that asphalt mixtures containing WSF have the potential to heal cracks through induction heating, and the healing ability can be improved depending on theWSF content of the wearing and binder layer. In addition, it was shown that ACL and BBTM samples with higher stiffness values are much more difficult to heal in terms of Fmax and K-IC.
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    Exploring the effect of basalt fibers on maximum deviator stress and failure deformation of silty soils using ANN, SVM and FL supported by experimental data
    (Elsevier Sci Ltd, 2022) Ndepete, Cyrille Prosper; Sert, Sedat; Beycioglu, Ahmet; Katanalp, Burak Yigit; Eren, Ezgi; Bagriacik, Baki; Topolinski, Syzmon
    Because the experimental trials in civil engineering field are difficult and time-consuming, the application of artificial intelligence (AI) techniques is attracting considerable attention, with their use enabling successful results to be more easily obtained. In this study, we investigated the effect of fiber size, fiber amount, water content, and cell pressure on maximum deviator stress (MDS) and failure deformation (FD) of basalt fiber (BF) -reinforced, unsaturated silty soils using three AI techniques: the artificial neural network (ANN), support vector machine (SVM), and fuzzy logic (FL). The numerical analyses and experiments were conducted using varying amounts (1, 1.5, and 2%) and lengths (6, 12, and 24 mm) of BF, and a total of 180 samples were prepared for the detailed investigation. In order to compare model performances, R-2 and MAPE goodness-of-fit metrics were used. The experimental results revealed that the addition of BF generally increased the MDS of the soils, which corresponds to the shearing resistance. According to AI models result, FL outperformed the SVM and ANN, with a R-2 value of 0.938, especially in FD prediction. The sensitivity analysis was performed to ascertain the effect of the inputs on the MDS and FD response variables. Results revealed that fiber length and cell pressure have substantial influence in MDS estimations.
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    Farklı arazi kullanımlarına dayalı alternatif bisiklet paylaşım istasyonu yer seçimi için cbs tabanlı hibrit bir yaklaşım
    (Adana Alparslan Türkeş Bilim Ve Teknoloji Üniversitesi, 2020) Eren, Ezgi; Çalım, Faruk Fırat
    Son on yılda dünya çapında giderek yaygınlaşan Bisiklet Paylaşım Sistemleri (BPS), akıllı hareketliliği desteklemeyi amaçlayan paylaşımlı bir akıllı ulaşım sistemi (AUS) teknolojisidir. Şehirlerde trafik sıkışıklıklarının, hava ve gürültü kirliliğinin ve doğal kaynak tüketiminin azaltılması açısından BPS'lerin verimliliğinin arttırılmasını sağlayacak karmaşık karar problemlerine çözüm önerilerinin geliştirilmesi, sürdürülebilir şehirlerde daha yaşanılabilir bir çevre için önem arz etmektedir. BPS'lerin verimliliğinin arttırılması noktasında en önemli stratejik kararlardan biri sisteme ait istayon yerlerinin belirlenmesi sürecidir. Bu çalışma, farklı arazi kullanım türüne göre alternatif istasyon yerlerinin belirlenmesi ve mevcut istasyon yerlerinin İzmir'deki bir BPS için uygunluğunun değerlendirilmesi için bilimsel bir çerçevenin sunulmasını amaçlamaktadır. Bu amaçla, BPS istasyonlarının konumlandırılmasında etkili olan kriterler belirlenmiş ve kriterler farklı arazi kullanım türüne göre AHP yöntemi kullanılarak ağırlıklandırılmıştır. Aynı zamanda, arazi kullanım türüne göre kriter ağırlıklarındaki değişim değerlendirilmiştir. Potansiyel yolcuların, kriterlere ait tesislerden belirli bir erişim mesafesinde bulunan istasyonlarda potansiyel yolcuların gezi üretme eğiliminin belirsizliği, bulanık mantık yaklaşımını kullanarak karakterize edilmiştir. Son olarak İzmir ilinde yer alan bir BPS için ulaşım, rekreasyon ve eğitim amaçlı potansiyel istasyonlar tespit edilmiş ve mevcut istasyonlar ve potansiyel istasyonlar en iyiden en kötüye doğru VIKOR yardımıyla listelenmiştir. Çalışma sonucunda kentsel ulaşım sistemine entegre edilebilecek, rekreasyon faaliyetlerini destekleyebilecek ve eğitim alanlarına kolayca erişilebilek ulaşım, rekreasyon ve eğitim arazi kullanım türleri için 42, 28 ve 48 alternatif istasyon yerleri belirlenmiştir. Ayrıca, arazi kullanımına göre mevcut istasyonlardan 1105 numaralı istasyonun ulaşım, rekreasyon ve eğitim amaçlı gezileri en iyi şekilde destekleyeceği belirlenmiştir.
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    The novel approaches to classify cyclist accident injury-severity: Hybrid fuzzy decision mechanisms
    (Pergamon-Elsevier Science Ltd, 2020) Katanalp, Burak Yigit; Eren, Ezgi
    In this study, two novel fuzzy decision approaches, where the fuzzy logic (FL) model was revised with the C4.5 decision tree (DT) algorithm, were applied to the classification of cyclist injury-severity in bicycle-vehicle accidents. The study aims to evaluate two main research topics. The first one is investigation of the effect of road infrastructure, road geometry, street, accident, atmospheric and cyclist related parameters on the classification of cyclist injury-severity similarly to other studies in the literature. The second one is examination of the performance of the new fuzzy decision approaches described in detail in this study for the classification of cyclist injury-severity. For this purpose, the data set containing bicycle-vehicle accidents in 2013-2017 was analyzed with the classic C4.5 algorithm and two different hybrid fuzzy decision mechanisms, namely DT-based converted FL (DT-CFL) and novel DT-based revised FL (DT-RFL). The model performances were compared according to their accuracy, precision, recall, and F-measure values. The results indicated that the parameters that have the greatest effect on the injury-severity in bicycle-vehicle accidents are gender, vehicle damage-extent, road-type as well as the highly effective parameters such as pavement type, accident type, and vehicle-movement. The most successful classification performance among the three models was achieved by the DT-RFL model with 72.0 % F measure and 69.96 % Accuracy. With 59.22 % accuracy and %57.5 F-measure values, the DT-CFL model, rules of which were created according to the splitting criteria of C4.5 algorithm, gave worse results in the classification of the injury-severity in bicycle-vehicle accidents than the classical C4.5 algorithm. In light of these results, the use of fuzzy decision mechanism models presented in this study on more comprehensive datasets is recommended for further studies.