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Article Citation - WoS: 1Citation - Scopus: 1Machine Vs. Deep Learning Comparision for Developing an International Sign Language Translator(Taylor & Francis Ltd, 2022) Eryilmaz, Meltem; Balkaya, Ecem; Ucan, Eylul; Turan, Gizem; Oral, Seden GulayThis study aims to enable deaf and hard-of-hearing people to communicate with other individuals who know and do not know sign language. The mobile application was developed for video classification by using MediaPipe Library in the study. While doing this, considering the problems that deaf and hearing loss individuals face in Turkey and abroad modelling and training stages were carried out with the English language option. With the real-time translation feature added to the study individuals were provided with instant communication. In this way, communication problems experienced by hearing-impaired individuals will be greatly reduced. Machine learning and Deep learning concepts were investigated in the study. Model creation and training stages were carried out using VGG16, OpenCV, Pandas, Keras, and Os libraries. Due to the low success rate in the model created using VGG16, the MediaPipe library was used in the formation and training stages of the model. The reason for this is that, thanks to the solutions available in the MediaPipe library, it can normalise the coordinates in 3D by marking the regions to be detected in the human body. Being able to extract the coordinates independently of the background and body type in the videos in the dataset increases the success rate of the model in the formation and training stages. As a result of an experiment, the accuracy rate of the deep learning model is 85% and the application can be easily integrated with different languages. It is concluded that deep learning model is more accure than machine learning one and the communication problem faced by hearing-impaired individuals in many countries can be reduced easily.Article Mixed Method Investigation of the Major Challenges to the Sustainable Deployment of the Electric Vehicle Charging Station Network in Türkiye(Taylor & Francis Ltd, 2025) Erol, Ismail; Oztel, Ahmet; Peker, Iskender; Ar, Ilker Murat; Benli, Tolga; Turan, IsmetCharging the increasing number of electric vehicles (EVs) in use requires the deployment of EV charging station networks (EVCSN). However, there are various challenges to deploying EVCSN in a sustainable manner. T & uuml;rkiye, a developing country, should also build a robust EVCSN to encourage future adoption of EVs as the country's market for EVs has been rapidly growing. The literature review concludes that no previous study has systematically explored challenges to the sustainable deployment of EVCSN. The goal of this study is, therefore, twofold: first, it identifies those challenges through the lenses of commonly used theories. Second, it explores them using a multi-criteria decision-making (MCDM) framework that incorporates a rough-derived interval-valued neutrosophic set (R-IVN)-based ISM into MICMAC. By deriving interval neutrosophic information from single-valued expert inputs using rough number operators, the proposed approach more accurately captures epistemic uncertainty and variability in expert judgments compared to conventional interval-based models. The method is further validated through a novel Dice-S & oslash;rensen similarity index-based simulation approach. The findings of this study suggest that developing government policies and regulations and addressing the existence of vertically integrated companies are the critical challenges with higher driving powers. These findings provide key responsibilities for stakeholders, including urban municipalities, in developing guidelines for EVCSN deployment.Article Citation - WoS: 18Citation - Scopus: 18A New Outlier Detection Method Based on Convex Optimization: Application To Diagnosis of Parkinson's Disease(Taylor & Francis Ltd, 2021) Taylan, Pakize; Yerlikaya-Ozkurt, Fatma; Bilgic Ucak, Burcu; Weber, Gerhard-WilhelmNeuroscience is a combination of different scientific disciplines which investigate the nervous system for understanding of the biological basis. Recently, applications to the diagnosis of neurodegenerative diseases like Parkinson's disease have become very promising by considering different statistical regression models. However, well-known statistical regression models may give misleading results for the diagnosis of the neurodegenerative diseases when experimental data contain outlier observations that lie an abnormal distance from the other observation. The main achievements of this study consist of a novel mathematics-supported approach beside statistical regression models to identify and treat the outlier observations without direct elimination for a great and emerging challenge in humankind, such as neurodegenerative diseases. By this approach, a new method named as CMTMSOM is proposed with the contributions of the powerful convex and continuous optimization techniques referred to as conic quadratic programing. This method, based on the mean-shift outlier regression model, is developed by combining robustness of M-estimation and stability of Tikhonov regularization. We apply our method and other parametric models on Parkinson telemonitoring dataset which is a real-world dataset in Neuroscience. Then, we compare these methods by using well-known method-free performance measures. The results indicate that the CMTMSOM method performs better than current parametric models.Article Citation - WoS: 2Citation - Scopus: 2Influence of Surface Finish on Flexural Strength and Microhardness of Indirect Resin Composites and the Effect of Thermal Cycling(Taylor & Francis Ltd, 2012) Bicer, Arzu Zeynep Yildirim; Dogan, Arife; Dogan, Orhan Murat; Sengonul, Merih Cemal; Artvin, ZaferThis study investigated the effect of surface finish and thermal cycling procedures on flexural strength and surface microhardness of three indirect resin composites, Artglass (R), Signum (R), and Solidex (R). The specimens were prepared in sufficient number and size according to flexural and microhardness test requirements (n=10). Scanning electron microscopy-energy dispersive x-ray (SEM-EDX) analysis was also used for studying the morphology, dispersion, and elemental compositions of fillers. The EDX results showed that Artglass contained 1.57% aluminium oxide (Al2O3), 53.29% silicon dioxide (SiO2), and 2.62% barium oxide (BaO); Signum had 55.69% silicon dioxide (SiO2) and Solidex had 44.99% silicon dioxide (SiO2) of total mass. Artglass appeared to display the best flexural strength values under all the test conditions employed (range: 116.8 +/- 32.18 to 147.8 +/- 47.97 MPa), and it was followed by Signum (range: 93.7 +/- 22.84 to 118.0 +/- 33.45 MPa). Thermal cycling did not seem to have affected the flexural strength of Artglass and Signum (p > 0.05); however, it led to a significant decrease, from (110.5 +/- 20.69 MPa) to 74.0 +/- 13.30 MPa (p < 0.001), in the strength of polished Solidex specimens. While surface microhardness of the three materials increased by polishing ( Artglass: 55.7 +/- 2.64/74.1 +/- 8.63 Vickers Hardness Numbers (VHN); Signum: 44.8 +/- 3.12/60.7 +/- 4.50 VHN; Solidex: 44.0 +/- 2.31/53.4 +/- 3.58 VHN for unpolished/polpolished specimens), thermal cycling had a deleterious effect on this property (p < 0.001).Article Citation - WoS: 19Citation - Scopus: 20Human Body Shadowing Variability in Short-Range Indoor Radio Links at 3-11 Ghz Band(Taylor & Francis Ltd, 2009) Kara, AliMeasurement results for human body shadowing and local environmental effects in short-range indoor radio channels are presented. A narrowband measurement system, comprising a signal generator, two identical triangular monopoles and a spectrum analyser, was used in the measurements. When the radio link was periodically blocked by a human body with various objects in and around the link, fading depths of up to 15dB and even more were observed at spot frequencies of 3-11GHz band. Standard deviation and its range for human body blockage are estimated for different radio link scenarios simulating real environments. The distribution of human body shadowing was analysed and compared with known distribution functions.Article Citation - WoS: 4Citation - Scopus: 5Roof Shape Modelling for Multiple Diffraction Loss in Cellular Mobile Communication Systems(Taylor & Francis Ltd, 2002) Kara, A; Yazgan, EThe effects of roof shapes on multiple diffraction loss in cellular mobile communication systems are investigated. Building roofs are modelled as finitely conducting wedges with different, included angles (peaked roofs). Multiple diffraction loss, a measure of diffraction loss due to multiple building geometry, is computed by using the method of UTD (uniform theory of diffraction) for 90degrees and 120degrees wedges over the communication paths oblique to building blocks. The results, compared with the absorbing edge model, 0degrees wedge, show that multiple diffraction loss decreases with increasing wedge angle.Article Citation - WoS: 10Citation - Scopus: 12Further Properties of the Laplace Transform on Time Scales With Arbitrary Graininess(Taylor & Francis Ltd, 2013) Bohner, Martin; Guseinov, Gusein Sh; Karpuz, BasakIn this work, we generalize several properties of the usual Laplace transform to the Laplace transform on arbitrary time scales. Among them are translation theorems, transforms of periodic functions, integration of transforms, transforms of derivatives and integrals, and asymptotic values.Article Citation - WoS: 27Citation - Scopus: 39Properties of the Laplace transform on time scales with arbitrary graininess(Taylor & Francis Ltd, 2011) Bohner, Martin; Guseinov, Gusein Sh.; Karpuz, BasakWe generalize several standard properties of the usual Laplace transform to the Laplace transform on arbitrary time scales. Some of these properties were justified earlier under certain restrictions on the graininess of the time scale. In this work, we have no restrictions on the graininess.Article Citation - WoS: 60Citation - Scopus: 64Seeding the Initial Population With Feasible Solutions in Metaheuristic Optimization of Steel Trusses(Taylor & Francis Ltd, 2018) Azad, Saeid KazemzadehIn spite of considerable research work on the development of efficient algorithms for discrete sizing optimization of steel truss structures, only a few studies have addressed non-algorithmic issues affecting the general performance of algorithms. For instance, an important question is whether starting the design optimization from a feasible solution is fruitful or not. This study is an attempt to investigate the effect of seeding the initial population with feasible solutions on the general performance of metaheuristic techniques. To this end, the sensitivity of recently proposed metaheuristic algorithms to the feasibility of initial candidate designs is evaluated through practical discrete sizing of real-size steel truss structures. The numerical experiments indicate that seeding the initial population with feasible solutions can improve the computational efficiency of metaheuristic structural optimization algorithms, especially in the early stages of the optimization. This paves the way for efficient metaheuristic optimization of large-scale structural systems.Article Citation - WoS: 7Citation - Scopus: 8Analysis of the Two-Unit Cold Standby Repairable System With Damage and Repair Time Dependency Via Matrix-Exponential Distributions(Taylor & Francis Ltd, 2021) Kus, Coskun; Eryilmaz, SerkanIn this paper, two-unit standby repairable system is studied via matrix-exponential distributions. The system under concern consists of one active and one standby components, and fails if either a damage size upon the failure of the active component is larger than a repair limit or the repair time of the failed unit exceeds the lifetime of the active unit, whichever happens first. Under the assumption that the damage size and repair time are statistically dependent, the Laplace transform of the system's lifetime is obtained. The Laplace transform is shown to be rational under particular cases, and the reliability evaluation of the system is performed via well-known distributional properties of the matrix-exponential distributions. The problem of estimating the unknown parameters of the operation time and repair time distributions is also discussed based on system's lifetime data.
