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Article Citation - WoS: 6Citation - Scopus: 6Understanding the Effect of Handedness on Both-Handed Task Performance: an Experimental Study Based on a Haptic-Controlled, Simulation-Based Surgical Skill Training Scenario(Taylor & Francis inc, 2019) Topalli, Damla; Eyuboglu, Burak Gokberk; Cagiltay, Nergiz ErcilUnderstanding the performance on both-handed tasks, such as endoscopic surgery, is critical to better organize and develop appropriate instructional systems to improve the necessary skills of surgeons. However, in the literature, only a limited number of studies have investigated the effect of handedness on both-handed task performance. This study aimed to provide an understanding of the participants' performance differences while performing both-handed tasks through a haptic user interface in a simulated virtual environment specifically developed for surgical training purposes. Twenty-four surgeons attending a medical school in Turkey voluntarily participated in the study. The duration, accuracy, and collision measures were automatically recorded by software. The results revealed that the left-handed participants performed the both-handed tasks (camera: nondominant hand, tool: dominant-hand) in a significantly shorter time than the right-handed participants. This study also showed that haptic-controlled simulation-based surgical skill training systems can potentially provide measures for better understanding the individual behaviors and deliver alternative training environments specific to individual requirements.Conference Object Aldose Reductase Natural Inhibitors From Ethyl Acetate Extracts From Southern Turkey(Taylor & Francis inc, 2010) Onay, Melih; Coruh, Nursen; Isgor, Belgin[No Abstract Available]Article Citation - WoS: 10Citation - Scopus: 12An Intelligent Indoor Guidance and Navigation System for the Visually Impaired(Taylor & Francis inc, 2022) Kahraman, M.; Turhan, C.Intelligent guidance in complex environments where various procedures are required for navigation is critical to achieving mobility for the visually impaired. This study presents a newly developed software prototype with a hybrid RFID/BLE infrastructure to provide intelligent navigation and guidance to the visually impaired in complex indoor environments. The system enables the users to input their purpose via a specially designed user interface, and provides intelligent guidance through a chain of destination targets which are determined according to the inherent procedures of the environment. Path optimization is performed by adaptation of the traveling salesman problem, and real-time instantaneous instructions are provided to guide the users through the predetermined destination points. For evaluation purposes, a hospital environment is constructed as an example of a complex environment and the system is tested by visually impaired participants. The results show that the intelligent purpose selection and destination evaluation mechanism modules of the system are found to be effective by all the participants.Review Citation - WoS: 22Citation - Scopus: 39Cybersecurity Deep: Approaches, Attacks Dataset, and Comparative Study(Taylor & Francis inc, 2022) Barik, Kousik; Misra, Sanjay; Konar, Karabi; Fernandez-Sanz, Luis; Murat, KoyuncuCyber attacks are increasing rapidly due to advanced digital technologies used by hackers. In addition, cybercriminals are conducting cyber attacks, making cyber security a rapidly growing field. Although machine learning techniques worked well in solving large-scale cybersecurity problems, an emerging concept of deep learning (DL) that caught on during this period caused information security specialists to improvise the result. The deep learning techniques analyzed in this study are convolution neural networks, recurrent neural networks, and deep neural networks in the context of cybersecurity.A framework is proposed, and a real-time laboratory setup is performed to capture network packets and examine this captured data using various DL techniques. A comparable interpretation is presented under the DL techniques with essential parameters, particularly accuracy, false alarm rate, precision, and detection rate. The DL techniques experimental output projects improvise the performance of various real-time cybersecurity applications on a real-time dataset. CNN model provides the highest accuracy of 98.64% with a precision of 98% with binary class. The RNN model offers the second-highest accuracy of 97.75%. CNN model provides the highest accuracy of 98.42 with multiclass class. The study shows that DL techniques can be effectively used in cybersecurity applications. Future research areas are being elaborated, including the potential research topics to improve several DL methodologies for cybersecurity applications.Article Citation - WoS: 8Citation - Scopus: 7The Underlying Reasons of the Navigation Control Effect on Performance in a Virtual Reality Endoscopic Surgery Training Simulator(Taylor & Francis inc, 2019) Cagiltay, Nergiz Ercil; Ozcelik, Erol; Berker, Mustafa; Dalveren, Gonca Gokce MenekseNavigation control skills of surgeons become very critical for surgical procedures. Strategies improving these skills are important for developing higher-quality surgical training programs. In this study, the underlying reasons of the navigation control effect on performance in a virtual reality-based navigation environment are evaluated. The participants' performance is measured in conditions: navigation control display and paper-map display. Performance measures were collected from 45 beginners and experienced residents. The results suggest that navigation display significantly improved performance of the participants. Also, navigation was more beneficial for beginners than experienced participants. The underlying reason of the better performance in the navigation condition was due to lower number of looks to the map, which causes attention shifts between information sources. Accordingly, specific training scenarios and user interfaces can be developed to improve the navigation skills of the beginners considering some strategies to lower their number of references to the information sources.Article Citation - WoS: 20Citation - Scopus: 20The Stress Response of Partially Plastic Rotating Fgm Hollow Shafts: Analytical Treatment for Axially Constrained Ends(Taylor & Francis inc, 2006) Eraslan, Ahmet N.; Akis, Tolgaanalytical solutions to estimating the elastoplastic response of rotating functionally graded (FGM) hollow shafts with fixed ends are presented. The modulus of elasticity, as well as the uniaxial yield limit of the shaft material, are assumed to vary nonlinearly in the radial direction. The plastic model is based on Tresca's yield criterion, its associated flow rule, and ideal plastic material behaviour. Elastic, partially plastic, fully plastic, and residual stress states are investigated. It is shown that the elastoplastic stress response of a rotating FGM hollow shaft is affected significantly by the nonhomogeneity of the material. Unlike the case of a homogeneous hollow shaft, plastic deformation may commence at the inner surface, at the outer surface, or simultaneously at both surfaces. Accordingly, each case requires different mathematical treatment to arrive at its partially plastic solution. It is also shown that, by taking a numerical limit, the complete FGM solution presented herein converge to the solution of a homogeneous rotating shaft.Review Citation - WoS: 25Citation - Scopus: 23Real-Time Biosensing Bacteria and Virus With Quartz Crystal Microbalance: Recent Advances, Opportunities, and Challenges(Taylor & Francis inc, 2023) Bonyadi, Farzaneh; Kavruk, Murat; Ucak, Samet; Cetin, Barbaros; Bayramoglu, Gulay; Dursun, Ali D. D.; Ozalp, Veli C. C.Continuous monitoring of pathogens finds applications in environmental, medical, and food industry settings. Quartz crystal microbalance (QCM) is one of the promising methods for real-time detection of bacteria and viruses. QCM is a technology that utilizes piezoelectric principles to measure mass and is commonly used in detecting the mass of chemicals adhering to a surface. Due to its high sensitivity and rapid detection times, QCM biosensors have attracted considerable attention as a potential method for detecting infections early and tracking the course of diseases, making it a promising tool for global public health professionals in the fight against infectious diseases. This review first provides an overview of the QCM biosensing method, including its principle of operation, various recognition elements used in biosensor creation, and its limitations and then summarizes notable examples of QCM biosensors for pathogens, focusing on microfluidic magnetic separation techniques as a promising tool in the pretreatment of samples. The review explores the use of QCM sensors in detecting pathogens in various samples, such as food, wastewater, and biological samples. The review also discusses the use of magnetic nanoparticles for sample preparation in QCM biosensors and their integration into microfluidic devices for automated detection of pathogens and highlights the importance of accurate and sensitive detection methods for early diagnosis of infections and the need for point-of-care approaches to simplify and reduce the cost of operation.Article Citation - WoS: 72Citation - Scopus: 98Mapping Human-Computer Interaction Research Themes and Trends From Its Existence To Today: a Topic Modeling-Based Review of Past 60 Years(Taylor & Francis inc, 2021) Gurcan, Fatih; Cagiltay, Nergiz Ercil; Cagiltay, KursatAs it covers a wide spectrum, the research literature of human-computer interaction (HCI) studies has a rich and multi-disciplinary content where there are limited studies demonstrating the big picture of the field. Such an analysis provides researchers with a better understanding of the field, revealing current issues, challenges, and potential research gaps. This study aims to explore the research trends in the developmental stages of the HCI studies over the past 60 years. Automated text mining with probabilistic topic modeling has been used to analyze 41,720 journal articles that are indexed by the SCOPUS database between 1957 and 2018. The results of this study reveal 21 major topics mapping the research landscape of HCI. By extending the discovered topics beyond a snapshot, the topics were analyzed considering their developmental stages, volume, and accelerations to provide a panoramic view that shows the increase and decrease of trends over time. In this context, the transition of HCI studies from machine-oriented systems to human-oriented systems indicates its future direction toward context-aware adaptive systems.Article Citation - WoS: 16Citation - Scopus: 16Analytical Solutions To Variable Thickness and Variable Material Property Rotating Disks for a New Three-Parameter Variation Function(Taylor & Francis inc, 2012) Argeso, HakanAnalytical solutions of two different annular rotating disk problems are obtained under the assumptions of plane stress, isotropy, and small deformations. The first problem involves a homogeneous variable profile disk, whereas the second one is a functionally graded disk having a variation in elasticity modulus. For the variations of disk thickness and elasticity modulus in these problems, a new form of nonlinear function controlled by three parameters is introduced. The derivations of the closed form solutions for both type of rotating disk problems are carried out in a unified form. The closed form solutions are verified numerically by the nonlinear shooting method.Article Citation - WoS: 2Citation - Scopus: 2Large Deflection Analysis of Functionally Graded Reinforced Sandwich Beams With Auxetic Core Using Physics-Informed Neural Network(Taylor & Francis inc, 2025) Nopour, Reza; Fallah, Ali; Aghdam, Mohammad MohammadiThis paper aims to investigate the large deflection behavior of a sandwich beam reinforced with functionally graded (FG) graphene platelets (GPL) together with an auxetic core, rested on a nonlinear elastic foundation. The nonlinear governing equations of the problem are derived using Hamilton's principle based on the Euler-Bernoulli beam theory for large deflections. Five different distributions are considered to describe the dispersion of GPL in the top and bottom faces of the sandwich beam. The Physics-Informed Neural Network (PINN) method is employed to model the nonlinear deflection of the beam under various boundary conditions. This study highlights the effectiveness of PINN in handling the complexities of nonlinear structural analyses. The findings underscore the impact of the core auxeticity, GPL amount and distribution, and elastic foundation coefficient on the nonlinear deflection of the sandwich beam under different loading scenarios. For instance, using Type I configuration can reduce the deflection of the beam by nearly half compared to using Type IV. Furthermore, a nonlinear foundation with a unit coefficient results in a 48% reduction in deflection compared to the scenario without an elastic foundation.
