PubMed İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8650
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Article Citation - WoS: 2Comparing Hand-Based and Controller-Based Interactions in Virtual Reality Learning: Effects on Presence and Interaction Performance(PeerJ Inc, 2025) Saran, MuratVirtual reality (VR) holds significant promise for enhancing science education by providing immersive and interactive learning experiences. However, the optimal interaction modality within educational VR environments remains an open question. This study investigates the impact of hand-based vs. controller-based interaction on sixth-grade students' sense of presence and interaction performance in a VR science laboratory simulation. Fifty-four sixth-grade students were randomly assigned to either a hand-based interaction group or a controller-based interaction group. Participants completed three interactive science experiments (solar system, electrical circuits, and force/energy) within a virtual laboratory environment designed to mimic their school's physical lab. Presence was assessed using a validated Turkish adaptation of the Presence Questionnaire (PQ), while interaction performance was evaluated using a structured observation form completed by a school teacher. Independent samples t-tests and Mann-Whitney U tests were used to compare the presence and performance scores between the groups. Supplementary analyses explored the effects of gender and prior VR experience. Contrary to expectations, no significant differences were found in either presence (t(49.4) = -0.01, p = 0.992) or interaction performance (t(52) = -1.30, p = 0.199) between the hand-based and controller-based interaction groups. Both interaction modalities yielded comparable levels of self-reported presence and observed performance. However, an unexpected finding emerged regarding performance. A supplementary analysis revealed a significant main effect of gender on performance scores (F(1, 50) = 4.844, p = 0.032), independent of interaction type. Specifically, males demonstrated significantly higher performance than females. This study suggests that, for sixth-grade students engaging in these specific VR science simulations, hand-based and controller-based interactions are equally effective in terms of fostering presence and supporting interaction performance. These findings have practical implications for the design and implementation of VR learning environments, particularly in resource-constrained settings where the reduced maintenance and hygiene concerns associated with hand-based interaction may be advantageous.Article Citation - WoS: 6Citation - Scopus: 6Modeling the Transmission Dynamics of Middle Eastern Respiratory Syndrome Coronavirus with the Impact of Media Coverage(Elsevier, 2021) Fatima, BiBi; Alqudah, Manar A.; Zaman, Gul; Jarad, Fahd; Abdeljawad, ThabetMiddle East respiratory syndrome coronavirus has been persistent in the Middle East region since 2012. In this paper, we propose a deterministic mathematical model to investigate the effect of media coverage on the transmission and control of Middle Eastern respiratory syndrome coronavirus disease. In order to do this we develop model formulation. Basic reproduction number R-0 will be calculated from the model to assess the transmissibility of the (MERS-CoV). We discuss the existence of backward bifurcation for some range of parameters. We also show stability of the model to figure out the stability condition and impact of media coverage. We show a special case of the model for which the endemic equilibrium is globally asymptotically stable. Finally all the theoretical results will be verified with the help of numerical simulation for easy understanding.Article Detection and Classification of Femoral Neck Fractures From Plain Pelvic X-Rays Using Deep Learning and Machine Learning Methods(Turkish Assoc Trauma Emergency Surgery, 2025) Sevinc, Huseyin Fatih; Ureten, Kemal; Karadeniz, Talha; Gultekin, Gokhan KorayBackground: Femoral neck fractures are a serious health concern, particularly among the elderly. The aim of this study is to diagnose and classify femoral neck fractures from plain pelvic X-rays using deep learning and machine learning algorithms, and to compare the performance of these methods. Methods: The study was conducted on a total of 598 plain pelvic X-ray images, including 296 patients with femoral neck fractures and 302 individuals without femoral neck fractures. Initially, transfer learning was applied using pre-trained deep learning models: VGG-16, ResNet-50, and MobileNetv2. Results: The pre-trained VGG-16 network demonstrated slightly better performance than ResNet-50 and MobileNetV2 for detecting and classifying femoral neck fractures. Using the VGG-16 model, the following results were obtained: 95.6% accuracy, 95.5% sensitivity, 93.3% specificity, 95.7% precision, 95.5% F1 Score, a Cohen's kappa of 0.91, and the Receiver Operating Characteristic (ROC) curve of 0.99. Subsequently, features extracted from the convolution layers of VGG-16 were classified using common machine learning algorithms. Among these, the k-nearest neighbor (k-NN) algorithm outperformed the others and exceeded the accuracy of the VGG-16 model by 1%. Conclusion: Successful results were obtained using deep learning and machine learning methods for the detection and classification of femoral neck fractures. The model can be further improved through multi-center studies. The proposed model may be especially useful for physicians working in emergency departments and for those not having sufficient experience in evaluating plain pelvic radiographs.Article Citation - WoS: 10Citation - Scopus: 11Low-Diameter Topic-Based Pub/Sub Overlay Network Construction With Minimum Maximum Node Degree(Peerj inc, 2021) Yumusak, Semih; Layazali, Sina; Oztoprak, Kasim; Hassanpour, RezaIn the construction of effective and scalable overlay networks, publish/subscribe (pub/sub) network designers prefer to keep the diameter and maximum node degree of the network low. However, existing algorithms are not capable of simultaneously decreasing the maximum node degree and the network diameter. To address this issue in an overlay network with various topics, we present herein a heuristic algorithm, called the constant-diameter minimum-maximum degree (CD-MAX), which decreases the maximum node degree and maintains the diameter of the overlay network at two as the highest. The proposed algorithm based on the greedy merge algorithm selects the node with the minimum number of neighbors. The output of the CD-MAX algorithm is enhanced by applying a refinement stage through the CD-MAX-Ref algorithm, which further improves the maximum node degrees. The numerical results of the algorithm simulation indicate that the CD-MAX and CD-MAX-Ref algorithms improve the maximum node-degree by up to 64% and run up to four times faster than similar algorithms.Article Citation - WoS: 2Citation - Scopus: 6Fast Binary Logistic Regression(Peerj inc, 2025) Saran, Nurdan Ayse; Nar, FatihThis study presents a novel numerical approach that improves the training efficiency of binary logistic regression, a popular statistical model in the machine learning community. Our method achieves training times an order of magnitude faster than traditional logistic regression by employing a novel Soft-Plus approximation, which enables reformulation of logistic regression parameter estimation into matrix-vector form. We also adopt the L-f-norm penalty, which allows using fractional norms, including the L-2-norm, L-1-norm, and L-0-norm, to regularize the model parameters. We put L-f-norm formulation in matrix-vector form, providing flexibility to include or exclude penalization of the intercept term when applying regularization. Furthermore, to address the common problem of collinear features, we apply singular value decomposition (SVD), resulting in a low-rank representation commonly used to reduce computational complexity while preserving essential features and mitigating noise. Moreover, our approach incorporates a randomized SVD alongside a newly developed SVD with row reduction (SVD-RR) method, which aims to manage datasets with many rows and features efficiently. This computational efficiency is crucial in developing a generalized model that requires repeated training over various parameters to balance bias and variance. We also demonstrate the effectiveness of our fast binary logistic regression (FBLR) method on various datasets from the OpenML repository in addition to synthetic datasets.Article Stability Analysis and Solutions of Fractional Boundary Value Problem on the Cyclopentasilane Graph(Cell Press, 2024) Wang, Guotao; Yuan, Hualei; Baleanu, DumitruThe study is being applied to a model involving silane and on cyclopentasilane graph. We consider a graph with labeled vertices by 0 or 1 inspired by the molecular structure of cyclopentasilane. In this paper, we first study the existence of solutions to fractional conformable boundary value problem on the cyclopentasilane graph by applying Scheafer and Krasnoselskii fixed point theorems. Furthermore, we investigate different kinds of Ulam stability such as Ulam-Hyers stable, generalized Ulam-Hyers stable, Ulam-Hyers-Rassias stable and generalized Ulam-HyersRassias stable for the given problem. Finally, we give an example to support our important results.Article Citation - WoS: 1Citation - Scopus: 2Initial Validation of the Turkish Version of the Defense Mechanisms Rating Scales-Self(Frontiers Media Sa, 2024) Yilmaz, Meltem; Tas, Berke; Celik, Deniz; Perry, J. Christopher; Tanzilli, Annalisa; Di Giuseppe, Mariagrazia; Lingiardi, VittorioThe Defense Mechanisms Rating Scales-Self Report-30 (DMRS-SR-30) was recently developed to add a self-report alternative to the assessment of defenses, reflecting their generally accepted hierarchical organization. In this study, we aimed to examine psychometric properties and factor structure of the Turkish language version of the DMRS-SR-30. The sample consisted of 1.002 participants who filled out a survey comprising the DMRS-SR-30, the Brief Symptom Inventory, and the Inventory of Personality Organization through Qualtrics. Confirmatory Factor Analysis indicated a three-factor structure (CFI = 0.89, RMSEA = 0.05) that confirms the DMRS theoretical frame with a relatively acceptable fit. Defensive categories and total scale scores showed good to excellent reliability (alpha values ranging from 0.64 to 0.89). Correlations between defenses, symptoms, and personality functioning demonstrated good convergent and discriminant validity. The individuals with clinically significant BSI scores (T-score >= 63) differed on the DMRS-SR-30 scores from the individuals in the non-clinical range. The Turkish version of the DMRS-SR-30 is a reliable and valid instrument to self-assess the hierarchy of defense mechanisms and overall defensive functioning. Moreover, the current study supports the validity of the tripartite model of defenses in a language and culture different from the origins of the DMRS and DMRS-SR-30.Article Citation - WoS: 41Citation - Scopus: 44Psychological Well-Being in Europe After the Outbreak of War in Ukraine(Nature Portfolio, 2024) Scharbert, Julian; Humberg, Sarah; Kroencke, Lara; Reiter, Thomas; Sakel, Sophia; ter Horst, Julian; Back, Mitja D.The Russian invasion of Ukraine on February 24, 2022, has had devastating effects on the Ukrainian population and the global economy, environment, and political order. However, little is known about the psychological states surrounding the outbreak of war, particularly the mental well-being of individuals outside Ukraine. Here, we present a longitudinal experience-sampling study of a convenience sample from 17 European countries (total participants = 1,341, total assessments = 44,894, countries with >100 participants = 5) that allows us to track well-being levels across countries during the weeks surrounding the outbreak of war. Our data show a significant decline in well-being on the day of the Russian invasion. Recovery over the following weeks was associated with an individual's personality but was not statistically significantly associated with their age, gender, subjective social status, and political orientation. In general, well-being was lower on days when the war was more salient on social media. Our results demonstrate the need to consider the psychological implications of the Russo-Ukrainian war next to its humanitarian, economic, and ecological consequences.Article Citation - WoS: 1Citation - Scopus: 4Teaching Computer Architecture by Designing and Simulating Processors From Their Bits and Bytes(Peerj inc, 2024) Dogan, Mustafa; Oztoprak, Kasim; Tolun, Mehmet ResitTeaching computer architecture (Comp-Arch) courses in undergraduate curricula is becoming more of a challenge as most students prefer software-oriented courses. In some computer science/engineering departments, Comp-Arch courses are offered without the lab component due to resource constraints and differing pedagogical priorities. This article demonstrates how students working in teams are motivated to study the Comp-Arch course and how instructors can increase student motivation and knowledge by taking advantage of hands-on practices. The teams are asked to design and implement a 16-bit MIPS-like processor with constraints as a specific instruction set, and limited data and instruction memory. Student projects include following three phases, namely, design, desktop simulator implementation, and verification using hardware description language (HDL). In the design phase, teams develop their Comp-Arch to implement specified instructions. A range of designs resulted, e.g., (a) a processor with extensive user-defined instructions resulting in longer cycle times (b) a processor with a minimal instruction set but with a faster clock cycle time. Next, teams developed a desktop simulator in any programming language to execute instructions on the architecture. Finally, students engage in Verilog Hardware Description Language (HDL) projects to simulate and verify the data-path designed during the initial phase. Student feedback and their current understanding of the project were collected through a questionnaire featuring varying Likert scale questions, some with a ten-point scale, and others with a five- point scale. Results of the survey show that the hands-on approach increases students' motivation and knowledge in the Comp-Arch course, which is centered around computer system design principles. This approach can also be effectively extended to related courses, such as Microprocessor Design, which delves into the intricacies of creating and implementing microprocessors or central processing units (CPUs) at the hardware level. Furthermore, the present study demonstrates that interactions, specifically through peer reviews and public presentations, between students in each phase increases their knowledge and perspective on designing custom processors.Article Citation - WoS: 7Citation - Scopus: 8Quantitative Assessment and Objective Improvement of the Accuracy of Neurosurgical Planning Through Digital Patient-Specific 3d Models(Frontiers Media Sa, 2024) Hanalioglu, Sahin; Gurses, Muhammet Enes; Baylarov, Baylar; Tunc, Osman; Isikay, Ilkay; Cagiltay, Nergiz Ercil; Berker, MustafaObjective Neurosurgical patient-specific 3D models have been shown to facilitate learning, enhance planning skills and improve surgical results. However, there is limited data on the objective validation of these models. Here, we aim to investigate their potential for improving the accuracy of surgical planning process of the neurosurgery residents and their usage as a surgical planning skill assessment tool.Methods A patient-specific 3D digital model of parasagittal meningioma case was constructed. Participants were invited to plan the incision and craniotomy first after the conventional planning session with MRI, and then with 3D model. A feedback survey was performed at the end of the session. Quantitative metrics were used to assess the performance of the participants in a double-blind fashion.Results A total of 38 neurosurgical residents and interns participated in this study. For estimated tumor projection on scalp, percent tumor coverage increased (66.4 +/- 26.2%-77.2 +/- 17.4%, p = 0.026), excess coverage decreased (2,232 +/- 1,322 mm2-1,662 +/- 956 mm2, p = 0.019); and craniotomy margin deviation from acceptable the standard was reduced (57.3 +/- 24.0 mm-47.2 +/- 19.8 mm, p = 0.024) after training with 3D model. For linear skin incision, deviation from tumor epicenter significantly reduced from 16.3 +/- 9.6 mm-8.3 +/- 7.9 mm after training with 3D model only in residents (p = 0.02). The participants scored realism, performance, usefulness, and practicality of the digital 3D models very highly.Conclusion This study provides evidence that patient-specific digital 3D models can be used as educational materials to objectively improve the surgical planning accuracy of neurosurgical residents and to quantitatively assess their surgical planning skills through various surgical scenarios.