Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
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Article Self-Supervised Learning With BYOL for Non-Alcoholic Fatty Liver Disease Diagnosis Using Ultrasound Imaging(Springer London Ltd, 2025) Buktash, Ali; Gorur, Abdul KadirPurpose:The study aims to evaluate the effectiveness of Bootstrap Your Own Latent (BYOL), a self-supervised learning method for diagnosing NAFLD from ultrasound images using limited labeled data, which represents a novel approach in this domain. Self-supervised learning provides an alternative approach to traditional supervised learning by learning useful representations from unlabeled data, thereby reducing the time and cost required by radiologists to annotate images.Methods:The pre-trained ResNet-50 and ResNet-101 on the labeled ImageNet dataset were used for BYOL pre-training on ultrasound images without relying on labels. The training was conducted using default and custom augmentation, as well as balanced and imbalanced class distribution protocols. The model was then evaluated using linear and fine-tuning protocols with varying percentages of labeled data. The model was trained using three shuffled subsets, each trained 10 times. The custom augmentation set was derived by testing various augmentation settings using 100% and 1% of the labels to enhance feature learning.Results:BYOL with ResNet-101 and using the proposed custom augmentation set achieved average accuracies of 93.44%, 92.29%, and 88.49% using 100%, 10%, and 1% of the training labels across three shuffled datasets. In addition, our proposed method attained an average accuracy of 96.9% using patient-specific leave-one-out cross-validation (LOOCV).Conclusion:BYOL, with the proposed custom augmentation set, can learn effective image representations without relying on a large amount of labeled data, thereby enhancing scalability since unlabeled images are easier to acquire. It surpasses BYOL with default augmentation and training under supervised learning, especially with a low-labeled data regime.Article Enhancing Content-Based Retrieval Through an End-to-End Approach Utilizing Deep Learning and Multidimensional Indexing(Springer London Ltd, 2025) Uzel, Omer; Arslan, SerdarRecent advancements in technology, coupled with reductions in hardware and software costs, have propelled visual search applications into the spotlight, making them both popular and indispensable. Consequently, the rapid and precise retrieval of images from vast databases through image queries has become a critical task. We introduce a novel end-to-end retrieval architecture that significantly enhances retrieval performance when compared to a baseline system that conducts database searches at the video frame level. Leveraging a pre-trained convolutional neural network model, we employ unsupervised image retrieval processes to extract and store low-level features for efficient indexing. To facilitate swift and effective access, we implement a tree-based indexing structure known as VP-Tree. This structure utilizes the extracted low-level features. To make these features compatible with our system, we employ dimension reduction techniques to represent them in a lower-dimensional space. Our experiments, conducted on three benchmark datasets, demonstrate that VP-Tree consistently outperforms k-nearest neighbor (KNN) search in terms of retrieval accuracy and efficiency. Specifically, for image data set, VP-Tree achieves a precision of 56.3903, an F1-score of 68.703, and an area under the curve (AUC) of 93.518719, all slightly surpassing KNN. Similarly, for news video data set, VP-Tree attains a precision of 38.704011, an F1-score of 55.029674, and an AUC of 64.6412, again outperforming KNN. For documentary data set, VP-Tree achieves a notable improvement with a precision of 73.511723, an F1-score of 84.734013, and an AUC of 80.981328, demonstrating superior performance over KNN. In addition to accuracy, we evaluated retrieval time across different dataset sizes. While KNN performs slightly faster on smaller datasets, VP-Tree scales significantly better as dataset size increases. For 100,000 images, VP-Tree reduces retrieval time from 79.77 to 54.34 ms, and for 200,000 images, it improves performance from 108.75 to 44.63 ms, confirming its efficiency in large-scale retrieval scenarios. These results highlight VP-Tree as a robust and scalable alternative to traditional KNN-based methods, ensuring both accuracy and efficiency in large-scale image retrieval tasks.Article Low Signature UAVs: Radar Cross Section Analysis, Simulation, and Measurement in X-Band(Springer London Ltd, 2025) Unalir, Dizdar; Yalcinkaya, Bengisu; Aydin, ElifThe increasing prevalence of unmanned aerial vehicles (UAVs) is driving the development of radar systems capable of detecting them. This hampers the deployment of UAVs in military operations. While radar cross section reduction (RCSR) can be a valuable solution, the research on this subject is inadequate. This paper presents an RCSR approach adopting a shaping technique for UAVs, demonstrating the proposed approach's efficacy through simulations and actual experimental measurements performed in X-Band on a four-legged UAV model. Using electromagnetic computational instruments, the shaping is applied to the designed UAV model with parameter-based simulations, the simulated radar cross section (RCS) values are derived, and the comparative analysis of these instruments is conducted. Experimental measurements are performed in laboratory conditions using a vector network analyzer. Actual measurement results are validated by simulative findings with the examination of the influence of frequency, polarization, and aspect angle on RCS. The demonstrated measuring approach allows cost-effective and easily applicable research on RCS in X-Band, a commonly utilized frequency range in military. An average RCSR of 10 dBsm has been accomplished with the presented shaping approach.Article Citation - WoS: 40Citation - Scopus: 42Numerical and Experimental Analysis of Temperature Distribution and Melt Flow in Fiber Laser Welding of Inconel 625(Springer London Ltd, 2022) Baleanu, Dumitru; Sajadi, S. Mohammad; Ghaemi, Ferial; Fagiry, Moram A.; Tlili, Iskander; Mohammad Sajadi, S.In these days, laser is a useful and valuable tool. Low input heat, speed, accuracy, and high controllability of laser welding have led to widespread use in various industries. Nickel-based superalloys are creep-resistant materials used in high-temperature conditions. Also, these alloys have high strength, fatigue, and suitable corrosion resistance. Inconel 625 is a material that is strengthened by a complex deposition mechanism. Therefore, the parameters related to laser welding affect the microstructure and mechanical properties. Therefore, in this study, the effect of fiber laser welding parameters on temperature distribution, weld bead dimensions, melt flow velocity, and microstructure was investigated by finite volume and experimental methods. In order to detect the temperature history during continuous laser welding, two thermocouples were considered at a distance of 2 mm from the welding line. The heat energy from the laser beam was modeled as surface and volumetric heat flux. The results of numerical simulation showed that Marangoni stress and buoyancy force are the most important factors in the formation of the flow of liquid metal. Enhancing the laser power to 400 W led to the expansion of the width of the molten pool by 1.44 mm, which was in good agreement with the experimental results. Experimental results also showed that increasing the temperature from 500 degrees C around the molten pond leads to the formation of a coarse-grained austenitic structure.Article Citation - WoS: 7Citation - Scopus: 7Prediction of White Layer Formation in Μ-Wedm Process of Niti Shape Memory Superalloy: Fem With Experimental Verification(Springer London Ltd, 2021) Akar, Samet; Meshri, Hassan Ali M.; Seyedzavvar, Mirsadegh; Ilkhchi, Reza NajatiMicroscopic changes in the surface of nickel-titanium (nitinol) shape memory alloys (SMAs) in micro-wire electro-discharge machining (mu-WEDM) due to the formation of a resolidified layer on the machined surface, called white layer, are one of the main drawbacks in the processing of such alloys. Since these changes significantly affect the shape memory and elastic recovery characteristics of these alloys, reduction of the white layer thickness (WLT) based on the selection of optimum process parameters is essential to raise the quality of the machined parts. In this regard, a finite element model (FEM) has been developed to simulate the effects of mu-WEDM process parameters, including discharge current, pulse on-time, pulse off-time, and servo voltage, on the heat distributing in Ni55.8Ti SMA to predict the WLT. The flushing efficiency of electric discharges and the effect of flow regime of the dielectric fluid on the heat distribution in the workpiece and the formation of the WLT are analyzed. Experimental data are used to verify the accuracy of the FEM. The results show that the developed model can predict the WLT in mu-WEDM process of Ni55.8Ti SMA with an average error of 14%. The effects of discharge parameters on the formation of the WLT are discussed in details based on the results of the FEM.Article Citation - WoS: 11Citation - Scopus: 15Nimrad: Novel Technique for Respiratory Data Treatment(Springer London Ltd, 2014) Nigmatullin, R. R.; Ionescu, C.; Baleanu, D.This paper illustrates the efficiency and simplicity of a new technique which is determined in this paper as NIMRAD (the non-invasive methods of the reduced analysis of data) for describing information extracted from biological signals. As a specific example, we consider the respiratory data. The NIMRAD can be applied for quantitative description of data recorded for complex systems in cases where the adequate model is absent and the treatment procedure should not contain any uncontrollable error. The theoretical developments are applied to signals measured from the respiratory system by means of the forced oscillation technique based on non-invasive lung function test. In order to verify the feasibility of the proposed algorithm for developing new diagnosis tools, we apply NIMRAD on two different respiratory data sets, namely from a healthy subject and from a patient diagnosed with asthma. The results are promising and suggest that NIMRAD could be further tailored and used for specific clinical applications.Article Citation - WoS: 3Citation - Scopus: 6Lot Streaming in a Two-Machine Mixed Shop(Springer London Ltd, 2010) Duman, Mehmet; Cetinkaya, Ferda C.Most classical scheduling models overlook the fact that products are often produced in job lots and assume that job lots are indivisible single entities, although an entire job lot consists of many identical items. However, splitting an entire lot (process batch) into sublots (transfer batches) to be moved to downstream machines allows the overlapping of different operations on the same product while work needs to be completed on the upstream machine. This approach is known as lot streaming in scheduling theory. In this study, the lot streaming problem of multiple jobs in a two-machine mixed shop where there are two different job types as flow shop and open shop is addressed so as to minimize the makespan. The optimal solution method is developed for the mixed shop scheduling problem in which lot streaming can improve the makespan.Article Citation - WoS: 7Citation - Scopus: 9An Experimental Work on Using Conductive Powder-Filled Polymer Composite Cast Material as Tool Electrode in Edm(Springer London Ltd, 2014) Cogun, Can; Yaman, KemalThis paper introduces the composite tool electrodes made of electrical conductive powder-filled polyester resin matrix material, providing promise for the electrical discharge machining (EDM) process. The dendrite-shaped copper powder, graphite powder, and their mixture were used as conductive fillers. Six different types of composite electrodes, namely, plain copper-polyester, pressed copper-polyester, furnaced copper-polyester, plain copper-graphite-polyester, pressed copper-graphite-polyester, and furnaced copper-graphite-polyester were prepared. It is found experimentally that increasing v (f) improved workpiece material removal rate, tool wear rate, relative wear, and electrical conductivity of electrodes. The pressed copper-polyester electrodes were found to be promising in the ED finishing of workpieces at low machining current settings. The practical applicability of the proposed composite electrodes in the industry was also illustrated.Article Citation - WoS: 4Citation - Scopus: 6Analysis of Uv Spectral Bands Using Multidimensional Scaling(Springer London Ltd, 2015) Dinc, Erdal; Baleanu, Dumitru; Tenreiro Machado, J. A.; Machado, J. A. TenreiroThis study describes the change of the ultraviolet spectral bands starting from 0.1 to 5.0 nm slit width in the spectral range of 200-400 nm. The analysis of the spectral bands is carried out by using the multidimensional scaling (MDS) approach to reach the latent spectral background. This approach indicates that 0.1 nm slit width gives higher-order noise together with better spectral details. Thus, 5.0 nm slit width possesses the higher peak amplitude and lower-order noise together with poor spectral details. In the above-mentioned conditions, the main problem is to find the relationship between the spectral band properties and the slit width. For this aim, the MDS tool is to used recognize the hidden information of the ultraviolet spectra of sildenafil citrate by using a Shimadzu UV-VIS 2550, which is in the world the best double monochromator instrument. In this study, the proposed mathematical approach gives the rich findings for the efficient use of the spectrophotometer in the qualitative and quantitative studies.Article Citation - WoS: 3Citation - Scopus: 4Application of Continuous Wavelet Transform To the Analysis of the Modulus of the Fractional Fourier Transform Bands for Resolving Two Component Mixture(Springer London Ltd, 2015) Duarte, Fernando B.; Machado, J. A. Tenreiro; Baleanu, Dumitru; Dinc, ErdalIn this paper, the fractional Fourier transform (FrFT) is applied to the spectral bands of two component mixture containing oxfendazole and oxyclozanide to provide the multicomponent quantitative prediction of the related substances. With this aim in mind, the modulus of FrFT spectral bands are processed by the continuous Mexican Hat family of wavelets, being denoted by MEXH-CWT-MOFrFT. Four modulus sets are obtained for the parameter of the FrFT going from 0.6 up to 0.9 in order to compare their effects upon the spectral and quantitative resolutions. Four linear regression plots for each substance were obtained by measuring the MEXH-CWT-MOFrFT amplitudes in the application of the MEXH family to the modulus of the FrFT. This new combined powerful tool is validated by analyzing the artificial samples of the related drugs, and it is applied to the quality control of the commercial veterinary samples.