Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/11
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Article Citation - WoS: 5Citation - Scopus: 7Adaptive Resizer-Based Transfer Learning Framework for the Diagnosis of Breast Cancer Using Histopathology Images(Springer, 2023) Düzyel, Okan; Çatal, Mehmet Sergen; Kayan, Ceyhun Efe; Sevinç, Arda; Gümüş, AbdurrahmanBreast cancer is a major global health concern, and early and accurate diagnosis is crucial for effective treatment. Recent advancements in computer-assisted prediction models have facilitated diagnosis and prognosis using high-resolution histopathology images, which provide detailed information on cancerous tissue. However, these high-resolution images often require resizing, leading to potential data loss. In this study, we demonstrate the effect of a learnable adaptive resizer for breast cancer classification using the BreakHis dataset. Our approach incorporates the adaptive resizer with various convolutional neural network models, including VGG16, VGG19, MobileNetV2, InceptionResnetV2, DenseNet121, DenseNet201, and EfficientNetB0. Despite producing visually less appealing images, the learnable resizer effectively improves classification performance. DenseNet201, when jointly trained with the adaptive resizer, achieves the highest accuracy of 98.96% for input images of 448x448 resolution. Our experimental results demonstrate that the adaptive resizer performs better at a magnification factor of 40x compared to higher magnifications. While its effectiveness becomes less pronounced as image resolution increases to 100x, 200x, and 400x, the adaptive resizer still outperforms bilinear interpolation. In conclusion, this study highlights the potential of adaptive resizers in enhancing performance for medical image classification. By outperforming traditional image resizing methods, our work contributes to the advancement of deep neural networks in the field of breast cancer diagnostics.Article Citation - WoS: 3Citation - Scopus: 5Event Distortion-Based Clustering Algorithm for Energy Harvesting Wireless Sensor Networks(Springer, 2021) Al-Qamaji, Ali; Atakan, BarışWireless sensor networks (WSNs) consist of compact deployed sensor nodes which collectively report their sensed readings about an event to the Base Station (BS). In WSNs, due to the dense deployment, sensor readings can be spatially correlated and it is nonessential to transmit all their readings to the BS. Therefore, for more energy efficient, it is vital to choose which sensor node should report their sensed readings to the BS. In this paper, the event distortion-based clustering (EDC) algorithm is proposed for the spatially correlated sensor nodes. Here, the sensor nodes are assumed to harvest energy from ambient electromagnetic radiation source. The EDC algorithm allows the energy-harvesting sensor nodes to select and eliminate nonessential nodes while maintain an acceptable level of distortion at the BS. To measure the reliability, a theoretical framework of the distortion function is first derived for both single-hop and two-hop communication scenarios. Then, based on the derived theoretical framework, the EDC algorithm is introduced. Through extensive simulations, the performance of the EDC algorithm is evaluated in terms of achievable distortion level, number of alive nodes and harvested energy levels. As a result, EDC algorithm can successfully exploit both the spatial correlation and energy harvesting to improve the energy efficiency while preserving an acceptable level of distortion. Furthermore, the performance comparisons reveal that the two-hop communication model outperforms the single-hop model in terms of the distortion and energy-efficiency.Article Time-Efficient Evaluation of Adaptation Algorithms for Dash With Svc: Dataset, Throughput Generation and Stream Simulator(Springer, 2021) Çalı, Mehmet; Özbek, NükhetBitrate adaptation algorithms have received considerable attention recently. In order to evaluate these algorithms objectively, multiple DASH datasets have been proposed. However, only few of them are compatible to SVC-based adaptation algorithms. Apart from the dataset, to fully implement and evaluate an adaptation algorithm, many time-consuming steps are required such as MPD parser design, adaptation logic design and network environment setup. In this paper, a dash simulator which assesses the performance of SVC-based adaptation algorithms without the requirement of any additional implementation steps is proposed. Also, an SVC dataset that includes both CBR and VBR encoded videos is designed. Demonstration is performed as evaluation of an SVC-based adaptation algorithm under several throughput scenarios using the designed dataset. Results show that the proposed system considerably reduces time requirement compared to real-time assessment. Dataset, throughput generation tool and simulator are all publicly available so that the researchers can test their implementation and compare with the results presented in this paper.Conference Object Citation - Scopus: 8Localization of a Passive Molecular Transmitter With a Sensor Network(Springer, 2020) Güleç, Fatih; Atakan, BarışMacroscale molecular communication (MC), which has a potential for practical applications, is a promising area for communication engineering. In a practical scenario such as monitoring air pollutants released from an unknown source, it is essential to estimate the location of the molecular transmitter (TX). This paper presents a novel Sensor Network-based Localization Algorithm (SNCLA) for passive transmission by using a novel experimental platform which mainly comprises a clustered sensor network (SN) with 24 sensor nodes and evaporating ethanol molecules as the passive TX. With the usage of the SN concept, novel methods can be developed for the problems in macroscale MC by utilizing the wide literature of sensor networks. In SNCLA, Gaussian plume model is employed to derive the location estimator. The parameters such as transmitted mass, wind velocity, detection time and actual concentration are calculated or estimated from the measured signals via the SN to be employed as the input for the location estimator. The numerical results show that the performance of SNCLA is better for stronger winds in the medium. Our findings show that evaporated molecules do not propagate homogeneously through the SN due to the presence of the wind. In addition, the estimation error of SNCLA decreases for higher detection threshold values. © 2020, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.Book Citation - Scopus: 17Feedback Strategies for Wireless Communication(Springer, 2014) Özbek, Berna; Le Ruyet, DidierThis book explores the different strategies regarding limited feedback information. The book analyzes the impact of quantization and the delay of CSI on the performance. The author shows the effect of the reduced feedback information and gives an overview about the feedback strategies in the standards. This volume presents theoretical analysis as well as practical algorithms for the required feedback information at the base stations to perform adaptive resource algorithms efficiently and mitigate interference coming from other cells. © 2014 Springer Science+Business Media New York. All rights are reserved.Book Citation - Scopus: 37Molecular Communications and Nanonetworks: From Nature To Practical Systems(Springer, 2014) Atakan, BarışThis book will introduce the concept of molecular communications and nanonetworks. The publication addresses why nanoscale communication is needed for the sophisticated nano and biotechnology applications. The text introduces the frontier applications of the molecular communication and nanonetworks. The book examines the molecular communication types called active, passive, and gap junction molecular communications. The author presents the molecular transmitter, receiver, encoding and decoding mechanisms used in these systems. Discussing the molecular communication system model and looking at the unique characteristics of practical molecular communication systems and these chemical reactions and their effects on the communication performance. Finally, the book examines the point-to-point, broadcast, and multiple-access molecular channel and shows two promising application examples of the nanonetworks. The first application example is the body area nanonetworks used in nanomedicine. the second nanonetwork application example, i.e., NanoSensor Networks (NSNs) with Molecular Communication. © Springer Science+Business Media New York 2014.Article A Saliency-Weighted Orthogonal Regression-Based Similarity Measure for Entropic Graphs(Springer, 2019) Ergün, Aslı; Ergün, Serkan; Ünlü, Mehmet Zübeyir; Güngör, CengizVarious measures are used to determine similarity ratios among images before and after image registration. Image registration methods are based on finding the translation, rotation, and scaling parameters that maximize the similarity between two images by taking advantage of the feature points and densities that are found. While the similarity criterion is calculated, it is possible and advantageous to use approximation methods on the graphs based on information theory. The current study proposes a new similarity measure based on saliency-weighted orthogonal regression derived from the weighted sums of the saliency map of the orthogonal regression residuals formed on the entropic graph. It is evaluated in terms of both quantitative and qualitative methods and compared with other graph-based similarity measures.Article Citation - WoS: 9Citation - Scopus: 11Robust Backstepping Control for a Four-Bar Linkage Mechanism Driven by a Dc Motor(Springer, 2019) Salah, Mohammad; Al-Jarrah, Ahmad; Banihani, Suleiman; Tatlıcıoğlu, EnverFour-bar linkage mechanisms have dragged the attention of many specialists due to its importance in the academic and industrial sectors. Hence, a lot of research work has been conducted to understand their complex behavior and explore various control techniques. In fact, such mechanisms possess highly nonlinear dynamics that require advanced nonlinear control methods. In addition, the four-bar linkage mechanism is exposed to significant dynamic fluctuations at high speeds due to the system inertias. In this paper, a backstepping control algorithm with a robust scheme is designed and applied on the four-bar linkage mechanism to investigate and explore its dynamical performance under various operating conditions and without a priori knowledge of the model parameters. Five operating conditions are introduced and tested in numerical simulations to show that the proposed nonlinear controller successfully regulates and tracks the speed of the driving link of the mechanism and shows a satisfactory performance.Conference Object Citation - WoS: 1Citation - Scopus: 2Glottal Source Estimation Using an Automatic Chirp Decomposition(Springer, 2010) Drugman, Thomas; Bozkurt, Barış; Dutoit, ThierryIn a previous work, we showed that the glottal source can be estimated from speech signals by computing the Zeros of the Z-Transform (ZZT). Decomposition was achieved by separating the roots inside (causal contribution) and outside (anticausal contribution) the unit circle. In order to guarantee a correct deconvolution, time alignment on the Glottal Closure Instants (GCIs) was shown to be essential. This paper extends the formalism of ZZT by evaluating the Z-transform on a contour possibly different from the unit circle. A method is proposed for determining automatically this contour by inspecting the root distribution. The derived Zeros of the Chirp Z-Transform (ZCZT)-based technique turns out to be much more robust to GCI location errors. © 2010 Springer-Verlag.