Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Energy Harvesting in High Altitude Platform Station Enabled Sensor Networks(Institute of Electrical and Electronics Engineers Inc., 2026) Tuylu, M.; Erdoǧan, E.High altitude platform station (HAPS) systems are becoming crucial facilitators for future wireless communication networks, enhancing connectivity across all vertical communication layers, including small Internet of Things (IoT) sensors and devices, terrestrial users, and aerial devices. In the context of the widely recognized vertical heterogeneous network (VHetNet) architecture, HAPS systems can provide service to both aerial and ground users. However, integrating HAPS systems as a core element in the VHetNet architecture presents a considerable energy challenge, marking a prominent constraint for their operation. Driven by this challenge, we introduce an energy harvesting (EH) strategy tailored for HAPS systems, enabling a HAPS system to gather energy from another HAPS system, which is not constrained by energy limitations. To assess the performance capabilities of the proposed model, we derive outage probability (OP), ergodic capacity (EC) and verify them by using Monte Carlo (MC) simulations. Moreover, we explore the system in terms of throughput. The findings reveal that harnessing full potential of EH stands as a viable approach to meet the energy demands of HAPS systems. © 2001-2012 IEEE.Conference Object A Comparative Study of Attention-Augmented YOLO Architectures for Defect Detection in Fused Deposition Modelling(Institute of Electrical and Electronics Engineers Inc., 2025) Cezayirli, H.; Tetik, H.; Dede, M.I.C.; Phone, W.L.; Alkan, B.Additive manufacturing (AM), particularly fused deposition modelling (FDM), facilitates the fabrication of complex geometries with increasing flexibility and efficiency. Ensuring consistent print quality in FDM processes necessitates the development of accurate defect detection mechanisms. Attention-augmented YOLO (You Only Look Once) models have emerged as a promising solution for addressing this challenge. In this study, we systematically benchmark and evaluate the performance of YOLO architectures enhanced with attention mechanisms within the context of FDM 3D printing applications. The models were trained and evaluated using representative defect datasets. The attention-augmented models demonstrate improved detection performance. © 2025 IEEE.Article Citation - WoS: 1Citation - Scopus: 2Localization of a Passive Source With a Sensor Network-Based Experimental Molecular Communication Platform(Institute of Electrical and Electronics Engineers Inc., 2024) Gulec,F.; Koda,D.Y.; Atakan,B.; Eckford,A.W.In a practical molecular communication 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. In SNCLA, a 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, our statistical analysis based on the measured experimental data shows that the sensed signals by the SN have a log-normal distribution, while the additive noise follows a Student's t-distribution in contrast to the Gaussian assumption in the literature. © 2015 IEEE.Conference Object Citation - WoS: 1Citation - Scopus: 2Predicting the Soft Error Vulnerability of Gpgpu Applications(Institute of Electrical and Electronics Engineers Inc., 2022) Topçu, Burak; Öz, IşılAs Graphics Processing Units (GPUs) have evolved to deliver performance increases for general-purpose computations as well as graphics and multimedia applications, soft error reliability becomes an important concern. The soft error vulnerability of the applications is evaluated via fault injection experiments. Since performing fault injection takes impractical times to cover the fault locations in complex GPU hardware structures, prediction-based techniques have been proposed to evaluate the soft error vulnerability of General-Purpose GPU (GPGPU) programs based on the hardware performance characteristics.In this work, we propose ML-based prediction models for the soft error vulnerability evaluation of GPGPU programs. We consider both program characteristics and hardware performance metrics collected from either the simulation or the profiling tools. While we utilize regression models for the prediction of the masked fault rates, we build classification models to specify the vulnerability level of the programs based on their silent data corruption (SDC) and crash rates. Our prediction models achieve maximum prediction accuracy rates of 96.6%, 82.6%, and 87% for masked fault rates, SDCs, and crashes, respectively.Article Citation - WoS: 3Citation - Scopus: 4A Novel Efficient Method for Tracking Evolution of Communities in Dynamic Networks(Institute of Electrical and Electronics Engineers Inc., 2022) Karataş, Arzum; Şahin, SerapTracking community evolution can provide insights into significant changes in community interaction patterns, promote the understanding of structural changes, and predict the evolutionary behavior of networks. Therefore, it is a fundamental component of decision-making mechanisms in many fields such as marketing, public health, criminology, etc. However, in this problem domain, it is an open challenge to capture all possible events with high accuracy, memory efficiency, and reasonable execution times under a single solution. To address this gap, we propose a novel method for tracking the evolution of communities (TREC). TREC efficiently detects similar communities through a combination of Locality Sensitive Hashing and Minhashing. We provide experimental evidence on four benchmark datasets and real dynamic datasets such as AS, DBLP, Yelp, and Digg and compare them with the baseline work. The results show that TREC achieves an accuracy of about 98%, has a minimal space requirement, and is very close to the best performing work in terms of time complexity. Moreover, it can track all event types in a single solution.Article Citation - WoS: 7Citation - Scopus: 8Tracking Code Bug Fix Ripple Effects Based on Change Patterns Using Markov Chain Models(Institute of Electrical and Electronics Engineers Inc., 2022) Ufuktepe, Ekincan; Tuğlular, Tuğkan; Palaniappan, KanappanChange impact analysis evaluates the changes that are made in the software and finds the ripple effects, in other words, finds the affected software components. Code changes and bug fixes can have a high impact on code quality by introducing new vulnerabilities or increasing their severity. A recent high-visibility example of this is the code changes in the log4j web software CVE-2021-45105 to fix known vulnerabilities by removing and adding method called change types. This bug fix process exposed further code security concerns. In this article, we analyze the most common set of bug fix change patterns to have a better understanding of the distribution of software changes and their impact on code quality. To achieve this, we implemented a tool that compares two versions of the code and extracts the changes that have been made. Then, we investigated how these changes are related to change impact analysis. In our case study, we identified the change types for bug-inducing and bug fix changes using the Quixbugs dataset. Furthermore, we used 13 of the projects and 621 bugs from Defects4J to identify the common change types in bug fixes. Then, to find the change types that cause an impact on the software, we performed an impact analysis on a subset of projects and bugs of Defects4J. The results have shown that, on average, 90% of the bug fix change types are adding a new method declaration and changing the method body. Then, we investigated if these changes cause an impact or a ripple effect in the software by performing a Markov chain-based change impact analysis. The results show that the bug fix changes had only impact rates within a range of 0.4-5%. Furthermore, we performed a statistical correlation analysis to find if any of the bug fixes have a significant correlation with the impact of change. The results have shown that there is a negative correlation between caused impact with the change types adding new method declaration and changing method body. On the other hand, we found that there is a positive correlation between caused impact and changing the field type.Article Citation - WoS: 7Citation - Scopus: 8The Resilience of Massive Mimo Pnc To Jamming Attacks in Vehicular Networks(Institute of Electrical and Electronics Engineers Inc., 2021) Okyere, Bismark; Musavian, Leila; Özbek, Berna; Busari, Sherif A.; Gonzalez, JonathanIn this article, we investigate the resilience of Massive MIMO Physical Layer Network Coding (PNC) to jamming attack in both sub-6 GHz and millimeter-Wave (mmWave) systems in vehicular networks. Massive MIMO generally is resilient to jamming attacks, and we investigate the impact that PNC has on this resilience, if combined with Massive MIMO. The combination of Massive MIMO and PNC has shown a significant improvement in the bit error rate (BER) in our previous investigation. The corresponding framework is analysed against a barraging attack from a jammer, where the jamming channel is not known to the base station (BS), and the jammer can use any number of transmit antennas. Over Rayleigh channel, our simulation results reveal that Massive MIMO PNC performs better in the lower signal-to-noise ratio (SNR) regions to jamming attacks and this is achieved at twice the spectral efficiency. A similar performance is observed over mmWave channel.Article Citation - WoS: 3Citation - Scopus: 5Design and Implementation of Spatial Correlation-Based Clustering for Multiuser Miso-Noma Systems(Institute of Electrical and Electronics Engineers Inc., 2021) Göztepe, Caner; Özbek, Berna; Karabulut Kurt, GüneşIn this letter, we propose a novel user clustering algorithm for downlink multiuser multiple-input single-output (MISO) non-orthogonal multiple access (NOMA) systems along with its implementation in a real-time testing environment. The proposed method selects the clusters by considering users' spatial channel properties against the generated orthogonal directions. This is then followed by power allocation and zero-forcing precoding steps to mitigate the interference between the selected clusters. Performance comparisons are provided in terms of both real-time tests and simulations. It is demonstrated that a notable improvement in capacity and reliability can be obtained through the proposed approach in multiuser MISO-NOMA systems with reduced complexity.Conference Object Doğal Dil Çıkarımı Modellerinde Bert Vektörlerinin Başarım Değerlendirmesi(Institute of Electrical and Electronics Engineers Inc., 2021) Oğul, İskender Ülgen; Tekir, SelmaDoğal dil çıkarımı, düşünce ifade eden cümlelerin arasındaki ilişkiyi; karşıtlık, gerekseme veya tarafsızlık olarak sınıflandırmayı hedefler. Sınıflandırma görevini gerçekleştirmek için metinsel kaynaklar, vektör ya da gömme olarak adlandırılan matematiksel gösterimlere dönüştürülür. Bu çalışmada, hem statik (Glove, OntoNotes5) hem de bağlamsal (BERT) kelime gömme yöntemleri kullanılmıştır. Fikirsel cümleler arasındaki mantıksal ilişkilerin sınıflandırılması zordur zira cümleler karmaşık gramer yapılarına sahiptir ve cümlelerin işlenerek mantıksal gösterimlere dönüştürülmesi geleneksel doğal dil işleme çözümleri ile yetersiz kalmaktadır. Bu çalışma, sınıflandırma görevini gerçekleştirmek için ayrıştırılabilir ilgi ve doğal dil çıkarımı için gelişmiş LSTM (ESIM) derin öğrenme modellerini kullanmıştır. En iyi sonuç olan %88 doğruluk değeri SNLI veri kümesi üzerinde ESIM-BERT ile elde edilmiştir.Conference Object Citation - Scopus: 1Yüksek İrtifa Platform İstasyonları için Korelasyon Matrisinin Yaklaşımı(Institute of Electrical and Electronics Engineers Inc., 2021) Cengiz, Aybüke; Tedik Başaran, Semiha; Karabulut Kurt, Güneş; Özbek, Berna; Yanıkömeroğlu, HalimA High Altitude Platform Station (HAPS) is a new and promising technology with different uses like wireless communication services, traffic monitoring, navigation applications and Internet of Things (IoT) applications. Since it is positioned much higher than ground-level users, line-of-sight (LOS) is more common in HAPS systems. Especially in HAPS systems that include multiple antennas, the effect of correlation between antennas is an important factor limiting the performance. The effect of correlation is strongly influenced by the spacing between the antenna elements and environmental factors. This effect can be reduced by the effect of rich scattering environment in terrestrial Multi-Input/Multi-Output (MIMO) systems, yet this observation is not applicable to HAPS systems. In this study, a tight bound expression for the correlation matrix which does not have an expression in closed form and has a significant place in the performance of HAPS systems has been obtained. Comprehensive numerical values have been obtained under different system parameters to demonstrate the convergence performance of the approximate expression to the real value, and the results have been compared. © 2021 IEEE.