Makale Koleksiyonu | Elektrik-Elektronik Mühendisliği Bölümü

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Kararlılık sınır eğrisi kullanarak birleştirilmiş sıvı tank sistemi için PI denetleyici tasarımı
(Fırat Üniversitesi, 2022) Değirmenci, Ali Murat; Tan, Musret; İstefanopulos, Yorgo
Bu çalışmada, birbirine bağlı ikili sıvı tank sistemi için, Kararlılık Sınır Eğrisi yöntemi kullanılarak, bir PI denetleyici (Oransal–Tümlevsel) tasarlanmıştır. Tasarıma başlamadan önce iki ayrı tankın matematiksel modeli elde edilmiştir. Elde edilen modelden yola çıkarak, tanklarda bulunan sıvıların seviye kontrolü için PI denetleyici tasarlanmış ve tasarım sonuçları MATLAB/SIMULINK ortamında modellenmiştir. Sonuç olarak, sistemin benzetim ve gerçek zamanlı tepkileri incelenerek kuramsal çalışma desteklenmiştir.
Design of voltage-mode and current-mode PID controllers using a single Add-Differentiate IC (AD-IC)
(Birkhauser, 2025-12-22) Minayi, Elham; Göknar, İzzet Cem
In this paper, voltage and current mode proportional–integral–derivative (PID) controller circuits are presented in one topology, utilizing only a single active component, Add-Differentiate Integrated Circuit (AD-IC) along with two passive resistors and two passive capacitors. The effectiveness and performance of the proposed circuits are validated through sensitivity, non-ideality analyses and PSPICE and MatLab simulations.
Eco-friendly bacterial cellulose/castor oil hydrogels: physicochemical behavior and biocompatibility
(Sakarya University, 2025-10-27) Işıkçı Koca, Elif; Pınar, Orkun; Yalçın Çapan, Özlem; Çaylı, Gökhan; Kazan, Dilek; Çakır Hatır, Pınar
In the present work, novel thermoresponsive hydrogels were developed from renewable resources, and the influence of bacterial cellulose molar ratio on their chemical structure, thermal properties, swelling behavior, morphology, and biocompatibility was systematically investigated. The hydrogels were fabricated using castor oil, 4,4'-diphenylmethane diisocyanate, bacterial cellulose, Nisopropylacrylamide, and N,N'-Methylenebisacrylamide. Structural and physicochemical characterizations were performed by Fourier-transform infrared spectroscopy, scanning electron microscopy, differential scanning calorimetry, and thermogravimetric analysis. The highest equilibrated swelling degree was achieved as 592.6% at the maximum bacterial cellulose content. SEM images revealed that the formation of spongy architecture is caused by the increase in the bacterial cellulose content. In vitro biocompatibility studies revealed that the hydrogel with the highest bacterial cellulose content exhibited the greatest cytocompatibility, with an IC50 value of 11.16 mg/ml. Overall, the findings demonstrate the successful fabrication of a novel bio-based thermoresponsive hydrogel through an eco-friendly approach, highlighting its potential for diverse biomedical applications.
Goal-Oriented Random Access (GORA)
(Cornell Univ, 2025-05-05) Topbaş, Ahsen; Ari, Çağrı; Kaya, Onur; Uysal, Elif
We propose Goal-Oriented Random Access (GORA), where transmitters jointly optimize what to send and when to access the shared channel to a common access point, considering the ultimate goal of the information transfer at its final destination. This goal is captured by an objective function, which is expressed as a general (not necessarily monotonic) function of the Age of Information. Our findings reveal that, under certain conditions, it may be desirable for transmitters to delay channel access intentionally and, when accessing the channel, transmit aged samples to reach a specific goal at the receiver.
Age of information in practice
(Cornell Univ, 2021-06-02) Uysal, Elif; Kaya, Onur; Baghaee, Sajjad; Beytur, Hasan Burhan
While age of Information (AoI) has gained importance as a metric characterizing the fresh-ness of information in information-update systems and time-critical applications, most previous studies on AoI have been theoretical. In this chapter, we compile a set of recent works reporting API measurements in real-life networks and experimental testbeds, and investigating practical issues such as synchronization, the role of various transport layer protocols, congestion control mechanisms, application of machine learning for adaptation to network conditions, and device related bottlenecks such as limited processing power.
Quantum Zeno repeaters
(Cornell Univ, 2022-06-17) Bayrakçı, Veysel; Özaydın, Fatih
Quantum repeaters pave the way for long-distance quantum communications and quantum Internet, and the idea of quantum repeaters is based on entanglement swapping which requires the implementation of controlled quantum gates. Frequently measuring a quantum system affects its dynamics which is known as the quantum Zeno effect (QZE). Beyond slowing down its evolution, QZE can be used to control the dynamics of a quantum system by introducing a carefully designed set of operations between measurements. Here, we propose an entanglement swapping protocol based on QZE, which achieves almost unit fidelity. Implementation of our protocol requires only simple frequent threshold measurements and single particle rotations. We extend the proposed entanglement swapping protocol to a series of repeater stations for constructing quantum Zeno repeaters which also achieve almost unit fidelity regardless of the number of repeaters. Requiring no controlled gates, our proposal reduces the quantum circuit complexity of quantum repeaters. Our work has potential to contribute to long distance quantum communications and quantum computing via quantum Zeno effect.
Intelligent health monitoring in 6G networks: machine learning-enhanced VLC-based medical body sensor networks
(MDPI, 2025-04-30) Antaki, Bilal; Dalloul, Ahmed Hany; Miramirkhani, Farshad
Recent advances in Artificial Intelligence (AI)-driven wireless communication demand innovative Sixth Generation (6G) solutions, particularly in hospitals where reliability and secure communication are crucial. Visible Light Communication (VLC) leverages existing lighting systems to deliver high data rates while mitigating electromagnetic interference. However, VLC systems in medical settings face fluctuating signal strength and dynamic channel conditions due to patient movement, necessitating advanced optimization techniques. This paper employs a site-specific ray tracing technique in Medical Body Sensor Networks (MBSNs) channel modeling within hospital scenarios to derive channel impulse responses (CIRs) and model path loss (PL) and Root Mean Square (RMS) delay spread in two distinct hospital settings. In the first section, we evaluate Machine Learning (ML)-based adaptive modulation in VLC-enabled MBSNs and introduce a Q-learning technique enabling real-time adaptation without prior environmental knowledge. In the second section, we propose a Long Short Term Memory (LSTM) based approach to estimate PL and RMS delay spread in dynamic hospital environments. The Q-learning method consistently achieved the target symbol error rate (SER), though spectral efficiency (SE) was sometimes lower than optimal due to quantization limits and a cautious approach near the SER threshold. For LSTM-based channel estimation algorithm, simulation studies show that in the Intensive Care Unit (ICU) ward scenario, D1 has the highest Root Mean Squared Error (RMSE) for estimated path loss (1.6797 dB) and RMS delay spread (1.0567 ns), whereas in the Family-Type Patient Rooms (FTPR) scenario, D3 exhibits the highest RMSE for estimated path loss (1.0652 dB) and RMS delay spread (0.7657 ns).
An active discharge scheme for DC-bus capacitors in EV powertrain
(Institute of Electrical and Electronics Engineers Inc., 2025-07-18) Sezer, Mustafa Murat; Norwood, Daniel; Geiger, John; Hava, Ahmet Masum; Akın, Bilal
During the emergency situations, key-OFFs, or maintenance, discharging the inverter dc-bus capacitor voltage within seconds is imperative due to safety concerns (inverter not used to control motor). Conventional discharge methods rely on external resistors, additional switches, or motor windings, increasing cost, space requirements, and control complexity. This article presents a cost-effective and space-efficient solution that enables fast capacitor discharge by operating the inverter's SiC mosfets-either discrete devices or power modules-in linear mode. The proposed method utilizes a constant power tracking approach with pulse frequency modulation to safely discharge the high-voltage bus capacitor without external components. When the car is off, the proposed scheme discharges a 1000-V dc bus within 1 s using a single low-side SiC switch to test a worst-case scenario. In practice, all six devices can be used to share thermal stress, and the discharge time can be extended to 5 s as suggested by safety standards. Optimal operating conditions, including gate-source voltage (V{GS}) and pulse width (t{ON}}), are identified for different mosfets from various vendors. To assess long-term reliability, devices undergo more than 200 000 discharge cycles, with intrinsic parameter monitoring and failure analysis conducted to determine degradation mechanisms. The findings help establish safe operating conditions, ensuring robust and reliable integration of the proposed discharge method within the main powertrain inverter.
Intelligent health monitoring in 6G networks: machine learning-enhanced VLC-based medical body sensor networks
(Multidisciplinary Digital Publishing Institute (MDPI), 2025-05-23) Antaki, Bilal; Dalloul, Ahmed Hany; Miramirkhani, Farshad
Recent advances in Artificial Intelligence (AI)-driven wireless communication are driving the adoption of Sixth Generation (6G) technologies in crucial environments such as hospitals. Visible Light Communication (VLC) leverages existing lighting infrastructure to deliver high data rates while mitigating electromagnetic interference (EMI); however, patient movement induces fluctuating signal strength and dynamic channel conditions. In this paper, we present a novel integration of site-specific ray tracing and machine learning (ML) for VLC-enabled Medical Body Sensor Networks (MBSNs) channel modeling in distinct hospital settings. First, we introduce a Q-learning-based adaptive modulation scheme that meets target symbol error rates (SERs) in real time without prior environmental information. Second, we develop a Long Short-Term Memory (LSTM)-based estimator for path loss and Root Mean Square (RMS) delay spread under dynamic hospital conditions. To our knowledge, this is the first study combining ray-traced channel impulse response modeling (CIR) with ML techniques in hospital scenarios. The simulation results demonstrate that the Q-learning method consistently achieves SERs with a spectral efficiency (SE) lower than optimal near the threshold. Furthermore, LSTM estimation shows that D1 has the highest Root Mean Square Error (RMSE) for path loss (1.6797 dB) and RMS delay spread (1.0567 ns) in the Intensive Care Unit (ICU) ward, whereas D3 exhibits the highest RMSE for path loss (1.0652 dB) and RMS delay spread (0.7657 ns) in the Family-Type Patient Rooms (FTPRs) scenario, demonstrating high estimation accuracy under realistic conditions.
Goal-Oriented Random Access (GORA)
(Institute of Electrical and Electronics Engineers Inc., 2025-08) Topbaş, Ahsen; Ari, Çağrı; Kaya, Onur; Uysal, Elif
We propose Goal-Oriented Random Access (GORA), where transmitters jointly optimize what to send and when to access the shared channel to a common access point, considering the ultimate goal of the information transfer at its final destination. This goal is captured by an objective function, which is expressed as a general (not necessarily monotonic) function of the Age of Information. Our findings reveal that, under certain conditions, it may be desirable for transmitters to delay channel access intentionally and, when accessing the channel, transmit aged samples to reach a specific goal at the receiver.
Design and control of high-frequency buck converter fed six-step drive for air-core PMSM
(Institute of Electrical and Electronics Engineers Inc., 2025-02) Jena, Sritam; Kumar, Saurabh; Deshmukh, Akshay Vijayrao; Hava, Ahmet Masum; Akın, Bilal; Gabrys, Christopher; Rodgers, Timothy
Air-core permanent magnet synchronous motors (PMSMs) machines are becoming known for their higher efficiency, lighter weight designs, and superior performance compared to widely utilized induction motors (IMs). They hold great potential for diverse industrial applications. However, effectively harnessing this potential requires overcoming drive hardware and control challenges. This research introduces a silicon carbide (SiC)-based two-phase interleaved buck-converter-fed quasi-current source inverter (quasi-CSI) drive tailored for driving low-inductance air-core PMSMs which is ideal for heavy-duty fan and pump applications. Operating in the discontinuous current mode (DCM) with an effective switching frequency of 1 MHz, this drive is designed to address efficiency and the very low-cost market constraints while simultaneously reducing control complexity an issue associated with its high switching frequency. The article also analyzes two critical control challenges of mitigating high current spikes due to air-core machines' low inductance and finding solutions to overcome microcontroller resource limitations when executing time-critical functions within interrupt subroutines (ISRs). The culmination of this work is a 300 V dc-bus and five-horsepower electric drive prototype with closed-loop speed control. Experimental results illustrate a 2% enhancement in overall efficiency compared to conventional induction machine (IM) drives in similar applications (e.g., fan and pump) and ratings, alongside a significant 50% reduction in drive volume.
A practical control method for single-phase input PMSM drives with small DC-Link capacitor
(Institute of Electrical and Electronics Engineers Inc., 2025-03) Deshmukh, Akshay Vijayrao; Afshar, Mojtaba; Jena, Sritam; Hava, Ahmet Masum; Yu, Zhen; Akın, Bilal
The primary function of the large electrolytic dc-link capacitor in the single-phase input motor drives is to enhance dc voltage stability by minimizing voltage fluctuations. Because they are both bulky and unreliable components, reducing the size of dc-link capacitors or substituting them with significantly low capacitance value film capacitors offers numerous advantages. This article introduces a method that allows using a voltage source inverter with a small film dc-link capacitor, which results in equivalent performance to high-value capacitor drives. In this approach, the effect of dc-link voltage ripple is designed as a periodic disturbance in the current loop. A proportional-integral-resonant (PIR) control strategy is implemented to eliminate the designed double-line frequency disturbance observed in motor currents, thereby ensuring a smooth motor torque response. This solution meets crucial criteria for home appliances, specifically addressing input current harmonic requirements through power factor correction while effectively reducing the adverse effects of substantial dc-link ripple on motor torque, even when employing a film capacitor (10–50 µF range). The proposed framework is experimentally tested on permanent magnet synchronous motors with fan-load and dynamometers. Experimental results demonstrate, with PIR, an 80% reduction in current and torque ripple occurring due to the use of a low-value dc-link film capacitor. This also achieves performance within ±5% of the results obtained with a drive equipped with a 1200 µF dc capacitor. In addition, the line-side power factor exceeds 0.98 for loads exceeding 8% of the rated power.
A multi-frequency iterative method for reconstruction of rough surfaces separating two penetrable media
(Institute of Electrical and Electronics Engineers Inc., 2024-12-18) Sefer, Ahmet; Yapar, Ali; Bağcı, Hakan
A numerical scheme that uses multi-frequency Newton iterations to reconstruct a rough surface profile between two dielectric media is proposed. At each frequency sample, the scheme employs Newton iterations to solve the nonlinear inverse scattering problem. At every iteration, the Newton step is computed by solving a linear system that involves the Frechet derivative of the integral operator, which represents the scattered fields, and the difference between these fields and the measurements. This linear system is regularized using the Tikhonov method. The multi-frequency data is accounted for in a recursive manner. More specifically, the profile reconstructed at a given frequency is used as an initial guess for the iterations at the next frequency. The effectiveness of the proposed method is validated through numerical examples, which demonstrate its ability to accurately reconstruct surface profiles even in the presence of measurement noise. The results also show the superiority of the multi-frequency approach over single-frequency reconstructions, particularly in terms of handling surfaces with sharp variations.
Machine learning-driven adaptive modulation for VLC-enabled medical body sensor networks
(Iran University of Science and Technology, 2024-12) Rizi, Reza Bayat; Forouzan, Amir R.; Miramirkhani, Farshad; Sabahi, Mohamad F.
Visible Light Communication, a key optical wireless technology, offers reliable, high-bandwidth, and secure communication, making it a promising solution for a variety of applications. Despite its many advantages, optical wireless communication faces challenges in medical environments due to fluctuating signal strength caused by patient movement. Smart transmitter structures can improve system performance by adjusting system parameters to the fluctuating channel conditions. The purpose of this research is to examine how adaptive modulation performs in a medical body sensor network system that uses visible light communication. The analysis focuses on various medical situations and investigates machine learning algorithms. The study compares adaptive modulation based on supervised learning with that based on reinforcement learning. The findings indicate that both approaches greatly improve spectral efficiency, emphasizing the significance of implementing link adaptation in visible light communication-based medical body sensor networks. The use of the Q-learning algorithm in adaptive modulation enables real-time training and enables the system to adjust to the changing environment without any prior knowledge about the environment. A remarkable improvement is observed for photodetectors on the shoulder and wrist since they experience more DC gain.
An Inverse recursive algorithm to retrieve the shape of the inaccessible dielectric objects
(Ramazan YAMAN, 2024-10-16) Sefer, Ahmet
A regularized electromagnetic iterative inverse algorithm is formulated and im-plemented to reconstruct the shape of 2D dielectric objects using the far-fieldpattern of the scattered field data. To achieve this, an integral operator thatmaps the unknown boundary of the object onto the far-field pattern of thescattered field is defined and solved for the unknown boundary. The addressedinverse problem has an ill-posed nature and inherits nonlinearity. To over-come these, the proposed solution is linearized via Newton and regularized byTikhonov in the sense of least squares. Besides, the dominance of the shadowregion in the inverse-imaging process is exceeded by considering the superpo-sition of multi-incoming plane waves, leading to less computational cost and avery fast inversion process. Comprehensive numerical analyses are carried outto ascertain the algorithm’s feasibility, revealing that it is very efficient andpromising.
Imaging of rough surfaces by RTM method
(IEEE, 2024) Sefer, Ahmet; Yapar, Ali; Yelkenci, Tanju
An electromagnetic imaging framework is implemented utilizing a single frequency reverse time migration (RTM) technique to accurately reconstruct inaccessible two-dimensional (2D) rough surface profiles from the knowledge of scattered field data. The unknown surface profile, which is expressed as a 1D height function, is either perfectly electric conducting (PEC) or an interface between two penetrable media. For both cases, it is assumed that the surface is illuminated by a number of line sources located in the upper medium. The scattered fields, which should be collected by real measurements in practical applications, are obtained synthetically by solving the associated direct scattering problem through the surface integral equations. RTM is subsequently applied to generate a cross-correlation imaging functional which is evaluated numerically and provides a 2D image of the region of interest. A high correlation is observed by the functional in the regions where the transitions between two media occur. Hence, it results in the acquisition of the unknown surface profile at the sites where the functional attains its highest values. The efficiency of the proposed method is comprehensively tested by numerical examples covering various types of scattering scenarios.
Engineering four-qubit fuel states for protecting quantum thermalization machine from decoherence
(Multidisciplinary Digital Publishing Institute (MDPI), 2024-01-10) Özaydın, Fatih; Sarkar, Ramita; Bayrakçı, Veysel; Bayındır, Cihan; Altıntaş, Azmi Ali; Müstecaplıoğlu, Özgür E.
Decoherence is a major issue in quantum information processing, degrading the performance of tasks or even precluding them. Quantum error-correcting codes, creating decoherence-free subspaces, and the quantum Zeno effect are among the major means for protecting quantum systems from decoherence. Increasing the number of qubits of a quantum system to be utilized in a quantum information task as a resource expands the quantum state space. This creates the opportunity to engineer the quantum state of the system in a way that improves the performance of the task and even to protect the system against decoherence. Here, we consider a quantum thermalization machine and four-qubit atomic states as its resource. Taking into account the realistic conditions such as cavity loss and atomic decoherence due to ambient temperature, we design a quantum state for the atomic resource as a classical mixture of Dicke and W states. We show that using the mixture probability as the control parameter, the negative effects of the inevitable decoherence on the machine performance almost vanish. Our work paves the way for optimizing resource systems consisting of a higher number of atoms.
A review of recent innovations in remote health monitoring
(Multidisciplinary Digital Publishing Institute (MDPI), 2023-12) Dalloul, Ahmed Hany; Miramirkhani, Farshad; Kouhalvandi, Lida
The development of remote health monitoring systems has focused on enhancing healthcare services’ efficiency and quality, particularly in chronic disease management and elderly care. These systems employ a range of sensors and wearable devices to track patients’ health status and offer real-time feedback to healthcare providers. This facilitates prompt interventions and reduces hospitalization rates. The aim of this study is to explore the latest developments in the realm of remote health monitoring systems. In this paper, we explore a wide range of domains, spanning antenna designs, small implantable antennas, on-body wearable solutions, and adaptable detection and imaging systems. Our research also delves into the methodological approaches used in monitoring systems, including the analysis of channel characteristics, advancements in wireless capsule endoscopy, and insightful investigations into sensing and imaging techniques. These advancements hold the potential to improve the accuracy and efficiency of monitoring, ultimately contributing to enhanced health outcomes for patients.
IEEE 802.11BB reference channel models for light communications
(IEEE, 2023-12-01) Miramirkhani, Farshad; Baykaş, Tunçer; Elamassie, Mohammed; Uysal, Murat
Increasing industrial attention to visible light communications (VLC) technology led the IEEE 802.11 to establish the task group 802.11bb 'Light Communications' (LC) for the development of a VLC standard. As a part of the standard development process, the development of realistic channel models according to possible use cases is of critical importance for physical layer system design. This article presents the reference channel models for the mandatory usage models adopted by IEEE 802.11bb for the evaluation of system proposals. The use cases include industrial, medical, enterprise, and residential scenarios. Channel impulse responses and corresponding frequency responses are obtained for each use case using a ray tracing approach based on realistic specifications for transmitters and receivers, and optical characterization of the environment.
Superactivating bound entanglement in quantum networks via quantum Zeno dynamics and a novel algorithm for optimized Zeno evolution
(MDPI, 2023-01) Özaydın, Fatih; Bayrakçı, Veysel; Altıntaş, Azmi Ali; Bayındır, Cihan
An arbitrary amount of entanglement shared among nodes of a quantum network might be nondistillable if the nodes lack the information on the entangled Bell pairs they share. Making such a system distillable, which is called the superactivation of bound entanglement (BE), was shown to be possible through systematic quantum teleportation between the nodes, requiring the implementation of controlled-gates scaling with the number of nodes. In this work, we show in two scenarios that the superactivation of BE is possible if nodes implement the proposed local quantum Zeno strategies based on only single qubit rotations and simple threshold measurements. In the first scenario we consider, we obtain a two-qubit distillable entanglement system as in the original superactivation proposal. In the second scenario, we show that superactivation can be achieved among the entire network of eight qubits in five nodes. In addition to obtaining all-particle distillable entanglement, the overall entanglement of the system in terms of the sum of bipartite cuts is increased. We also design a general algorithm with variable greediness for optimizing the QZD evolution tasks. Implementing our algorithm for the second scenario, we show that a significant improvement can be obtained by driving the initial BE system into a maximally entangled state. We believe our work contributes to quantum technologies from both practical and fundamental perspectives bridging nonlocality, bound entanglement and the quantum Zeno dynamics among a quantum network.

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