Scopus İndeksli Yayınlar Koleksiyonu

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Citation - Scopus: 0
The Influence of Eye Gaze Interaction Technique Expertise and the Guided Evaluation Method on Text Entry Performance Evaluations
(Association for Computing Machinery, 2025) Mutasim, A.K.; Batmaz, A.U.; Hudhud Mughrabi, M.; Stuerzlinger, W.
Any investigation of learning unfamiliar text entry systems is affected by the need to train participants on multiple new components simultaneously, such as novel interaction techniques and layouts. The Guided Evaluation Method (GEM) addresses this challenge by bypassing the need to learn layout-specific skills for text entry. However, a gap remains as the GEM's performance has not been assessed in situations where users are unfamiliar with the interaction technique involved, here eye-gaze-based dwell. To address this, we trained participants on only the eye-gaze-based interaction technique over eight days with QWERTY and then evaluated their performance on the OPTI layout with the GEM. Results showed that the unfamiliar OPTI layout outperformed QWERTY, with QWERTY's speed aligning with previous findings, suggesting that interaction technique expertise significantly impacts performance outcomes. Importantly, we also identified that for scenarios where the familiarity with the involved interaction technique(s) is the same, the GEM analyzes the performance of keyboard layouts effectively and quickly identifies the best option. © 2025 ACM.
Citation - Scopus: 0
Promoting Sustainable Urban Mobility: an Integrated Fuzzy Decision-Making Model for Assessing Autonomous Bus Alternatives
(Elsevier Ltd, 2025) Görçün, Ö.F.; Özçalıcı, M.; Gurler, H.E.; Pamucar, D.; Simic, V.
Today, in addition to the increasing pressures on urban transportation authorities to achieve sustainability goals, it has become necessary to comprehensively evaluate innovative transportation technologies such as autonomous (driverless) buses due to the increasing demand for public transportation applications that will contribute to making urban transportation more sustainable with its environmental, social, economic and social dimensions. In addition, the reservations and hesitations of decision-makers about integrating autonomous buses into urban transportation systems have not been eliminated. These hesitations and reservations are mainly due to critical research, theoretical gaps, and limitations in practice. Considering these gaps, this study presents an innovative model that integrates the fuzzy logarithm methodology of additive weights (LMAW) method and the fuzzy Dombi Bonferroni (DOBI) method to evaluate and rank 20 different autonomous bus alternatives with 33 sustainability criteria. The proposed integrated decision-making procedure can effectively manage complex uncertainties while examining whether autonomous bus alternatives can be integrated into urban transportation systems based on sustainability, considering four-dimensional sustainability criteria. This finding indicates that urban transportation's user-oriented and reliable nature is critical to achieving sustainability goals. In addition, the Proterra Catalyst (A9) is the autonomous bus with the highest sustainability performance for use in urban transport, followed by the Mercedes-Benz Future Bus (A18) and Mercedes-Benz eCitaro (A8). These results regarding alternatives underline the importance of advances in autonomous vehicle technology and making these vehicles more sustainable in evaluation processes. © 2025 Elsevier Ltd
Citation - Scopus: 0
Women's Representation in Top-Management Positions in the Energy Sector: a Case Study of Türkiye and Nigeria's Petroleum Industries
(Elsevier Ltd, 2025) Oyejide, O.S.
Women's representation in top-management positions remains a critical issue in various sectors, including the energy industry, where gender equity has historically been limited. This study critically examines the representation of women in top-management roles within the petroleum sectors of Türkiye and Nigeria, two countries with contrasting gender equity landscapes. In particular, the study asks: “To what extent are women in Nigeria and Türkiye's petroleum industry underrepresented, and what factors contribute to the underrepresentation of women in management positions in the countries' petroleum sectors? The research utilized quantitative and qualitative data, focusing on female employment statistics and qualitative claims on diversity, equity, and inclusion from company websites regarding their diversity and inclusion efforts. Data was collected from five leading oil and gas companies in Türkiye and six in Nigeria, covering 2018–2023. The findings reveal that while some companies in Nigeria show promising strides toward gender balance, many Turkish companies continue to exhibit substantial gender gaps, particularly in senior management. These disparities reflect broader global trends and underscore the need for targeted interventions. Additionally, the theme from the qualitative analysis hints at a potential gap between rhetoric and practice. The analyses show that the diversity, equity, and inclusion statements do not necessarily translate into measurable outcomes. Consequently, the study concludes with actionable suggestions for policymakers to enhance female representation and to implement policies that challenge existing stereotypes and support career advancement for women in the industry. © 2025 Elsevier Ltd
Citation - Scopus: 0
Biocontrol Potential of Vibrio Maritimus Chitinase: Heterologous Expression and Insecticidal Activity Against Acanthoscelides Obtectus
(Elsevier B.V., 2025) Dikbaş, N.; Tülek, A.; Uçar, S.; Alim,; Servili, B.; Paçal, N.; Ercisli, S.
In this study, the chitinase gene from the marine bacterium Vibrio maritimus was heterologously expressed in Escherichia coli, purified via affinity chromatography and tested for its insecticidal activity against the storage pest Acanthoscelides obtectus. The recombinant VmChiA protein exhibited a molecular mass of ∼60 kDa, with optimum activity observed at pH 6.0 and 40 °C. Enzyme kinetic analysis revealed a Km value of 0.042 mM, Vmax of 17.48 μmol min−1, kcat of 1.75 min−1 and catalytic efficiency of 41.61 mM−1 min−1, respectively. Furthermore, a dose of 40 U mL−1 of recombinant VmChiA showed similar efficacy to malathion insecticide against A. obtectus, with 100 % mortality in both treatments. LC50 and LC90 values of VmChiA were 13.95 U mL−1 and 27.66 U mL−1, respectively. Furthermore, the three-dimensional structure of the catalytic site of VmChiA was modeled. Molecular dynamics simulation technique was used to explore and analyze the dynamics and interactions. A salt bridge (GLU274-ARG296) in the α + β domain was observed as a critical feature facilitating substrate (GlcNAc)2 binding and enzymatic activity. These findings demonstrate that recombinant VmChiA possesses potent insecticidal properties, highlighting its potential as a bio-based, eco-friendly alternative for managing significant agricultural pests. © 2025 Elsevier B.V.
Citation - Scopus: 0
Mistake Rumination Scale: Psychometric Properties for the Turkish Version
(Association for Clinical Psychology Research, 2025) Altan-Atalay, A.; Kaya-Kızılöz, B.; Özdemir, A.B.
The Mistake Rumination Scale (MRS) was developed to evaluate the inclination to engage in mistake rumination (MR), a reaction to perceived mistakes in the form of intense, repetitive negative thoughts. The present study aimed to investigate the psychometric qualities of the Turkish version of the MRS in 2 studies. Data were collected from 214 participants (118 females) between the ages of 18 and 56 (M = 33.45, SD = 11.82) through measures of MR, repetitive negative thinking, per-fectionism, procrastination, depression, and anxiety. The findings confirmed the original factor structure and indicated adequate reliability, convergent, and incremental validity. In the second study, the criterion-related validity of the MRS was tested using an experimental design. Participants (127 individuals aged between 18 and 28) were asked to imagine committing a series of mistakes or a regular event. Results provided support for the criterion-related validity of the MRS. In conclusion, MRS can be utilized to assess MR in Turkish individuals. © 2025, Association for Clinical Psychology Research. All rights reserved.
Citation - Scopus: 0
Depth3DSketch: Freehand Sketching Out of Arm's Reach in Virtual Reality
(Association for Computing Machinery, 2025) Bashar, M.R.; Amini, M.; Stuerzlinger, W.; Sarac, M.; Pfeuffer, K.; Machuca, M.D.B.; Batmaz, A.U.
Due to the increasing availability and popularity of virtual reality (VR) systems, 3D sketching applications have also boomed. Most of these applications focus on peripersonal sketching, e.g., within arm’s reach. Yet, sketching in larger scenes requires users to walk around the virtual environment while sketching or to change the sketch scale repeatedly. This paper presents Depth3DSketch, a 3D sketching technique that allows users to sketch objects up to 2.5 m away with a freehand sketching technique. Users can select the sketching depth with three interaction methods: using the joystick on a single controller, the intersection from two controllers, or the intersection from the controller ray and the user’s gaze. We compared these interaction methods in a user study. Results show that users preferred the joystick to select visual depth, but there was no difference in user accuracy or sketching time between the three methods. © 2025 Copyright held by the owner/author(s).
Citation - Scopus: 0
Decoding Rhythmic Complexity: a Nonlinear Dynamics Approach Via Visibility Graphs for Classifying Asymmetrical Rhythmic Frameworks of Turkish Classical Music
(Elsevier Inc., 2025) Mirza, F.K.; Baykaş, T.; Hekimoğlu, M.; Pekcan, Ö.; Tunçay, G.P.
The non-isochronous, hierarchical rhythmic cycles (usuls) of Turkish Classical Music (TCM) exhibit emergent temporal structures that challenge conventional rhythm analysis based on metrical regularity. To address this challenge, this study presents a complexity-oriented framework for usul classification, grounded in nonlinear time series analysis and network-based representations. Rhythmic signals are processed through energy envelope extraction, diffusion entropy analysis, and spectral transformations to capture multiscale temporal dynamics. Visibility graphs (VGs) are constructed from these representations to encode underlying structural complexity and temporal dependencies. Features derived from VG adjacency matrices serve as complexity-sensitive descriptors and enable high-accuracy classification (0.99) across 40 usul classes and 628 compositions. Energy envelope-derived graphs provide the most discriminative information, highlighting the importance of amplitude modulation in encoding rhythmic structure. Beyond classification, the analysis reveals self-organizing patterns and signatures of complexity, such as quasi-periodicity, scale-dependent variability, and entropy saturation, suggesting that usuls function as adaptive, nonlinear systems rather than metrically constrained patterns. The topological features extracted from the resulting graphs align with theoretical constructs from complexity science, such as modularity and long-range temporal correlations. This positions usul as an exemplary case for studying structured temporal complexity in cultural artifacts through the lens of dynamical systems. These findings contribute to computational rhythm analysis by demonstrating the efficacy of complexity measures in characterizing culturally specific rhythmic systems. © 2025
Citation - Scopus: 0
Stock Price Forecasting Through Symbolic Dynamics and State Transition Graphs With a Convolutional Recurrent Neural Network Architecture
(Springer Science and Business Media Deutschland GmbH, 2025) Mirza, F.K.; Pekcan, Ö.; Hekimoğlu, M.; Baykaş, T.
Accurate stock price forecasting remains a critical challenge in financial analytics due to volatile market conditions, non-stationary dynamics, and abrupt regime shifts that often defy traditional modeling techniques. This study proposes a comprehensive framework for stock price forecasting that integrates symbolic dynamics, graph-based state representations, and deep learning. By converting continuous-valued stock prices into discrete symbolic states representing amplitude and trend information, the method constructs transition matrices capturing probabilistic relationships within financial time series. These transition matrices are then processed by a convolutional recurrent neural network (CRNN), in which convolutional layers isolate local spatial dependencies in the symbolic-state domain, while recurrent LSTM layers capture multi-scale temporal dynamics extending across multiple time horizons. Experimental evaluations are conducted over prediction horizons of 1 day, 10 days, and 100 days, spanning pre-COVID, COVID, and post-COVID market regimes. The results indicate that while longer prediction horizons naturally incur greater forecasting uncertainty due to compounding variability, the integration of symbolic-state preprocessing with deep temporal modeling demonstrates significant robustness in handling non-stationary financial environments. During the stable pre-COVID period, the proposed methodology achieves reductions in mean squared error (MSE) of up to 98% relative to the volatile COVID phase, highlighting its capability to effectively leverage well-defined market patterns in stable economic conditions. Furthermore, the model consistently delivers competitive forecasting performance across all prediction horizons and market regimes. Collectively, these findings emphasize the potential of symbolic-state-based deep learning architectures as a viable pathway to address the complexity and volatility characteristic of modern financial markets. © The Author(s) 2025.
Citation - Scopus: 0
Electro-Pneumatic Assessment of Airflow in a Double-Piston Cylinder Ventilator
(Institute of Electrical and Electronics Engineers Inc., 2024) Oyejide, A.J.; Atoyebi, E.O.; Ugo, H.C.; Chukwudi, F.O.; Akindel, G.; Adeyemi, A.A.
Mechanical ventilation is crucial for patients with severe respiratory distress. While single piston-actuated ventilation is popular, this study presents an electro-pneumatic assessment of airflow in a coupled-double-acting piston ventilator (DPDACV) using simulation results from FluidSIM. The DPDACV design aims to leverage a dual-piston mechanism for enhanced stability and performance in tidal volume delivery. Simulations conducted over 2, 10, 30, and 60 seconds revealed that the DPDACV provides more consistent volume delivery, stable flow rates, and relatively higher, more stable pressure levels compared to single-piston systems. These findings suggest that the DPDACV can offer improved ventilation efficiency and patient safety, contributing valuable insights to the field of mechanical ventilation. © 2024 IEEE.
Citation - WoS: 0
Citation - Scopus: 0
A Real-World Case Study Towards Net Zero: Ev Charger and Heat Pump Integration in End-User Residential Distribution Networks
(Mdpi, 2025) Tun, Thet Paing; Ceylan, Oguzhan; Pisica, Ioana
The electrification of energy systems is essential for carbon reduction and sustainable energy goals. However, current network asset ratings and the poor thermal efficiency of older buildings pose significant challenges. This study evaluates the impact of heat pump and electric vehicle (EV) penetration on a UK residential distribution network, considering the highest coincident electricity demand and worst weather conditions recorded over the past decade. The power flow calculation, based on Python, is performed using the pandapower library, leveraging the actual distribution network structure of the Hillingdon area by incorporating recent smart meter data from a distribution system operator alongside historical weather data from the past decade. Based on the outcome of power flow calculation, the transformer loadings and voltage levels were assessed for existing and projected heat pump and EV adoption rates, in line with national policy targets. Findings highlight that varied consumer density and diverse usage patterns significantly influence upgrade requirements.
Citation - WoS: 0
Citation - Scopus: 0
Acculturation Strategies of International Higher Education Students in Türkiye: the Role of Social Support, Cultural Capital, Self-Esteem, General Trust, and General Self-Efficacy
(Springer, 2025) Ergin-Kocaturk, Hatice; Tekel, Esra; Su, Ahmet; Kocaturk, Metin; Karadag, Engin
Understanding the factors influencing acculturation strategies among international students cannot be overstated, as successful adaptation is crucial for academic success and overall well-being. Although extensive research has explored these dynamics in various contexts, a notable gap remains in the literature on international students in T & uuml;rkiye. This study aimed to investigate the effects of social support, cultural and economic capital, self-esteem, general trust, and general self-efficacy on the acculturation strategies of international higher-education students in T & uuml;rkiye. Utilizing data from 3,554 international students, various scales and questionnaires were employed, including the Acculturation Strategies Scale, Cultural Capital Questionnaire, Economic Capital Questionnaire, Self-Esteem Scale, General Confidence Scale, General Self-Efficacy Scale, and Social Support Questionnaire. The collected data were analyzed using correlation and multiple regression analyses. The results revealed significant relationships between the examined factors and acculturation strategies adopted by international students. These findings highlight the crucial roles of social support, cultural capital, and psychological attributes in shaping how international students adapt to new cultural environments. The implications of these results underscore the importance of targeted support programs to enhance international students' acculturation experiences and overall well-being in T & uuml;rkiye's higher education context.
Citation - WoS: 0
Citation - Scopus: 0
Examining the Role of Dark and Light Triad Traits on Sociosexuality
(Routledge Journals, Taylor & Francis Ltd, 2025) Urganci, Betul; Sevi, Baris; Dogruyol, Burak; Sakman, Ezgi
Sociosexual orientation-the tendency toward casual sex, is associated with dispositional components of personality such as higher scores of Dark Triad traits (narcissism, Machiavellianism, and psychopathy). Yet, it remains unknown which specific Dark Triad traits and Light Triad traits (Kantianism, Humanism, and Faith in Humanity) predict sociosexuality and its dimensions while controlling for the others. In the current study, using an online community sample (N = 308), we examined the links between Dark Triad traits, Light Triad traits, overall sociosexuality, and sociosexuality dimensions (attitude, behavior, desire). Using hierarchical regression, we found that only psychopathy emerged as the predictor of behavior, desire, attitude dimensions, and sociosexuality total score. This effect held when controlling for age, sex, relationship status, the other two Dark personality traits, and the Light Triad. Results suggest that individuals high on psychopathy have a greater tendency toward uncommitted relationships.
Citation - WoS: 0
Citation - Scopus: 0
The Associations Between Deviation From the Balanced Time Perspective and Depression and Anxiety: The Moderator Role of Mindfulness in a Two-Wave Study
(Sage Publications inc, 2025) Altan-Atalay, Ayse; Ranjbar, Hamed Abdollahpour; Altintas, Seda
Deviation from the balanced time perspective (DBTP) refers to difficulties in switching between different time frames in a flexible way by considering the situational demands. DBTP is associated with higher levels of depression and anxiety. Mindfulness acts as a protective mechanism against depression and anxiety. The current study examined the moderator role of mindfulness in the relationship between DBTP and psychological distress. The participants were 243 university students (53.09% women) between ages 18 and 29 (M = 19.88, SD = 1.42) who answered self-report measures of time perspective, mindfulness, anxiety, and depression at two-time points with a five-week time interval. The results showed that the interaction between DBTP and mindfulness measured at time one could prospectively predict both anxiety and depression measured at time two. Mindfulness plays a significant moderating role in the relationship between DBTP and anxiety and depression. The data indicate that for individuals with low levels of DBTP, those with higher mindfulness experience significantly lower anxiety and depression compared to those with lower mindfulness. However, as DBTP increases, anxiety and depression levels in the high mindfulness group rise significantly, ultimately converging with those observed in the low mindfulness group. This indicates that while high mindfulness offers buffering effects against anxiety and depression, these effects diminish under increased DBTP.
Citation - WoS: 0
Citation - Scopus: 0
Neural Signatures of Depression: Classifying Drug-Naive Mdd Patients With Time- and Frequency-Domain Eeg Features During Emotional Processing
(Iop Publishing Ltd, 2025) Sutcubasi, Bernis; Balli, Tugce; Metin, Baris; Tulay, Emine Elif
Accurate classification of major depressive disorder (MDD) remains a significant challenge, particularly because of the confounding effect of medications. This study bridges this gap by focusing on the classification of drug-na & iuml;ve individuals diagnosed with MDD and healthy controls (HCs) using electroencephalogram (EEG) data recorded during emotional processing tasks. This study involved 14 HCs and 14 drug-na & iuml;ve individuals diagnosed with MDD (aged 18-31, 12+ years of education, 12 F/2 M). The participants were presented with positive, neutral, and negative images collected from the International Affective Picture System. The mean power amplitudes of event-related potentials (ERP), including the P200, P300, early, middle, and late components of the late positive potential (LPP), were computed, along with band power features, and used as features for classifiers. A support vector machine model was employed for classification to evaluate the individual contributions of ERP components and band power features and explore the combined effects of ERP components and band power features within themselves. The alpha band power achieved the highest individual classification accuracy among the band power features for negative stimuli (92.86%). The late LPP component was the most discriminative ERP component for positive stimuli, yielding an accuracy rate of 89.29%. Combined analysis of the band power features exhibited high accuracy for both positive and negative stimuli (92.86% each). When the ERP components were combined, the classifier achieved the highest accuracy of 89.29% for both negative and neutral stimuli. Our findings suggest that alpha band power and LPP responses to negative and positive stimuli, respectively, can be used to detect MDD. The comparable performance of individual features to that of the combined feature sets indicates their strength as indicators of emotional processing in MDD. These findings provide valuable insights into the development of more reliable diagnostic tools and treatment monitoring strategies that focus on emotional processing in MDD.
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Citation - Scopus: 0
Design and Synthesis of Thiosemicarbazides and 1,2,4-Triazoles Derived From Ibuprofen as Potential Metap (Type II) Inhibitors
(Elsevier Ireland Ltd, 2025) Yilmaz, Ozgur; Biliz, Yagmur; Ayan, Sumeyra; Cevik, Ozge; Karahasanoglu, Mufide; Cotuker, Reyhan; Kucukguzel, S. . Guniz
In the present study, a range of novel thiosemicarbazides 4a-i and 1,2,4-triazoles 5a-i derived from ibuprofen, were synthesized. Structural elucidation of these synthesized compounds was performed utilizing a variety of spectroscopic methods, including FTIR, 1H NMR, 13C NMR and HR-MS. The synthesized compounds were tested for cytotoxicity in five different cancer cell lines (cervical cancer (HeLa), human breast cancer (MCF-7), human gastric adenocarcinoma (MKN-45), human metastatic prostate cancer (PC3) and human glioblastoma (U87)). The compounds were compared with healthy cells (NIH-3T3) and the most effective compounds were determined by means of the selectivity index. Thiosemicarbazides derived form ibuprofen 4i and 4d showed anticancer activity, while 1,2,4-triazoles derived form ibuprofen 5b, 5c, 5d, 5e, 5h, 5g showed anticancer activity in HeLa, MCF-7, MKN-45, PC3 and U87 cells. To test the stability of the protein-drug complexes all 18 compounds 4a-i and 5a-i were docked into the active site of the MetAP2 enzyme In general, computational inhibition constants values were correlated with the experimental values. The dynamic behavior of MetAP2-inhibitor complexes was analyzed using all atoms Molecular Dynamic (MD) simulations for 200 ns duration. MD revealed that the drugs bind in the active center of MetAP2 with stable RMSD and RMSF. In conclusion, in-silico results and in-vitro studies suggests that thiosemicarbazides and 1,2,4-triazoles derived from ibuprofen may be novel anticancer drug candidates for treating cervical, breast, prostate, gastric and glioblastoma. Compounds provided induction of apoptotic proteins in the cell by inhibiting MetAP2 enzyme. Furthermore, the potential antioxidant activities of the compounds were evaluated using the 2,2-Diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity assay. Among the compounds tested, 4a, 4b, 4e, 4f, 4h, and 4i exhibited values closely resembling the DPPH activity of the standards.
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Citation - Scopus: 0
High-Speed and Area-Efficient Arithmetic and Logic Unit Architecture Using Quantum-Dot Cellular Automata for Digital Signal Processing
(Elsevier, 2025) Zohaib, Muhammad; Navimipour, Nima Jafari; Aydemir, Mehmet Timur; Ahmadpour, Seyed-Sajad
Signal processing has significantly influenced our lives in many domains, including telecommunications, education, healthcare, industry, and security. The efficiency of signal processing heavily relies on the Arithmetic and Logic Unit (ALU), which stands as an essential hardware component. In addition, ALU is a fundamental part of a central processing unit (CPU), leading to fundamental operations inside the processor. However, the growing demand for small, robust hardware systems has led researchers to create nano-electronic technologies under consideration. One of the leading technologies in this field is Quantum-dot cellular automata (QCA), which demonstrates promising value as a possible alternative to complementary metal-oxide-semiconductor (CMOS) designs since it enables compact circuit designs with minimal power consumption. The existing QCA-based ALU designs face limitations in cell count density together with high occupied area and high delay, which reduces their performance for real-time signal processing. This research presents a 1-bit ALU through a QCA-optimized approach for DSP applications. QCADesigner is used to validate and verify all proposed designs. Results show a statistically significant improvement in cell count reduction of 46.84 % and a total occupied area of 64.28 % lower than the most advanced version published to date.
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Does Attention Sharing Support Attention Focusing? Investigating the Link Between Infants' Sustained Attention and Joint Attention With Caregivers
(Elsevier Science inc, 2025) Uzundag, Berna A.
Sustained attention in infancy is a known predictor of executive functions, self-regulation, and language. This study investigated the relationship between 9-to 16-month-old infants' sustained attention and joint attention in mother-infant dyads. Data were collected from 98 infants (M(SD) = 11.8(1.3) months) and their mothers. Results showed that joint attention during mother-infant play significantly predicted sustained attention during solo play, after accounting for infant age and socioeconomic status. These cross-sectional findings suggest that joint attention may play a role in supporting sustained attention, though the directionality of this relationship warrants further longitudinal investigation.
Citation - Scopus: 0
Luxury Tourism
(Springer Nature, 2025) Kozak, Metin; Kozak, M.; Advertising
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Feedback-Based Quantum Algorithm for Constrained Optimization Problems
(Springer Science and Business Media Deutschland GmbH, 2025) Karabacak, Özkan; Karabacak, Ö.; Wisniewski, R.; Mechatronics Engineering
The feedback-based algorithm for quantum optimization (FALQON) has recently been proposed to find ground states of Hamiltonians and solve quadratic unconstrained binary optimization problems. This paper efficiently generalizes FALQON to tackle quadratic constrained binary optimization (QCBO) problems. For this purpose, we introduce a new operator that encodes the problem’s solution as its ground state. Using control theory, we design a quantum control system such that the state converges to the ground state of this operator. When applied to the QCBO problem, we show that our proposed algorithm saves computational resources by reducing the depth of the quantum circuit and can perform better than FALQON. The effectiveness of our proposed algorithm is further illustrated through numerical simulations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
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Scholars
(Springer Nature, 2025) Kozak, Metin; Advertising

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