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Yayın Construction of the nodal conductance matrix of a planar resistive grid and derivation of the analytical expressions of its eigenvalues and eigenvectors using the Kronecker Product and Sum(IEEE, 2016-07-09) Tavşanoğlu, Ahmet VedatThis paper considers the task of constructing an (MxN+1)-node rectangular planar resistive grid as: first forming two (MxN+1)-node planar sub-grids; one made up of M of (N+1)-node horizontal, and the other of N of (M+1)-node vertical linear resistive grids, then joining their corresponding nodes. By doing so it is shown that the nodal conductance matrices GH and GV of the two sub-grids can be expressed as the Kronecker products GH = I-M circle times G(N), G(V) = G(M)circle times I-N, and G of the resultant planar grid as the Kronecker sum G = G(N circle plus) G(M), where G(M) and I-M are, respectively, the nodal conductance matrix of a linear resistive grid and the identity matrix, both of size M. Moreover, since the analytical expressions for the eigenvalues and eigenvectors of G(M) - which is a symmetric tridiagonal matrix- are well known, this approach enables the derivation of the analytical expressions of the eigenvalues and eigenvectors of G(H), G(V) and G in terms of those of G(M) and G(N), thereby drastically simplifying their computation and rendering the use of any matrix-inversion-based method unnecessary in the solution of nodal equations of very large grids.Yayın Kübit-Kütrit kuantum haberleşme sistemleri için negatiflik ve dolanıklığın göreceli entropisi ölçütlerinin analizi(IEEE, 2015-06-19) Erol, Volkan; Özaydın, Fatih; Altıntaş, Azmi AliKuantum Bilgi Teorisi ve Kuantum Hesaplama konuları geleceğin bilgisayar teknolojisi olarak nitelendirilen ve çok yüksek hızlarda işlem yapacak olması öngörülen Kuantum Bilgisayarlarının teorik temelini oluşturan oldukça sıcak çalışma alanlarıdır. Kuantum Bilgisayarlarında bilginin taşınacağı birim kübit olarak nitelendirilse de, bazı problemler için bu birimlerin üç seviye (trinary) olan kütritlerce kurgulanabileceği teorik olarak gösterilmiştir. Bu çalışma kapsamında, kübit-kütrit Kuantum Haberleşme Sistemlerinin dolanıklıklığını ölçmek için kullanılan Negatiflik ve Dolanıklığın Göreceli Entropisi ölçütlerinin karşılaştırmalı analizi yapılmıştır. Bu bağlamda, rastgele türetilmiş 1000 adet kübit-kütrit sistem durumlarının adı geçen ölçütleri hesaplanmış ve bu değerler sistem durumlarının sıralanması amacıyla karşılaştırılmıştır. Yapılan analiz kapsamında sistem durumlarının sıralaması problemi açısından oldukça ilginç sonuçlar gözlemlenmiştir.Yayın Cross-layer ransomware detection framework for SDN using HMM, LSTM, and Bayesian inference(Institute of Electrical and Electronics Engineers Inc., 2025-08-28) Serter, Cemal Emre; Çeliktaş, BarışRansomware continues to pose a serious threat to endpoint computers as well as network systems, especially in Software Defined Networks (SDN) environments where programmability and centralized control offer novel attack surfaces. In this paper, a cross-layer detection model for ransomware is introduced that integrates host-based behavioral modeling using Hidden Markov Models (HMM), anomaly detection at flow level using Long Short-Term Memory (LSTM) networks, and probabilistic fusion through Bayesian inference. By correlating host and SDN layer anomalies, the system enhances early-stage detection and reduces false positives. A variational Bayesian approximation technique is utilized for decision score stabilization under ambiguous conditions. The model is evaluated with new ransomware datasets and obtains a range between 97.5%-99.92% F1-score across three benchmark datasets with less than 50 ms latency for detection. The hybrid framework gives a promising direction for real-time threat detection in resilient programmable networks.Yayın Secure and interpretable dyslexia detection using homomorphic encryption and SHAP-based explanations(Institute of Electrical and Electronics Engineers Inc., 2025-10-25) Harb, Mhd Raja Abou; Çeliktaş, Barış; Eroğlu, GünetProtecting sensitive healthcare data during machine learning inference is critical, particularly in cloud-based environments. This study addresses the privacy and interpretability challenges in dyslexia detection using Quantitative EEG (QEEG) data. We propose a privacy-preserving framework utilizing Homomorphic Encryption (HE) to securely perform inference with an Artificial Neural Network (ANN). Due to the incompatibility of non-linear activation functions with encrypted arithmetic, we employ a dedicated approximation strategy. To ensure model interpretability without compromising privacy, SHapley Additive exPlanations (SHAP) are computed homomorphically and decrypted client-side. Experimental evaluations demonstrate that the encrypted inference achieves an accuracy of 90.03% and an AUC of 0.8218, reflecting only minor performance degradation compared to plaintext inference. SHAP value comparisons (Spearman correlation = 0.59) validate the reliability of the encrypted explanations. These results confirm that integrating privacy-preserving and explainable AI approaches is feasible for secure, ethical, and compliant healthcare deployments.
