Arama Sonuçları

Listeleniyor 1 - 10 / 10
  • Yayın
    A short proof of the size of edge-extremal chordal graphs
    (Mahmut Akyiğit, 2022-08-30) Shalom, Mordechai
    Blair et. al. [3] have recently determined the maximum number of edges of a chordal graph with a maximum degree less than d and the matching number at most ? by exhibiting a family of chordal graphs achieving this bound. We provide simple proof of their result.
  • Yayın
    A comparison of Auto Train Brain neurofeedback rewarding interfaces in terms of efficacy
    (Acıbadem Mehmet Ali Aydınlar Üniversitesi, 2023-01-01) Eroğlu, Günet
    Background/aim: Auto Train Brain is a mobile app that was specifically developed for dyslexic children to increase their reading speed and reading comprehension. In the original mobile app, only one unique neurofeedback user interface provided visually and audibly rewarding feedback to the subject with a red-green colored arrow on the screen. Later, new modules are added to the app with the end-users requests. These are the “youtube” video-based interface and “Spotify” auditory-based interface. In this research, we have compared the efficacy of the neurofeedback rewarding interfaces. Materials and methods: The experiment group consists of 20 dyslexic children aged 7-to 10 (15 males, 5 females) who were randomly assigned to one rewarding interface and used it at home for more than six months. Results: The result indicates that though the “youtube” interface is liked most by the participants, the arrow-based simple neurofeedback interface reduces theta brain waves more than other rewarding schemes. On the other hand, “youtube” and “Spotify” based interfaces increase Beta band powers more than the arrow interfaces in the cortex. The ”Spotify” user interface improves the fast brain waves more on the temporal lobes (T7 and T8) as the feedback given was only auditory. Conclusion: The results indicate that the relevant neurofeedback rewarding interface should be chosen based on the dyslexic child’s specific condition.
  • Yayın
    Evaluating the English-Turkish parallel treebank for machine translation
    (TÜBİTAK, 2022-01-19) Görgün, Onur; Yıldız, Olcay Taner
    This study extends our initial efforts in building an English-Turkish parallel treebank corpus for statistical machine translation tasks. We manually generated parallel trees for about 17K sentences selected from the Penn Treebank corpus. English sentences vary in length: 15 to 50 tokens including punctuation. We constrained the translation of trees by (i) reordering of leaf nodes based on suffixation rules in Turkish, and (ii) gloss replacement. We aim to mimic human annotator's behavior in real translation task. In order to fill the morphological and syntactic gap between languages, we do morphological annotation and disambiguation. We also apply our heuristics by creating Nokia English-Turkish Treebank (NTB) to address technical document translation tasks. NTB also includes 8.3K sentences in varying lengths. We validate the corpus both extrinsically and intrinsically, and report our evaluation results regarding perplexity analysis and translation task results. Results prove that our heuristics yield promising results in terms of perplexity and are suitable for translation tasks in terms of BLEU scores.
  • Yayın
    Türkçe için biçimbirim temelli bir bileşen grameri yaklaşımı
    (Beykoz Üniversitesi, 2024-12-26) Özenç, Berke; Solak, Ercan
    Dilin modellenmesi, dil çalışmalarında önemli bir temel olarak yer alır. Farklı modelleme yöntemleri, farklı diller için uyarlanabilir olsa da bu uyarlamalar, hedef dil için her zaman yeterli olmayabilir. Bu durumdan en çok biçimbirimsel açıdan zengin diller etkilenir. Böyle bir dil için hazırlanacak model kurgulanırken dilin evrensel olarak ortak olan özelliklerinin yanı sıra, dilin kendine özgü özelliklerine odaklanılmalıdır. Bu makalede, bağımlı biçimbirim bakımından zengin bir görünüm sunan Türkçe ele alınarak uyarlanan gramer sunulmuştur. Çalışmada açıklanan gramer temelleri geleneksel üretici gramer yönteminden uyarlanmıştır. Bununla birlikte, sunulan gramer, biçimbirimleri söz dizimi elemanı olarak geleneksel söz dizimi elemanlarıyla birlikte, söz dizimine olan etkilerini ele almasıyla ve kullanılan özel bileşen kümesiyle geleneksel üretici gramer yöntemden ayrılır. Geleneksel yöntemden farklı olarak önerilen gramerde, tümce çözümlemesine sözcüklerden değil, biçimbirim elemanları olan sözcük gövdeleri, ekler, biçimbirimler ve bu gibi elemanların oluşturduğu gruplardan başlanır. Buna ek olarak Türkçenin söz dizimsel ve birimbirimsel özelliklerine göre kurgulanan bir bileşen kümesi de sunulmuştur. Sunulan bileşen kümesi, tümce, ad öbeği, eylem öbeği, belirteç öbeği gibi geleneksel sözdizimsel bileşenleri, öbek gövdesi olarak adlandırılan ara bir yapıyı ve çoğul eki, durum eki, zaman çekimi eki gibi, biçimbirimleri veya biçimbirim gruplarını temsil eden bileşenleri içerir.
  • Yayın
    Analyst-aware incident assignment in security operations centers: a multi-factor prioritization and optimization framework
    (Uğur Şen, 2025-07-15) Kılınçdemir, Eyüp Can; Çeliktaş, Barış
    In this paper, we propose a comprehensive and scalable framework for incident assignment and prioritization in Security Operations Centers (SOCs). The proposed model aims to optimize SOC workflows by addressing key operational challenges such as analyst fatigue, alert overload, and inconsistent incident handling. Our framework evaluates each incident using a multi-factor scoring model that incorporates incident severity, service-level agreement (SLA) urgency, incident type, asset criticality, threat intelligence indicators, frequency of repetition, and a correlation score derived from historical incident data. We formalize this evaluation through a set of mathematical functions that compute a dynamic incident score and derive incident complexity. In parallel, analyst profiles are quantified using Analyst Load Factor (ALF) and Experience Match Factor (EMF), two novel metrics that account for both workload distribution and expertise alignment. The incident–analyst matching process is expressed as a constrained optimization problem, where the final assignment score is computed by balancing incident priority with analyst suitability. This formulation enables automated, real-time assignment of incidents to the most appropriate analysts, while ensuring both operational fairness and triage precision. The model is validated using algorithmic pseudocode, scoring tables, and a simplified case study, which illustrates the realworld applicability and decision logic of the framework in large-scale SOC environments. To validate the framework under real-world conditions, an empirical case study was conducted using 10 attack scenarios from the CICIDS2017 benchmark dataset. Overall, our contributions lie in the formalization of a dual-factor analyst scoring scheme and the integration of contextual incident features into an adaptive, rule-based assignment framework. To further strengthen operational value, future work will explore adaptive weighting mechanisms and integration with real-time SIEM pipelines. Additionally, feedback loops and supervised learning models will be incorporated to continuously refine analyst-incident matching and prioritization.
  • Yayın
    Text-to-SQL: a methodical review of challenges and models
    (TÜBİTAK, 2024-05-20) Kanburoğlu, Ali Buğra; Tek, Faik Boray
    This survey focuses on Text-to-SQL, automated translation of natural language queries into SQL queries. Initially, we describe the problem and its main challenges. Then, by following the PRISMA systematic review methodology, we survey the existing Text-to-SQL review papers in the literature. We apply the same method to extract proposed Text-to-SQL models and classify them with respect to used evaluation metrics and benchmarks. We highlight the accuracies achieved by various models on Text-to-SQL datasets and discuss execution-guided evaluation strategies. We present insights into model training times and implementations of different models. We also explore the availability of Text-to-SQL datasets in non-English languages. Additionally, we focus on large language model (LLM) based approaches for the Text-to-SQL task, where we examine LLM-based studies in the literature and subsequently evaluate the LLMs on the cross-domain Spider dataset. Finally, we conclude with a discussion of future directions for Text-to-SQL research, identifying potential areas of improvement and advancements in this field.
  • Yayın
    Evaluation of password hashing competition finalists: performance, security, compliance mapping, and post-quantum readiness
    (Karyay Karadeniz Yayımcılık Ve Organizasyon Ticaret Limited Şirketi, 2025-11-15) Ulutaş, Erdem; Çeliktaş, Barış
    Password hashes and key derivation functions (KDFs) are central to authentication and cryptographic security schemes crafted to defend user credentials from brute-force attacks and unauthorized access. Password hashing algorithms, for example PBKDF2, bcrypt, or scrypt, are very popular today, but are lacking in the face of modern hardware acceleration, parallel processing, and advanced cryptanalytic attacks. To contest these shortcomings, the Password Hashing Competition (PHC) was started in 2013 and had 22 candidates for functions for hashing passwords. After thorough evaluation, 9 finalists were selected based on how secure, fast, memory-friendly, flexible, and efficient these functions were. This study evaluates the nine PHC finalists—Argon2, battcrypt, Catena, Lyra2, MAKWA, Parallel, POMELO, Pufferfish, and yescrypt—through survey findings and performance benchmarks. We have evaluated these functions from an architectural standpoint and studied their security features, memory hardness, performance tradeoff, and practical usage. We also compare these finalists with traditional password hashing functions to highlight their advantages and limitations. We also investigate the post-quantum assumption for password hashing – the effectiveness of these functions against quantum assaults, their position in a new cryptography set, and the role of peppering as an additional security measure. In addition, we perform a comprehensive compliance mapping of the PHC finalists against major global standards and regulations such as NIST SP 800-63B, OWASP ASVS, PCI DSS, GDPR, KVKK, and ISO/IEC 27001, highlighting their practical suitability for secure deployment in regulated environments. Finally, we provide usage recommendations for these functions for web authentication, KDFs, and embedded platforms. This paper serves as a reference for researchers, developers, and security engineers, while also introducing a complianceaware, post-quantum-ready framework that bridges cryptographic design with regulatory and deployment needs.
  • Yayın
    An analysis of enterprise-level cloud transition barriers within the Technology-Organization-Environment (TOE) framework and strategic solution proposals
    (Gazi Üniversitesi, 2025-10-31) Çeliktaş, Barış; Birgin, Berat; Tok, Mevlüt Serkan
    Enterprise-level transitions to cloud service providers are frequently delayed or disrupted due to the multilayered nature of technical, organizational, and legal barriers. This study classifies these obstacles within the TechnologyOrganization-Environment (TOE) theoretical framework and provides a comprehensive analysis. Methodologically, a triangulated data source approach was adopted, combining systematic literature review, the 2025 Flexera Cloud Report, and Cloud Adoption Framework (CAF) documentation from major providers such as AWS, Azure, and Google Cloud. Findings indicate that technological barriers particularly cryptographic complexity, cost unpredictability, and weak system integration, are the most dominant. These barriers were visually modeled, and the structural interdependencies among five core cryptographic components (key management, secure computation, algorithm selection, access control, and regulatory compliance) were illustrated through a flow diagram. By aligning FinOps and compliance-oriented solution strategies with the TOE framework, the study offers a strategic roadmap for decision-makers and cloud architects planning cloud adoption. It links conceptual models to applied practices, providing structured support for organizations seeking to mature their cloud strategy.
  • Yayın
    A multi-criteria evaluation of cybersecurity incident management frameworks: integrating AHP, CMMI and SWOT
    (Karyay Karadeniz Yayımcılık Ve Organizasyon Ticaret Limited Şirketi, 2026-01-15) Ağar, Hasan Çağlar; Çeliktaş, Barış
    With the growing complexity and frequency of cybersecurity incidents, the selection of an appropriate incident management framework has emerged as a strategic imperative and a nontrivial decision-making problem for organizations operating across diverse sectors. This study presents a multi-dimensional evaluation of four globally recognized frameworks and standards—ISO 27035, NIST 800-61, ITIL v4, and PCI DSS—to determine their effectiveness across 10 rigorously selected key performance parameters. The initial stage of the study involved the identification of 20 preliminary parameters through expert input and literature synthesis. These were then evaluated by 70 cybersecurity professionals using a hybrid decision-making model combining Likert scale scoring, standard deviation filtering, CV score, Z-score normalization and the Analytic Hierarchy Process (AHP) for pairwise comparisons. The top 10 key parameters were derived based on calculated priority weights. To assess each framework, we applied the Capability Maturity Model Integration (CMMI) and visualized results via radar charts and heatmaps, offering comparative insights into operational maturity. Additionally, SWOT analysis was conducted to examine strategic positioning and identify opportunities for improvement. The outcomes not only provide a practical benchmarking guide for practitioners but also introduce a replicable, evidence-based methodology for academic and industry adoption. This work offers a novel and structured lens to evaluate incident management maturity, addressing the pressing need for strategic alignment, automation integration, and adaptive resilience in cybersecurity operations.