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Privacy-preserving federated machine learning on FAIR health data: A real-world application Sınacı, Ali Anıl; Gencturk, Mert; Alvarez-Romero, Celia; Laleci Erturkmen, Gokce Banu; Martinez-Garcia, Alicia; Escalona-Cuaresma, María José; Parra-Calderon, Carlos Luis (2024-12-01) Objective: This paper introduces a privacy-preserving federated machine learning (ML) architecture built upon Findable, Accessible, Interoperable, and Reusable (FAIR) health data. It aims to devise an architecture for exec...
Constructing ensembles for hate speech detection Kucukkaya, Izzet Emre; Toraman, Çağrı (2024-09-13) Hate speech against individuals and groups with certain demographics is a major issue in social media. Supervised models for hate speech detection mostly utilize labeled data collections to understand textual semantics. Ho...
Relative distances approach for multi-traveling salesmen problem Ergüven, Emre; Polat, Faruk (2024-09-01)
Diversity-aware strategies for static index pruning Yigit-Sert, Sevgi; Altıngövde, İsmail Sengör; Ulusoy, Özgür (2024-09-01) Static index pruning aims to remove redundant parts of an index to reduce the file size and query processing time. In this paper, we focus on the impact of index pruning on the topical diversity of query results obtained o...
BF-BigGraph: An efficient subgraph isomorphism approach using machine learning for big graph databases Yazıcı, Adnan; Taşkomaz, Ezgi (2024-09-01) Graph databases are flexible NoSQL databases used to efficiently store and query complex and big data. One of the most difficult problems in graph databases is the problem of subgraph isomorphism, which involves finding a ...
Drug Repurposing Approach to Identify Candidate Drug Molecules for Hepatocellular Carcinoma Baser, Tugce; Rifaioğlu, Ahmet Süreyya; Atalay, Mehmet Volkan; Atalay, Rengül (2024-09-01) Hepatocellular carcinoma (HCC) is the most prevalent primary liver cancer, with a high mortality rate due to the limited therapeutic options. Systemic drug treatments improve the patient’s life expectancy by only a few mon...
UNCERTAINTY EVALUATION USING LAW OF PROPAGATION AND MONTE CARLO SIMULATION METHODS WITH THE AUTORFPOWER MEASUREMENT SOFTWARE Danacı, Erkan; Kartal Doğan, Aliye; Çiçek, Engin Can; Çetinkaya, Anıl; Kaya, Muhammed Çağrı; Oğuztüzün, Mehmet Halit S.; Tünay, Gülsün (2024-09-01) RF power measurement is essential in RF and microwave metrology. For reliable and accurate power measurement, automatic measurement is preferred. A software application in C#, named AutoRFPower, was developed for automatic...
3D geometric kernel computation in polygon mesh structures Asiler, Merve; Sahillioğlu, Yusuf (2024-08-01) This paper introduces a novel approach to compute the geometric kernel of a polygon mesh embedded in 3D. The geometric kernel defines the set of points inside or on the shape's boundary, ensuring visibility of the entire s...
CALPAGAN: Calorimetry for Particles Using Generative Adversarial Networks Simsek, Ebru; IŞILDAK, Bora; Dogru, Anil; Aydogan, Reyhan; Bayrak, Burak; Ertekin Bolelli, Şeyda (2024-08-01) In this study, a novel approach is demonstrated for converting calorimeter images from fast simulations to those akin to comprehensive full simulations, utilizing conditional Generative Adversarial Networks (GANs). The con...
Potential-based reward shaping using state–space segmentation for efficiency in reinforcement learning Bal, Melis İlayda; Aydın, Hüseyin; İyigün, Cem; Polat, Faruk (2024-08-01) Reinforcement Learning (RL) algorithms encounter slow learning in environments with sparse explicit reward structures due to the limited feedback available on the agent's behavior. This problem is exacerbated particularly ...
Uncertainty Calculation as a Service: Integrating Cloud-Based Microservices for Enhanced Calibration and DCC Generation Çetinkaya, Anıl; Kaya, M. Cagri; Danaci, Erkan; Oğuztüzün, Mehmet Halit S. (2024-08-01) The calibration industry is renowned for its diverse and sophisticated equipment and complex processes, which necessitate innovative solutions to keep pace with rapidly advancing technology. This paper introduces an enhanc...
Shadow-aware terrain classification: advancing hyperspectral image sensing through generative adversarial networks and correlated sample synthesis Peker, Ali Gokalp; Yuksel, Seniha Esen; Cinbiş, Ramazan Gökberk; Cetin, Yasemin Yardimci (2024-07-01) In recent years, the utilization of hyperspectral sensors for remote sensing has marked a profound advancement due to the success of machine learning techniques. Nevertheless, difficulties still exist, especially in locati...
Path guiding for wavefront path tracing: A memory efficient approach for GPU path tracers Yalçıner, Bora; Akyüz, Ahmet Oğuz (2024-06-01) We propose a path-guiding algorithm to be incorporated into the wavefront style of path tracers (WFPTs). As WFPTs are primarily implemented on graphics processing units (GPUs), the proposed method aims to leverage the capa...
Field teams coordination for earthquake-damaged distribution system energization Işık, İlker; Aydın Göl, Ebru (2024-05-01) The re-energization of electrical distribution systems in a post-disaster scenario is of grave importance as most modern infrastructure systems rely heavily on the presence of electricity. This paper introduces a method to...
Design tactics for tailoring transformer architectures to cybersecurity challenges Avcı, Çiğdem; Tekinerdogan, Bedir; Catal, Cagatay (2024-04-24) In the rapidly evolving landscape of cyber threats, effective defense strategies are crucial for safeguarding sensitive information and critical systems. Deep learning methods, notably the Transformer architecture, have sh...
Faster MIL-based Subgoal Identification for Reinforcement Learning by Tuning Fewer Hyperparameters Sunel, Saim; Çilden, Erkin; Polat, Faruk (2024-4-20) Various methods have been proposed in the literature for identifying subgoals in discrete reinforcement learning (RL) tasks. Once subgoals are discovered, task decomposition methods can be employed to improve the learning ...
SegIns: A simple extension to instance discrimination task for better localization learning Baydar, Melih; Akbaş, Emre (2024-04-01) Recent self-supervised learning methods, where instance discrimination task is a fundamental way of pretraining convolutional neural networks (CNN), excel in transfer learning performance. Even though instance discriminati...
Targeted marketing on social media: utilizing text analysis to create personalized landing pages Çetinkaya, Yusuf Mucahit; Külah, Emre; Toroslu, İsmail Hakkı; Davulcu, Hasan (2024-04-01) The widespread use of social media has rendered it a critical arena for online marketing strategies. To optimize conversion rates, the landing pages must effectively respond to a visitor segment’s pain points that they nee...
GEMLIDS-MIOT: A Green Effective Machine Learning Intrusion Detection System based on Federated Learning for Medical IoT network security hardening Ioannou, Iacovos; Nagaradjane, Prabagarane; Angın, Pelin; Balasubramanian, Palaniappan; Kavitha, Karthick Jeyagopal; Murugan, Palani; Vassiliou, Vasos (2024-03-15) The increasing use of Internet of Things (IoT) gadgets in a daily rate has heightened security apprehension, particularly within the healthcare sector. In order to prevent the unauthorized disclosure of sensitive data, it ...
GEMLIDS-MIOT: A Green Effective Machine Learning Intrusion Detection System based on Federated Learning for Medical IoT network security hardening Ioannou, Iacovos; Nagaradjane, Prabagarane; Angın, Pelin; Balasubramanian, Palaniappan; Kavitha, Karthick Jeyagopal; Murugan, Palani; Vassiliou, Vasos (2024-03-01)

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