CS-REG-NET: Termal ve optik görüntülerde çapraz-spektral çakıştırma için görsel-durum uzayı tabanlı özgözetimli ögrenmeli mimari

Modern deep models for multispectral image matching typically rely on large, supervised datasets, which can be prohibitively expensive. To overcome this challenge, we introduce CS-REG-NET, a self-supervised, detector-based framework that requires no external labels. Instead, it uses RIFT2 detector to generate pseudo-ground-truth keypoints. A VMamba encoder, pre-trained on a segmentation task, processes image pairs, while two output heads learn feature heatmaps and descriptors. CSREG-NET significantly outperforms existing methods, delivering superior keypoint detection and homography estimation. This real-time framework thus provides a robust, extensible solution for multispectral image matching.TÜBİTA

Drowsiness and fatigue recognition systems for connected vehicles, 6G and the EU AI Act

The European Union (EU) has passed binding rules mandating the integration of drowsiness and fatigue detection systems in vehicles. This paper explores the impact of future 6G standards in advancing such in-vehicle monitoring systems. The paper, from an interdisciplinary legal and technical perspective, specifically looks at the requirements for AI-based drowsiness and fatigue recognition that have been established by the EU AI Act (Regulation (EU) 2024/1689) passed in 2024. Moreover, it discusses the secure technical implementation of those requirements as well as societal and ethical challenges and impacts on that context.EU-COST Associatio

Developing a robust question and answer system for the Turkish language utilizing deep learning techniques

Research on open-ended question and answer systems faces several complex challenges within the domain of natural language processing, one of which is limited data availability. Although numerous studies have been conducted in widely spoken languages such as English, there is a notable scarcity of research in languages such as Turkish. In our preliminary investigation, we proposed a solution to address the data shortage issue in Turkish by translating the English SQuAD dataset into Turkish. Another challenge is the success of deep learning models that use large language models. We developed various baseline models using deep learning techniques on this newly created dataset and performed analyses from multiple perspectives. Deep learning models and large language models often present an architectural enigma for many researchers, so analyzing both the questions and the corresponding answer-bearing data is of utmost importance. We have shown that the structuralization and enrichment of the data contribute significantly to the success of the model. In our research, we devised an architecture that incorporates a structural transformation of data before use in model training. This approach enabled us to enhance the learning capacity of the system without altering the underlying closed-box architecture of the large language models and deep learning systems employed.Publisher versio

Integrating user needs with collection mapping: A definitive case study of Özyeği̇n University Library

In this study, the collection mapping method aims to evaluate the efficiency and adequacy of Özyeğin University Library's collection. Collection mapping has revealed to what extent the collections align with academic programs and changing user profiles. In recent years, user profiles in university libraries have undergone significant changes. This study aims to address this need while increasing the collection's visibility. Search in the LC web Classification. The Library of Congress Classification System is used in the collection mapping process. All classification numbers from A to Z were scanned using the LC Classification Search. Additionally, based on the faculties of Ozyeğin University, currency, and subject distribution were analysed, and strengths and areas for improvement were identified. The collection scope was limited to printed books and ebooks accessed through the ownership model. This study provides quantitative evidence on faculty course content, addressing user needs and academic expectations

The rubber tool illusion reveals how body image modifies body schema

Rubber hand illusion and tool-use paradigms have been extensively used to investigate body representation. Although both approaches rely on multisensory integration and external object incorporation, they are typically studied in isolation. Here, we introduce a novel paradigm that combines these methods to investigate whether perceptual modifications to body representation can induce motor changes, and vice versa. First, participants completed a tool-use task, actively using a short or long grabber tool to move cubes. When asked to point toward the forearm midpoint, only long tool users exhibited a distal shift, denoting an expansion in motor representation. Next, participants experienced the "rubber tool illusion" by passively holding the same tool while observing a rubber hand grasp an identical-looking tool. Notably, participants holding a short tool exhibited an expanded forearm representation when they observed a synchronously stroked long tool during illusion. Control experiments revealed that this effect depended on prior active tool use, embodiment of the observed rubber hand/tool, and a length mismatch between the held and observed tools. These findings reveal for the first time that motor representation of forearm length, a component of body schema, can be modulated by changes in body image. Public Significance Statement Over the past 25 years, research on how the brain represents the body has identified (at least) two distinct systems: body image, which governs conscious perception, and body schema, which guides unconscious movement. While body schema is known to influence body image, evidence for the reverse has been limited. This study provides new evidence that changes in body image can, in fact, alter body schema. By combining two classical methods for studying the embodiment of external objects-tool use and the rubber hand illusion-we found that merely perceiving a longer tool as part of the body had a similar effect on unconscious motor responses as actively using it. These findings challenge traditional views by showing that conscious body perception can shape unconscious movement.TÜBİTAK ; Bogazici Universit

From managers to employees to customers: The hidden toll of technology-induced workload

Retailers like Walmart, Target, and Home Depot have adopted Enterprise Resource Planning (ERP), leading to cost savings and efficient inventory and supply chain management. However, some companies, such as Nike, Waste Management, and Lidl, have faced challenges in transitioning from old to new systems, marked by changes in employee behavior, increased workload, and rising stress levels. Although extant literature focuses on employees' technology-induced workload, limited insight exists into whether and how such workload transpired by ERP is transmitted from managers to employees and the implications on customer service. To address these gaps, we draw on the conservation of resources theory, utilizing multilevel and multirespondent data collected during the initial phases of ERP implementation in retail stores. We find an indirect crossover effect of technology-induced workload from managers to employees, mediated through manager close monitoring, and an indirect effect of manager technology-induced workload on customer-directed sabotage, serially mediated by manager close monitoring and employee technology-induced workload. Furthermore, surface acting amplifies the impact of employee technology-induced workload on customer-directed sabotage. The study contributes to the discourse between technology-induced workload as a technology-related stressor and customer service, two areas that have evolved in parallel fashion without much cross-pollination

The Turkish Constitutional Court’s struggle with the European human rights law: An evaluation of the court’s case-law on the crime of ‘Defamation against the President’ in light of the jurisprudence of the European Court of Human Rights

This paper evaluates the Turkish Constitutional Court's norm review and individual application decisions concerning Article 299 of the Turkish Penal Code containing the crime of 'Defamation against the President'. The evaluation is conducted within the context of international human rights law, specifically on the European Court of Human Rights' jurisprudence on crimes that protect heads of state. While the Turkish Constitutional Court did not see an existential problem with Article 299, this paper argues that the Court overlooks significant issues regarding the provision's legality, purpose and proportionality. The view presented is that the Constitutional Court's open disregard of the European Court of Human Rights' judgments, even when these judgments specifically focus on the Turkish crime of 'Defamation against the President' is an example of judicial restraint in which the Court refrains from contesting the President's standing in the current political setting. According to this paper, such a stance cannot be taken, especially in light of the problems of the provision, and the Court should acknowledge that the only way to protect the freedom of expression effectively is to get rid of Article 299

A robust and gain-free direct model predictive control for nine-level t-type converter

Model predictive control (MPC) is a powerful strategy for tackling multiobjective control challenges, but it often involves a laborious process of tuning weighting factors. This article proposes a gain-free MPC method for a recently developed nine-level T-type converter (9L-T-2C), which offers advantages over traditional topologies, such as fewer components and improved efficiency. Drawing inspiration from Lyapunov's theory, this method avoids the use of weighting factors while effectively handling three targets, including current tracking, balancing of flying capacitors (FCs), and regulation of the neutral point (NP). Comparable with the traditional finite-control-set MPC (FCS-MPC), the proposed controller demonstrates high performance concerning all objectives. Additionally, it showcases superior resilience against model uncertainties when compared with the traditional approach. Experimental validation of the proposed MPC method is conducted in grid-connected operation under several conditions. The proposed method is subjected to a comparative analysis via the experimental implementation, where it is compared with a proportional-resonant (PR) controller and other state-of-the- art MPC methods. This analysis reveals the advantages of the proposed method, including eliminating the need for gains or weighting factors, improved robustness, and effective control of the FCs.Deutscher Akademischer Austauschdienst ; German Academic Exchange Service ; Technische Universität München ; Agencia Nacional de Investigación y Desarrollo ; Agencia Nacional de Investigación y Desarroll

Multiple item economic lot sizing problem with inventory dependent demand

We consider a multiple item Economic Lot Sizing problem where the demands for items depend on their stock quantities. The objective is to find a production plan such that the resulting stock levels (and hence demands) maximize total profit over a finite planning horizon. The single item version of this problem has been studied in the literature, and a polynomial time algorithm has been proposed when there are no bounds on production. It has also been proven that the single item version is NP-hard even when there are constant (i.e., time-invariant) finite capacities on production. We extend this single item model by considering multiple items and production capacities. We propose a Lagrangian relaxation method to find an initial solution to the problem. This solution is a hybrid solution obtained by combining two distinct solutions generated in the process of solving the Lagrangian dual problem. Starting with this initial solution, we then implement a Tabu Search algorithm to find better solutions. The performance of the proposed solution method is compared with the performance of a standard commercial software that works on a mixed integer programming formulation of the problem. We show that our solution approach finds better solutions within a predetermined time limit in general.TÜBİTAKPublisher versio

The differential effects of leader Food safety priority and ethical leadership on food safety promotive and prohibitive voices: A socially desirable responding theory perspective

Studies on impact of different leadership styles on the promotive and prohibitive forms of food safety voices are limited. Therefore, drawing on socially desirable responding theory, this study examined the differential effects of leader food safety priority and ethical leadership on food handlers’ promotive and prohibitive forms of food safety voices. We found that leader food safety priority and ethical leadership influence employee voice through different mechanisms. Moreover, the indirect impact of leader food safety priority on promotive voices was stronger, while ethical leadership had a stronger indirect effect on prohibitive voice. Finally, leader–member exchange strengthened the indirect effects of leadership antecedents on both forms of food safety voices. This study provides theoretical and practical contributions to food safety voice literature