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Yayın Maximum likelihood blind channel estimation for space-time coding systems(Hindawi Publishing Corporation, 2002-05) Çırpan, Hakan Ali; Panayırcı, Erdal; Çekli, ErdinçSophisticated signal processing techniques have to be developed for capacity enhancement of future wireless communication systems, In recent years, space-time coding is proposed to provide significant capacity gains over the traditional communication systems in fading wireless channels. Space-time codes are obtained by combining channel coding, modulation, transmit diversity, and optional receive diversity in order to provide diversity at the receiver and coding gain without sacrificing the bandwidth. In this paper, we consider the problem of blind estimation of space-time coded signals along with the channel parameters. Both conditional and unconditional maximum likelihood approaches are developed and iterative solutions are proposed. The conditional maximum likelihood algorithm is based on iterative least squares with projection whereas the unconditional maximum likelihood approach is developed by means of finite state Markov process modelling. The performance analysis issues of the proposed methods are studied. Finally, some simulation results are presented.Yayın Evolutionary route to diploidy and sex(National Academy of Sciences, 2001-11-20) Tüzel, Erkan; Sevim, Volkan; Erzan, AyşeBy using a bit-string model of evolution, we find a successful route to diploidy and sex in simple organisms. Allowing the sexually reproducing diploid individuals to also perform mitosis, as they do in a haploid-diploid cycle, leads to the complete takeover of the population by sexual diploids. This mechanism is so robust that even the accidental conversion and pairing of only two diploids give rise to a sexual population.Yayın Learning to rank(Işık Üniversitesi, 2011-04-28) Kılıç, Yasin Ozan; Yıldız, Olcay Taner; Işık Üniversitesi, Fen Bilimleri Enstitüsü, Bilgisayar Mühendisliği Yüksek Lisans ProgramıThe web has grown so rapidly in the last decade and it brought the need for proper ranking. Learning to rank (LTR) is the collection of machine learning technolo- gies that construct a ranking model using training data. The model can sort documents according to their degrees of relevance or preference. In this thesis, we introduce LTR technologies and divide them into three ap- proaches: the point-wise, pair-wise and list-wise. We review the theoritical aspects of each category and introduce the representative algorithms of them. We also introduce a new LTR method GRwC which uses classifîcation and graph algorithms. We reduce the ranking problem to a two class classifîcation problem and apply KNN algorithm on a modified LTR dataset. We compared it with the popular ranking algorithm RankingSVM. Experiments on the well-known ranking datasets show that our proposed method gives slightly worse results than RankingSVM.Yayın Relocating sensor nodes to maximize cumulative connected coverage in wireless sensor networks(Molecular Diversity Preservation Int, 2008-04) Coşkun, VedatIn order to extend the availability of the wireless sensor network and to extract maximum possible information from the surveillance area, proper usage of the power capacity of the sensor nodes is important. Our work describes a dynamic relocation algorithm called MaxNetLife, which is mainly based on utilizing the remaining power of individual sensor nodes as well as properly relocating sensor nodes so that all sensor nodes can transmit the data they sense to the sink. Hence, the algorithm maximizes total collected information from the surveillance area before the possible death of the sensor network by increasing cumulative connected coverage parameter of the network. A deterministic approach is used to deploy sensor nodes into the sensor field where Hexagonal Grid positioning is used to address and locate each sensor node. Sensor nodes those are not planned to be actively used in the close future in a specific cell are preemptively relocated to the cells those will be in need of additional sensor nodes to improve cumulative connected coverage of the network. MaxNetLife algorithm also includes the details of the relocation activities, which include preemptive migration of the redundant nodes to the cells before any coverage hole occurs because of death of a sensor node. Relocation Model, Data Aggregation Model, and Energy model of the algorithm are studied in detail. MaxNetLife algorithm is proved to be effective, scalable, and applicable through simulations.Yayın Disinformation, social media, and populism : emotional politics and polarization dynamics in Turkey’s 2023 presidential elections(Işık Üniversitesi, Lisansüstü Eğitim Enstitüsü, 2024-07-01) Avcı Çeken, İnci Secem; Kayhan Pusane, Özlem; Işık Üniversitesi, Lisansüstü Eğitim Enstitüsü, Uluslararası İlişkiler Yüksek Lisans Programı; Işık University, School of Graduate Studies, Master’s Program in International RelationsThis thesis explores the relationship between populist discourse and social media algorithms, examining their role in exacerbating political polarization. Its primary aim is to identify the correlation between the use of populist rhetoric and the algorithms driving social media engagement, highlighting how this relationship fosters societal divisions and benefits both platforms and political entities. Using critical discourse analysis (CDA), the thesis analyzes X (formerly Twitter) posts shared by 2023 Turkish presidential election candidates Recep Tayyip Erdoğan and Kemal Kılıçdaroğlu. In the first round of the campaign, shared posts were analyzed between 06.05.2024 and 14.05.2024. A total of 173 posts, 108 by Erdoğan and 65 by Kılıçdaroğlu, were analyzed. The full texts of these posts were obtained from X's official website. The findings reveal that posts featuring emotionally charged and popülist discourse have garnered higher views and engagement in the run-up to the 2023 presidential elections. This analysis will help to understand the political polarization in Turkey. Social media algorithms shape social interaction by strengthening populist discourses. This suggests that social media algorithms, prioritizing emotionally charged content, unintentionally promote populism. The study concludes that the design of social media platforms increases divisive content, leading to a rise in populist rhetoric among political candidates and voters.Yayın Hierarchical secure key assignment scheme(Public Library of Science, 2026-02-18) Çeliktaş, Barış; Çelikbilek, İbrahim; Güzey, Süeda; Özdemir, EnverThis work presents a novel hierarchical key assignment mechanism for access control, designed to be computationally lightweight and optimized for digital environments with structured access policies. By leveraging orthogonal projection and distributing a basis to each group, it enables flexible and efficient left-to-right and top-down access structures. The scheme ensures that parent groups can derive the secret keys of their child groups while preventing unauthorized reverse access. It is resilient against collusion attacks and privilege escalation, offering robust key recovery and indistinguishability properties. Moreover, it guarantees strong key indistinguishability under adversarial models and facilitates a secure rekeying process without reliance on a trusted third party. To demonstrate practical efficiency, we provide a full analytical complexity evaluation showing that key derivation requires at most ∂(n2i ) operations, where ni is the dimension of the assigned subspace. For typical deployment parameters used in the experiments, the total key material per user remains compact (≈ 3,072 bits), significantly smaller than well-known post-quantum schemes such as Dilithium-5 (38,912 bits). The storage requirement scales linearly with the number of groups (ck+1 bases for c groups with at most k members), ensuring that even large hierarchies remain lightweight. Our evaluation further shows that selective rekeying affects only the descendants of the modified group, resulting in communication overhead of ∂(m′λ) bits, where m′ is the number of affected users and λ is the key length. These results collectively highlight the scheme’s scalability, low storage footprint, and suitability for large access hierarchies.
