Computer Engineering / Bilgisayar Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/10
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Conference Object Enhancing genomic data sharing with blockchain-enabled dynamic consent in beacon V2(Springernature, 2024) Binokay, Leman; Celik, Hamit Mervan; Gurdal, Gultekin; Ayav, Tolga; Tuglular, Tugkan; Oktay, Yavuz; Karakulah, GokhanConference Object Citation - Scopus: 1Applying Weighted Graph Embeddings To Turkish Metaphor Detection(Institute of Electrical and Electronics Engineers Inc., 2024) İnan, EmrahMetaphor is a common literary mechanism that allows abstract concepts to be conceptualised using more concrete terminology. Existing methods rely on either end-to-end models or hand-crafted pre-processing steps. Generating well-defined training datasets for supervised models is a time-consuming operation for this type of problem. There is also a lack of pre-processing steps for resource-poor natural languages. In this study, we propose an approach for detecting Turkish metaphorical concepts. Initially, we collect non-literal concepts including their meaning and reference sentences by employing a Turkish dictionary. Secondly, we generate a graph by discovering super-sense relations between sample texts including target metaphorical expressions in Turkish WordNet. We also compute weights for relations based on the path closeness and word occurrences. Finally, we classify the texts by leveraging a weighted graph embedding model. The evaluation setup indicates that the proposed approach reaches the best F1 and Gmean scores of 0.83 and 0.68 for the generated test sets when we use feature vector representations of the Node2Vec model as the input of the logistic regression for detecting metaphors in Turkish texts. © 2024 IEEE.Conference Object A News Chain Evaluation Methodology Along With a Lattice-Based Approach for News Chain Construction(Association for Computational Linguistics (ACL), 2017) Toprak, Mustafa; Özkahraman,Ö.; Tekir, SelmaChain construction is an important requirement for understanding news and establishing the context. A news chain can be defined as a coherent set of articles that explains an event or a story. There's a lack of well-established methods in this area. In this work, we propose a methodology to evaluate the "goodness" of a given news chain and implement a concept latticebased news chain construction method by Hossain et al. The methodology part is vital as it directly affects the growth of research in this area. Our proposed methodology consists of collected news chains from different studies and two "goodness" metrics, minedge and dispersion coefficient respectively. We assess the utility of the lattice-based news chain construction method by our proposed methodology. © EMNLP 2017.All right reserved.Conference Object Citation - Scopus: 11An Analysis of Large Language Models and Langchain in Mathematics Education(Association for Computing Machinery, 2023) Soygazi,F.; Oğuz, DamlaThe development of large language models (LLMs) has led to the consideration of new approaches, particularly in education. Word problems, especially in subjects like mathematics, and the need to solve these problems by collectively addressing specific stages of reasoning, have raised the question of whether LLMs can be successful in this area as well. In our study, we conducted analyses by asking mathematics questions especially related to word problems using ChatGPT, which is based on the latest language models like Generative Pretrained Transformer (GPT). Additionally, we compared the correct and incorrect answers by posing the same questions to LLMMathChain, a mathematics-specific LLM based on the latest language models like LangChain. It was observed that the answers obtained were more successful with ChatGPT (GPT 3.5), particularly in the field of mathematics. However, both language models were found to be below expectations, particularly in word problems, and suggestions for improvement were provided. © 2023 ACM.Conference Object Size Measurement and Effort Estimation in Microservicebased Projects: Results From Pakistan(CEUR-WS, 2023) Soylu, Görkem Kılınç; Ünlü, Hüseyin; Ahmad, Isra Shafique; Demirörs, OnurDuring the last decade, microservice-based software architecture has been a common design paradigm in the industry and has been successfully utilized by organizations. Microservice-based software architecture, specifically in the form of reactive systems, has substantial differences from the more conventional design paradigms, such as the object-oriented paradigm. The architecture moved away from being data-driven and evolved into a behavior-oriented structure. The usage of a single database is replaced by the structures in which each microservice is developed independently and has its own database. Therefore, adaptation demands software organizations to transform their culture. In this study, we aimed to get an insight into how Pakistani software organizations perform size measurement and effort estimation in their software projects which embrace the microservice-based software architecture paradigm. For this purpose, we surveyed 49 Pakistani participants from different agile organizations over different roles and domains to collect information on their experience in microservice-based projects. Our results reveal that although Pakistani organizations face challenges, they continue using familiar subjective size measurement and effort estimation approaches that they have used for traditional architectures. © 2023 Copyright for this paper by its authors.Conference Object Citation - Scopus: 1Computing a Parametric Reveals Relation for Bounded Equal-Conflict Petri Nets(Springer, 2024) Adobbati, Federica; Bernardinello, Luca; Kılınç Soylu, Görkem; Pomello, LuciaIn a distributed system, in which an action can be either “hidden” or “observable”, an unwanted information flow might arise when occurrences of observable actions give information about occurrences of hidden actions. A collection of relations, i.e. reveals and its variants, is used to model such information flow among transitions of a Petri net. This paper recalls the reveals relations defined in [3], and proposes an algorithm to compute them on bounded equal-conflict PT systems, using a smaller structure than the one defined in [3]. © 2024, The Author(s), under exclusive license to Springer-Verlag GmbH, DE, part of Springer Nature.Conference Object Citation - Scopus: 1Monocular Vision-Based Prediction of Cut-In Manoeuvres With Lstm Networks(Springer, 2023) Nalçakan, Yağız; Baştanlar, YalınAdvanced driver assistance and automated driving systems should be capable of predicting and avoiding dangerous situations. In this paper, we first discuss the importance of predicting dangerous lane changes and provide its description as a machine learning problem. After summarizing the previous work, we propose a method to predict potentially dangerous lane changes (cut-ins) of the vehicles in front. We follow a computer vision-based approach that only employs a single in-vehicle RGB camera, and we classify the target vehicle’s maneuver based on the recent video frames. Our algorithm consists of a CNN-based vehicle detection and tracking step and an LSTM-based maneuver classification step. It is computationally efficient compared to other vision-based methods since it exploits a small number of features for the classification step rather than feeding CNNs with RGB frames. We evaluated our approach on a publicly available driving dataset and a lane change detection dataset. We obtained 0.9585 accuracy with the side-aware two-class (cut-in vs. lane-pass) classification model. Experiment results also reveal that our approach outperforms state-of-the-art approaches when used for lane change detection. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.Conference Object Kurt saldırıları için sentetik irislerde örnek seçilimi(IEEE, 2023) Akdeniz, Eyüp Kaan; Erdoğmuş, NesliIn this study, samples with higher potential to succeed in wolf attacks are picked among synthetically generated iris images, and the composed subset is shown to pose a more significant threat toward an iris recognition system backed by a Presentation Attack Detection (PAD) module with respect to randomly selected samples. Iris images generated by Deep Convolutional Generative Adversarial Networks (DCGAN) are firstly filtered by rejection sampling on PAD score distribution of real iris image PAD scores. Next, the probability of zero success in all attack attempts is calculated for each synthetic iris image, using real iris images in the training set, and match and non-match score distributions are calculated on those. Synthetic images with the lowest probabilities of zero success are included in the final set. Our hypothesis that this set would be more successful in wolf attacks is tested by comparing its spoofing performances with randomly selected sample sets.Conference Object Citation - Scopus: 1A Lightweight and Energy Efficient Secrecy Outage Probability-Based Friendly Jamming(IEEE, 2023) Yaman, Okan; Ayav, Tolga; Erten, Yusuf MuratThird parties and legitimate entities can reach and process users' private data through most wireless networks. However, attackers such as intruders and eavesdroppers may also try to exploit this property in communication. Hence, wireless networks are intrinsically more vulnerable to threats, unlike their wired alternatives. Cryptographic techniques are the conventional approaches to deal with that weakness. Nevertheless, they still need to meet the requirements of contemporary technologies, including IoT nodes with energy and processing power constraints. In that respect, friendly jamming (FJ) is one of the encouraging countermeasures to overcome the mentioned susceptibility since it has an energy-efficient and computation-friendly nature. However, that promising approach brings another challenge, applicability. Although various models exist against this issue, a lightweight scheme compliant with novel technologies is needed. Hence, we propose a more straightforward FJ model evaluated on cellular network-based simulations in this study. Moreover, introducing a lightweight secrecy outage probability definition increases robustness and energy efficiency. © 2023 IEEE.Conference Object Citation - WoS: 2Citation - Scopus: 2Effort Prediction With Limited Data: a Case Study for Data Warehouse Projects(IEEE, 2022) Unlu, Huseyin; Yildiz, Ali; Demirors, OnurOrganizations may create a sustainable competitive advantage against competitors by using data warehouse systems with which they can assess the current status of their operations at any moment. They can analyze trends and connections using up-to-date data. However, data warehouse projects tend to fail more often than other projects as it can be tough to estimate the effort required to build a data warehouse system. Functional size measurement is one of the methods used as an input for estimating the amount of work in a software project. In this study, we formed a measurement basis for DWH projects in an organization based on the COSMIC Functional Size Measurement Method. We mapped COSMIC rules on two different architectures used for DWH projects in the organization and measured the size of the projects. We calculated the productivity of the projects and compared them with the organization's previous projects and DWH projects in the ISBSG repository. We could not create an organization-wide effort estimation model as we had a limited number of projects. As an alternative, we evaluated the success of effort estimation using DWH projects in the ISBSG repository. We also reported the challenges we faced during the size measurement process.