Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Department: search.filters.department.İzmir Institute of Technology. Computer EngineeringWoS Q: search.filters.wosQuartile.N/A

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Now showing 1 - 10 of 214
  • Conference Object
    Citation - Scopus: 1
    Applying Weighted Graph Embeddings To Turkish Metaphor Detection
    (Institute of Electrical and Electronics Engineers Inc., 2024) İnan, Emrah
    Metaphor 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, Selma
    Chain 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: 11
    An Analysis of Large Language Models and Langchain in Mathematics Education
    (Association for Computing Machinery, 2023) Soygazi,F.; Oğuz, Damla
    The 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.
  • Article
    Citation - Scopus: 3
    Development of Chrono-Spectral Gold Nanoparticle Growth Based Plasmonic Biosensor Platform
    (Elsevier, 2024) Sözmen, Alper Baran; Elveren, Beste; Erdoğan, Duygu; Mezgil, Bahadır; Baştanlar, Yalın; Yıldız, Ümit Hakan; Arslan Yıldız, Ahu
    Plasmonic sensor platforms are designed for rapid, label-free, and real-time detection and they excel as the next generation biosensors. However, current methods such as Surface Plasmon Resonance require expertise and well-equipped laboratory facilities. Simpler methods such as Localized Surface Plasmon Resonance (LSPR) overcome those limitations, though they lack sensitivity. Hence, sensitivity enhancement plays a crucial role in the future of plasmonic sensor platforms. Herein, a refractive index (RI) sensitivity enhancement methodology is reported utilizing growth of gold nanoparticles (GNPs) on solid support and it is backed up with artificial neural network (ANN) analysis. Sensor platform fabrication was initiated with GNP immobilization onto solid support; immobilized GNPs were then used as seeds for chrono-spectral growth, which was carried out using NH2OH at varied incubation times. The response to RI change of the platform was investigated with varied concentrations of sucrose and ethanol. The detection of bacteria E.coli BL21 was carried out for validation as a model microorganism and results showed that detection was possible at 102 CFU/ml. The data acquired by spectrophotometric measurements were analyzed by ANN and bacteria classification with percentage error rates near 0% was achieved. The proposed LSPR-based, label-free sensor application proved that the developed methodology promises utile sensitivity enhancement potential for similar sensor platforms. © 2024 The Author(s)
  • Conference Object
    Kurt saldırıları için sentetik irislerde örnek seçilimi
    (IEEE, 2023) Akdeniz, Eyüp Kaan; Erdoğmuş, Nesli
    In 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.
  • Book Part
    Citation - Scopus: 2
    Dementia Detection With Deep Networks Using Multi-Modal Image Data
    (CRC Press, 2023) Yiğit, Altuğ; Işık, Zerrin; Baştanlar, Yalın
    Neurodegenerative diseases give rise to irreversible neural damage in the brain. By the time it is diagnosed, the disease may have progressed. Although there is no complete treatment for many types of neurodegenerative diseases, by detecting the disease in its early stages, treatments can be applied to relieve some symptoms or prevent disease progression. Many invasive and non-invasive methods are employed for the diagnosis of dementia. Computer-assisted diagnostic systems make the diagnosis based on volumetric features (structural or functional) or some two-dimensional brain perspectives obtained from a single image modality. This chapter firstly introduces a broad review of multi-modal imaging approaches proposed for dementia diagnosis. Then it presents deep neural networks, which extract structural and functional features from multi-modal imaging data, are employed to diagnose Alzheimer’s and mild cognitive impairments. While MRI scans are safer than most types of scans and provide structural information about the human body, PET scans provide information about functional activities in the brain. Thus, the setup has been designed to make experiments using both MRI and FDG-PET scans. Performances of multi-modal models were compared with single-modal solutions. The multi-modal solution showed superiority over single-modals due to the advantage of focusing on assorted features. © 2023 selection and editorial matter, Jyotismita Chaki; individual chapters, the contributors.
  • Conference Object
    Citation - Scopus: 1
    A Lightweight and Energy Efficient Secrecy Outage Probability-Based Friendly Jamming
    (IEEE, 2023) Yaman, Okan; Ayav, Tolga; Erten, Yusuf Murat
    Third 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.
  • Data Paper
    Citation - WoS: 15
    Citation - Scopus: 20
    Database Covering the Prayer Movements Which Were Not Available Previously
    (Nature Publishing Group, 2023) Mihçin, Şenay; Şahin, Ahmet Mert; Yılmaz, Mehmet; Alpkaya, Alican Tuncay; Tuna, Merve; Akdeniz, Sevinç; Can, Nuray Korkmaz; Tosun, Aliye; Şahin, Serap
    Lower body implants are designed according to the boundary conditions of gait data and tested against. However, due to diversity in cultural backgrounds, religious rituals might cause different ranges of motion and different loading patterns. Especially in the Eastern part of the world, diverse Activities of Daily Living (ADL) consist of salat, yoga rituals, and different style sitting postures. A database covering these diverse activities of the Eastern world is non-existent. This study focuses on data collection protocol and the creation of an online database of previously excluded ADL activities, targeting 200 healthy subjects via Qualisys and IMU motion capture systems, and force plates, from West and Middle East Asian populations with a special focus on the lower body joints. The current version of the database covers 50 volunteers for 13 different activities. The tasks are defined and listed in a table to create a database to search based on age, gender, BMI, type of activity, and motion capture system. The collected data is to be used for designing implants to allow these sorts of activities to be performed.
  • Conference Object
    Citation - Scopus: 3
    A Novel Countermeasure for Selective Forwarding Attacks in Iot Networks
    (IEEE, 2022) Yaman, Okan; Sokat, Barış; Ayav, Tolga; Erten, Yusuf Murat
    As the Internet of Things (IoT) devices become more widespread there are rising public concerns about whether or not IoT devices and their services are secure. One of the major threats they face is selective forwarding attacks performed by malicious nodes. Although packets can be lost inherently due to network conditions, malicious nodes, such as those performing blackhole attacks, may deliberately drop some, but not all of them. Therefore, distinguishing these nodes from legitimate ones is not so easy. This study has proposed a lightweight countermeasure to deal with this kind of attack in IoT networks, using the standard IPv6 Routing Protocol for Low Power and Lossy Networks (RPL). The mechanism is based on Mobile Trusted Nodes (MTNs). For the given threat model, we showed that our model has robust detection accuracy and brings no additional overhead to the network. © 2022 IEEE.
  • Editorial
    Message From the Symposium Chairs: Isssr 2022
    (IEEE, 2022) Wong, W. Eric; Wotawa, Franz; Zheng, Liwei; Tuğlular, Tuğkan
    Security, safety, and reliability are the three most important attributes of a system. This is especially the case for mission-critical and life-threatening systems. As the complexity of many systems continues to grow, ensuring security, safety, and reliability has become very critical. Not only does existing technology and tool support need to be enhanced, but we also need new strategies and approaches to satisfy more strict requirements on system security, safety, and reliability. In response to this challenge, the Steering Committee of ISSSR has decided to change its conference name from International Symposium on System and Software Reliability to International Symposium on System Security, Safety, and Reliability. The acronym ISSSR is still the same, but the full name has been slightly modified to emphasize the importance of security, safety, and reliability of many systems.