Computer Engineering / Bilgisayar Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/10

Browse

Filters

2001 - 2009382010 - 2019602020 - 202328

Settings

Publication Index: search.filters.publicationIndex.WoSWoS Q: search.filters.wosQuartile.N/A

Search Results

Now showing 1 - 10 of 126
  • 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.
  • 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 - WoS: 2
    Citation - Scopus: 2
    Effort Prediction With Limited Data: a Case Study for Data Warehouse Projects
    (IEEE, 2022) Unlu, Huseyin; Yildiz, Ali; Demirors, Onur
    Organizations 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.
  • Conference Object
    Citation - WoS: 7
    Citation - Scopus: 12
    Utilization of Three Software Size Measures for Effort Estimation in Agile World: a Case Study
    (IEEE, 2022) Unlu, Huseyin; Hacaloglu, Tuna; Buber, Fatma; Berrak, Kivilcim; Leblebici, Onur; Demirors, Onur
    Functional size measurement (FSM) methods, by being systematic and repeatable, are beneficial in the early phases of the software life cycle for core project management activities such as effort, cost, and schedule estimation. However, in agile projects, requirements are kept minimal in the early phases and are detailed over time as the project progresses. This situation makes it challenging to identify measurement components of FSM methods from requirements in the early phases, hence complicates applying FSM in agile projects. In addition, the existing FSM methods are not fully compatible with today's architectural styles, which are evolving into event-driven decentralized structures. In this study, we present the results of a case study to compare the effectiveness of different size measures: functional -COSMIC Function Points (CFP)-, event-based - Event Points-, and code length-based - Line of Code (LOC)- on projects that were developed with agile methods and utilized a microservice- based architecture. For this purpose, we measured the size of the project and created effort estimation models based on three methods. It is found that the event-based method estimated effort with better accuracy than the CFP and LOC-based methods.
  • Conference Object
    Citation - WoS: 2
    Citation - Scopus: 3
    Adopting Heterogeneous Computing Modules: Experiences From a Touch Summer Workshop
    (Institute of Electrical and Electronics Engineers Inc., 2022) Bunde, D.P.; Ahmed, K.; Ayloo, S.; Brown-Gaines, T.; Fuentes, J.; Jatala, V.; Yeh, T.Y.
    We present efforts to encourage the adoption of modules for teaching heterogeneous parallel computing through a faculty development workshop. The workshop was held remotely using a novel format to exploit the advantages of a virtual format and mitigate its disadvantages. Adoption at a wide variety of institutions showed module effectiveness and also gathered feedback leading to several module improvements. We also report on the adoptions themselves, which show the importance of supporting adaptation of the modules for diverse settings. © 2022 IEEE.
  • Conference Object
    Citation - WoS: 2
    Citation - Scopus: 3
    Secure Iot Update Using Blockchain
    (IEEE, 2021) Kaptan, Melike; Tomur, Emrah; Ayav, Tolga; Erten, Yusuf Murat
    In this study a platform is devised to send automatic remote updates for embedded devices. In this scenario there are Original Equipment Manufacturers (OEMs), Software suppliers, blockchain nodes, Gateways and embedded devices. OEMs and software suppliers are there to keep their software on Inter Planetary File System (IPFS) and send the meta-data and hashes of their software to the blockchain nodes in order to keep this information distributed and ready to be requested and used. There are also gateways which are the members of the blockchain and the IPFS network. Gateways are responsible for asking for a specific update for specific devices from IPFS database using the meta-data kept on the blockchain, and they will send those hashed secure updates to the devices. In order to provide a traceable data keeping platform, gateway update operations are handled as transactions in a second blockchain network which is the clockchain of the gateways. The system was implemented as of the two separate blockchain networks and it has been shown that, despite the calculation overhead of the member devices, by separating the functions between the two blockchain networks a more reliable and secure platform can be achieved.
  • Conference Object
    Citation - Scopus: 5
    Nfa Based Regular Expression Matching on Fpga
    (IEEE, 2021) Sert, Kamil; Bazlamaçcı, Cüneyt
    String matching is about finding all occurrences of a string within a given text. String matching algorithms have important roles in various real world areas such as web and security applications. In this work, we are interested in solving regular expression matching hence a more general form of string matching problem targeting especially the field of network intrusion detection systems (NIDS). In our work, we enhance a non-deterministic finite automata (NFA) based method on FPGA considerably. We propose to use a matching structure that processes two consecutive characters instead of one in order to yield better memory utilization and provide a novel mapping of this new architecture onto FPGA. The amount of digital circuitry needed to represent the NFA is reduced due to having less number of states and less number of LUTs in the devised 2-character regex matching process. An evaluation study is performed using the well-known Snort rule set and a sizable performance improvement is demonstrated.
  • Conference Object
    Citation - Scopus: 2
    Workload Distribution on Heterogeneous Platforms
    (IEEE, 2021) Alasmar, Mahmoud; Bazlamaçcı, Cüneyt
    This paper targets the problem of finding an efficient distribution of a computational task on a heterogeneous computing platform. The heterogeneity of the processing elements arise due to differences in computation speed and memory capacity of the processors. We first consider using a discrete functional performance model that integrates processing speed and capacity of processing elements and then develop a mathematical model and propose a heuristic mapping algorithm for distributing a given total workload of size N on p processing elements such that the total computation time is minimized. Computational results show that the proposed method provides a significant improvement in reducing the computation time in comparison to equal distribution approach.
  • Conference Object
    Citation - WoS: 3
    Citation - Scopus: 3
    Assessment of Human-Robot Interaction Between Householders and Robotic Vacuum Cleaners
    (IEEE, 2022) Yapıcı, Nur Beril; Tuğlular, Tuğkan; Başoğlu, Ahmet Nuri
    The study presented in this paper investigates the application of the Hybrid Model, which is the combination of the two strategies of the Built-to-Order Model and the Dynamic Eco-strategy Explorer Model, to robotic vacuum cleaners. The Hybrid Model aims to switch the market power from seller-driven perception to buyer-driven one by creating an individual perspective from the eye of users rather than traditional customer segmentation. The human-centered approach established theoretically has been tested with a determined procedure that includes prototyping, testing, and evaluating the proposed customization system for robotic vacuum cleaners to increase the interaction degree with purchasers. In this case, robotic vacuum cleaners have been chosen to implement and assess the hypothesis. Firstly, the successful prototyping of the Hybrid Model requires well customer analysis and habits determination to build well-constructed and coherent interaction between the purchaser and the robot. We utilized a content analysis of robotic vacuum cleaners and elaborative, conventional interviews with early adopters and early majority of this technology in Turkey to establish credible scenarios and product options during the phases of the Hybrid Model practice. The results of the interview were discussed, and the evaluations have been reported.
  • Conference Object
    Citation - WoS: 7
    Citation - Scopus: 6
    Semantic Pose Verification for Outdoor Visual Localization With Self-Supervised Contrastive Learning
    (IEEE, 2022) Guerrero, Jose J.; Orhan, Semih; Baştanlar, Yalın
    Any city-scale visual localization system has to overcome long-term appearance changes, such as varying illumination conditions or seasonal changes between query and database images. Since semantic content is more robust to such changes, we exploit semantic information to improve visual localization. In our scenario, the database consists of gnomonic views generated from panoramic images (e.g. Google Street View) and query images are collected with a standard field-of-view camera at a different time. To improve localization, we check the semantic similarity between query and database images, which is not trivial since the position and viewpoint of the cameras do not exactly match. To learn similarity, we propose training a CNN in a self-supervised fashion with contrastive learning on a dataset of semantically segmented images. With experiments we showed that this semantic similarity estimation approach works better than measuring the similarity at pixel-level. Finally, we used the semantic similarity scores to verify the retrievals obtained by a state-of-the-art visual localization method and observed that contrastive learning-based pose verification increases top-1 recall value to 0.90 which corresponds to a 2% improvement.