In this project we built a simple IoT system where  clients gather fingerprint data and encrypt it with AES where encryption and decryption keys are public agreements generated via FourQ’s compressed  DH Key Exchange functions. To ensure high security the system performs a key exhange before every sensor data transfer.

Duris ve diğerlerinin makalesindeki bazı teoremlerin ve kanıtlarının üzerinden tekrar geçtim, kısa ve öz ifadelerini daha açık ve anlaşılır yapmaya çalıştım, önek-hassas dillerin boy artış hızı için bir alt sınır buldum. Küçük’ün tezindeki bir teorem için alternatif bir kanıt gösterdim. Küçük’ün tezindekine benzer, polinom öğüt gerektiren bir dil ailesi gösterdim. Tanınabilir iki dilin girdi uzunlukları özel bir şartı sağladığında bitiştirme dilinin de tanınabildiğini gösterdim. Soru-cevap fikrini genelleyip görselleştirmeye çalıştım, bunun için bir taayyün tablosu kullandım.

5G widely defines network slicing concept which aims to provide different and separate dedicated logical networks that can be customized to respective services. All slices under a cloud infrastructure are put together with their different requirements, e.g. bandwidth, latency. The purpose of this project is to provide a simulation suite for a network consisting of base stations and clients that possible scenarios of 5G can fit into and make analysis of different concepts easier. 

For the spell correction task, vocabulary based methods have been replaced with methods that take morphological and grammar rules into account. However, such tools are fairly immature, and, worse,  non-existent for many low resource languages. Checking only if a word is well-formed with respect to the morphological rules of a language may produce false negatives due to the ambiguity resulting from the presence of numerous homophonic words. In this work, we propose an approach to detect and correct the "de/da'' clitic errors in Turkish text.

Shot-text classification is a challenging topic in particular for Turkish text due to sparsity of distinguishing features and high dimensionality.

Most of the jobs related to Turkish tweets are done for sentiment analysis. This project aims to analyze and classify Turkish tweets on Twitter based on their topics which are decided as follow: polity, economics&investment, health, technology&informatics, history, literature&film, sports, education&personal growth and magazine.