Published in IEEE, 2022
In this study, a new message packet is defined for the 6TiSCH protocol and a mechanism is proposed for the nodes to recognize their neighbors before synchronization to the network. After running extensive tests, it is seen that the network synchronization time improved. Read more
Published in IEEE, 2022
In this paper; A new parent selection function is proposed for RPL running on top of IETF 6TiSCH protocol stack, which, for each node, takes into account the number of neighbors and the traffic through these routing nodes. Our tests showed a significant improvement in terms of the total number of parent switches and packet delivery rates. Read more
Published in IEEE, 2021
This study presents mechanisms for integrating low complexity smart antenna solutions into IETF 6TiSCH protocol with the aim of creating scalable and reliable industrial IoT networks. The solution defines extensions to MAC layer and scheduling mechanisms of IETF 6TiSCH protocol to enable its seamless integration with low complexity steerable smart antennas. Read more
Published in TUBITAK, 2019
Here the integration of a low-complexity directional antenna system with IETF 6TiSCH protocol is investigated with the aim of creating a 6TiSCH solution with higher spatial reuse. 6TiSCH nodes equipped with such smart directional antennas can schedule bandwidth resources not only in time and frequency domain but also in spatial (space) domain. Read more
Published in Karaelmas, 2017
Computer vision is a science that extracts useful information about an object from an observed image or image sequence automatically by analyzing in theoretical and algorithmic bases. Computer vision systems are increasingly used for detection of the surface defects, contamination, and quality inspection of the foods in the food industry. Read more
Published in IEEE, 2016
Social Network Analysis (SNA) has become a very important and increasingly popular topic among researchers in recent years especially after emerging Semantic Web and Big Data technologies. This survey focuses on recently developed systems for SNA and summarizes the state-of-the-art technologies used by them and points out to future research directions. Read more
Published in IEEE, 2016
We present a framework for sentiment analysis on tweets related to news items. Given a set of tweets and news items, our framework classifies tweets as positive or negative and links them to the related news items. For the classification of tweets we use three of the most used machine learning methods, namely Naive Bayes, Complementary Naive Bayes, and Logistic Regression, and for linking tweets to news items, Natural Language Processing (NLP) techniques are used, including Zemberek NLP library for stemming and morphological analysis and then bag-of-words method for mapping. Read more