Teknolojide elde edilen gelişmelerle birlikte İnsansız Hava Aracı (İHA) sistemlerinin kullanım alanları yaygınlaşmakta ve çeşitlenmektedir. Günümüzde İHA’lar uzaktan algılama, fotogrametri, trafik denetimi ve büyük tesislerin gözetimi gibi birçok farklı amaçla kullanılmaktadırlar. İHA’lar tarafından fotogrametri ve uzaktan algılama görevlerinin yerine getirilmesi istediğinde video, dijital, termal ve kızıl ötesi kamera gibi farklı algılayıcı sistemler yerleştirilebilmektedir. Bu makalede uçan bir İHA’da bulunan kamerayla elde edilen görüntülerle hareketli nesnelerin tespiti ve takibi için bir Optik Akış yöntemi önerilmiştir. Uçan bir İHA'dan hareket eden nesneleri tespit etmeye çalışırken çözülmesi gereken asıl problem, aracın hareketinin neden olduğu görüntüdeki değişiklikleri hareketli nesnelerden ayırmaktır. Bu makalede, bir dikuçarın kameralarından alınan anlık görüntülerden hareketli nesnelerin gerçek zamanlı olarak tespit ve takip edilmesi için MATLAB Grafiksel Kullanıcı Arayüzü ortamında geliştirilen Optik Akış yöntemlerinin kullanıldığı bir yazılım ile yapılmıştır. En uygun Optik Akış algoritmasının seçilebilmesi için Optik Akış yöntemlerinde kullanılan; fark teknikleri, alan tabanlı teknikler, enerji tabanlı teknikler ve faz tabanlı teknikler ana sınıfları altında toplanan yöntemler uygulanarak, elde edilen sonuçlar karşılaştırılmıştır.
The types and application areas of cyber attacks are increasing and diversifying. Accordingly, the effects of attacks are constantly increasing or changing every moment. Among the attacks, malware attacks also have diversified and gained a wide place in the cyber world. With the use of different techniques and methods, there are problems in detecting and preventing malware attacks. These problems cause the systems' cyber security not to be fully ensured. Due to these situations, different malware attacks are discussed in the study, and the effects of attacks on Windows security are examined. A test-bed called AyEs has been prepared. Different attacks have been carried out, such as screenshots, vnc, aimed at hijacking or corrupting the victim system. The AyEs dataset was created by listening to the system network packets obtained due to the attacks. The dataset was preprocessed and made suitable for analysis. Machine learning methods such as Naive Bayes, J48, BayesNet, IBk, AdaBoost and LogitBoost were used on the dataset to detect malware attacks. J48 and IBk methods, which were found to provide high performance as a result of the analyzes, were suggested in the study. In this way, detection systems suitable for possible attack situations against Windows systems will be implemented easily and effectively. In addition to attack detection, an active role will be assumed in determining the type of attack.
With the developments in technology, the usage areas of Unmanned Air Vehicle (UAV) systems become widespread and diversify. Nowadays, UAVs are used for many different purposes such as remote sensing, photogrammetry, traffic control and monitoring of large facilities. In this work, a quadcopter was built as UAV. The eCalc program was used to extract the performance characteristics of this quadcopter. eCalc's design process and simulation processes are interactive. With the eCalc, the real elements can be created which are very close to the reality. The results obtained with eCalc were compared with the results obtained from MATLAB applications, and the hardware and software architectures required for an UAV general system and subsystems were designed and the quadcopter to be used in practice was realized. Mission Planner was used as a ground control station.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.