FBE- Elektronik Mühendisliği Lisansüstü Programı - Yüksek Lisans
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Sustainable Development Goal "Goal 9: Industry, Innovation and Infrastructure" ile FBE- Elektronik Mühendisliği Lisansüstü Programı - Yüksek Lisans'a göz atma
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ÖgeA hardware based gunshot sound detection system(Institute of Science and Technology, 2020) Akçocuk, Mustafa Koray ; Güneş, Ece Olcay ; 637005 ; Elektronik ve Haberleşme Mühendisliği Anabilim DalıWith the development of semiconductor technology, embedded systems' capacity of operations also increases day by day. In this way, small-sized devices are able to perform complex works. As a result, people take advantage of embedded systems in a wide variety of areas to enhance the life quality of living. As a result of technological developments, the use of tools that assist law enforcement officers in crime detection is also increasing. Available gunshot detection systems mainly focuses on preventing illegal hunting, decreasing crime rates in public space, and detecting gunshot direction in battlefield areas. When the literature is examined, it is seen that machine learning methods are used in the studies used in gunshot sound detection. However, the number of hardware-based systems used in gunshot sound detection is quite a few and mostly simple methods such as cross-correlation threshold, edge detection are implemented. In this work, it is aimed to realize a gunshot sound detection system on hardware. In this context, it is aimed to select the system that uses the advantages of machine learning methods and is the most suitable for implementation on the hardware. When the literature is examined, it has been observed that the mel coefficients, signal energy and zero crossing properties perform well in determining the gunshot sound. For this reason, the mentioned features were obtained from the audio signal and used in k-nearest neighbors (k-NN) and support vector machines (SVM) classification algorithms. An accuracy rate of 96.1538% was obtained with the k-NN classifier and 91.3462% with the SVM classifier.
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ÖgeLow power general purpose processor design and instructions set extension for AES(Institute of Science and Technology, 2020) Şairoğlu, Muhammed ; Yalçın Örs , Sıddıka Berna ; 633565 ; Electronics Engineering ProgrammeIn the last years, there has been a big growth in the demand for portable electronic devices. Most of these devices need to operate on a thrifty energy budget and they must be designed to work under extreme energy constraints for a long time. Also, a lot of smart devices need to communicate with the outer world and with other devices, and all these communications must be secure. These requirements have increased the investments in developing low-power integrated circuits with encryption capabilities. In this thesis, a low-power general purpose processor design is presented. Then the processor design is improved by extending the instruction set with instructions for the Advanced Encryption Standard (AES). In chapter one, many embedded systems architectures for low-power applications are introduced, then in chapter two the Advanced Encryption Standard is explained. In chapter four, the designed processor's instruction set is given, and its architecture is explained in detail. Then the processor architecture is improved by adding many pipeline stages. Pipeline hazards are handled without complicating the processor architecture. In chapter five, both processor designs (the non-pipelined and the pipelined) were tested with simple programs to compare its performances. The pipelined processor showed better results in terms of the required clock cycles to finish test programs, the throughput and the consumed energy. Both processor designs were also compared with the well-known Xilinx PicoBlaze processor. The pipelined processor beat PicoBlaze according to the maximum clock rate and dynamic on chip power. In chapter six, The AES algorithm is implemented in Assembly language and is run on the pipelined processor. Then AES algorithm code is investigated using its control flow graphs.