IEEE Dayton Section

The Dayton Section AES Society is pleased to host (https://ieee-aess.org/contact/vince-socci)(IEEE DL) for a multi-topic presentation on UAV Technology Overview, Biz Ops & Policies and Regulations. Part 1: Commercial level drones and UAVs are readily available to everyone today. New users can benefit from and drone technology familiarization. This lecture provides a technology overview of unmanned air vehicles and systems (UAV/UAS). A system overview with component descriptions is provided. UAV flight dynamics are discussed. Subsystems and component functions of UAS interfaces are outlined. Hardware and software are demonstrated. Participants will become familiar with the methods and practices of flight operations. Part 2: UAS technology, sensing, and software are advancing at such a rapid rate, that operators are always finding new ways to use them in commercial applications. Whereas drone used to be primarily used for photography, by adding advanced sending systems, they can be used for surveillance, inspection, security, and even VLOS/NVLOS material delivery. This lecture provides an overview of the currently popular commercial applications for UAVs as well as an exploration of future possibilities. An overview of business operations will guide entrepreneurs to start their own UAV operator business. Part 3: UAS technology and applications are advancing at such a rapid rate, that operator regulations and public education are struggling to keep up. Before a drone hobbyist can become a commercial UAV operator, she must be knowledgeable of current UAV policies and regulations and pass a certification exam to become a licensed operator. This lecture provides an overview of the knowledge areas necessary to become an FAA licensed UAV operator. An exploration of current FAA concerns and near-term considerations is also provided. Speaker(s): Mr. Vince Socci, Virtual: https://events.vtools.ieee.org/m/334704

Video-based source camera identification (V-SCI) task in digital forensics relies on the extracted photo response non-uniformity (PRNU) patterns that deteriorate when the electronic image stabilization (EIS)---designed to reduce handshake motion of videos in modern cameras---is activated. We present a data-driven approach to exploit PRNU signals derived from EIS video via "device-specific" neural networks implemented with a novel PRNU image training and transfer learning strategy. Our technique is motivated by a discrepancy between how PRNU is used in real-world scenarios and existing methods' design of SCI. Specifically, a forensics examiner in the field often has possession of the device in question, which is a source of richer device-specific features besides just the reference PRNU used in current SCI methods. We benchmarked the proposed method using EIS video sequences from the well-known VISION dataset and UDAYTON22VSCI, a new dataset we collected containing video sequences from 53 modern smartphone cameras, which confirms the advantages of our approach over state-of-the-art SCI methods. Speaker(s): Nicholas Hopkins, Virtual: https://events.vtools.ieee.org/m/339057

Artificial Intelligence (AI) and Deep Learning (DL) are shaping modern world. AI is revolutionizing the advancement in computer vision, natural language processing, autonomous vehicles, security, and industrial production. However, the existing AI infrastructure is highly driven by von-Neumann computing technology, which is facing the barriers of memory wall, heat wall, and data transfer bottleneck for meeting the overwhelming demand for big data computing. Computing-in-Memory (CIM) is an emerging computing paradigm that addresses the data transfer bottleneck in designing modern computing architecture for DL and AI applications. CIM computing promises to improve the throughput and energy efficiency compared to existing computing architecture. Emerging non-volatile memory (NVM) devices such as Resistive Random Access Memory (RRAM) and Static Random Access Memory (SRAM) devices are mainly considered for CIM architectures. This review started with the introduction of memory devices used for CIM. Then, we have discussed the mode of operation for macro and system-level architectures. We have reviewed the single and multi-bit macro-operations. In the end, this review discusses the limitations of CIM architecture and the prospects of the CIM research area. Speaker(s): Shahanur Alam, Virtual: https://events.vtools.ieee.org/m/340625