Topic: Deep Learning with MATLAB
Abstract: Deep learning can achieve state-of-the-art accuracy for image segmentation and classification, speech recognition and enhancement, predictive maintenance, and many other domains. This machine learning technique has been adopted across many different industries, including automated driving, aerospace design, medical diagnostics, industrial automation, energy forecasting, and robotics. This session will feature industry examples, a deep learning workflow overview, and an update on the latest Artificial Intelligence capabilities available in MATLAB that help overcome common implementation challenges.
· Managing, automated labeling, and augmenting large data sets (images, signals, text, etc.)
· Utilizing intuitive interfaces to easily create, visualize, analyze, and train networks or manage multiple experiments
· Leveraging pre-trained models (e.g. GoogLeNet and ResNet) and imported models from Keras-TensorFlow, Caffe, and the ONNX Model format for transfer learning
Aycan Hacioglu is a Customer Success Engineer at MathWorks. She has a BS in Chemical Engineering from Bogazici University, Turkey and a jointly awarded Ph.D. in Chemical Engineering from the University of Florida and Universite Lille1-Sciences and Technologies, France. Before joining MathWorks, she was an Assistant Teaching Professor at the Chemical Engineering Department of the University of Missouri for 3.5 years. She extensively used MATLAB for fluid dynamics and mass transfer simulations. She is experienced in mathematical modeling, process simulations, numerical methods and perturbation theory. She also integrated MATLAB to separation processes and transport phenomena courses she taught. She is excited to share her experience and passion to use MathWorks products in academia.
Topics: Security in the world of IoTs
Abstract: Sensors are the building block of Internet of things and smart cities. Form environmental (Ph, Temperature, Light, humidity) and optical sensors, to G-force sensors, we rely on these sensors data. The signal from the sensor is a message that needs to be kept private before being transmitted over a public channel. This privacy is implemented differently in different sensors. CMOS based sensors are popular due to the low cost and ability to integrate signal processing and other modules in a low form factor. However, in CMOS sensors, encryption is typically implemented in software or using microprocessors which can be power hungry. To facilitate low power portable and wearable sensors, encryption must be integrated directly with the sensor hardware. This talk goes through the different modes of on-chip encryptions usable for low power sensors.
Dr. Ava Hedayatipour joined the CSULB Department of Electrical Engineering as an Assistant Professor in Fall 2020. Dr. Ava received her Ph.D. in Electrical Engineering from University of Tennessee, Knoxville. She earned a B.S. degree in Electrical Engineering from the Iran University of Science and Technology in 2012, and a M.S. degree in Electrical Engineering from Shahid Rajaee Teacher Training University in Iran in 2015. Dr. Hedayatipour’s current research interests include analog integrated circuit designs, bio-implantable and biomedical devices, low- power and low-noise designs, microelectronics, mixed-signal VLSI designs, and hardware security. During graduate studies, she developed the first integrated secure multimodal sensor that uses low power blocks to implement impedance and temperature sensor, with security fabricated with a Lorenz chaotic circuit. Her impedance sensor has been used to detect thoracic impedance (to detect heart failure) and hand gestures (to translate sign language). Her recent work in designing a printable electrode enables individuals to do electrochemical experiments in remote locations. Dr. Hedayatipour is also the recipient of a University of Tennessee Fellowship Award in 2019 and Outstanding Teaching Assistant award in 2018.
Topics: Automated Substation Test Tools – Overview of testing techniques for next-generation substation architecture
Abstract: As substation architectures evolve and shift towards fully digital environments, engineers require expanded testing capabilities from tools used in the lab to validate the new substation architectures. Existing substation project Factory Acceptance Tests (FAT) and Site Acceptance Tests (SAT) involve the manual evaluation of one function at a time. This process typically takes several weeks to months depending on the size of the project to complete. The use of automated test tools can add efficiency to the test process and reduce commissioning time without compromising the completeness and quality of lab testing. Automation through scripting tools can be used to run tests for many iterations without user interaction, and the ability to run many tests over a shorter period of time allows engineers to allocate more time to the evaluation and analysis of results and to troubleshoot more effectively. In addition, the ability to implement automated test scripts can lead to the development of testing templates which will further reduce the time required to prepare for testing.
This presentation will provide an overview of the benefits gained from implementing automated test tools and will explore two use cases where these tools were leveraged. The first application involved automating multiple fault scenarios to test various protection element configurations using Real Time Digital Simulator (RTDS). The second tool used simulated IEC 61850 Intelligent Electronic Devices and scripting capabilities to test the substation Human Machine Interface and Programmable Logic Controllers.
Ms. Nicole Rexwinkel is an Engineer at Southern California Edison for the Substation Demonstrations team at Southern California Edison after receiving her Bachelor of Science in Electrical Engineering from California Polytechnic State University, San Luis Obispo. The Substation Demonstrations team performs testing and evaluates new technology before it is introduced into the substation environment. Since joining the team, Nicole has worked on integrating automated substation test tools and applications into SCE’s Grid Technology Innovation labs. Nicole developed scripts to automate testing with the Real Time Digital Simulator and has also worked on implementing a test tool which simulates IEC 61850 capable Intelligent Electronic Devices and allows users to create scripts which automatically run tests and report results.
Topics: an Overview of SDR Tool Chains for Wireless Research
Abstract: In this presentation Haydn Nelson will share the tradeoffs and benefits of several different SDR tool chain design flow options, from LabVIEW, MatLab, to Open source tools like GNU Radio. Several demonstrations will be shared for each. By the end of this talk you should have a good understanding of software development options for SDR devices and how you can use such tools in your research applications.
Haydn Nelson is a technical marketing manager for wireless research and deployment at NI, having been in the RF, DSP, SDR, and Wireless industry for over 17 years his career has spanned 4 years in the US Navy, followed by a bachelors and masters from UT Austin embedded systems, digital architectures and DSP. Haydn began his engineering career at MIT doing research on Radar algorithms with real world over the air experimentation, Haydn joined NI in 2009 engineering solutions for wireless test and now manages marketing for wireless research and deployment applications. https://www.linkedin.com/in/haydnnelson/
Topics: Update on Zero-Emissions Technology Demonstrations at the Port of Long Beach
Abstract: The San Pedro Bay Ports 2017 Clean Air Action Plan (CAAP) Update set ambitious goals to reduce air and greenhouse gas emissions from goods movement with the ultimate goal to transition to zero-emissions port operations. Critical to meeting the goals of the CAAP is the successful development and deployment of zero-emissions technologies. This presentation provides an update on zero-emissions technology demonstrations at the Port of Long Beach. Attendees will also be presented with an overview of the Port’s clean air initiatives, and how partnerships between funding agencies, technology manufacturers and stakeholders to leverage resources have enabled wider-scale deployment of zero-emissions technologies at the Port.
Rose Szoke is an Environmental Specialist for the Port of Long Beach, Environmental Planning Division. Since 2008, her focus at the Port has been on air quality, community health, and technology advancement. She currently leads and manages the San Pedro Bay Ports Technology Advancement Program in a joint partnership with the Port of Los Angeles. In addition, she has secured and managed over $23 million in multiple state and federal grants for emission reduction and zero-emission projects. Rose holds a Bachelor of Science degree in Applied Ecology from the University of California, Irvine and a Master of Science degree in Environmental Health Sciences with a concentration in Industrial Hygiene from the University of California, Los Angeles.