Particle path based tomographic image velocimetry

Particle path based image velocimetry has been developed for 3D volumetric velocity measurement of fluid flows. The proposed method is basically based on the tomographic reconstruction of 3D particle paths by using multiple camera views of long exposure particle images. Particle path based image velocimetry was popular in the early days of 2D...

Tuning Transitions in Rotating Rayleigh-Bénard Turbulence

Rayleigh-Bénard convection is a canonical system for the investigation of buoyancy-driven natural convection phenomena which abound in nature and technology. Under the influence of rotation and depending on the system parameters, the flow exhibits different regimes with disparate heat transfer characteristics even in the turbulent state. The...

Novel Method for Adhesion between PI-PDMS Using Butyl Rubber for Large Area Flexible Body Patches

This paper reports the use of rubber—Polybutadiene as an intermediate adhesive layer for improving the adhesion between polyimide (PI) and silicone polydimethylsiloxane (PDMS) which is required for a reliable fabrication of flexible/stretchable body patches for various applications. The adhesive bond initiated by the butyl rubber (BR), apart...

Unbalanced Bit-slicing Scheme for Accurate Memristor-based Neural Network Architecture

Emerging memristor-based computing has the potential to achieve higher computational efficiency over conventional architectures. Bit-slicing scheme, which represents a single neural weight using multiple memristive devices, is usually introduced in memristor-based neural networks to meet high bit-precision demands. However, the accuracy of such...

A Reference Economic Model for Airborne Wind Energy Systems

CIM-based Robust Logic Accelerator using 28 nm STT-MRAM Characterization Chip Tape-out

Spin-transfer torque magnetic random access memory (STT-MRAM) based computation-in-memory (CIM) architectures have shown great prospects for an energy-efficient computing. However, device variations and non-idealities narrow down the sensing margin that severely impacts the computing accuracy. In this work, we propose an adaptive referencing...

Accelerating RRAM Testing with a Low-cost Computation-in-Memory based DFT

Emerging non-volatile resistive RAM (RRAM) device technology has shown great potential to cultivate not only high-density memory storage, but also energy-efficient computing units. However, the unique challenges related to RRAM fabrication process render the traditional memory testing solutions inefficient and inadequate for high product quality...

Referencing-in-Array Scheme for RRAM-based CIM Architecture

Resistive random access memory (RRAM) based computation-in-memory (CIM) architectures are attracting a lot of attention due to their potential in performing fast and energy-efficient computing. However, the RRAM variability and non-idealities limit the computing accuracy of such architectures, especially for multi-operand logic operations....

A Reference Economic Model for Airborne Wind Energy Systems

Modelling and Sizing of a Hybrid Power Plant using Airborne Wind Energy Systems

Drivetrain Concepts for Pumping Airborne Wind Energy Systems

Read-disturb Detection Methodology for RRAM-based Computation-in-Memory Architecture

Resistive random access memory (RRAM) based computation-in-memory (CIM) architectures can meet the unprecedented energy efficiency requirements to execute AI algorithms directly on edge devices. However, the read-disturb problem associated with these architectures can lead to accumulated computational errors. To achieve the necessary level of...

A 115.1 TOPS/W, 12.1 TOPS/mm²Computation-in-Memory using Ring-Oscillator based ADC for Edge AI

Analog computation-in-memory (CIM) architecture alleviates massive data movement between the memory and the processor, thus promising great prospects to accelerate certain computational tasks in an energy-efficient manner. However, data converters involved in these architectures typically achieve the required computing accuracy at the expense...

Mapping-aware Biased Training for Accurate Memristor-based Neural Networks

Memristor-based computation-in-memory (CIM) can achieve high energy efficiency by processing the data within the memory, which makes it well-suited for applications like neural networks. However, memristors suffer from conductance variation problem where their programmed conductance values deviate from the desired values. Such variations lead...

The Road Ahead: Advancing Interactions between Autonomous Vehicles, Pedestrians, and Other Road Users

While great strides have been taken in advancing the field of Human-Robot Interaction (HRI), challenges abound in understanding and improving how Autonomous Vehicles (AVs) will interact with and within society. Through this paper, the authors attempt to paint the picture of challenges unique to the study and advancement of interfaces between AVs...

Developing a Reference Economic Model for Airborne Wind Energy Systems