The ferromagnetic resonance (FMR) phenomenon serves as a sensitive probe of the effective internal fields in a magnetic material. FMR spectroscopy has consequently become a well-established technique, extensively employed in assessing material properties such as magnetic anisotropy, Landé g-factor, damping parameter, and the magnetoelastic constants of magnetic materials. Determining these...
A multidisciplinary perspective is necessitated for the analysis of wave energy conversion systems, spanning hydrodynamics, mechanics, electric power, and control systems. The complexity inherent in these scientific domains poses challenges for unified analysis. This paper addresses these challenges by connecting various domains through the application of circuit theory, characterizing the...
Learning to recognize objects is a fundamental and essential step in human perception and understanding of the world. Accordingly, research of object discovery across diverse modalities plays a pivotal role in the context of computer vision. This field not only contributes significantly to enhancing our understanding of visual information but...
There has been tremendous growth in using data analytic and machine learning algorithms to make critical decisions, such as in the national power grid, healthcare operations, and autonomous vehicles. Employing data analytic for decision-making allows cyber attackers to manipulate the decisions of these algorithms through data falsification. Hence, the trustworthiness...
High-potential molecules derived from biomass sources may suitably replace or supplement traditional nonrenewable hydrocarbon fuels to reduce pollution and fuel processing costs. Due to expensive and time-consuming property testing, models that predict key properties from optical data would initially vet potential additives before investment and bench-scale testing. Attenuated Total Reflection...
Movement intent decoders, which interpret volitional movement intent from human bioelectric signals, can be incorporated into modern neuroprostheses to offer people living with limb loss or paralysis the potential to regain their lost motor control. Machine learning methods have become the research standard for continuous decoders with high degrees of...
We present a theoretical free-space optical (FSO) transmitter that utilizes a dynamically steered and shaped laser beam to communicate with a randomly moving receiver adorned with a retroreflector. The transmitter tracks the receiver's position by repeatedly scanning the field of view (FOV), measuring reflections from the retroreflector, and estimating the...
Sensor system plays an important role in connecting everything including human body to the electrical information systems that we have built and that we are going to build, to make the world more intelligent and efficient. One of the key propulsive forces behind these emerging techniques is CMOS scaling that...
High-performance mechatronic systems are widely used in precision manufacturing equipment such as CNC machine tools, 3D-Printers, photolithography systems, industrial robots, and Coordinate Measuring Machines (CMMs). These equipment are utilized in producing parts and components for aviation, semiconductor, optics, and many other emerging industries, with geometric features and surface properties within...
Significance: Movement intent decoding algorithms can interpret human bioelectrical signals to control prosthetic limbs with many degrees of freedom (DOFs). This work involves decoding volitional movement intent from surface electromyogram (sEMG) signals to control prosthetic arms. To train these algorithms, patients flex their muscles to “follow” a movement prompt, and...