Tao Wei - US grants

This project studies a new computing and communication architecture, reflex-tree, with massive parallel sensing, data processing, and control functions designed to meet the challenges imposed by future smart cities. The central feature of this novel reflex-tree architecture is inspired by a fundamental element of the human nervous system -- reflex arcs, or neuro-muscular reactions and instinctive motions in response to urgent situations that do not require the direct intervention of the brain. The scientific foundation and engineering framework built by this project will pave the way for enhanced monitoring and management of critical smart city infrastructure, from gas/oil pipelines, water management, communication networks, and power grids, to public transportation and healthcare. The interdisciplinary and collaborative nature of the project will inspire broader participation in related areas of research.

Within the human body, a neural reflex arc is able to cause an individual to immediately react to a source of discomfort without the need for direct control from the brain. The reflex-tree architecture mimics such human neural circuits, using massive numbers of intermediate computing nodes, edge devices, and sensors to gather, process, and, most importantly, to react to data concerning critical infrastructure elements. Key innovations of the proposed reflex-tree architecture include: 1) A novel, 4-level, large scale, and application-specific hierarchical computing and communication structure capable of carrying out sensor-based decision-making processes. The required computation and nodal computing power increases at each successive stage in the hierarchy, with the level-1 cloud performing the most complex tasks. 2) A densely distributed fiber-optic sensing network and parallel machine learning algorithms will be developed targeting smart city applications. 3) Novel, complementary machine intelligence algorithms will be developed, providing accurate control decisions via multi-layer adaptive learning, spatial-temporal association, and complex system behavior analysis. 4) New parallel algorithms and software run-time environments will be proposed and developed that are specifically tailored to the novel reflex-tree system architecture.

To demonstrate the feasibility and performance of the reflex-tree architecture, a proof-of-concept prototype will be constructed utilizing a miniaturized, laboratory-scale municipal gas pipeline system. The prototype will incorporate a complete 4-level reflex-tree--a distributed fiber-optic sensing network deployed alongside pipelines, edge devices performing data classification using parallel SVM, intermediate nodes performing massively-parallel spatial and temporal machine learning, and the cloud as the root node running sophisticated parallel behavioral analysis and decision making tasks. The resulting system is a cross layer, high performance, and massively parallel computing platform, providing a foundational sensing and computer architecture for future smart cities.

1442623
Wei

This grant supports development and testing of a distributed coaxial cable strainmeter that has the potential to offer high accuracy (~ ppm) and high temporal resolution (~1 sec) measurements with unprecedented high spatial (~ 10 m) resolution over kilometers. The concept will rely on tests of coaxial cables that have been imparted with periodic electromagnetic impedance discontinuities (a Bragg grating) which allow for weak reflections of a pulsed input of an electromagnetic wave through the coaxial waveguide or implanted reflectors within the coaxial cable that will enable a coaxial strainmeter based on Fabry-Perot interferometry. A vector network analyzer then is then used to analyze transmission and reflection spectra. The PI would also explore novel signal amplification techniques to reduce losses from returned EM pulses along longer lengths of cable with multiple sensors points along the length of the cable.

The potential of the coaxial cable based strainmeter to survive large deformations (5%) and strong lateral collision/impact, may provide valuable and otherwise inaccessible information under certain extreme conditions where fiber optic based strain technologies may fail (e.g., landslides, subglacial deformation, steel structure deformation). The development will engage a graduate student to assist with: 1) development of new modelling methodology for device design and optimization, 2) explore hybrid software-hardware signal processing technology; and 3) build a portable prototype coaxial strainmeter; and 4) characterize the prototype?s performance in the laboratory and in the field.


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This award supports fundamental research on a novel sensing modality, namely, microwave photonic velocimetry (MPV). In shock wave experimentation, velocimetry is the measurement of the speed of a shock wave as it develops, propagates, and fades. This provides critical information on shock wave behavior. The goal of this project is to support the measurement of the velocity of ultrafast shock waves, traveling at speeds in the order of several tens of km/s, in-situ and in real-time. This will enable the study of energetic materials, and eventually lead to much safer industrial workplaces where explosions may pose a hazard. Robust and accurate velocimetry that can measure ultrafast shock waves is an outstanding technical challenge that limits our understanding of shock wave physics and chemistry. If successful, the MPV technology will fill this void by substantially expanding our knowledge of materials' ability to detonate under a wide variety of physical conditions (temperature, pressure, concentration, etc.). Thus, breakthroughs in MPV as pursued in this project, will have significant societal benefits in preventing disasters and improving safety in hazardous environments. In particular, MPV is anticipated to be an enabling tool in the safe handling and storage of non-ideal (borderline) explosives. These are materials that are conventionally rated as safe, but may become a deadly threat in workplaces under certain conditions.

Specific research objectives include understanding and characterizing the MPV concept, investigating novel signal processing methodologies, and validating this novel sensing modality using large-scale, outdoor detonation tests. The direct outcome is the fundamental knowledge, implementation, and demonstration of the MPV concept. Key innovations include: 1) the innovative use of interactions between microwave and optical waves, enabling the creation of a precise, robust, and low-cost velocimetery, 2) the innovative integration of optical frequency comb technologies in the MPV system to precisely separate elements measured in the frequency-domain, 3) the novel MPV probe with integrated graded index fiber (GIF) collimator, which significantly enhances MPV's performance, 4) a novel signal processing algorithm that intelligently reconstructs the velocity history profiles of explosion events, and 5) enhanced multiplexing capability allowing for simultaneous, multi-probe shock wave velocity measurement.

As traditional data processing devices are no longer adequate to handle complex data sets and large computations due to the continuing information explosion, a high performance computing cluster (HPCC) has become an essential instrument for a wide variety of leading-edge research and educational activities. Lamar University (LU), a medium-sized non-PhD granting four-year university with more than 15,000 students will acquire and deploy a HPCC to enhance compute-intensive and data-intensive studies and to facilitate discipline-specific and multidisciplinary research through a shared state-of-the-art computing platform. The instrumentation will strongly support LU's high priority current and future research needs as well as benefit a variety of regional academic institutions and industries.

Specifically, the project will acquire a hybrid CPU/GPU HPCC which will make it possible to deploy the best suited computing nodes to perform traditional CPU-based, GPU-based, and hybrid CPU/GPU-based data-intensive computing tasks at LU. The resource will enable the exploration of creative research areas and establish new cross-disciplinary studies in the areas of imaging genomics, deep learning, big data, computational neuroscience, molecular physics, advanced materials research, scientific optimization, water and air quality analysis, transportation systems, electronic structure calculations, nucleic acid biomarker discovery and epigenetics, and many more.

Furthermore, as a shared research resource, the HPCC will not only promote cross-disciplinary collaborations among faculty members from different departments within the university, but also enable LU to promote and strengthen collaborative opportunities with other research institutions. In addition, the instrument will also become an essential educational tool with the potential to foster interest among faculty in the development of new courses that will integrate state-of-the-art research into undergraduate and graduate curricula. Additionally, the project will provide access to the resource to users from other academic institutions and industrial partners in the Golden Triangle area in Southeast Texas. Finally, the project will organize outreach activities for K-12 students from local Independent School Districts (ISDs) that have high minority and low-income ratios to study in science, technology, engineering, and mathematics (STEM) areas.

A variety of diseases are identified by protein markers. Nano-sized particles using metals such as gold and silver possess unique electronic and optical properties, which can be significantly altered when effected by an external cue, such as the interaction with a specific protein. Developing a fundamental understanding of nanoparticle-protein interactions and their associated optical properties is critical for the development of novel detection devices with high sensitivity and selectivity for detection of diseases, such as cancer and Alzheimer's. The knowledge obtained from this proposed research on nanoparticle-protein interactions will further assist in the development of novel technologies for the biomedical, materials, and energy sectors. This project connects researchers and resources at Howard University and Winston-Salem State University to integrate education and research training for students at the undergraduate and graduate levels. The project will provide rigorous training opportunities for the next generation of African-American and other students from underrepresented groups pursuing careers in Chemistry, Chemical Engineering, Physics and Mechanical Engineering. Results from the current and developing research on the nanoparticle-protein interactions, bio-simulations and biosensor design will be incorporated into workshops and classes, to expand the interests and experience of under-represented students in the STEM fields. This will promote successful academic and career paths.

Understanding the fundamental plasmonic response of gold and silver nanoparticles interacting with proteins is critical for molecular detection. This includes understanding the electronic properties and electromagnetic spectrum of discrete uniform gold and silver nanoparticles. This also includes understanding nanoparticle interactions with protein markers in a biochemical environment. The interactions of interest include physical and chemical coordination of the nanoparticles to the protein and the electromagnetic and plasmonic response from protein-nanoparticle interactions. The project will be achieved by coupling experimental spectroscopy with computational simulations at multiple scales (quantum, atomistic, molecular and continuum). The proposed study aims to elucidate different factors, including proteins' packing structure based on nanoparticles varying in type, shape, and means of surface functionalization. These fundamental nanoparticle-protein interactions will determine the plasmonic effect on electromagnetic and plasmonic signals. Simulations at the microscopic and macroscopic levels will provide knowledge on both the physical interactions and chemical reactions of nanoparticles and proteins, which are crucial for correlating nanoparticles' optic signals following environmental responses. Moreover, chemically modified nanoparticles' electronic structure, optical spectra, and magnetic properties will be studied using local surface plasmon resonance spectrum or surface enhanced Raman spectroscopy. These experimental results will be validated with quantum simulations. Subsequently, theoretical studies will more clearly explain spectrum signals and lead to improved experimental design of the target sensor. The multidisciplinary research team consists of experts in quantum and atomistic simulations, bio-nano interface, protein folding, experimental optical sensor design, and nanoparticle synthesis.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

The Major Research Instrumentation (MRI) program and the Historically Black Colleges and Universities-Undergraduate Program (HBCU-UP) together with the Office of Multidisciplinary Activities (OMA) in the Mathematical and Physical Sciences (MPS) directorate provide support for the acquisition of a cryogen-free Physical Property Measurement System DynaCool (PPMSD) instrument at Howard University. This acquisition supports Howard University researchers' participation in the National Quantum Initiative and the Materials Genome Initiative. The PPMSD provides a state-of-the-art resource to support students and researchers in cutting-edge quantum and materials science research. The PPMSD enhances the active learning experience at the undergraduate and graduate levels in science and engineering departments. Students receive training in magnetic, electrical transport, and heat capacity measurements, experimental data analysis, scientific writing, and presentation skills, which enhances their competitiveness with prospective employers in academia and industry. This, in turn, attracts the next generation of science and engineering students from underrepresented groups who can acquire the requisite skills and then go on to be leaders in their respective fields.

The PPMSD provides the ability to perform variable temperature and magnetic field dependent magnetic, electrical transport, and heat capacity studies relating to quantum materials, magnetic materials, functional materials, and quantum devices. The PPMSD provides advanced research capabilities to undertake several basic and applied research projects that enhance understanding of: (1) the effects of dimensional crossover in mesoscale spin glass dynamics and the role it plays on cooperative phase transitions; (2) the relationships between magnetic and structural entropies, and the performance of magnetocaloric materials; (3) the relationships between electronic transport and magnetic properties in porphyrin molecular junctions; (4) the effects of adatom doping on magnetic, spectroscopic, and transport properties of two-dimensional materials, such as graphene; (5) magnetic and spin transport properties of single molecular magnets covalently bonded between the two ferromagnetic electrodes of a magnetic tunnel junction; and (6) the study of electrical and magnetic properties of recovered high-pressure phases of novel carbon-based clathrate materials.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

This project introduces a new security technology that protects data confidentiality, data integrity, and correctness in computer systems. Specifically, the new technology is able to instantly detect malicious hardware attacks so that appropriate actions can be taken to prevent information from stolen and alteration when information is transmitted between components inside a computer system. The new technology can be realized using a simple digital hardware as part of a computer system. One of the objectives of this project is to design, develop, and implement the new hardware structure to be incorporated in future secure computers. 

The direct outcome of this project is fundamental knowledge gained from theoretical study and experimental implementation of the new security architecture, referred to as DIVOT (Detecting Impedance Variation Of Transmission-lines).  DIVOT is a generic, scalable, and low-overhead security solution for any computer system. It is made possible by several new concepts including analog-to-probability conversion (APC) and probability density modulation (PDM). A runtime-accessible, CMOS-compatible, and I/O-integrated DIVOT hardware structure will be designed, implemented, and tested in this project. Integrating DIVOT with a variety of interconnecting transmission-lines will lead to a transformative secure and trustworthy architecture that substantially reduces attack surface.

The broader impact of DIVOT architecture is significant.  It represents a universal countermeasure to fight against many physical probing/tampering threats and significantly enhances hardware security of various computing platforms ranging from servers to embedded computers in mobile devices and IoTs (Internet of things). Moreover, the outcomes of the project pave the way for many other future applications, including smart grid security, health care security, robotics security, etc. Many innovative architecture designs and security protocols will be generated that are likely to be published or transferred to the computer industry. Research results will be incorporated into our computer engineering curriculum.

Experimental data will be stored in ASCII format, source codes will be in C language, FPGA implementation will be in Verilog or VHDL format, and technical papers/reports will be in PDF format. Besides technical publications, annual and final reports will be presented to NSF on research progress and discoveries. All the data will be retained for at least four years after conclusion of the project on PIs? website: www.ele.uri.edu/~wei and www.ele.uri.edu/~qyang.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.