On Correlated Knowledge Distillation for Monitoring Human Pose with Radios

In this work, we propose and develop a simple experimental testbed to study the feasibility of a novel idea by coupling radio frequency (RF) sensing technology with Correlated Knowledge Distillation (CKD) theory towards designing lightweight, near real-time and precise human pose monitoring systems. The proposed CKD framework transfers and fuses pose knowledge from a robust "Teacher" model to a parameterized "Student" model, which can be a promising technique for obtaining accurate yet lightweight pose estimates. To assure its efficacy, we implemented CKD for distilling logits in our integrated Software Defined Radio (SDR)-based experimental setup and investigated the RF-visual signal correlation. Our CKD-RF sensing technique is characterized by two modes -- a camera-fed Teacher Class Network (e.g., images, videos) with an SDR-fed Student Class Network (e.g., RF signals). Specifically, our CKD model trains a dual multi-branch teacher and student network by distilling and fusing knowledge bases. The resulting CKD models are then subsequently used to identify the multimodal correlation and teach the student branch in reverse. Instead of simply aggregating their learnings, CKD training comprised multiple parallel transformations with the two domains, i.e., visual images and RF signals. Once trained, our CKD model can efficiently preserve privacy and utilize the multimodal correlated logits from the two different neural networks for estimating poses without using visual signals/video frames (by using only the RF signals)

Performance Analysis of OPC UA for Industrial Interoperability towards Industry 4.0

Open Platform Communications Unified Architecture (OPC UA) incorporates a wide range of features and covers most of the requirements for a platform-independent interoperability standard which can be used to transmit data and information from the factory production floor to the enterprise and management level. Due to its highly scalable and interoperable architecture, it is well-positioned for future deployment in smart embedded devices towards Industry 4.0, especially in environments where there are heterogeneous communication nodes. In this paper, we aim to evaluate the performance of OPC UA for communication in Industrial Internet of Things (IIoT) environments to better understand the technical implementation of OPC UA and the feasibility of incorporating OPC UA directly to resource-constrained edge devices. We propose an architectural system framework for OPC UA performance evaluation across a wide range of experiments. Our experimental results demonstrated the efficacy of the proposed system and evaluation framework. The OPC UA-based IIoT system architecture and budget-friendly/cost-effective testbed setup can be flexibly adopted for protocol testing, prototyping and educational purposes

Utilization of NMR surface coil techniques to study muscle fatigue

Skeletal muscle has a greater biochemical dynamic range than any other tissue. Upon strenuous exercise its oxidative demands may increase a hundredfold, and its glycolytic rate, a thousandfold. It is particularly for this tissue that the distinction between conditioning and disease becomes blurred, since poor conditioning may produce more functional compromise in muscle than many diseases produce in other target organs. Muscle, which amounts to about 40% of the body mass, is thus a prime candidate for functional or metabolic diseases. Therefore, muscle provides a convenient biochemical "window" for early detection of potentially life-threatening diseases. In this thesis a modified Chance/Radda method was used to investigate the use of P-31 NMR Spectroscopy (NMRS or MRS) to monitor patients with muscle diseases. The work described is divided into two parts: (a) design and evaluation of NMR surface coils of various configurations, and assessment of a preliminary clinical protocol, (b) optimization of the technique by normalizing the results with respect to the cross-sectional area of the human upper arm, and to the various parameters which influence the mechanical output of the appropriate muscles. The highlight of the work presented in this thesis has involved the development, improvement, characterization, and experimental implementation of a novel design of surface coil, namely the spiral resonator surface coil gantry, as well as the delineation, refinement, and clinical execution of a tractable protocol to study muscle fatigue. Assessment of the role of P-31 NMRS as a screening and diagnostic modality indicates that it can serve as an adjunctive tool. The P-31 NMR spectrum can provide information regarding the composition and level of the phosphate metabolites and thus can characterize cellular energetic state. It can also be used to determine the intracellular pH. The specific exercise protocol outlined in this thesis improves both the sensitivity and the selectivity of the diagnosis of mitochondrial disease, even when little or no muscle symptoms are present. It is also a useful technique to monitor drug therapy of patients with mitochondrial myopathy. The most important feature of the spiral resonator surface coil, developed during the course of our clinical investigation, is its flexibility with respect to the location where it can operate. Its stability and improved sensitivity are added advantages. Potential extension of the spiral resonator surface coil design to observe other nuclei of biological interest, such as C-13, as well as the adaptation of our clinical protocol to study the effect on muscular function of patients with Acquired Immune Deficiency Syndrome (AIDS) during anti-HIV drug therapy (AZT or DDI) have been explored and experimentally demonstrated. At the time when this work was initiated, only the research groups of Britton Chance in Philadelphia, George Radda in Oxford, plus a few others were active in the use of P-31 NMRS to study intact muscle weakness. Since then, worldwide interest has increased; it is our hope that the technique developed at UBC with limited resources will be easily implemented in many other NMR facilities.Science, Faculty ofChemistry, Department ofGraduat

Application of NMR to study biological change

The aim of this study was directed towards the application of NMR as an analytical tool to follow biological changes, by integrating imaging capabilities with an analytical NMR instrument. The work described here is divided into three parts: application of ¹³C NMR to follow biochemical transformations, evaluation of the usefulness of relaxation studies in detection of biological changes and, finally, testing of a combination of both NMR imaging and spectroscopic techniques to study a selected model system. Spectroscopic techniques were used to study systems of interest not only to chemists but also to technologists interested in milk-souring, grape-juice fermentation, soybean germination and cartilage-degradation. Our immediate objective was to identify biological changes and to fit them into known biochemical pathways; in the long term, this would lay down the ground work for future in-vivo studies. Relaxation techniques were used to obtain biological information and to follow biochemical changes. Initial studies involved cultured cells and their NMR relaxation rates were shown to be dependent on factors affecting cellular activities, such as growth and infection. Animal models of Arthritis and Multiple Sclerosis were followed by relaxation rates with moderate success. Finally, a preliminary study is described, in which a combination of spectroscopic and imaging techniques was used to follow the storage and cooking of an egg.Science, Faculty ofChemistry, Department ofGraduat

Automatic Failure Recovery for Container-Based IoT Edge Applications

Recent years have seen the rapid adoption of Internet of Things (IoT) technologies, where billions of physical devices are interconnected to provide data sensing, computing and actuating capabilities. IoT-based systems have been extensively deployed across various sectors, such as smart homes, smart cities, smart transport, smart logistics and so forth. Newer paradigms such as edge computing are developed to facilitate computation and data intelligence to be performed closer to IoT devices, hence reducing latency for time-sensitive tasks. However, IoT applications are increasingly being deployed in remote and difficult to reach areas for edge computing scenarios. These deployment locations make upgrading application and dealing with software failures difficult. IoT applications are also increasingly being deployed as containers which offer increased remote management ability but are more complex to configure. This paper proposes an approach for effectively managing, updating and re-configuring container-based IoT software as efficiently, scalably and reliably as possible with minimal downtime upon the detection of software failures. The approach is evaluated using docker container-based IoT application deployments in an edge computing scenario