Tamper-evident seals are commonly used for non-proliferation applications. A properly engineered tamper-evident seal enables the detection of unauthorized access to a protected item or a secured zone. Tamper-evident seals must be susceptible to malicious attacks. These attacks should cause irreversible and detectable damage to the seals. At the same time, tamper-evident seals must demonstrate robustness to environmental changes in order to minimize false-positive and false-negative rates under real operating conditions. The architecture of the tamper-evident seal presented in this paper features a compressive sampling (CS) acquisition scheme, which provides the seal with a means for self- authentication and self-state of health awareness. The CS acquisition scheme is implemented using a micro-controller unit (MCU) and an array of resistors engraved on a graphite oxide (GO) film. CS enables compression and encryption of messages sent from the seal to the remote reader in a non-bit sensitive fashion. As already demonstrated in our previous work through the development of a simulation framework, the CS non-bit sensitive property ensures satisfactory reconstruction of the encrypted messages sent back to the reader when the resistance values of the resistor array are simultaneously affected by modest changes. This work investigates the resistive behavior of the reduced GO film to changes in temperature and humidity when tested in an environmental chamber. The goal is to characterize the humidity and temperature range for reliable operation of a GO-based seal.
Despite advances in computational cognition, there are many cyber-physical systems where human supervision and control is desirable. One pertinent example is the control of a robot arm, which can be found in both humanoid and commercial ground robots. Current control mechanisms require the user to look at several screens of varying perspective on the robot, then give commands through a joystick-like mechanism. This control paradigm fails to provide the human operator with an intuitive state feedback, resulting in awkward and slow behavior and underutilization of the robot's physical capabilities. To overcome this bottleneck, we introduce a new human-machine interface that extends the operator's proprioception by exploiting sensory substitution. Humans have a proprioceptive sense that provides us information on how our bodies are configured in space without having to directly observe our appendages. We constructed a wearable device with vibrating actuators on the forearm, where frequency of vibration corresponds to the spatial configuration of a robotic arm. The goal of this interface is to provide a means to communicate proprioceptive information to the teleoperator. Ultimately we will measure the change in performance (time taken to complete the task) achieved by the use of this interface.
The blossoming of sensing solutions based on the use of carbon materials and the pervasive exploration of compressed sensing (CS) for developing structural health monitoring applications suggest the possibility of combining these two research areas in a novel family of smart structures. Specifically, the authors propose an architecture for security-related applications that leverages the tunable electrical properties of a graphite oxide (GO) paper-based tamper-evident seal with a compressed-sensing (CS) encryption/authentication protocol. The electrical properties of GO are sensitive to the traditional methods that are commonly used to remove and replace paper-based tamper-evident seals (mechanical lifting, solvents, heat/cold temperature changes, steam). The sensitivity of the electro-chemical properties of GO to such malicious insults is exploited in this architecture. This is accomplished by using GO paper to physically realize the measurement matrix required to implement a compressive sampling procedure. The proposed architecture allows the seal to characterize its integrity, while simultaneously providing an encrypted/authentication feature making the seal difficult to counterfeit, spoof, or remove/replace. Traditional digital encryption/authentication techniques are often bit sensitive making them difficult to implement as part of a measurement process. CS is not bit sensitive and can tolerate deviation caused by noise and allows the seal to be robust with respect to environmental changes that can affect the electrical properties of the GO paper during normal operation. Further, the reduced amount of samples that need to be stored and transmitted makes the proposed solution highly attractive for power constrained applications where the seal is interrogated by a remote reader.
The acoustic emission (AE) phenomena generated by a rapid release in the internal stress of a material represent a
promising technique for structural health monitoring (SHM) applications. AE events typically result in a discrete number
of short-time, transient signals. The challenge associated with capturing these events using classical techniques is that
very high sampling rates must be used over extended periods of time. The result is that a very large amount of data is
collected to capture a phenomenon that rarely occurs. Furthermore, the high energy consumption associated with the
required high sampling rates makes the implementation of high-endurance, low-power, embedded AE sensor nodes
difficult to achieve. The relatively rare occurrence of AE events over long time scales implies that these measurements
are inherently sparse in the spike domain. The sparse nature of AE measurements makes them an attractive candidate for
the application of compressed sampling techniques. Collecting compressed measurements of sparse AE signals will relax
the requirements on the sampling rate and memory demands. The focus of this work is to investigate the suitability of
compressed sensing techniques for AE-based SHM. The work explores estimating AE signal statistics in the compressed
domain for low-power classification applications. In the event compressed classification finds an event of interest, ι1
norm minimization will be used to reconstruct the measurement for further analysis. The impact of structured noise on
compressive measurements is specifically addressed. The suitability of a particular algorithm, called Justice Pursuit, to
increase robustness to a small amount of arbitrary measurement corruption is investigated.