Damage identification scheme based on compressive sensing

Civil infrastructures are critical to every nation, due to their substantial investment, long service period, and enormous negative impacts after failure. However, they inevitably deteriorate during their service lives. Therefore, methods capable of assessing conditions and identifying damage in a structure timely and accurately have drawn increasing attention. Recently, compressive sensing (CS), a significant breakthrough in signal processing, has been proposed to capture and represent compressible signals at a rate significantly below the traditional Nyquist rate. Due to its sound theoretical background and notable influence, this methodology has been successfully applied in many research areas. In order to explore its application in structural damage identification, a new CS-based damage identification scheme is proposed in this paper, by regarding damage identification problems as pattern classification problems. The time domain structural responses are transferred to the frequency domain as sparse representation, and then the numerical simulated data under various damage scenarios will be used to train a feature matrix as input information. This matrix can be used for damage identification through an optimization process. This will be one of the first few applications of this advanced technique to structural engineering areas. In order to demonstrate its effectiveness, numerical simulation results on a complex pipe soil interaction model are used to train the parameters and then to identify the simulated pipe degradation damage and free-spanning damage. To further demonstrate the method, vibration tests of a steel pipe laid on the ground are carried out. The measured acceleration time histories are used for damage identification. Both numerical and experimental verification results confirm that the proposed damage identification scheme will be a promising tool for structural health monitoring.

Deploying aptameric sensing technology for rapid pandemic monitoring

The genome of virulent strains may possess the ability to mutate by means of antigenic shift and/or antigenic drift as well as being resistant to antibiotics with time. The outbreak and spread of these virulent diseases including avian influenza (H1N1), severe acute respiratory syndrome (SARS-Corona virus), cholera (Vibrio cholera), tuberculosis (Mycobacterium tuberculosis), Ebola hemorrhagic fever (Ebola Virus) and AIDS (HIV-1) necessitate urgent attention to develop diagnostic protocols and assays for rapid detection and screening. Rapid and accurate detection of first cases with certainty will contribute significantly in preventing disease transmission and escalation to pandemic levels. As a result, there is a need to develop technologies that can meet the heavy demand of an all-embedded, inexpensive, specific and fast biosensing for the detection and screening of pathogens in active or latent forms to offer quick diagnosis and early treatments in order to avoid disease aggravation and unnecessary late treatment costs. Nucleic acid aptamers are short, single-stranded RNA or DNA sequences that can selectively bind to specific cellular and biomolecular targets. Aptamers, as new-age bioaffinity probes, have the necessary biophysical characteristics for improved pathogen detection. This article seeks to review global pandemic situations in relation to advances in pathogen detection systems. It particularly discusses aptameric biosensing and establishes application opportunities for effective pandemic monitoring. Insights into the application of continuous polymeric supports as the synthetic base for aptamer coupling to provide the needed convective mass transport for rapid screening is also presented.

Mobile phone-based electrochemiluminescence sensing exploiting the 'USB On-The-Go' protocol

A low-cost system to generate, control and detect electrochemiluminescence using a mobile smartphone is described. A simple tone-detection integrated circuit is used to switch power sourced from the phone's Universal Serial Bus (USB) 'On-The-Go' (OTG) port, using audible tone pulses played over the device's audio jack. We have successfully applied this approach to smartphones from different manufacturers and with different operating system versions. ECL calibrations of a common luminophore, tris(2,2′-bipyridine)ruthenium(II) ([Ru(bpy)3]²⁺), with 2-(dibutylamino)ethanol (DBAE) as a co-reactant, showed no significant difference in light intensities when an electrochemical cell was controlled by a mobile phone in this manner, compared to the same calibration generated using a conventional potentiostat. Combining this novel approach to control the applied potential with the measurement of the emitted light through the smart phone camera (using an in-house built Android app), we explored the ECL properties of a water-soluble iridium(III) complex that emits in the blue region of the spectrum. The iridium(III) complex exhibited superior co-reactant ECL intensities and limits of detection to that of the conventional [Ru(bpy)3]²⁺ luminophore.

On the security of compressed sensing-based signal cryptosystem

With the development of the cyber-physical systems (CPS), the security analysis of the data therein becomes more and more important. Recently, due to the advantage of joint encryption and compression for data transmission in CPS, the emerging compressed sensing (CS)-based cryptosystem has attracted much attention, where security is of extreme importance. The existing methods only analyze the security of the plaintext under the assumption that the key is absolutely safe. However, for sparse plaintext, the prior sparsity knowledge of the plaintext could be exploited to partly retrieve the key, and then the plaintext, from the ciphertext. So, the existing methods do not provide a satisfactory security analysis. In this paper, it is conducted in the information theory frame, where the plaintext sparsity feature and the mutual information of the ciphertext, key, and plaintext are involved. In addition, the perfect secrecy criteria (Shannon-sense and Wyner-sense) are extended to measure the security. While the security level is given, the illegal access risk is also discussed. It is shown that the CS-based cryptosystem achieves the extended Wyner-sense perfect secrecy, but when the key is used repeatedly, both the plaintext and the key could be conditionally accessed.

Sensing celebrities

Sensing celebrities involves recognition of the way complementary sensory-based elements come together to create, produce and transmit levels of affect and intensities. This chapter explores celebrity through the lens of sensory aesthetics. It begins by defining sensory aesthetics, linking it to the phenomenology of celebrity, and particularly the work of Vivian Sobchack and Laura U. Marks. The chapter draws upon the unique concept of the celebaesthetic subject to address the intersubjective relationship between fan and celebrity. Using Miley Cyrus as a case study, the chapter draws into the analysis the issue of gender and race, and the way conductive “skin” can be made to function as a sensory stereotype. It highlights that mobilization of the celebrity senses touched by transgression may be best understood to take place through the confession, and in the celebrity carnival.

Locally sparsified compressive sensing in magnetic resonance imaging

Magnetic Resonance Imaging (MRI) is a widely used technique for acquiring images of human organs/tissues. Due to its complex imaging process, it consumes a lot of time to produce a high quality image. Compressive Sensing (CS) has been used by researchers for rapid MRI. It uses a global sparsity constraint with variable density random sampling and L1 minimisation. This work intends to speed up the imaging process by exploiting the non-uniform sparsity in the MR images. Locally Sparsified CS suggests that the image can be even better sparsified by applying local sparsity constraints. The image produced by local CS can further reduce the sample set. This paper establishes the basis for a methodology to exploit non-uniform nature of sparsity and to make the MRI process time efficient by using local sparsity constraints.

Synthesis and characterisation of graphene hybrid nanoarchitechures for potential sensing applications

 The main focus of our project is to find a novel method to construct graphene hybrid systems and functionalised AuNPs with graphene which opens a new pathway for the potential and highly sensing applications in the area of graphene hybrid nanoarchitecture such as actuators and touch sensors. Adsorption of different CH3 and COOH alkanethiols on the surface of modified Au electrode with different CRGO's sheets to increase the efficient electron pathways for the development of new class graphene electrodes.

Big data sensing and service: a tutorial

As the advance of the Internet of Things (IoT), more M2M sensors and devices are connected to the Internet. These sensors and devices generate sensor-based big data and bring new business opportunities and demands for creating and developing sensor-oriented big data infrastructures, platforms and analytics service applications. Big data sensing is becoming a new concept and next technology trend based on a connected sensor world because of IoT. It brings a strong impact on many sensor-oriented applications, including smart city, disaster control and monitor, healthcare services, and environment protection and climate change study. This paper is written as a tutorial paper by providing the informative concepts and taxonomy on big data sensing and services. The paper not only discusses the motivation, research scope, and features of big data sensing and services, but also exams the required services in big data sensing based on the state-of-the-art research work. Moreover, the paper discusses big data sensing challenges, issues, and needs.