Novel e-nose for the discrimination of volatile organic biomarkers with an array of carbon nanotubes (CNT) conductive polymer nanocomposites (CPC) sensors

We report the original design of a new type of electronic nose (e-nose) consisting of only five sensors made of hierarchically structured conductive polymer nanocomposites (CPC). Each sensor benefits from both the exceptional electrical properties of carbon nanotubes (CNT) used to build the conductive architecture and the spray layer by layer (sLbL) assembly technique, which provides the transducers with a highly specific 3D surface structure. Excellent sensitivity and selectivity were obtained by optimizing the amount of CNT with five different polymer matrices: poly(caprolactone) (PCL), poly(lactic acid) (PLA), poly(carbonate) (PC), poly(methyl methacrylate) (PMMA) and a biobased polyester (BPR). The ability of the resulting e-nose to detect nine organic solvent vapours (isopropanol, tetrahydrofuran, dichloromethane, n-heptane, cyclohexane, methanol, ethanol, water and toluene), as well as biomarkers for lung cancer detection in breath analysis, has been demonstrated. Principal component analysis (PCA) proved to be an excellent pattern recognition tool to separate vapour clusters.     

Hydrogen sensor based on Pd-functionalized film bulk acoustic resonator

We present an application of the Pd-functionalized film bulk acoustic resonator for hydrogen detection. The resonator consisted of an AlN piezoelectric stack and a Bragg reflector has a working resonance near 2.23 GHz and a high performance. A 50 nm thick Pd film was coated on the top electrode as a specific layer to capture hydrogen. The absorption of hydrogen can trigger changes of elastic properties of the Pd layer, which affects the resonance frequency of the resonator. The experimental results show that the Pd-functionalized film bulk acoustic resonator can yield a rapid, sensitive, reversible and reproducible response to hydrogen in the concentrations from 0.3% to 2%. The advantages of this sensor, including the simple fabrication process, ease of detection method, rapid response and high sensitivity and working at room temperature, make this promising in the early alarm of hydrogen leaking.     

Screen-printed carbon electrode for choline based on MnO2 nanoparticles and choline oxidase/polyelectrolyte layers

This paper presents the amperometric biosensor that determines choline and cholinesterase activity using a screen printed graphite electrode. In order to detect H₂O₂ we have blanket modified the electrode material with manganese dioxide nanoparticles layer. Using layer-by-layer technique on the developed hydrogen peroxide sensitive electrode surface choline oxidase was incorporated into the interpolyelectrolyte nanofilm. Its ability to serve as a detector of choline in bulk analysis and cholinesterase assay was investigated. We examined the interferences from red-ox species and heavy metals in the blood and in the environmental sample matrixes. The sensor exhibited a linear increase of the amperometric signal at the concentration of choline ranging from 1.3 × 10⁻⁷ to 1.0 × 10⁻⁴ M, with a detection limit (evaluated as 3σ) of 130 nM and a sensitivity of 103 mA M⁻¹ cm⁻² under optimized potential applied (480 mV vs. Ag/AgCl). The biosensor retained its activity for more than 10 consecutive measurements and kept 75% of initial activity for three weeks of storage at 4 °C. The R.S.D. was determined as 1.9% for a choline concentration of 10⁻⁴ M (n = 10) with a typical response time of about 10 s. The developed choline biosensor was applied for butyrylcholinesterase assay showing a detection limit of 5 pM (3σ). We used the biosensor to develop the cholinesterase inhibitor assay. Detection limit for chlorpyrifos was estimated as 50 pM.     

Key management systems for sensor networks in the context of the Internet of Things

If a wireless sensor network (WSN) is to be completely integrated into the Internet as part of the Internet of Things (IoT), it is necessary to consider various security challenges, such as the creation of a secure channel between an Internet host and a sensor node. In order to create such a channel, it is necessary to provide key management mechanisms that allow two remote devices to negotiate certain security credentials (e.g. secret keys) that will be used to protect the information flow. In this paper we will analyse not only the applicability of existing mechanisms such as public key cryptography and pre-shared keys for sensor nodes in the IoT context, but also the applicability of those link-layer oriented key management systems (KMS) whose original purpose is to provide shared keys for sensor nodes belonging to the same WSN.     

Geometrically invariant image watermarking using SVR correction in NSCT domain

Based on the support vector regression (SVR) geometric distortions correction, we propose a robust image watermarking algorithm in nonsubsampled contourlet transform (NSCT) domain with good visual quality and reasonable resistance toward geometric attacks in this paper. Firstly, the NSCT is performed on original host image, and corresponding low-pass subband is selected for embedding watermark. Then, the selected low-pass subband is divided into small blocks. Finally, the digital watermark is embedded into host image by modulating the NSCT coefficients in small blocks. In digital watermark detecting procedure, the SVR geometrical distortions correction is utilized. Experimental results show that the proposed image watermarking is invisible, and robust against common image processing and some geometrical attacks.     

A non-reference image fusion metric based on mutual information of image features

The widespread usage of image fusion causes an increase in the importance of assessing the performance of different fusion algorithms. The problem of introducing a suitable quality measure for image fusion lies in the difficulty of defining an ideal fused image. In this paper, we propose a non-reference objective image fusion metric based on mutual information which calculates the amount of information conducted from the source images to the fused image. The considered information is represented by image features like gradients or edges, which are often in the form of two-dimensional signals. In this paper, a method of estimating the joint probability distribution from marginal distributions is also presented which is employed in calculation of mutual information. The proposed method is compared with the most popular existing algorithms. Various experiments, performed on several databases, certify the efficiency of our proposed method which is more consistent with the subjective criteria.     

A novel cryptoprocessor architecture for chained Merkle signature scheme

One-time signature schemes rely on hash functions and are, therefore, assumed to be resistant to attacks by quantum computers. These approaches inherently raise a key management problem, as the key pair can be used only for one message. That means, for one-time signature schemes to work, the sender must deliver the verification key together with the message and the signature. Upon reception, the receiver has to verify the authenticity of the verification key before verifying the signature itself. Hash-tree based solutions tackle this problem by basing the authenticity of a large number of verification keys on the authenticity of a root key. This approach, however, causes computation, communication, and storage overhead. Due to hardware acceleration, this paper proposes, for the first time, a processor architecture which boosts the performance of a one-time signature scheme without degrading memory usage and communication properties. This architecture realizes the chained Merkle signature scheme on the basis of Winternitz one-time signature scheme. All operations, i.e., key generation, signing, and verification are implemented on an FPGA platform, which acts as a coprocessor. Timing measurements on the prototype show a performance boost of at least one order of magnitude compared to an identical software solution.     

Open-hardware e-puck Linux extension board for experimental swarm robotics research

In this paper we describe the implementation of a Linux extension board for the e-puck educational mobile robot, designed to enhance the computation, memory and networking performance of the robot at very low cost. The extension board is based on a 32-bit ARM9 microprocessor and provides wireless network support. The ARM9 extension board runs in parallel with the dsPIC microprocessor on the e-puck motherboard with communication between the two via an SPI bus. The extension board is designed to handle computationally intensive image processing, wireless communication and high-level intelligent robot control algorithms, while the dsPIC handles low-level sensor interfacing, data processing and motor control. The extension board runs an embedded Linux operating system, along with a Debian-based port of the root file system stored in a Micro SD card. The extended e-puck robot platform requires minimal effort to integrate the well-known open-source robot control framework Player and, when placed within a TCP/IP networked infrastructure, provides a powerful and flexible platform for experimental swarm robotics research.     

A deadlock-free routing algorithm for dynamically reconfigurable Networks-on-Chip

We address routing in Networks-On-Chip (NoC) architectures that use irregular mesh topologies with Long-Range Links (LRL). These topologies create difficult conditions for routing algorithms, as standard algorithms assume a static, regular link structure and exploit the uniformity of regular meshes to avoid deadlock and maintain routability. We present a novel routing algorithm that can cope with these irregular topologies and adapt to run-time LRL insertion and topology reconfiguration. Our approach to accommodate dynamic topology reconfiguration is to use a new technique that decomposes routing relations into two stages: the calculation of output ports on the current minimal path and the application of routing restrictions designed to prevent deadlock. In addition, we present a selection function that uses local topology data to adaptively select optimal paths.The routing algorithm is shown to be deadlock-free, after which an analysis of all possible routing decisions in the region of an LRL is carried out. We show that the routing algorithm minimises the cost of sub-optimally placed LRL and display the hop savings available. When applied to LRLs of less than seven hops, the overall traffic hop count and associated routing energy cost is reduced. In a simulated 8 × 8 network the total input buffer usage across the network was reduced by 6.5%.