Condition-based diagnosis of mechatronic systems using a fractional calculus approach

While fractional calculus (FC) is as old as integer calculus, its application has been mainly restricted to mathematics. However, many real systems are better described using FC equations than with integer models. FC is a suitable tool for describing systems characterised by their fractal nature, long-term memory and chaotic behaviour. It is a promising methodology for failure analysis and modelling, since the behaviour of a failing system depends on factors that increase the model’s complexity. This paper explores the proficiency of FC in modelling complex behaviour by tuning only a few parameters. This work proposes a novel two-step strategy for diagnosis, first modelling common failure conditions and, second, by comparing these models with real machine signals and using the difference to feed a computational classifier. Our proposal is validated using an electrical motor coupled with a mechanical gear reducer.     

Skill Memory in Biped Locomotion

Robots must be able to adapt their motor behavior to unexpected situations in order to safely move among humans. A necessary step is to be able to predict failures, which result in behavior abnormalities and may cause irrecoverable damage to the robot and its surroundings, i.e. humans. In this paper we build a predictive model of sensor traces that enables early failure detection by means of a skill memory. Specifically, we propose an architecture based on a biped locomotion solution with improved robustness due to sensory feedback, and extend the concept of Associative Skill Memories (ASM) to periodic movements by introducing several mechanisms into the training workflow, such as linear interpolation and regression into a Dynamical Motion Primitive (DMP) system such that representation becomes time invariant and easily parameterizable. The failure detection mechanism applies statistical tests to determine the optimal operating conditions. Both training and failure testing were conducted on a DARwIn-OP inside a simulation environment to assess and validate the failure detection system proposed. Results show that the system performance in terms of the compromise between sensitivity and specificity is similar with and without the proposed mechanism, while achieving a significant data size reduction due to the periodic approach taken.     

Set‐based fault detection and isolation for detectable linear parameter‐varying systems

In the context of fault detection and isolation of linear parameter‐varying systems, a challenging task appears when the dynamics and the available measurements render the model unobservable, which invalidates the use of standard set‐valued observers. Two results are obtained in this paper, namely, using a left‐coprime factorization, one can achieve set‐valued estimates with ultimately bounded hyper‐volume and convergence dependent on the slowest unobservable mode; and by rewriting the set‐valued observer equations and taking advantage of a coprime factorization, it is possible to have a low‐complexity fault detection and isolation method. Performance is assessed through simulation, illustrating, in particular, the detection time for various types of faults. Copyright © 2017 John Wiley & Sons, Ltd.     

Mobile-cloud assisted framework for selective encryption of medical images with steganography for resource-constrained devices

In this paper, the problem of outsourcing the selective encryption of a medical image to cloud by resource-constrained devices such as smart phone is addressed, without revealing the cover image to cloud using steganography. In the proposed framework, the region of interest of the medical image is first detected using a visual saliency model. The detected important data is then embedded in a host image, producing a stego image which is outsourced to cloud for encryption. The cloud which has powerful resources, encrypts the image and sent back the encrypted marked image to the client. The client can then extract the selectively encrypted region of interest and can combine it with the region of non-interest to form a selectively encrypted image, which can be sent to medical specialists and healthcare centers. Experimental results and analysis validate the effectiveness of the proposed framework in terms of security, image quality, and computational complexity and verify its applicability in remote patient monitoring centers.     

From software extensions to product lines of dataflow programs

Dataflow programs are widely used. Each program is a directed graph where nodes are computations and edges indicate the flow of data. In prior work, we reverse-engineered legacy dataflow programs by deriving their optimized implementations from a simple specification graph using graph transformations called refinements and optimizations. In MDE speak, our derivations were PIM-to-PSM mappings. In this paper, we show how extensions complement refinements, optimizations, and PIM-to-PSM derivations to make the process of reverse engineering complex legacy dataflow programs tractable. We explain how optional functionality in transformations can be encoded, thereby enabling us to encode product lines of transformations as well as product lines of dataflow programs. We describe the implementation of extensions in the \(\mathtt{ReFlO}\) tool and present two non-trivial case studies as evidence of our work’s generality.     

Studies on a LaF3‐coated MgO protecting layer in AC‐plasma‐display panels

A new protecting layer, a LaF₃‐coated MgO layer, in color AC‐plasma‐display panels (PDPs) was studied in order to overcome the weakness of the conventional single MgO protecting layer. The material characteristics of the new layer were examined by using variations in the deposition process. The display characteristics were also examined by implementing their processes to actual PDPs. It was demonstrated that this method is effective in lowering the firing and sustaining voltages of PDPs and enhancing the brightness of the panel as well.     

Food vacuole proteome of the malarial parasite Plasmodium falciparum

The Plasmodium falciparum food vacuole (FV) is a lysosome-like organelle where erythrocyte hemoglobin digestion occurs. It is a favorite target in the development of antimalarials. We have used a tandem mass spectrometry approach to investigate the proteome of an FV-enriched fraction and identified 116 proteins. The electron microscopy analysis and the Western blot data showed that the major component of the fraction was the FV and, as expected, the majority of previously known FV markers were recovered. Of particular interest, several proteins involved in vesicle-mediated trafficking were identified, which are likely to play a key role in FV biogenesis and/or FV protein trafficking. Recovery of parasite surface proteins lends support to the cytostomal pathway of hemoglobin ingestion as a FV trafficking route. We have identified 32 proteins described as hypothetical in the databases. This insight into FV protein content provides new clues towards understanding the biological function of this organelle in P. falciparum.     

Oxidation of proteins: Basic principles and perspectives for blood proteomics

Protein oxidation mechanisms result in a wide array of modifications, from backbone cleavage or protein crosslinking to more subtle modifications such as side chain oxidations. Protein oxidation occurs as part of normal regulatory processes, as a defence mechanism against oxidative stress, or as a deleterious processes when antioxidant defences are overcome. Because blood is continually exposed to reactive oxygen and nitrogen species, blood proteomics should inherently adopt redox proteomic strategies. In this review, we recall the biochemical basis of protein oxidation, review the proteomic methodologies applied to analyse redox modifications, and highlight some physiological and in vitro responses to oxidative stress of various blood components.     

Three-dimensional micro-channel fabrication in polydimethylsiloxane(PDMS) elastomer

This paper describes a fabrication technique for building three-dimensional (3-D) micro-channels in polydimethylsiloxane (PDMS) elastomer. The process allows for the stacking of many thin (less than 100-μm thick) patterned PDMS layers to realize complex 3-D channel paths. The master for each layer is formed on a silicon wafer using an epoxy-based photoresist (SU 8). PDMS is cast against the master producing molded layers containing channels and openings. To realize thin layers with openings, a sandwich molding configuration was developed that allows precise control of the PDMS thickness. The master wafer is clamped within a sandwich that includes flat aluminum plates, a flexible polyester film layer, a rigid Pyrex wafer, and a rubber sheet. A parametric study is performed on PDMS surface activation in a reactive-ion-etching system and the subsequent methanol treatment for bonding and aligning very thin individual components to a substrate. Low RF power and short treatment times are better than high RF power and long treatment times, respectively, for instant bonding. Layer-to-layer alignment of less then 15 μm is achieved with manual alignment techniques that utilize surface tension driven self-alignment methods. A coring procedure is used to realize off-chip fluidic connections via the bottom PDMS layer, allowing the top layer to remain smooth and flat for complete optical access