Inter-application redundancy elimination in sensor networks with compiler-assisted scheduling

Most current-generation Wireless Sensor Network (WSN) nodes are equipped with multiple sensors of various types, and therefore support for multi-tasking and multiple concurrent applications is becoming increasingly common. This trend has been fostering the design of WSNs allowing several concurrent users to deploy applications with dissimilar requirements. In this paper, we extend the advantages of a holistic programming scheme by designing a novel compiler-assisted scheduling approach (called REIS) able to identify and eliminate redundancies across applications. To achieve this useful high-level optimization, we model each user application as a linear sequence of executable instructions. We show how well-known string-matching algorithms such as the Longest Common Subsequence (LCS) and the Shortest Common Super-sequence (SCS) can be used to produce an optimal merged monolithic sequence of the deployed applications that takes into account embedded scheduling information. We show that our approach can help in achieving about 60% average energy savings in processor usage compared to the normal execution of concurrent applications.

Realization of fractional-order controllers: analysis, synthesis and application to the velocity control of a servo system

The synthesis and application of fractional-order controllers is now an active research field. This article investigates the use of fractional-order PID controllers in the velocity control of an experimental modular servo system. The systern consists of a digital servomechanism and open-architecture software environment for real-time control experiments using MATLAB/Simulink. Different tuning methods will be employed, such as heuristics based on the well-known Ziegler Nichols rules, techniques based on Bode’s ideal transfer function and optimization tuning methods. Experimental responses obtained from the application of the several fractional-order controllers are presented and analyzed. The effectiveness and superior performance of the proposed algorithms are also compared with classical integer-order PID controllers.

Automated synthesis procedure of RF discrete tuning differential capacitance circuits

The paper presents a RFDSCA automated synthesis procedure. This algorithm determines several RFDSCA circuits from the top-level system specifications all with the same maximum performance. The genetic synthesis tool optimizes a fitness function proportional to the RFDSCA quality factor and uses the epsiv-concept and maximin sorting scheme to achieve a set of solutions well distributed along a non-dominated front. To confirm the results of the algorithm, three RFDSCAs were simulated in SpectreRF and one of them was implemented and tested. The design used a 0.25 mum BiCMOS process. All the results (synthesized, simulated and measured) are very close, which indicate that the genetic synthesis method is a very useful tool to design optimum performance RFDSCAs.

Cloud-assisted Wireless Body Area Networks

Wireless Body Area Networks (WBANs) have emerged as a promising technology for medical and non-medical applications. WBANs consist of a number of miniaturized, portable, and autonomous sensor nodes that are used for long-term health monitoring of patients. These sensor nodes continuously collect information of patients, which are used for ubiquitous health monitoring. In addition, WBANs may be used for managing catastrophic events and increasing the effectiveness and performance of rescue forces. The huge amount of data collected by WBAN nodes demands scalable, on-demand, powerful, and secure storage and processing infrastructure. Cloud computing is expected to play a significant role in achieving the aforementioned objectives. The cloud computing environment links different devices ranging from miniaturized sensor nodes to high-performance supercomputers for delivering people-centric and context-centric services to the individuals and industries. The possible integration of WBANs with cloud computing (WBAN-cloud) will introduce viable and hybrid platform that must be able to process the huge amount of data collected from multiple WBANs. This WBAN-cloud will enable users (including physicians and nurses) to globally access the processing and storage infrastructure at competitive costs. Because WBANs forward useful and life-critical information to the cloud – which may operate in distributed and hostile environments, novel security mechanisms are required to prevent malicious interactions to the storage infrastructure. Both the cloud providers and the users must take strong security measures to protect the storage infrastructure.

Lettuce (Lactuca sativa L.) leaf-proteome profiles after exposure to cylindrospermopsin and a microcystin-LR/cylindrospermopsin mixture: A concentration-dependent response

The intensification of agricultural productivity is an important challenge worldwide. However, environmental stressors can provide challenges to this intensification. The progressive occurrence of the cyanotoxins cylindrospermopsin (CYN) and microcystin-LR (MC-LR) as a potential consequence of eutrophication and climate change is of increasing concern in the agricultural sector because it has been reported that these cyanotoxins exert harmful effects in crop plants. A proteomic-based approach has been shown to be a suitable tool for the detection and identification of the primary responses of organisms exposed to cyanotoxins. The aim of this study was to compare the leaf-proteome profiles of lettuce plants exposed to environmentally relevant concentrations of CYN and a MC-LR/CYN mixture. Lettuce plants were exposed to 1, 10, and 100 lg/l CYN and a MC-LR/CYN mixture for five days. The proteins of lettuce leaves were separated by twodimensional electrophoresis (2-DE), and those that were differentially abundant were then identified by matrix-assisted laser desorption/ionization time of flight-mass spectrometry (MALDI-TOF/TOF MS). The biological functions of the proteins that were most represented in both experiments were photosynthesis and carbon metabolism and stress/defense response. Proteins involved in protein synthesis and signal transduction were also highly observed in the MC-LR/CYN experiment. Although distinct protein abundance patterns were observed in both experiments, the effects appear to be concentration-dependent, and the effects of the mixture were clearly stronger than those of CYN alone. The obtained results highlight the putative tolerance of lettuce to CYN at concentrations up to 100 lg/l. Furthermore, the combination of CYN with MC-LR at low concentrations (1 lg/l) stimulated a significant increase in the fresh weight (fr. wt) of lettuce leaves and at the proteomic level resulted in the increase in abundance of a high number of proteins. In contrast, many proteins exhibited a decrease in abundance or were absent in the gels of the simultaneous exposure to 10 and 100 lg/l MC-LR/CYN. In the latter, also a significant decrease in the fr. wt of lettuce leaves was obtained. These findings provide important insights into the molecular mechanisms of the lettuce response to CYN and MC-LR/CYN and may contribute to the identification of potential protein markers of exposure and proteins that may confer tolerance to CYN and MC-LR/CYN. Furthermore, because lettuce is an important crop worldwide, this study may improve our understanding of the potential impact of these cyanotoxins on its quality traits (e.g., presence of allergenic proteins).

Synthesis of molecular biomimetics

Biomimetics has paved the way toward new materials and technologies inspired in Nature. Biomolecules and their supramolecular organization have today a leading role in biomimetics, benefiting from the recent advances in nanotechnology. The production of biomimetic materials may be however a difficult task, because Nature does it very well. The use of several building blocks assembled in bottom-up arrangement is without doubt at the core of this process. Such building blocks include different molecules or molecular arrangements, of synthetic or natural origin, such as amino acids, lipids, carbohydrates, nucleic acids, carbon allotropes, dendrimers, or organosilanes, among others. The most common approaches to produce synthetic biomimetic materials are reported herein, with special emphasis to building blocks and their supramolecular arrangement.

Synthesis of an antibody-like material for the detection of Albumin

6th Graduate Student Symposium on Molecular Imprinting

Automated Synthesis Procedure of RF Discrete Tuning Differential Capacitance Circuits

The paper presents a RFDSCA automated synthesis procedure. This algorithm determines several RFDSCA circuits from the top-level system specifications all with the same maximum performance. The genetic synthesis tool optimizes a fitness function proportional to the RFDSCA quality factor and uses the epsiv-concept and maximin sorting scheme to achieve a set of solutions well distributed along a non-dominated front. To confirm the results of the algorithm, three RFDSCAs were simulated in SpectreRF and one of them was implemented and tested. The design used a 0.25 mum BiCMOS process. All the results (synthesized, simulated and measured) are very close, which indicate that the genetic synthesis method is a very useful tool to design optimum performance RFDSCAs.

New Concepts Towards the Synthesis of Digital Circuits Through Genetic Algorithms

This paper analyses the performance of a Genetic Algorithm using two new concepts, namely a static fitness function including a discontinuity measure and a fractional-order dynamic fitness function, for the synthesis of combinational logic circuits. In both cases, experiments reveal superior results in terms of speed and convergence to achieve a solution.

Vision-Based Assisted Teleoperation for Inspection Tasks with a Small ROV

It is well-known that ROVs require human intervention to guarantee the success of their assignment, as well as the equipment safety. However, as its teleoperation is quite complex to perform, there is a need for assisted teleoperation. This study aims to take on this challenge by developing vision-based assisted teleoperation maneuvers, since a standard camera is present in any ROV. The proposed approach is a visual servoing solution, that allows the user to select between several standard image processing methods and is applied to a 3-DOF ROV. The most interesting characteristic of the presented system is the exclusive use of the camera data to improve the teleoperation of an underactuated ROV. It is demonstrated through the comparison and evaluation of standard implementations of different vision methods and the execution of simple maneuvers to acquire experimental results, that the teleoperation of a small ROV can be drastically improved without the need to install additional sensors.

Bioelectrochemically-assisted reductive dechlorination of 1,2-dichloroethane by a Dehalococcoides-enriched microbial culture

The aim of this study was to verify the possibility to use a polarized graphite electrode as an electron donor for the reductive dechlorination of 1,2-dichloroethane, an ubiquitous groundwater contaminant. The rate of 1,2-DCA dechlorination almost linearly increased by decreasing the set cathode potential over a broad range of set cathode potentials (i.e., from −300 mV to −900 mV vs. the standard hydrogen electrode). This process was primarily dependent on electrolytic H2 generation. On the other hand, reductive dechlorination proceeded (although quite slowly) with a very high Coulombic efficiency (near 70%) at a set cathode potential of −300 mV, where no H2 production occurred. Under this condition, reductive dechlorination was likely driven by direct electron uptake from the surface of the polarized electrode. Taken as a whole, this study further extends the range of chlorinated contaminants which can be treated with bioelectrochemical systems.

Biosynthesis-Assisted Structural Elucidation of the Bartolosides, Chlorinated Aromatic Glycolipids from Cyanobacteria

The isolation of the bartolosides, unprecedented cyanobacterial glycolipids featuring aliphatic chains with chlorine substituents and C-glycosyl moieties, is reported. Their chlorinated dialkylresorcinol (DAR) core presented a major structural-elucidation challenge. To overcome this, we discovered the bartoloside (brt) biosynthetic gene cluster and linked it to the natural products through in vitro characterization of the DAR-forming ketosynthase and aromatase. Bioinformatic analysis also revealed a novel potential halogenase. Knowledge of the bartoloside biosynthesis constrained the DAR core structure by defining key pathway intermediates, ultimately allowing us to determine the full structures of the bartolosides. This work illustrates the power of genomics to enable the use of biosynthetic information for structure elucidation.

Kalman tracking linear predictor for vowel intelligibility enhancement on european portuguese HMM based speech synthesis

The recent developments on Hidden Markov Models (HMM) based speech synthesis showed that this is a promising technology fully capable of competing with other established techniques. However some issues still lack a solution. Several authors report an over-smoothing phenomenon on both time and frequencies which decreases naturalness and sometimes intelligibility. In this work we present a new vowel intelligibility enhancement algorithm that uses a discrete Kalman filter (DKF) for tracking frame based parameters. The inter-frame correlations are modelled by an autoregressive structure which provides an underlying time frame dependency and can improve time-frequency resolution. The system’s performance has been evaluated using objective and subjective tests and the proposed methodology has led to improved results.

Adaptive filtering for high quality HMM based speech synthesis

In this work an adaptive filtering scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for Hidden Markov Model (HMM) based speech synthesis quality enhancement. The objective is to improve signal smoothness across HMMs and their related states and to reduce artifacts due to acoustic model's limitations. Both speech and artifacts are modelled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. Themodel parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The quality enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. The system's performance has been evaluated using mean opinion score tests and the proposed technique has led to improved results.