High resolution demodulation platform for large capacity hybrid WDM/FDM microstructures sensing system assisted by tunable FP filter

In this paper we proposed a demodulation scheme based on tunable FP filter for the WDM/FDM sensing system of the microstructure mentioned in the previous work. Simulation is done to prove the feasibility of demodulating the microstructure with the tunable FP filter. The experiments result showed high consistence with the simulation. And with the help of the high speed FPGA module and a high resolution AD/DA card, the system has achieved a very high resolution, up to 2.5 pm, and wavelength ranges 1520nm to 1590 nm.

Progress in the development of mesoporous solid acid and base catalysts for converting carbohydrates into platform chemicals

This chapter provides a general overview of recent studies on catalytic conversion of fructose, glucose, and cellulose to platform chemicals over porous solid acid and base catalysts, including zeolites, ion-exchange resins, heteropoly acids, as well as structured carbon, silica, and metal oxide materials. Attention is focused on the dehydration of glucose and fructose to HMF, isomerization of glucose to fructose, hydrolysis of cellulose to sugar, and glycosidation of cellulose to alkyl glucosides. The correlation of porous structure, surface properties, and the strength or types of acid or base with the catalyst activity in these reactions is discussed in detail in this chapter.

eBEST platform a KKV-klaszterek operatív és együttműködési folyamatainak támogatására (eBEST platform for supporting operational and cooperative processes of SME's clusters)

Az Európai Bizottság jelentése szerint a magyar kis- és középvállalkozások helyzete 2005 óta stagnál. Bár ezek a vállalkozások adják a magyar vállalkozások 99%-át, mégis a közbeszerzési, valamint a növekvő piacokhoz való hozzáférés terén számos akadállyal kerülnek szembe. Az eBEST projekten (Empowering Business Ecosystems of Small Service Enterprises to Face the Economic Crisis) belül kialakított platform olyan funkcionalitással bír, ami mindamellett, hogy lehetővé teszi a vállalkozások szervezett csoportokba, azaz ökoszisztémákba rendeződését, hozzá tud járulni a fogyasztói igények kielégítése érdekében létrejövő ellátási lánc, illetve egyedi folyamatok mentén fellépő információszerzési, kommunikációs vagy együttműködési akadályok lebontásához. ____ It is widely recognised that the most important factor for increasing the productivity of small companies is a deep adoption of computer-based applications and services. The FP7 SME eBEST project proposed a new operational environment specifically conceived for net worked small companies, supported by an advanced suite of ICT services, the eBEST platform. The paper aims at presenting the projects achievements that are validated by a number of company clusters of different EU countries and industry sectors. The general objectives of the eBEST project are attracting customers to work with the clustered companies, facilitating companies to collaborate with each other, and enabling associations to foster the devised innovation.

Platform Competition with Intra-Group Externalities

In this article we analyze asymmetric two-sided markets. Two types of agents are assumed to interact with each other and we assume that agents of one type derive utility from inter-group interactions, while the other type of agents benefit from intra-group rather than from inter-group interactions as it is assumed in the standard symmetric two-sided markets model. First, we consider a monopoly platform, then we analyze competing platforms, both with single-homing and multi-homing abilities.

An integrated functional mapping and source localization platform for brain research

The premise of this dissertation is to create a highly integrated platform that combines the most current recording technologies for brain research through the development of new algorithms for three-dimensional (3D) functional mapping and 3D source localization. The recording modalities that were integrated include: Electroencephalography (EEG), Optical Topographic Maps (OTM), Magnetic Resonance Imaging (MRI), and Diffusion Tensor Imaging (DTI). This work can be divided into two parts: The first part involves the integration of OTM with MRI, where the topographic maps are mapped to both the skull and cortical surface of the brain. This integration process is made possible through the development of new algorithms that determine the probes location on the MRI head model and warping the 2D topographic maps onto the 3D MRI head/brain model. Dynamic changes of the brain activation can be visualized on the MRI head model through a graphical user interface. The second part of this research involves augmenting a fiber tracking system, by adding the ability to integrate the source localization results generated by commercial software named Curry. This task involved registering the EEG electrodes and the dipole results to the MRI data. Such Integration will allow the visualization of fiber tracts, along with the source of the EEG, in a 3D transparent brain structure. The research findings of this dissertation were tested and validated through the participation of patients from Miami Children Hospital (MCH). Such an integrated platform presented to the medical professionals in the form of a user-friendly graphical interface is viewed as a major contribution of this dissertation. It should be emphasized that there are two main aspects to this research endeavor: (1) if a dipole could be situated in time at its different positions, its trajectory may reveal additional information on the extent and nature of the brain malfunction; (2) situating such a dipole trajectory with respect to the fiber tracks could ensure the preservation of these fiber tracks (axons) during surgical interventions, preserving as a consequence these parts of the brain that are responsible for information transmission.

A research platform for artificial neural networks with applications in pediatric epilepsy

This dissertation established a state-of-the-art programming tool for designing and training artificial neural networks (ANNs) and showed its applicability to brain research. The developed tool, called NeuralStudio, allows users without programming skills to conduct studies based on ANNs in a powerful and very user friendly interface. A series of unique features has been implemented in NeuralStudio, such as ROC analysis, cross-validation, network averaging, topology optimization, and optimization of the activation function’s slopes. It also included a Support Vector Machines module for comparison purposes. Once the tool was fully developed, it was applied to two studies in brain research. In the first study, the goal was to create and train an ANN to detect epileptic seizures from subdural EEG. This analysis involved extracting features from the spectral power in the gamma frequencies. In the second application, a unique method was devised to link EEG recordings to epileptic and nonepileptic subjects. The contribution of this method consisted of developing a descriptor matrix that can be used to represent any EEG file regarding its duration and the number of electrodes. The first study showed that the inter-electrode mean of the spectral power in the gamma frequencies and its duration above a specific threshold performs better than the other frequencies in seizure detection, exhibiting an accuracy of 95.90%, a sensitivity of 92.59%, and a specificity of 96.84%. The second study yielded that Hjorth’s parameter activity is sufficient to accurately relate EEG to epileptic and non-epileptic subjects. After testing, accuracy, sensitivity and specificity of the classifier were all above 0.9667. Statistical tests measured the superiority of activity at over 99.99 % certainty. It was demonstrated that (1) the spectral power in the gamma frequencies is highly effective in locating seizures from EEG and (2) activity can be used to link EEG recordings to epileptic and non-epileptic subjects. These two studies required high computational load and could be addressed thanks to NeuralStudio. From a medical perspective, both methods proved the merits of NeuralStudio in brain research applications. For its outstanding features, NeuralStudio has been recently awarded a patent (US patent No. 7502763).

System-on-a-Chip (SOC) based environmental monitoring platform for the detection of hazardous materials

The purpose of this research is design considerations for environmental monitoring platforms for the detection of hazardous materials using System-on-a-Chip (SoC) design. Design considerations focus on improving key areas such as: (1) sampling methodology; (2) context awareness; and (3) sensor placement. These design considerations for environmental monitoring platforms using wireless sensor networks (WSN) is applied to the detection of methylmercury (MeHg) and environmental parameters affecting its formation (methylation) and deformation (demethylation). ^ The sampling methodology investigates a proof-of-concept for the monitoring of MeHg using three primary components: (1) chemical derivatization; (2) preconcentration using the purge-and-trap (P&T) method; and (3) sensing using Quartz Crystal Microbalance (QCM) sensors. This study focuses on the measurement of inorganic mercury (Hg) (e.g., Hg2+) and applies lessons learned to organic Hg (e.g., MeHg) detection. ^ Context awareness of a WSN and sampling strategies is enhanced by using spatial analysis techniques, namely geostatistical analysis (i.e., classical variography and ordinary point kriging), to help predict the phenomena of interest in unmonitored locations (i.e., locations without sensors). This aids in making more informed decisions on control of the WSN (e.g., communications strategy, power management, resource allocation, sampling rate and strategy, etc.). This methodology improves the precision of controllability by adding potentially significant information of unmonitored locations.^ There are two types of sensors that are investigated in this study for near-optimal placement in a WSN: (1) environmental (e.g., humidity, moisture, temperature, etc.) and (2) visual (e.g., camera) sensors. The near-optimal placement of environmental sensors is found utilizing a strategy which minimizes the variance of spatial analysis based on randomly chosen points representing the sensor locations. Spatial analysis is employed using geostatistical analysis and optimization occurs with Monte Carlo analysis. Visual sensor placement is accomplished for omnidirectional cameras operating in a WSN using an optimal placement metric (OPM) which is calculated for each grid point based on line-of-site (LOS) in a defined number of directions where known obstacles are taken into consideration. Optimal areas of camera placement are determined based on areas generating the largest OPMs. Statistical analysis is examined by using Monte Carlo analysis with varying number of obstacles and cameras in a defined space. ^

The Engaged University: Providing a Platform for Research That Transforms Society

Despite a growing recognition that the solutions to current environmental problems will be developed through collaborations between scientists and stakeholders, substantial challenges stifle such cooperation and slow the transfer of knowledge. Challenges occur at several levels, including individual, disciplinary, and institutional. All of these have implications for scholars working at academic and research institutions. Fortunately, creative ideas and tested models exist that provide opportunities for conversation and serious consideration about how such institutions can facilitate the dialogue between scientists and society

Gesture Recognition Using Neural Networks Based on HW/SW Cosimulation Platform

Hardware/software (HW/SW) cosimulation integrates software simulation and hardware simulation simultaneously. Usually, HW/SW co-simulation platform is used to ease debugging and verification for very large-scale integration (VLSI) design. To accelerate the computation of the gesture recognition technique, an HW/SW implementation using field programmable gate array (FPGA) technology is presented in this paper. The major contributions of this work are: (1) a novel design of memory controller in the Verilog Hardware Description Language (Verilog HDL) to reduce memory consumption and load on the processor. (2) The testing part of the neural network algorithm is being hardwired to improve the speed and performance. The American Sign Language gesture recognition is chosen to verify the performance of the approach. Several experiments were carried out on four databases of the gestures (alphabet signs A to Z). (3) The major benefit of this design is that it takes only few milliseconds to recognize the hand gesture which makes it computationally more efficient.

A Research Platform for Artificial Neural Networks with Applications in Pediatric Epilepsy

This dissertation established a state-of-the-art programming tool for designing and training artificial neural networks (ANNs) and showed its applicability to brain research. The developed tool, called NeuralStudio, allows users without programming skills to conduct studies based on ANNs in a powerful and very user friendly interface. A series of unique features has been implemented in NeuralStudio, such as ROC analysis, cross-validation, network averaging, topology optimization, and optimization of the activation function’s slopes. It also included a Support Vector Machines module for comparison purposes. Once the tool was fully developed, it was applied to two studies in brain research. In the first study, the goal was to create and train an ANN to detect epileptic seizures from subdural EEG. This analysis involved extracting features from the spectral power in the gamma frequencies. In the second application, a unique method was devised to link EEG recordings to epileptic and non-epileptic subjects. The contribution of this method consisted of developing a descriptor matrix that can be used to represent any EEG file regarding its duration and the number of electrodes. The first study showed that the inter-electrode mean of the spectral power in the gamma frequencies and its duration above a specific threshold performs better than the other frequencies in seizure detection, exhibiting an accuracy of 95.90%, a sensitivity of 92.59%, and a specificity of 96.84%. The second study yielded that Hjorth’s parameter activity is sufficient to accurately relate EEG to epileptic and non-epileptic subjects. After testing, accuracy, sensitivity and specificity of the classifier were all above 0.9667. Statistical tests measured the superiority of activity at over 99.99 % certainty. It was demonstrated that 1) the spectral power in the gamma frequencies is highly effective in locating seizures from EEG and 2) activity can be used to link EEG recordings to epileptic and non-epileptic subjects. These two studies required high computational load and could be addressed thanks to NeuralStudio. From a medical perspective, both methods proved the merits of NeuralStudio in brain research applications. For its outstanding features, NeuralStudio has been recently awarded a patent (US patent No. 7502763).

Analysis of bio-derived platform chemicals in ionic liquid media by desorption/ionization mass spectrometry

In this work, desorption/ionization mass spectrometry was employed for the analysis of sugars and small platform chemicals that are common intermediates in biomass transformation reactions. Specifically, matrix-assisted laser desorption/ionization (MALDI) and desorption electrospray ionization (DESI) mass spectrometric techniques were employed as alternatives to traditional chromatographic methods. Ionic liquid matrices (ILMs) were designed based on traditional solid MALDI matrices (2,5-dihydroxybenzoic acid (DHB) and α-cyano-4-hydroxycinnamic acid (CHCA)) and 1,3-dialkylimidazolium ionic liquids ([BMIM]Cl, [EMIM]Cl, and [EMIM]OAc) that have been employed as reaction media for biomass transformation reactions such as the conversion of carbohydrates to valuable platform chemicals. Although two new ILMs were synthesized ([EMIM][DHB] and [EMIM][CHCA] from [EMIM]OAc), chloride-containing ILs did not react with matrices and resulted in mixtures of IL and matrix in solution. Compared to the parent solid matrices, much less matrix interference was observed in the low mass region of the mass spectrum (< 500 Da) using each of the IL-matrices. Furthermore, the formation of a true ILM (i.e. a new ion pair) does not appear to be necessary for analyte ionization. MALDI sample preparation techniques were optimized based on the compatibility with analyte, IL and matrix. ILMs and IL-matrix mixtures of DHB allowed for qualitative analysis of glucose, fructose, sucrose and N-acetyl-D-glucosamine. Analogous CHCA-containing ILMs did not result in appreciable analyte signals under similar conditions. Small platform compounds such as 5-hydroxymethylfurfural (HMF) and levulinic acid were not detected by direct analysis using MALDI-MS. Furthermore, sugar analyte signals were only detected at relatively high matrix:IL:analyte ratios (1:1:1) due to significant matrix and analyte suppression by the IL ions. Therefore, chemical modification of analytes with glycidyltrimethylammonium chloride (GTMA) was employed to extend this method to quantitative applications. Derivatization was accomplished in aqueous IL solutions with fair reaction efficiencies (36.9 – 48.4 % glucose conversion). Calibration curves of derivatized glucose-GTMA yielded good linearity in all solvent systems tested, with decreased % RSDs of analyte ion signals in IL solutions as compared to purely aqueous systems (1.2 – 7.2 % and 4.2 – 8.7 %, respectively). Derivatization resulted in a substantial increase in sensitivity for MALDI-MS analyses: glucose was reliably detected at IL:analyte ratios of 100:1 (as compared to 1:1 prior to derivatization). Screening of all test analytes resulted in appreciable analyte signals in MALDI-MS spectra, including both HMF and levulinic acid. Using appropriate internal standards, calibration curves were constructed and this method was employed for monitoring a model dehydration reaction of fructose to HMF in [BMIM]Cl. Calibration curves showed wide dynamic ranges (LOD – 100 ng fructose/μg [BMIM]Cl, LOD – 75 ng HMF/μg [BMIM]Cl) with correlation coefficients of 0.9973 (fructose) and 0.9931 (HMF). LODs were estimated from the calibration data to be 7.2 ng fructose/μg [BMIM]Cl and 7.5 ng HMF/μg [BMIM]Cl, however relatively high S/N ratios at these concentrations indicate that these values are likely overestimated. Application of this method allowed for the rapid acquisition of quantitative data without the need for prior separation of analyte and IL. Finally, small molecule platform chemicals HMF and levulinic acid were qualitatively analyzed by DESI-MS. Both HMF and levulinic acid were easily ionized and the corresponding molecular ions were easily detected in the presence of 10 – 100 times IL, without the need for chemical modification prior to analysis. DESI-MS analysis of ILs in positive and negative ion modes resulted in few ions in the low mass region, showing great potential for the analysis of small molecules in IL media.

The importance of realistic dispersal models in planning for conservation : application of a novel modelling platform to evaluate management scenarios in an Afrotropical biodiversity hotspot

Funded by European Union's Horizon 2020 Marie Sklodowska-Curie. Grant Number: 661211 Research Foundation Flanders (FWO). Grant Numbers: G.0055.08, G.0149.09, G.0308.13 FWO Research Network on Eco-Evolutionary dynamics French Ministère de l'Energie de l'Ecologie du Développement Durable et de la Mer through the EU FP6 BiodivERsA Eranet NERC. Grant Number: NE/J008001/1

Design and analysis of a compliant parallel pan-tilt platform

In combination of the advantages of both parallel mechanisms and compliant mechanisms, a compliant parallel mechanism with two rotational DOFs (degrees of freedom) is designed to meet the requirement of a lightweight and compact pan-tilt platform. Firstly, two commonly-used design methods i.e. direct substitution and FACT (Freedom and Constraint Topology) are applied to design the configuration of the pan-tilt system, and similarities and differences of the two design alternatives are compared. Then inverse kinematic analysis of the candidate mechanism is implemented by using the pseudo-rigid-body model (PRBM), and the Jacobian related to its differential kinematics is further derived to help designer realize dynamic analysis of the 8R compliant mechanism. In addition, the mechanism’s maximum stress existing within its workspace is tested by finite element analysis. Finally, a method to determine joint damping of the flexure hinge is presented, which aims at exploring the effect of joint damping on actuator selection and real-time control. To the authors’ knowledge, almost no existing literature concerns with this issue.