Time-and-spatial-multiplexing tree topology for fiber-optic Bragg-grating sensors with interferometric wavelength-shift detection

A combined time-and-spatial-division-multiplexed tree topology with eight fiber-optic Bragg-grating sensors operating at the 830-nm wavelength was constructed and tested for both quasistatic and periodic strain and temperature measurements. The system uses a interferometric wavelength-shift discriminator and incorporates a reference channel for thermal drift compensation in the output. Dynamic sensor sensitivity, as determined by primary noise sources, is evaluated, and numerical results are presented and compared with experimental results.     

Design of a fiber-optic quasi-distributed strain sensors ring network based on a white-light interferometric multiplexing technique

A fiber-optic quasi-distributed strain sensors ring network has been designed based on a Mach-Zehnder optical paths interrogator. The optical paths matching for each sensor are discussed, and the optical power budgetary analysis is performed. The relation between the number of sensors and the intensity of the signals of the ring network is given for evaluation of the multiplexing capacity. Experimentally, a seven-sensor array ring network was realized under the condition of light source power 35 microW at 1310 nm, and the distribution strain test was also demonstrated.     

Counting signal processing and counting level normalization techniques of polarization-insensitive fiber-optic Michelson interferometric sensors

A counting signal processing technique of the fiber-optic interferometric sensor is proposed. The technique is capable of counting the numbers of the maximum and minimum of the output interferometric signal in a specific time duration, and it can be used as the basis to distinguish the sensing phase signal. It can also be used as a signal detector on applications such as intrusion detection. All sensors are subject to aging of the optical components and bending loss, and therefore the output signal of each sensor may vary with time. We propose a counting level normalization technique to compensate for these variations and to obtain the correct counting numbers.     

Broadband phase and intensity compensation with a deformable mirror for an interferometric nuller

Nulling interferometry has been proposed for the direct detection of Earth-like planets. Deep stable nulls require careful control of the relative intensity and phase of the beams that are being combined. We present a novel compensator, the Adaptive Nuller, that corrects the intensity and phase as a function of wavelength from 8 to 12 microm using a deformable mirror. This compensator has been used to produce rejection ratios of 82,000:1 over a bandwidth of 3.2 microm centered around 10 microm.     

Analysis of active ladder network by using coates flow graphs and continuants

A simple method for solving the matrix equation describing the general active ladder network, is presented. Using Coates flow graphs and continuants the expressions for current, voltage, and also example of application are given.     

Analysis and demonstration of single-passband response and tuning characteristics in a chirped ladder interferometric filter for a widely tunable laser diode

We have designed and demonstrated a chirped ladder-type tunable filter and discussed its potential application for a tunable diode laser. A ladder interferometric filter normally has a periodic passband, which makes it impossible to stabilize laser oscillation frequency. To overcome this drawback, we have designed, fabricated, and characterized a novel chirped tunable ladder filter. We have successfully demonstrated a single-passband response in the fabricated device. Furthermore, a tuning operation of more than 30 nm was achieved by introducing a current injection structure and optimizing electrode lengths at each single-stage ladder interferometer.     

Monitoring and multiplexing technique for interferometric fiber optic sensors with a linearly chirped Er:fiber laser

The monitoring of interferometer fiber optic sensors using a laser that is scanned over a wide frequency range is investigated. The interrogation technique is based on the principle that if the light-source frequency varies linearly with time, the optical signal reflected or transmitted is intensity modulated at a frequency that is proportional to the optical path difference (OPD) in the interferometer. Fourier components in the detected optical output signal then correspond to the OPDs of any interferometers that have contributed to this modulation. The temporal position of a peak in the power spectrum of this signal is proportional to the OPD of the interferometer that is responsible for that peak. A fine tuning of the OPD value is determined from the phase of the corresponding Fourier component. Experimentally, an Er:fiber laser scanned over a 48-nm range centered at 1540 nm was used to monitor intrinsic fiber Fabry-Perot interferometers (FFPIs). Variations in the laser scan rate were compensated with the optical signal modulated by a reference FFPI held at a constant temperature. The OPD measurement resolution was 3.6 nm, and the dynamic range was 1.3 x 10(7). The temperature was measured from 20 degrees C to 610 degrees C with a 0.02 degrees C resolution, and multiplexing of three of the sensors arranged in series was demonstrated.     

Exact topology discovery algorithm for the capacity and delay constrained loop network

We have developed an exact model and algorithm for the delay-constrained minimum cost loop problem (DC-MCLP) of finding broadcast loops from a source node. While the traditional minimum cost loop problem (MCLP) deals with only the traffic capacity constraint served by a port of source node, the DC-MCLP deals with the mean network delay and traffic capacity constraints simultaneously. The DC-MCLP consists of finding a set of minimum cost loops to link end-user nodes to a source node satisfying the traffic requirements at end-nodes and the required mean delay of the network. In the DC-MCLP, the objective function is to minimise the total link cost. We have formulated the DC-MCLP and proposed an exact algorithm for its solution. The proposed algorithm is composed of two phases: in the first phase, it generates feasible paths to satisfy the traffic capacity constraint; in the second phase it finds the exact loop topology through matching and allocating optimal link capacity to satisfy the mean delay constraint. In addition, we have derived several properties including the memory and time complexity of the proposed algorithm. Performance evaluation shows that the proposed algorithm has good efficiency for networks with less than thirty nodes and light traffic. Our proposed algorithm can be applied to find the broadcast loops for real-time multimedia traffic     

Odour measurement using conducting polymer gas sensors and anartificial neural network decision system

The conventional way of assessing the magnitude of nuisance odours using an olfactometer and a sensory panel is costly. This paper describes experiments that have been conducted into matching the results from trained sensory panellists to those from a conducting polymer-based electronic nose. By taking the data from the electronic nose and applying them to a trained neural network, it has been shown that the data can be manipulated to give rise to results that are within a few percent of those from the sensory panellists. This is the first time that an electronic nose has been calibrated in terms of odour intensity measurements and it points the way forward to more objective measurements of nuisance odours     

Transparent network for hybrid multiplexing of fiber Bragg gratings and intensity-modulated fiber-optic sensors

A network for multiplexing fiber Bragg gratings (FBGs) and intensity-modulated fiber-optic sensors with no need to distinguish between the two kinds of sensor is proposed and experimentally demonstrated. Two FBG sensors and two intensity-modulated sensors are wavelength-division multiplexed; the electrical phase of the output signal is measured as a common parameter for both types of sensor. Furthermore, the intensity sensors become power referenced, and the FBG sensors are interrogated by a low-cost technique. Low cross talk is achieved by use of a tunable optical filter at the detector.     

Impact of relative intensity noise of vertical-cavity surface-emitting lasers on optics-based micromachined audio and seismic sensors

The relative intensity noise of vertical-cavity surface-emitting lasers (VCSELs) in the 100 mHz to 50 kHz frequency range is experimentally investigated using two representative single-mode VCSELs. Measurements in this frequency range are relevant to recently developed optical-based micromachined acoustic and accelerometer sensing structures that utilize VCSELs as the light source to form nearly monolithic 1 mm3 packages. Although this frequency regime is far lower than the gigahertz range relevant to optical communication applications for which VCSELs are primarily designed, the intensity noise is found to be low and well within the range of cancellation using basic reference detection principles.     

基于负载估计和子域消减的并行网络模拟拓扑划分算法

针对目前研究Internet的主要方法--传统的基于拓扑划分的大规模并行网络模拟的效率低、划分不均衡的问题,提出并实现了基于负载估计和子域消减的并行网络模拟拓扑划分策略.基于启明星辰探测获得的实际拓扑进行的DDoS攻击模拟表明,该划分方法可适用于实际拓扑,并可进行大规模网络安全事件的模拟.实验结果表明,该拓扑划分方法可...     

Stretchable,self-healable and anti-freezing conductive hydrogel based on double network for strain sensors and arrays

Journal of Materials Science - The application of hydrogels for flexible sensor is gravely hampered due to their poor freezing resistance and fatigue fracture associated with durable deformation,...     

Continuous-flow chemical processing on a microchip by combining microunit operations and a multiphase flow network

A new design and construction methodology for integration of complicated chemical processing on a microchip was proposed. This methodology, continuous-flow chemical processing (CFCP), is based on a combination of microunit operations (MUOs) and a multiphase flow network. Chemical operations in microchannels, such as mixing, reaction, and extraction, were classified into several MUOs. The complete procedure for Co(II) wet analysis, including a chelating reaction, solvent extraction, and purification was decomposed into MUOs and reconstructed as CFCP on a microchip. Chemical reaction and molecular transport were realized in and between continuous liquid flows in a multiphase flow network, such as aqueous/aqueous, aqueous/organic, and aqueous/organic/aqueous flows. When the determination of Co(II) in an admixture of Cu(II) was carried out using this methodology, the determination limit (2sigma) was obtained as 18 nM, and the absolute amount of Co chelates detected was 0.13 zmol, that is, 78 chelates. The sample analysis time was faster than that of a conventional processing system. Moreover, troublesome operations such as phase separation and acid and alkali washing, all necessary for the conventional system, were simplified. The CFCP methodology proposed here can be applied to various on-chip applications.     

Hybrid artificial neural network based on BP-PLSR and its application in development of soft sensors

A novel hybrid artificial neural network (HANN) integrating error back propagation algorithm (BP) with partial least square regression (PLSR) was proposed to overcome two main flaws of artificial neural network (ANN), i.e. tendency to overfitting and difficulty to determine the optimal number of the hidden nodes. Firstly, single-hidden-layer network consisting of an input layer, a single hidden layer and an output layer is selected by HANN. The number of the hidden-layer neurons is determined according to the number of the modeling samples and the number of the neural network parameters. Secondly, BP is employed to train ANN, and then the hidden layer is applied to carry out the nonlinear transformation for independent variables. Thirdly, the inverse function of the output-layer node activation function is applied to calculate the expectation of the output-layer node input, and PLSR is employed to identify PLS components from the nonlinear transformed variables, remove the correlation among the nonlinear transformed variables and obtain the optimal relationship model of the nonlinear transformed variables with the expectation of the output-layer node input. Thus, the HANN model is developed. Further, HANN was employed to develop naphtha dry point soft sensor and the most important intermediate product concentration (i.e. 4-carboxybenzaldehyde concentration) soft sensor in p-xylene (PX) oxidation reaction due to the fact that there exist many factors having nonlinear effect on them and significant correlation among their factors. The results of two HANN applications show that HANN overcomes overfitting and has the robust character. And, the predicted squared relative errors of two optimal HANN models are all lower than those of two optimal ANN models and the mean predicted squared relative errors of HANN are lower than those of ANN in two applications.     

Preliminary results of combining low frequency low intensity ultrasound and liposomal drug delivery to treat tumors in rats

Ultrasound is a convenient trigger for site-specific drug delivery in cancer therapy. Nano-sized liposomes formulated from soy phosphatidyl choline, cholesterol, 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[carboxy(polyethylene glycol)-2000] and alpha-tocopherol were loaded with Doxorubicin (Dox) using a pH gradient. The liposomal suspension was infused through the tail vein of BDIX rats possessing bilateral intradermal DHD/K12 tumors on their hind legs. Then 20-kHz ultrasound was applied to only one of the tumors for 15 minutes. This therapy was repeated weekly for 4 weeks. The results showed that in five of six rats, the tumors regressed to non-measurable size within 4 weeks. A paired comparison of the normalized size of the insonated and non-insonated tumors in the same rat indicated that the insonated tumors were smaller (p < 0.0001, n = 6 rats, 21 pairs). This observation has significant potential for non-invasive site-specific therapy of solid tumors.     

Uricase-catalyzed oxidation of uric acid using an artificial electron acceptor and fabrication of amperometric uric acid sensors with use of a redox ladder polymer.

Electrochemical oxidation of uric acid catalyzed by uricase (uric acid oxidase, UOx; EC 1.7.3.3) was studied using several redox compounds including 5-methylphenazinium (MP) and 1-methoxy-5-methylphenazinium (MMP) as electron acceptors for UOx, which does not contain any redox cofactor. It was found that MP and MMP were useful to mediate electrons from UOx to an electrode in the enzymatic oxidation of uric acid. A novel redox polymer, poly(N-methyl-o-phenylenediamine)(poly-MPD), containing the MP units was also found to possess the mediation ability for UOx, and poly-MPD was immobilized together with UOx onto an electrode substrate covered with a self-assembled monolayer of 2-aminoethanethiolate with use of glutaraldehyde as a binding agent. The resulting electrode (poly-MPD/UOx/Au) exhibited amperometric responses to uric acid with very fast response of approximately 30 s, allowing reagentless amperometric determination in a concentration range covering that in the blood of a healthy human being. Kinetic parameters of the apparent Michaelis constant and the maximum current response obtained at the poly-MPD/UOx/Au suggested that electrochemical oxidation of uric acid was controlled by diffusion of uric acid into the enzyme film and that the redox polymer worked well in mediating between active sites of UOx molecules and the electrode substrate.     

Zinc oxide thin-film chemical sensors in conjunction with neural network pattern recognition for trimethylamine and dimethylamine gases

Transient response curves for exposure to several gases are observed using zinc oxide (ZnO) thin-film gas sensors. It is found that an aluminium-doped ZnO (ZnO:Al) sensor exhibits a high sensitivity and an excellent selectivity for amine gases. In order to discriminate between gas species such as trimethylamine (TMA), dimethylamine (DMA) and other gases pattern recognition analysis using a neural network is carried out using parameters which characterize the transient responses of the sensor for exposure to gases. The recognition probability of the neural network is 90% for TMA and DMA with constant concentration and is 100% for TMA and DMA with different concentrations, except for a concentration of 1 p.p.m.     

Optimizing water tanks in water distribution systems by combining network reduction,mathematical optimization and hydraulic simulation

In the last two decades, water consumption in Germany has been decreasing, which causes the water tanks and pipes in water distribution systems to work inefficiently. This paper proposes a method that supports the planning process for tanks in water distribution systems. The method uses a combination of network reduction, mathematical optimization and hydraulic simulation. The mathematical optimization model is a non-convex Mixed Integer Quadratically Constrained Program (MIQCP) that is solved by a piecewise linearization. As this may lead to many binary variables and therefore high computing times, the size of the water distribution system model is reduced before building the optimization model. After applying several network reduction techniques and using a piecewise approximation of the original model, there may be some hydraulic differences between the original network model and the reduced network model. To make sure that the solution obtained in the optimization process is feasible in the original water distribution system model, the solution is verified by a hydraulic simulation. If the solution is not feasible, the reduced model has to be modified and solved again until the hydraulic simulation verifies a solution as feasible. In this paper, each of these processes is described and the results indicate the usefulness of each of them.