Spatially-multiplexed fibre-optic Bragg grating strain and temperature sensor system based on interferometric wavelength-shift detection

A prototype fibre-optic system using interferometric wavelength-shift detection, capable of multiplexing up to 32 fibre-optic Bragg grating strain and temperature sensors with identical characteristics, has been demonstrated. This system is based on a spatially multiplexed scheme for use with fibre-based low-coherence interferometric sensors, reported previously. Four fibre-optic Bragg grating channels using the same fibre grating have been demonstrated for measuring quasi-static strain and temperature.

Probabilistic multiple model neural network based leak detection system:experimental study

This paper presents an effective decision making system for leak detection based on multiple generalized linear models and clustering techniques. The training data for the proposed decision system is obtained by setting up an experimental pipeline fully operational distribution system. The system is also equipped with data logging for three variables; namely, inlet pressure, outlet pressure, and outlet flow. The experimental setup is designed such that multi-operational conditions of the distribution system, including multi pressure and multi flow can be obtained. We then statistically tested and showed that pressure and flow variables can be used as signature of leak under the designed multi-operational conditions. It is then shown that the detection of leakages based on the training and testing of the proposed multi model decision system with pre data clustering, under multi operational conditions produces better recognition rates in comparison to the training based on the single model approach. This decision system is then equipped with the estimation of confidence limits and a method is proposed for using these confidence limits for obtaining more robust leakage recognition results.

Key Agreement Protocol (KAP) Based on Matrix Power Function

* Work is partially supported by the Lithuanian State Science and Studies Foundation.

Long-period fibre grating based biosensor for detection of DNA hybridisation

We implement an optical biosensor using long-period fibre grating immobilised with probe DNA. It has been used to detect hybridisation of target DNA, showing a high sensitivity and reusability function.

Self-Learning Fuzzy Spiking Neural Network as a Nonlinear Pulse-Position Threshold Detection Dynamic System Based on Second-Order Critically Damped Response Units

Architecture and learning algorithm of self-learning spiking neural network in fuzzy clustering task are outlined. Fuzzy receptive neurons for pulse-position transformation of input data are considered. It is proposed to treat a spiking neural network in terms of classical automatic control theory apparatus based on the Laplace transform. It is shown that synapse functioning can be easily modeled by a second order damped response unit. Spiking neuron soma is presented as a threshold detection unit. Thus, the proposed fuzzy spiking neural network is an analog-digital nonlinear pulse-position dynamic system. It is demonstrated how fuzzy probabilistic and possibilistic clustering approaches can be implemented on the base of the presented spiking neural network.

Real-time detection of DNA interactions with long-period fiber-grating-based biosensor

Using an optical biosensor based on a dual-peak long-period fiber grating, we have demonstrated the detection of interactions between biomolecules in real time. Silanization of the grating surface was successfully realized for the covalent immobilization of probe DNA, which was subsequently hybridized with the complementary target DNA sequence. It is interesting to note that the DNA biosensor was reusable after being stripped off the hybridized target DNA from the grating surface, demonstrating a function of multiple usability. © 2007 Optical Society of America.

Classification Trees as a Technique for Creating Anomaly-Based Intrusion Detection Systems

Intrusion detection is a critical component of security information systems. The intrusion detection process attempts to detect malicious attacks by examining various data collected during processes on the protected system. This paper examines the anomaly-based intrusion detection based on sequences of system calls. The point is to construct a model that describes normal or acceptable system activity using the classification trees approach. The created database is utilized as a basis for distinguishing the intrusive activity from the legal one using string metric algorithms. The major results of the implemented simulation experiments are presented and discussed as well.

Dehydroacetic acid based dioxaborine styryl dye:effective fluorescent probe for ammonia and amine detection

The newly synthesized dioxaborine dyes, derivatives of dehydroacetic acid, were tested for the detection of amines and ammonia. To discriminate the substance with efficient sensing parameters, series of ca. 20 dioxaborine dyes were synthesized and tested for reactivity with amines. The most promising one showed the fluorescent sensitivity to amines in the range of 1-4 ppm. © (2014) Trans Tech Publications.

Early Detection of Emergent Events Based on an Extremal Process Approach

2000 Mathematics Subject Classification: Primary 60G70, 62F03.

A sensing mechanism for the detection of carbon nanotubes using selective photoluminescent probes based on ionic complexes with organic dyes

The multifunctional properties of carbon nanotubes (CNTs) make them a powerful platform for unprecedented innovations in a variety of practical applications. As a result of the surging growth of nanotechnology, nanotubes present a potential problem as an environmental pollutant, and as such, an efficient method for their rapid detection must be established. Here, we propose a novel type of ionic sensor complex for detecting CNTs – an organic dye that responds sensitively and selectively to CNTs with a photoluminescent signal. The complexes are formed through Coulomb attractions between dye molecules with uncompensated charges and CNTs covered with an ionic surfactant in water. We demonstrate that the photoluminescent excitation of the dye can be transferred to the nanotubes, resulting in selective and strong amplification (up to a factor of 6) of the light emission from the excitonic levels of CNTs in the near-infrared spectral range, as experimentally observed via excitation-emission photoluminescence (PL) mapping. The chirality of the nanotubes and the type of ionic surfactant used to disperse the nanotubes both strongly affect the amplification; thus, the complexation provides sensing selectivity towards specific CNTs. Additionally, neither similar uncharged dyes nor CNTs covered with neutral surfactant form such complexes. As model organic molecules, we use a family of polymethine dyes with an easily tailorable molecular structure and, consequently, tunable absorbance and PL characteristics. This provides us with a versatile tool for the controllable photonic and electronic engineering of an efficient probe for CNT detection.

A rule-based approach to implicit emotion detection in text

Most research in the area of emotion detection in written text focused on detecting explicit expressions of emotions in text. In this paper, we present a rule-based pipeline approach for detecting implicit emotions in written text without emotion-bearing words based on the OCC Model. We have evaluated our approach on three different datasets with five emotion categories. Our results show that the proposed approach outperforms the lexicon matching method consistently across all the three datasets by a large margin of 17–30% in F-measure and gives competitive performance compared to a supervised classifier. In particular, when dealing with formal text which follows grammatical rules strictly, our approach gives an average F-measure of 82.7% on “Happy”, “Angry-Disgust” and “Sad”, even outperforming the supervised baseline by nearly 17% in F-measure. Our preliminary results show the feasibility of the approach for the task of implicit emotion detection in written text.

Channel model and lower capacity bound for the transmission based on nonlinear Fourier transform

The integrability of the nonlinear Schräodinger equation (NLSE) by the inverse scattering transform shown in a seminal work [1] gave an interesting opportunity to treat the corresponding nonlinear channel similar to a linear one by using the nonlinear Fourier transform. Integrability of the NLSE is in the background of the old idea of eigenvalue communications [2] that was resurrected in recent works [3{7]. In [6, 7] the new method for the coherent optical transmission employing the continuous nonlinear spectral data | nonlinear inverse synthesis was introduced. It assumes the modulation and detection of data using directly the continuous part of nonlinear spectrum associated with an integrable transmission channel (the NLSE in the case considered). Although such a transmission method is inherently free from nonlinear impairments, the noisy signal corruptions, arising due to the ampli¯er spontaneous emission, inevitably degrade the optical system performance. We study properties of the noise-corrupted channel model in the nonlinear spectral domain attributed to NLSE. We derive the general stochastic equations governing the signal evolution inside the nonlinear spectral domain and elucidate the properties of the emerging nonlinear spectral noise using well-established methods of perturbation theory based on inverse scattering transform [8]. It is shown that in the presence of small noise the communication channel in the nonlinear domain is the additive Gaussian channel with memory and signal-dependent correlation matrix. We demonstrate that the effective spectral noise acquires colouring", its autocorrelation function becomes slow decaying and non-diagonal as a function of \frequencies", and the noise loses its circular symmetry, becoming elliptically polarized. Then we derive a low bound for the spectral effiency for such a channel. Our main result is that by using the nonlinear spectral techniques one can significantly increase the achievable spectral effiency compared to the currently available methods [9]. REFERENCES 1. Zakharov, V. E. and A. B. Shabat, Sov. Phys. JETP, Vol. 34, 62{69, 1972. 2. Hasegawa, A. and T. Nyu, J. Lightwave Technol., Vol. 11, 395{399, 1993. 3. Yousefi, M. I. and F. R. Kschischang, IEEE Trans. Inf. Theory, Vol. 60, 4312{4328, 2014. 4. Yousefi, M. I. and F. R. Kschischang, IEEE Trans. Inf. Theory, Vol. 60, 4329{4345 2014. 5. Yousefi, M. I. and F. R. Kschischang, IEEE Trans. Inf. Theory, Vol. 60, 4346{4369, 2014. 6. Prilepsky, J. E., S. A. Derevyanko, K. J. Blow, I. Gabitov, and S. K. Turitsyn, Phys. Rev. Lett., Vol. 113, 013901, 2014. 7. Le, S. T., J. E. Prilepsky, and S. K. Turitsyn, Opt. Express, Vol. 22, 26720{26741, 2014. 8. Kaup, D. J. and A. C. Newell, Proc. R. Soc. Lond. A, Vol. 361, 413{446, 1978. 9. Essiambre, R.-J., G. Kramer, P. J. Winzer, G. J. Foschini, and B. Goebel, J. Lightwave Technol., Vol. 28, 662{701, 2010.

Graphene-based D-shaped polymer FBG for highly sensitive erythrocyte detection

Graphene-based silica fiber-optic sensors, with high sensitivity, fast response, and low cost, have shown great promise for gas sensing applications. In this letter, by covering a monolayer of p-doped graphene on a D-shaped microstructured polymer fiber Bragg grating (FBG), we propose and demonstrate a novel biochemical probe sensor, the graphene-based D-shaped polymer FBG (GDPFBG). Due to the graphene-based surface evanescent field enhancement, this sensor shows high sensitivity to detect surrounding biochemical parameters. By monitoring the Bragg peak locations of the GDPFBG online, human erythrocyte (red blood cell) solutions with different cellular concentrations ranging from 0 to 104 ppm were detected precisely, with the maximum resolution of sub-ppm. Such a sensor is structurally compact, is clinically acceptable, and provides good recoverability, offering a state-of-the-art polymer-fiber-based sensing platform for highly sensitive in situ and in vivo cell detection applications.