Feasibility study of automated detection of tunnel excavation by Brillouin optical time domain reflectometry

Cross-borders smuggling tunnels enable unmonitored movement of people, drugs and weapons and pose a very serious threat to homeland security. Recent advances in strain measurements using optical fibers allow the development of smart underground security fences that could detect the excavation of smuggling tunnels. This paper presents the first stages in the development of such a fence using Brillouin optical time domain reflectometry (BOTDR). Two fiber optic layouts are considered and evaluated in a feasibility study that includes evaluation of false detection and sensitivity: (1) horizontally laid fiber buried at a shallow depth, and (2) fibers embedded in vertical mini-piles. In the simulation study, two different ground displacement models are used in order to evaluate the robustness of the system against imperfect modeling. In both cases, soil–fiber and soil-structure interactions are considered. Measurement errors, and surface disturbances (obtained from a field test) are also included in the calibration and validation stages of the system. The proposed detection system is based on wavelet decomposition of the BOTDR signal, followed by a neural network that is trained to recognize the tunnel signature in the wavelet coefficients. The results indicate that the proposed system is capable of detecting even small tunnel (0.5 m diameter) as deep as 20 m (under the horizontal fiber) or as far as 10 m aside from the mini-pile (vertical fiber), if the volume loss is greater than 0.5%.     

Cell-based dynamic heat exchanger models—Direct determination of the cell number and size

Large amounts of thermal energy are transferred between fluids for heating or cooling in industry as well as in the residential and service sectors. Typical examples are crude oil preheating, ethylene plants, pulp and paper plants, breweries, plants with exothermic and endothermic reactions, space heating, and cooling or refrigeration of food and beverages. Heat exchangers frequently operate under varying conditions. Their appropriate use in flexible heat exchanger networks as well as maintenance/reliability related calculations requires adequate models for estimating their dynamic behaviour. Cell-based dynamic models are very often used to represent heat exchangers with varying arrangements. The current paper describes a direct method and a visualisation technique for determining the number of the modelling cells and their size.     

Using the biophysical CHARMED model to elucidate the underpinnings of contrast in diffusional kurtosis analysis of diffusion-weighted MRI

Object

The aim of this work was to understand biophysical substrate underpinning contrast in diffusional kurtosis imaging (DKI) in white matter, using the composite hindered and restricted model of diffusion (CHARMED).

Materials and methods

A theoretical relationship between the kurtosis function K and the CHARMED parameters, i.e., the restricted volume fraction RF and the axonal longitudinal diffusivity D was derived for the propagator used in the CHARMED model. Evidence for a similar correlation between these measures was then investigated in vivo across different WM regions in five healthy young subjects that underwent a CHARMED protocol at 3T.

Results

Our theoretical treatment shows that K has an increasing trend for both increasing RF values and increasing D. In vivo, a significant positive correlation (P?K _⊥ and RF. A multilinear regression showed that K _⊥ values are better explained by a mixed contribution of both RF and D.

Conclusions

The CHARMED model was used to understand whether and where DKI contrast can be explained in terms of the underlying axonal geometry. This work demonstrates that the information contained in DKI overlaps with the information extracted by CHARMED in areas of higher intra-voxel directional coherence.     

Simulation and experimental study for an inverted trickle solar still

An experimental study for an inverted trickle solar still was performed. The still was basically composed of an inclined absorber plate painted black on the top. Saline water flowed at the backside of the plate and was kept attached to the plate. The water flow rate was kept low so that its temperature was raised to produce vapor. Condensation took place in another compartment where a heat exchanger was placed to provide heat recovery. The still was tested using brackish water of 6000 ppm salinity during the month of November at 47° and 32° tilt angles. The condensate obtained was 2.8 and 2 L/d at the above angles, respectively. This represents an 18% increase in this kind of output over previous work, which is due to reduction in the salinity of feed water. However, the intermediate header production, which is saline water of reduced salinity (3600 ppm), was also reduced by 13%. A computer simulation program was developed to predict the performance of the still.     

Antibacterial and antiviral activity of camel milk protective proteins.

Lysozyme (LZ), lactoferrin (LF), lactoperoxidase (LP), immunoglobulin G and secretory immunoglobulin A were extracted from camel milk. The activity of these protective proteins was assayed against Lactococcus lactis subsp. cremoris, Escherichia coli, Staphylococcus aureus, Salmonella typhimurium and rotavirus. Comparative activities of egg white LZ, bovine LZ and bovine LF are also presented. The antibacterial activity spectrum of camel milk LZ was similar to that of egg white LZ, and differed from bovine milk LZ. Bovine and camel milk LF antibacterial activity spectra were similar. The camel milk LP was bacteriostatic against the Gram-positive strains and was bactericidal against Gram-negative cultures. The immunoglobulins had little effect against the bacteria but high titres of antibodies against rotavirus were found in camel milk. The LP system was ineffective against rotavirus.     

Computerized generation of technological structures

This paper introduces an algorithm which can determine the technology structure containing given chemical technological steps and producing given final products from given initial inlet materials.

With the aid of the algorithm all solutions of the problem or the solution with minimal sum of weights can be obtained. In the latter the user assigns weight factors to the different technological steps. It is also possible to determine all solutions haveing a sum of weights not greater than a limit given by the user. The algorithm and the datastructure introduced provide grounds for designing technologies with multi-component materials and recirculations.     

Compact samples for data dissemination

We consider data dissemination in a peer-to-peer network, where each user wishes to obtain some subset of the available information objects. In most of the modern algorithms for such data dissemination, the users periodically obtain samples of peer IDs (possibly with some summary of their content). They then use the samples for connecting to other peers and downloading data pieces from them. For a set O of information objects, we call a sample of peers, containing at least k possible providers for each object oO, a k-sample.In order to balance the load, the k-samples should be fair, in the sense that for every object, its providers should appear in the sample with equal probability. Also, since most algorithms send fresh samples frequently, the size of the k-samples should be as small as possible, to minimize communication overhead. We describe in this paper two novel techniques for generating fair and small k-samples in a P2P setting. The first is based on a particular usage of uniform sampling and has the advantage that it allows to build on standard P2P uniform sampling tools. The second is based on non-uniform sampling and requires more particular care, but is guaranteed to generate the smallest possible fair k-sample. The two algorithms exploit available dependencies between information objects to reduce the sample size, and are proved, both theoretically and experimentally, to be extremely effective.     

Providing <Emphasis Type="Italic">k</Emphasis>-anonymity in data mining

In this paper we present extended definitions of k-anonymity and use them to prove that a given data mining model does not violate the k-anonymity of the individuals represented in the learning examples. Our extension provides a tool that measures the amount of anonymity retained during data mining. We show that our model can be applied to various data mining problems, such as classification, association rule mining and clustering. We describe two data mining algorithms which exploit our extension to guarantee they will generate only k-anonymous output, and provide experimental results for one of them. Finally, we show that our method contributes new and efficient ways to anonymize data and preserve patterns during anonymization.