A novel method of embedding distributed optical fiber sensor for structural health monitoring

A distributed optical fiber sensor based on Brillouin scattering (BOTDR or BOTDA) can measure and monitor strain and temperature generated along optical fiber. Because it can measure in real-time with high precision and stability, it is quite suitable for health monitoring of large-scale civil infrastructures. However, the main challenge of applying it to structural health monitoring is to ensure it is robust and can be repaired by adopting a suitable embedding method. In this paper, a novel method based on air-blowing and vacuum grouting techniques for embedding long-distance optical fiber sensors was developed. This method had no interference with normal concrete construction during its installation, and it could easily replace the long-distance embedded optical fiber sensor (LEOFS). Two stages of static loading tests were applied to investigate the performance of the LEOFS. The precision and the repeatability of the LEOFS were studied through an overloading test. The durability and the stability of the LEOFS were confirmed by a corrosion test. The strains of the LEOFS were used to evaluate the reinforcing effect of carbon fiber reinforced polymer and thereby the health state of the beams.

Resolution theory, and static and frequency-dependent cross-talk in piezoresponse force microscopy

Probing the functionality of materials locally by means of scanning probe microscopy (SPM) requires a reliable framework for identifying the target signal and separating it from the effects of surface morphology and instrument non-idealities, e.g. instrumental and topographical cross-talk. Here we develop a linear resolution theory framework in order to describe the cross-talk effects, and apply it for elucidation of frequency-dependent cross-talk mechanisms in piezoresponse force microscopy. The use of a band excitation method allows electromechanical/electrical and mechanical/topographic signals to be unambiguously separated. The applicability of a functional fit approach and multivariate statistical analysis methods for identification of data in band excitation SPM is explored.

A New Android Malware Detection Method Using Bayesian Classification

Mobile malware has been growing in scale and complexity as smartphone usage continues to rise. Android has surpassed other mobile platforms as the most popular whilst also witnessing a dramatic increase in malware targeting the platform. A worrying trend that is emerging is the increasing sophistication of Android malware to evade detection by traditional signature-based scanners. As such, Android app marketplaces remain at risk of hosting malicious apps that could evade detection before being downloaded by unsuspecting users. Hence, in this paper we present an effective approach to alleviate this problem based on Bayesian classification models obtained from static code analysis. The models are built from a collection of code and app characteristics that provide indicators of potential malicious activities. The models are evaluated with real malware samples in the wild and results of experiments are presented to demonstrate the effectiveness of the proposed approach.

Fusion of Static and Temporal Information for Threat Evaluation in Sensor Networks

In many CCTV and sensor network based intelligent surveillance systems, a number of attributes or criteria are used to individually evaluate the degree of potential threat of a suspect. The outcomes for these attributes are in general from analytical algorithms where data are often pervaded with uncertainty and incompleteness. As a result, such individual threat evaluations are often inconsistent, and individual evaluations can change as time elapses. Therefore, integrating heterogeneous threat evaluations with temporal influence to obtain a better overall evaluation is a challenging issue. So far, this issue has rarely be considered by existing event reasoning frameworks under uncertainty in sensor network based surveillance. In this paper, we first propose a weighted aggregation operator based on a set of principles that constraints the fusion of individual threat evaluations. Then, we propose a method to integrate the temporal influence on threat evaluation changes. Finally, we demonstrate the usefulness of our system with a decision support event modeling framework using an airport security surveillance scenario.

Experimental and Numerical Benchmarking of an Improved Impeller Meanline Modelling Method for Automotive Turbocharger Centrifugal Compressors

After the development of a new single-zone meanline modelling technique, benchmarking of the technique and the modelling methods used during its development are presented. The new meanline model had been developed using the results of three automotive turbocharger centrifugal compressors, and single passage CFD models based on their geometry.

The target of the current study was to test the new meanline modelling method on two new centrifugal compressor stages, again from the automotive turbocharger variety. Furthermore the single passage CFD modelling method used in the previous study would be again employed here and also benchmarked.

The benchmarking was twofold; firstly test the overall performance prediction accuracy of the single-zone meanline model. Secondly, test the detailed performance estimation of the CFD model using detailed interstage static pressure tappings.

The final component of this study exposed the weaknesses in the current modelling methods used (explicitly during this study). The non-axisymmetric flow field at the leading and trailing edges for the two compressors was measured and is presented here for the complete compressor map, highlighting the distortion relative to the tongue.

Evaluation of La1−xSrxMnO3 (0 ≤ x < 0.4) synthesised via a modified sol–gel method as mediators for magnetic fluid hyperthermia

A range of lanthanum strontium manganates (La1−xSrxMnO3–LSMO) where 0 ≤ x < 0.4 were prepared using a modified peroxide sol–gel synthesis method. The magnetic nanoparticle (MNP) clusters obtained for each of the materials were characterised using scanning electron microscopy (SEM), X-ray powder diffraction (XRD) and infra-red (IR) spectroscopy in order to confirm the crystalline phases, crystallite size and cluster morphology. The magnetic properties of the materials were assessed using the Superconducting quantum interference device (SQUID) to evaluate the magnetic susceptibility, Curie temperature (Tc) and static hysteretic losses. Induction heating experiments also provided an insight into the magnetocaloric effect for each material. The specific absorption rate (SAR) of the materials was evaluated experimentally and via numerical simulations. The magnetic properties and heating data were linked with the crystalline structure to make predictions with respect to the best LSMO composition for mild hyperthermia (41 °C ≤ T ≤ 46 °C). La0.65Sr0.35MnO3, with crystallite diameter of 82.4 nm, (agglomerate size of ∼10 μm), Tc of 89 °C and SAR of 56 W gMn−1 at a concentration 10 mg mL−1 gave the optimal induction heating results (Tmax of 46.7 °C) and was therefore deemed as most suitable for the purposes of mild hyperthermia, vide infra.

Comparison of Two Pollen Counting Methods of Slides from a Hirst Type Volumetric Trap.

Two of the most frequently used methods of pollen counting on slides from Hirst type traps are evaluated in this paper: the transverse traverse method and the longitudinal traverse method. The study was carried out during June–July 1996 and 1997 on slides from a trap at Worcester, UK. Three pollen types were selected for this purpose: Poaceae, Urticaceae and Quercus. The statistical results show that the daily concentrations followed similar trends (p < 0.01, R-values between 0.78–0.96) with both methods during the two years, although the counts were slightly higher using the longitudinal traverses method. Significant differences were observed, however, when the distribution of the concentrations during 24 hour sampling periods was considered. For more detailed analysis, the daily counts obtained with both methods were correlated with the total number of pollen grains for the taxon over the whole slide, in two different situations: high and low concentrations of pollen in the atmosphere. In the case of high concentrations, the counts for all three taxa with both methods are significantly correlated with the total pollen count. In the samples with low concentrations, the Poaceae and Urticaceae counts with both methods are significantly correlated with the total counts, but none of Quercus counts are. Consideration of the results indicates that both methods give a reasonable approximation to the count derived from the slide as a whole. More studies need be done to explore the comparability of counting methods in order to work towards a Universal Methodology in Aeropalynology.

An efficient method for optimal location and sizing of fixed and switched shunt capacitors in large distribution systems

This paper proposes a computationally efficient methodology for the optimal location and sizing of static and switched shunt capacitors in large distribution systems. The problem is formulated as the maximization of the savings produced by the reduction in energy losses and the avoided costs due to investment deferral in the expansion of the network. The proposed method selects the nodes to be compensated, as well as the optimal capacitor ratings and their operational characteristics, i.e. fixed or switched. After an appropriate linearization, the optimization problem was formulated as a large-scale mixed-integer linear problem, suitable for being solved by means of a widespread commercial package. Results of the proposed optimizing method are compared with another recent methodology reported in the literature using two test cases: a 15-bus and a 33-bus distribution network. For the both cases tested, the proposed methodology delivers better solutions indicated by higher loss savings, which are achieved with lower amounts of capacitive compensation. The proposed method has also been applied for compensating to an actual large distribution network served by AES-Venezuela in the metropolitan area of Caracas. A convergence time of about 4 seconds after 22298 iterations demonstrates the ability of the proposed methodology for efficiently handling large-scale compensation problems.

Direct-on-line axial flux permanent magnet synchronous generator static and dynamic performance

In distributed energy production, permanent magnet synchronous generators (PMSG) are often connected to the grid via frequency converters, such as voltage source line converters. The price of the converter may constitute a large part of the costs of a generating set. Some of the permanent magnet synchronous generators with converters and traditional separately excited synchronous generators couldbe replaced by direct-on-line (DOL) non-controlled PMSGs. Small directly networkconnected generators are likely to have large markets in the area of distributed electric energy generation. Typical prime movers could be windmills, watermills and internal combustion engines. DOL PMSGs could also be applied in island networks, such as ships and oil platforms. Also various back-up power generating systems could be carried out with DOL PMSGs. The benefits would be a lower priceof the generating set and the robustness and easy use of the system. The performance of DOL PMSGs is analyzed. The electricity distribution companies have regulations that constrain the design of the generators being connected to the grid. The general guidelines and recommendations are applied in the analysis. By analyzing the results produced by the simulation model for the permanent magnet machine, the guidelines for efficient damper winding parameters for DOL PMSGs are presented. The simulation model is used to simulate grid connections and load transients. The damper winding parameters are calculated by the finite element method (FEM) and determined from experimental measurements. Three-dimensional finite element analysis (3D FEA) is carried out. The results from the simulation model and 3D FEA are compared with practical measurements from two prototype axial flux permanent magnet generators provided with damper windings. The dimensioning of the damper winding parameters is case specific. The damper winding should be dimensioned based on the moment of inertia of the generating set. It is shown that the damper winding has optimal values to reach synchronous operation in the shortest period of time after transient operation. With optimal dimensioning, interferenceon the grid is minimized.

Energy-Efficient Cluster based Routing Schemes for Static and Mobile Sensor Networks

The theme of the thesis is centred around one important aspect of wireless sensor networks; the energy-efficiency.The limited energy source of the sensor nodes calls for design of energy-efficient routing protocols. The schemes for protocol design should try to minimize the number of communications among the nodes to save energy. Cluster based techniques were found energy-efficient. In this method clusters are formed and data from different nodes are collected under a cluster head belonging to each clusters and then forwarded it to the base station.Appropriate cluster head selection process and generation of desirable distribution of the clusters can reduce energy consumption of the network and prolong the network lifetime. In this work two such schemes were developed for static wireless sensor networks.In the first scheme, the energy wastage due to cluster rebuilding incorporating all the nodes were addressed. A tree based scheme is presented to alleviate this problem by rebuilding only sub clusters of the network. An analytical model of energy consumption of proposed scheme is developed and the scheme is compared with existing cluster based scheme. The simulation study proved the energy savings observed.The second scheme concentrated to build load-balanced energy efficient clusters to prolong the lifetime of the network. A voting based approach to utilise the neighbor node information in the cluster head selection process is proposed. The number of nodes joining a cluster is restricted to have equal sized optimum clusters. Multi-hop communication among the cluster heads is also introduced to reduce the energy consumption. The simulation study has shown that the scheme results in balanced clusters and the network achieves reduction in energy consumption.The main conclusion from the study was the routing scheme should pay attention on successful data delivery from node to base station in addition to the energy-efficiency. The cluster based protocols are extended from static scenario to mobile scenario by various authors. None of the proposals addresses cluster head election appropriately in view of mobility. An elegant scheme for electing cluster heads is presented to meet the challenge of handling cluster durability when all the nodes in the network are moving. The scheme has been simulated and compared with a similar approach.The proliferation of sensor networks enables users with large set of sensor information to utilise them in various applications. The sensor network programming is inherently difficult due to various reasons. There must be an elegant way to collect the data gathered by sensor networks with out worrying about the underlying structure of the network. The final work presented addresses a way to collect data from a sensor network and present it to the users in a flexible way.A service oriented architecture based application is built and data collection task is presented as a web service. This will enable composition of sensor data from different sensor networks to build interesting applications. The main objective of the thesis was to design energy-efficient routing schemes for both static as well as mobile sensor networks. A progressive approach was followed to achieve this goal.

A semi-automatic method for segmentation and 3D modeling of glioma tumors from brain MRI

This work presents an efficient method for volume rendering of glioma tumors from segmented 2D MRI Datasets with user interactive control, by replacing manual segmentation required in the state of art methods. The most common primary brain tumors are gliomas, evolving from the cerebral supportive cells. For clinical follow-up, the evaluation of the pre- operative tumor volume is essential. Tumor portions were automatically segmented from 2D MR images using morphological filtering techniques. These seg- mented tumor slices were propagated and modeled with the software package. The 3D modeled tumor consists of gray level values of the original image with exact tumor boundary. Axial slices of FLAIR and T2 weighted images were used for extracting tumors. Volumetric assessment of tumor volume with manual segmentation of its outlines is a time-consuming proc- ess and is prone to error. These defects are overcome in this method. Authors verified the performance of our method on several sets of MRI scans. The 3D modeling was also done using segmented 2D slices with the help of a medical software package called 3D DOCTOR for verification purposes. The results were validated with the ground truth models by the Radi- ologist.

An improved method for discovering link criticality in transport networks

Quantitatively assessing the importance or criticality of each link in a network is of practical value to operators, as that can help them to increase the network's resilience, provide more efficient services, or improve some other aspect of the service. Betweenness is a graph-theoretical measure of centrality that can be applied to communication networks to evaluate link importance. However, as we illustrate in this paper, the basic definition of betweenness centrality produces inaccurate estimations as it does not take into account some aspects relevant to networking, such as the heterogeneity in link capacity or the difference between node-pairs in their contribution to the total traffic. A new algorithm for discovering link centrality in transport networks is proposed in this paper. It requires only static or semi-static network and topology attributes, and yet produces estimations of good accuracy, as verified through extensive simulations. Its potential value is demonstrated by an example application. In the example, the simple shortest-path routing algorithm is improved in such a way that it outperforms other more advanced algorithms in terms of blocking ratio

Simple finite field nuclear relaxation method for calculating vibrational contribution to degenerate four-wave mixing

A simple extended finite field nuclear relaxation procedure for calculating vibrational contributions to degenerate four-wave mixing (also known as the intensity-dependent refractive index) is presented. As a by-product one also obtains the static vibrationally averaged linear polarizability, as well as the first and second hyperpolarizability. The methodology is validated by illustrative calculations on the water molecule. Further possible extensions are suggested

Variational calculation of static and dynamic vibrational nonlinear optical properties

The vibrational configuration interaction method used to obtain static vibrational (hyper)polarizabilities is extended to dynamic nonlinear optical properties in the infinite optical frequency approximation. Illustrative calculations are carried out on H2 O and N H3. The former molecule is weakly anharmonic while the latter contains a strongly anharmonic umbrella mode. The effect on vibrational (hyper)polarizabilities due to various truncations of the potential energy and property surfaces involved in the calculation are examined

Multi-objective optimization scheme for static and dynamic multicast flows

Muchas de las nuevas aplicaciones emergentes de Internet tales como TV sobre Internet, Radio sobre Internet,Video Streamming multi-punto, entre otras, necesitan los siguientes requerimientos de recursos: ancho de banda consumido, retardo extremo-a-extremo, tasa de paquetes perdidos, etc. Por lo anterior, es necesario formular una propuesta que especifique y provea para este tipo de aplicaciones los recursos necesarios para su buen funcionamiento. En esta tesis, proponemos un esquema de ingeniería de tráfico multi-objetivo a través del uso de diferentes árboles de distribución para muchos flujos multicast. En este caso, estamos usando la aproximación de múltiples caminos para cada nodo egreso y de esta forma obtener la aproximación de múltiples árboles y a través de esta forma crear diferentes árboles multicast. Sin embargo, nuestra propuesta resuelve la fracción de la división del tráfico a través de múltiples árboles. La propuesta puede ser aplicada en redes MPLS estableciendo rutas explícitas en eventos multicast. En primera instancia, el objetivo es combinar los siguientes objetivos ponderados dentro de una métrica agregada: máxima utilización de los enlaces, cantidad de saltos, el ancho de banda total consumido y el retardo total extremo-a-extremo. Nosotros hemos formulado esta función multi-objetivo (modelo MHDB-S) y los resultados obtenidos muestran que varios objetivos ponderados son reducidos y la máxima utilización de los enlaces es minimizada. El problema es NP-duro, por lo tanto, un algoritmo es propuesto para optimizar los diferentes objetivos. El comportamiento que obtuvimos usando este algoritmo es similar al que obtuvimos con el modelo. Normalmente, durante la transmisión multicast los nodos egresos pueden salir o entrar del árbol y por esta razón en esta tesis proponemos un esquema de ingeniería de tráfico multi-objetivo usando diferentes árboles para grupos multicast dinámicos. (en el cual los nodos egresos pueden cambiar durante el tiempo de vida de la conexión). Si un árbol multicast es recomputado desde el principio, esto podría consumir un tiempo considerable de CPU y además todas las comuicaciones que están usando el árbol multicast serán temporalmente interrumpida. Para aliviar estos inconvenientes, proponemos un modelo de optimización (modelo dinámico MHDB-D) que utilice los árboles multicast previamente computados (modelo estático MHDB-S) adicionando nuevos nodos egreso. Usando el método de la suma ponderada para resolver el modelo analítico, no necesariamente es correcto, porque es posible tener un espacio de solución no convexo y por esta razón algunas soluciones pueden no ser encontradas. Adicionalmente, otros tipos de objetivos fueron encontrados en diferentes trabajos de investigación. Por las razones mencionadas anteriormente, un nuevo modelo llamado GMM es propuesto y para dar solución a este problema un nuevo algoritmo usando Algoritmos Evolutivos Multi-Objetivos es propuesto. Este algoritmo esta inspirado por el algoritmo Strength Pareto Evolutionary Algorithm (SPEA). Para dar una solución al caso dinámico con este modelo generalizado, nosotros hemos propuesto un nuevo modelo dinámico y una solución computacional usando Breadth First Search (BFS) probabilístico. Finalmente, para evaluar nuestro esquema de optimización propuesto, ejecutamos diferentes pruebas y simulaciones. Las principales contribuciones de esta tesis son la taxonomía, los modelos de optimización multi-objetivo para los casos estático y dinámico en transmisiones multicast (MHDB-S y MHDB-D), los algoritmos para dar solución computacional a los modelos. Finalmente, los modelos generalizados también para los casos estático y dinámico (GMM y GMM Dinámico) y las propuestas computacionales para dar slución usando MOEA y BFS probabilístico.