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In this study, an automatic method based on Triplanar Convolutional Neural Network is proposed for liver tumor segmentation using Computed Tomography (CT) images. The triplanar views consist of axial, sagittal and coronal planes and these three planes are fed into the Convolutional Neural Network input streams to automatically learn discriminative features for segmenting tumor from liver CT images. The preliminary results show that Triplanar Convolutional Neural Network approach has better performance than Single-view Convolutional Neural Network approach in liver tumor segmentation.

The Nurse Rostering Problem is an NP-hard combinatorial optimization, scheduling problem for assigning a set of nurses to shifts per day by considering both hard and soft constraints. A novel metaheuristic technique is required for solving Nurse Rostering Problem (NRP). This work proposes a metaheuristic technique called Directed Bee Colony Optimization Algorithm using the Modified Nelder-Mead Method for solving the NRP. To solve the NRP, the authors used a multiobjective mathematical programming model and proposed a methodology for the adaptation of a Multiobjective Directed Bee Colony Optimization (MODBCO). MODBCO is used successfully for solving the multiobjective problem of optimizing the scheduling problems. This MODBCO is an integration of deterministic local search, multiagent particle system environment, and honey bee decision-making process. The performance of the algorithm is assessed using the standard dataset INRC2010, and it reflects many real-world cases which vary in size and complexity. The experimental analysis uses statistical tools to show the uniqueness of the algorithm on assessment criteria.

Multi objective Quadratic Assignment problem is an NP-Hard complex problem for assigning facilities to locations which significantly influence the transportation cost multitude in real-world applications like facilities location, distributed computing and data analysis. QAP can be solved using metaheuristic algorithm with deterministic and local search by equalising facilities and location. QAP can be applied to decision making framework, economic problems, scheduling to assign and determine services. This work portrays the exhaustive survey of quadratic assignment problem and various methodologies to solve QAP. A comprehensive study has been carried out to solve QAP using optimization algorithms. In this survey many approaches is examined by including multiple objective flow of facilities to locations by using evolutionary algorithm.

The collaborative teleradiology system detailed here would enable multiple medical experts to view, analyze, and discuss regions of interest in medical images remotely. Current research into similar systems have mostly focused on creating effective mechanisms to securely access and store expert opinions on the medical images, with additional work including real-time interaction via web technologies for online discussions. As the popularity and usage of mobile and tablet devices are increasing, the need for a mobile collaborative teleradiology application has arisen. In this paper, we propose an online mobile collaborative medical image discussion prototype using the Android Mobile OS. Development issues and challenges on implementing the proposed Android-based mobile collaborative medical image discussion system prototype are discussed and some promising preliminary results from the early prototype development and testing are also presented.

In object class recognition, the state-of-the-art works shows using combination varies local features may produce a good performance in recognition. These local features may have a different performance on one category to other category which it depends on the richness of local features. Due to that limitation, the shape features of objects are taken into consideration to be combined with local features. In this paper, we use Fourier Descriptor (FD), Elliptical Fourier Descriptors (EFD) and Moment Invariant (MI) as a global shape feature and Scale Invariant Feature Transform (SIFT) as local features. For learning technique, boosting is used in improving the recognition objects. This approach identifies the correct and misclassified dataset iteratively. Experimental results indicate that the recognition model outperform improved the accuracy of classification by up to 10% that is comparable to or better than that of state-of-the-art approaches.

In this paper, we have addressed the issue of over-segmented regions produced in watershed by merging the regions using global feature. The global feature information is obtained from clustering the image in its feature space using Fuzzy C-Means (FCM) clustering. The over-segmented regions produced by performing watershed on the gradient of the image are then mapped to this global information in the feature space. Further to this, the global feature information is optimized using Simulated Annealing (SA). The optimal global feature information is used to derive the similarity criterion to merge the over-segmented watershed regions which are represented by the region adjacency graph (RAG). The proposed method has been tested on digital brain phantom simulated dataset to segment white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF) soft tissues regions. The experiments showed that the proposed method performs statistically better, with average of 95.242% regions are merged, than the immersion watershed and average accuracy improvement of 8.850% in comparison with RAG-based immersion watershed merging using global and local features.

Segmentation of hippocampus in the brain is one of a major challenge in medical image segmentation due to its’ imaging characteristics, with almost similar intensity between another adjacent gray matter structure, such as amygdala. The intensity similarity has causes the hippocampus to have weak or fuzzy boundaries. With this main challenge being demonstrated by hippocampus, a segmentation method that relies on image information alone may not produce accurate segmentation results. Therefore, it is needed an assimilation of prior information such as shape and spatial information into existing segmentation method to produce the expected segmentation. Previous studies has widely integrated prior information into segmentation methods. However, the prior information has been utilized through a global manner integration, and this does not reflect the real scenario during clinical delineation. Therefore, in this paper, a locally integrated prior information into a level set model is presented. This work utilizes a mean shape model to provide automatic initialization for level set evolution, and has been integrated as prior information into the level set model. The local integration of edge based information and prior information has been implemented through an edge weighting map that decides at voxel level which information need to be observed during a level set evolution. The edge weighting map shows which corresponding voxels having sufficient edge information. Experiments shows that the proposed integration of prior information locally into a conventional edge-based level set model, known as geodesic active contour has shown improvement of 9% in averaged Dice coefficient.

Image annotation is an important task in computer vision. The annotated images can be very useful for indexing and retrieval applications. In this paper, we propose a generative model for image annotation based on mixtures of the exponential family of distributions. The distributions considered are the Multivariate Gaussian, Rayleigh, Poisson, Bernoulli and Centered Laplacian. The model leads to a generic algorithm that is able to perform learning in a more efficient and flexible manner. Subsequently, it can be used to evaluate the performance of each distribution in the task of image annotation. The approach is also compared to a discriminative approach (i.e. Support Vector Machine) using the LabelMe dataset for the concepts Buildings, Street, Mountains and Coasts, where promising classification results were reported for some of the concepts.

Automatic road network extraction based on high resolution satellite image for urban planning holds great potential for significant reduction of database development/updating cost and turnaround time. Satellite remote sensing has been recognized worldwide as an effective technology for the monitoring and mapping the urban development. Two approaches for road network extraction for an urban region have been proposed. When an image is considered in original form it is difficult and computationally expensive to extract roads due to presence of other road-like features with straight edges. Hence roads are first extracted as elongated regions by removing bright regions (that mostly represent the buildings, parking lots and other open spaces), non-linear noise segments are removed median filtering (based upon the fact that road networks constitute large number of small linear structures).The roads are then modeled as boundaries and are extracted using Level set and Normalized cuts methods .Finally The extracted roads are overlayed on the original image. The experimental results show that these approaches are efficient in extracting road segments in urban region from high resolution satellite images. Evaluation of the results carried out by comparing the level set and normalized cuts results with manually extracted reference data. The methods were applied on the high resolution IKONOS image of urban area of Hobart, Australia.

Land use and land cover has a leading role in the part of urbanization. As the rapid urbanization led to various activities in a region and these changes generally takes place in the agricultural land. The satellite imageries LANDSAT TM (1990 and 2010) data are used. The scales are 1: 50, 000. From 1990 to 2010 covering a period of 20 years, the aerial distribution of the land use and land cover changes has been observed. The changes were identified, in which the decrease of Agricultural land, open Scrub and Water bodies and increase of Built-up land, Fallow land and current Fallow land. The land use and land cover maps are prepared by using GIS software to evaluate the changes and it showed strong variation. Image pre-processing and supervised technique analysis will be performed to classify the images into different land use categories. Thus, the information of urban growth, land use and land cover change are very useful to local government, urban and town planners, in order to have a planned city with reduction of congestion, pollution and to achieve a sustainable development of the city.

Problem statement: This study proposed multimodal integration method at the concept level to investigate information from multimodalities. The multimodal data was represented as two separate lists of concepts which were extracted from images and its related text. The concepts extracted from image analysis are often ambiguous, while the concepts extracted from text processing could be sense-ambiguous. The major problems that face the integration of the underlying modalities (image and text) were: The difference in the coverage and the difference in the granularity level. Approach: This study proposed a novel application using ontology alignment to unify the underlying ontologies. The said lists of concepts were represented in a structured form within the corresponding ontologies then the two structural lists are enriched and matched based on the alignment, this matching represent the final knowledge. Results: The difference in the coverage was solved in this study using the alignment process and the difference in the granularity level was solved using the enrichment process. Thus, the proposed integration produced accurate integrated results. Conclusion: Thus, integration of these concepts allows the totality of the knowledge be expressed more precisely.

Most supervised neural networks are trained by minimizing the mean square error (MSE) of the training set. In the presence of outliers, the resulting neural network model can differ significantly from the underlying model that generates the data. This paper outlines two robust learning methods for a dynamic structure neural network called incremental growing multi-experts network (IGMN). It is convincingly shown by simulation that by using a scaled robust objective function instead of the least squares function, the influence of the outliers in the training data can be completely eliminated. The network generates a much better approximation in the neighborhood of outliers. Thus, the two proposed robust learning methods namely robust least mean squares (RLMSs) and least mean log squares (LMLSs) are insensitive to the presence of outliers unlike the least mean squares (LMSs) cost function. Moreover, various types of supervised learning algorithms can easily adopt LMLS, which is a parameter-free method.

This paper presents two novel approaches to determine optimum growing multi-experts network (GMN) structure. The first method called direct method deals with expertise domain and levels in connection with local experts. The growing neural gas (GNG) algorithm is used to cluster the local experts. The concept of error distribution is used to apportion error among the local experts. After reaching the specified size of the network, redundant experts removal algorithm is invoked to prune the size of the network based on the ranking of the experts. However, GMN is not ergonomic due to too many network control parameters. Therefore, a self-regulating GMN (SGMN) algorithm is proposed. SGMN adopts self-adaptive learning rates for gradient-descent learning rules. In addition, SGMN adopts a more rigorous clustering method called fully self-organized simplified adaptive resonance theory in a modified form. Experimental results show SGMN obtains comparative or even better performance than GMN in four benchmark examples, with reduced sensitivity to learning parameters setting. Moreover, both GMN and SGMN outperform the other neural networks and statistical models. The efficacy of SGMN is further justified in three industrial applications and a control problem. It provides consistent results besides holding out a profound potential and promise for building a novel type of nonlinear model consisting of several local linear models.

This paper deals with a novel idea of identification of nonlinear dynamic systems via a constructivism inspired neural network. The proposed network is known as growing multi-experts network (GMN). In GMN, the problem space is decomposed into overlapping regions by expertise domain and local expert models are graded according to their expertise level. The network output is computed by the smooth combination of local linear models. In order to avoid over-fitting problem, GMN deploys a redundant experts removal algorithm to remove the redundant local experts from the network. In addition, growing neural gas (GNG) algorithm is used to generate an induced Delaunay triangulation that is highly desired for optimal function approximation. A variety of examples are taken from literature to establish the efficacy of GMN. Discrete time nonlinear dynamic system modeling and water bath temperature control have been found to give excellent results via this novel neural network.

Artificial neural networks (ANNs) have been used to construct empirical nonlinear models of process data. Because networks are not based on physical theory and contain nonlinearities, their predictions are suspect when extrapolating beyond the range of original training data. Standard networks give no indication of possible errors due to extrapolation. This paper describes a sequential supervised learning scheme for the recently formalized Growing multi-experts network (GMN). It is shown that certainty factor can be generated by GMN that can be taken as extrapolation detector for GMN. On-line GMN identification algorithm is presented and its performance is evaluated. The capability of the GMN to extrapolate is also indicated. Four benchmark experiments are dealt with to demonstrate the effectiveness and utility of GMN as a universal function approximator.

To segment an image using the random walks algorithm; users are often required to initialize the approximate lo- cations of the objects and background in the image. Due to its segmenting model that is mainly reflected by the relationship among the neighborhood pixels and its boundary conditions, random walks algorithm has made itself sensitive to the inputs of the seeds. Instead of considering the relationship between the neighborhood pixels solely, an attempt has been made to modify the weighting function that accounts for the intensity changes between the neighborhood nodes. Local affiliation within the defined neighborhood region of the two nodes is taken into consideration by incorporating an extra penalty term into the weighting function. Besides that, to better segment images, particularly medical images with texture features, GLCM variance is incorporated into the weighting function through kernel density estimation (KDE). The probability density of each pixel belonging to the initialized seeds is estimated and integrated into the weighting function. To test the performance of the proposed weighting model, several medical images that mainly made up of 174-brain tumor images are experimented. These experiments establish that the proposed method produces better segmentation results than the original random walks.

The growth of strongly oriented or epitaxial thin films of metal oxides generally requires relatively high growth temperatures or infusion of energy to the growth surface through means such as ion bombardment. We have grown high quality epitaxial thin films of $Co_3O_4$ on different substrates at a temperature as low as 450° C by low pressure metal organic chemical vapor deposition (MOCVD) using cobalt(II) acetylacetonate as the precursor. With oxygen as the reactant gas, polycrystalline $Co_3O_4$ films are formed on glass and Si(100) in the temperature range 350 550° C. Under similar conditions of growth, highly oriented films of $Co_3O_4$ are formed on $SrTiO_3(100)$ and $LaAlO_3(100)$. The film on $LaAlO_3(100)$ grown at 450° C show a rocking curve FWHM of 1.61°, which reduces to 1.32° when it is annealed in oxygen at 725° C. The film on $SrTiO_3(100)$ has a FWHM of 0.33° (as deposited) and 0.29° (after annealing at 725° C). The φ-scan analysis shows cube on cube epitaxy on both these substrates. The quality of epitaxy on $SrTiO_3$ (100) is comparable to the best of the perovskite basedoxide thin films grown at significantly higher temperatures

Recent research suggests that the charge carriers in the paramagnetic state of the magnetoresistive manganites are small polarons. Here we report studies of the oxygen-isotope effects on the intrinsic resistivity and thermoelectric power in several ferromagnetic manganites. The precise measurements of these isotope effects allow us to make a quantitative data analysis. Our results do not support a simple small-polaron model, but rather provide compelling evidence for the presence of small immobile bipolarons, i.e., pairs of small polarons. Since the bipolarons in the manganites are immobile, the present result alone appears not to give a positive support to the bipolaronic superconductivity theory for the copper-based perovskites., 6 pages, 5 figures, monor corrections

We report on the growth of La 0.8 Ce 0.2 MnO 3 thin films on (0 0 1) LaAlO 3 substrates by pulsed laser deposition. CeO 2 as an impurity is present in both the bulk and film samples. The electrical transport and magnetic properties of the films are similar to that of the divalent cation-doped or La deficient LaMnO 3 , which show colossal magnetoresistance. Thermopower measurements indicate that the carriers are holes. The results are explained in terms of a La site deficiency due to the existence of CeO 2 .

We report on resistivity measurements in La{sub 0.67}Ca{sub 0.33}MnO{sub 3} and Nd{sub 0.7}Sr{sub 0.3}MnO{sub 3} thin films in order to elucidate the underlying mechanism for the colossal magnetoresistance behavior. The experimental results are analyzed in terms of quantum phase-transition ideas to study the nature of the metal-insulator transition in manganese oxides. Resistivity curves as functions of magnetization for various temperatures show the absence of scaling behavior expected in a continuous quantum phase transition, which leads us to conclude that the observed metal-insulator transition is most likely a finite temperature crossover phenomenon. (c) 2000 The American Physical Society.

We report on the structural, transport, and magnetic properties of ${\mathrm{La}}_{0.67}{\mathrm{Sr}}_{0.33}{\mathrm{MnO}}_{x}$ thin films grown in vacuum by pulsed-laser deposition. The as-grown thin films have both the matrix ${\mathrm{La}}_{1.34}{\mathrm{Sr}}_{0.66}{\mathrm{MnO}}_{4}$ phase with ${\mathrm{K}}_{2}{\mathrm{NiF}}_{4}$ structure and an embedded MnO phase. The electrical transport and magnetic properties of the films are determined mainly by those of the matrix phase. By annealing, the as-grown thin films can be transformed into the normal ${\mathrm{La}}_{0.67}{\mathrm{Sr}}_{0.33}{\mathrm{MnO}}_{3}$ single phase, which shows the expected colossal magnetoresistance effect. Based on the composition of the matrix phase, and the structural, electrical, and magnetic properties of the films, we propose that the matrix phase is possibly electron doped with a mixed valence of ${\mathrm{Mn}}^{2+}{/\mathrm{M}\mathrm{n}}^{3+}$ instead of the ${\mathrm{Mn}}^{3+}{/\mathrm{M}\mathrm{n}}^{4+}$ as in the hole-doped case.

This paper examines the possibility of enhancing the room temperature magnetoresistance at low applied magnetic fields in single layer La0.7 Ba0.3 MnO3 thin films. The influence of lattice mismatch strain, as well as the effect of different frequency regimes, on the magnetoresistance is explored. The effects of lattice mismatch strain are studied by measuring the magnetoresistance as a function of the La0.7 Ba0.3 MnO3 film thickness, oxygen annealing, and lattice matched buffer layers. We find that the release of the lattice mismatch strain improves the magnetoresistance at room temperature and at low magnetic fields. In fact, the highest magnetoresistance at room temperature (−1.7% at 500 Oe) has been found for the 1600 A as-grown La0.7 Ba0.3 MnO3 film, whereas the largest magnetoresistance (−1.9% at 500 Oe) is found at 309 K for the 1000 A La0.7 Ba0.3 MnO3 film annealed in flowing O2 for 1 h at 900°C. Finally, we find that the microwave magnetoresistance is the same as the dc magnetoresistance when the cavity corrections are applied. In the single layer La0.7 Ba0.3 MnO3 system, the low field magnetoresistance at room temperature is far from being technologically viable.

(110) oriented La1−δMn1−δO3 thin films with different oxygen content were grown on (001) LaAlO3 substrates by pulsed laser deposition. Samples prepared in higher oxygen partial pressures show a ferromagnetic transition around 200 K. The transport is thermally activated with a change in slope at the ferromagnetic transition. Samples prepared and annealed in vacuum show signatures of mixed ferromagnetic and antiferromagnetic phases, and are insulators. The pure antiferromagnetic phase (as expected and observed in bulk materials with optimum oxygen stoichiometry) was not obtained in our experiments, even in the strongly reduced films.

We report on three different experiments on high temperature superconducting (HTS) cuprates and colossal magnetoresistive (CMR) manganites, which clearly bring out some of the important similarities and differences between the two material systems. The experiments involve the measurement of temperature dependence of the mean squared displacement of Cu and Mn ions from their equilibrium site in the case of the cuprates and the manganites, respectively, and their correlation with the transport property. In both cases the key ions in the materials (Cu for HTS and Mn for CMR) exhibit vibration amplitudes larger than that of ions in simple Debye solids and clearly show discontinuities in the vibration amplitudes as a function of temperature close to the phase transition temperatures. These point to the unequivocal participation of phonons in the transport processes and possibly in the onset of the phase transitions (i.e. superconductivity and ferromagnetism). The second set of experiments, involves femtosecond optical excitation of micro-strip resistors made of cuprates or manganites, and the subsequent measurement of the changes in the impedance on a 20 ps time scale. In the case of the manganites one measures the time scales involved in the ionization and reformation of a Jahn-Teller polaron and also the decay times of magnon excitors. In the case of the cuprates one sees a highly efficient pair breaking process with a very sharp resonance, with a width of only 100 meV, which is indicative of the role of a large intermediate excitation in the mechanism of high temperature superconductivity. In the third experiment, spin-polarized electrons injected from a manganite electrode into a superconductor are observed to break pairs at a rate far larger than unpolarized electrons. This effect seems very orientation dependent for the case of YBCO, which may shed new light on the transport of quasi-particles at YBCO interfaces.

The transient photoimpedance response of epitaxial YBa2Cu3O7−δ thin films has been studied using 100 fs Ti:Sapphire laser pulse excitation. Both temperature and photon energy dependence of the fast optical response signal (whose temperature dependence can be explained by a kinetic inductance model involving Cooper pair breaking) were studied. The pair breaking rate is strongly photon energy-dependent, with a resonance around 1.5 eV with a width of only 100 meV, which is very surprising given the strong electron correlation in this metallic system and may be explained in terms of the stripe phase model.

Epitaxial films of La0.7Ca0.3MnO3 have been irradiated with 90 MeV oxygen ions at different dose values ranging from 1011–1014 ions/cm2. The structural, magnetization, and magnetotransport properties have been studied as a function of the ion dose. It is found that the properties change gradually up to a dose of 1013 ions/cm2; however, drastic changes occur when the sample is irradiated at the higher dose of 1014 ions/cm2. Specifically, this sample exhibits a large, nearly temperature independent magnetoresistance in the low temperature regime. The Rutherford backscattering channeling data bring out the presence of defects in the irradiated films. The x-ray diffraction data, the temperature dependence of resistivity and magnetization, and the low temperature magnetic hysterisis data collectively indicate the presence of two different phases in the sample irradiated at 1014 ions/cm2. The surface morphology of this film, observed by atomic force microscopy, exhibits swelling, presumably due to subsurface cl...

Pulsed laser excitation induced conductance changes in colossal magnetoresistance material ${\mathrm{La}}_{0.7}{\mathrm{Ca}}_{0.3}{\mathrm{MnO}}_{3}$ were studied on the picosecond time scale. A two-component signal was seen consisting of a fast positive transient associated with the paramagnetic insulating state and a slower negative signal associated with the ferromagnetic metallic state. The fast component corresponds to the photoionization of the Jahn-Teller small polaron. The slow component is explained in terms of the reduced carrier mobility due to photogenerated magnetic excitations.

Since the rejuvenation of interest in the rare earth manganites owing to their potential use as magnetoresistive sensors, there has been adequate research to arrive at some evaluation of the potent...

We have prepared single phase ${\mathrm{PrBa}}_{2\ensuremath{-}x}{\mathrm{Sr}}_{x}{\mathrm{Cu}}_{3}{\mathrm{O}}_{7}$ ($x=0,$1.3,1.6) thin films with dopant concentration exceeding the solid solubility limit by using the pulsed laser deposition method. The resistivity of the doped thin films decreases with increasing dopant concentration. For $x=1.3,$ the electrical resistivity ratios $\ensuremath{\rho}(4.2\mathrm{}\mathrm{K})/\mathrm{\ensuremath{\rho}}(300\mathrm{}\mathrm{K})=2.56;$ while for $x=1.6,$ $\ensuremath{\rho}(4.2\mathrm{}\mathrm{K})/\mathrm{\ensuremath{\rho}}(300\mathrm{}\mathrm{K})=1.98,$ comparable to that of the ${\mathrm{Y}}_{0.5}{\mathrm{Pr}}_{0.5}{\mathrm{Ba}}_{2}{\mathrm{Cu}}_{3}{\mathrm{O}}_{7}$ sample, which is very close to the insulator-metal transition. Moreover, the resistivity of the ${\mathrm{PrBa}}_{0.4}{\mathrm{Sr}}_{1.6}{\mathrm{Cu}}_{3}{\mathrm{O}}_{7}$ thin film is very close to the Ioffe-Regel limit, also indicating its proximity to the insulator-metal transition. The decrease of the resistivity with doping for ${\mathrm{PrBa}}_{2\ensuremath{-}x}{\mathrm{Sr}}_{x}{\mathrm{Cu}}_{3}{\mathrm{O}}_{7}$ can be explained by the decrease of the hybridization between Pr $4f$ and O $2p$ states in the ${\mathrm{CuO}}_{2}$ planes due to the Sr doping induced increase of the Pr-O bond length.

The effect of laser power on the transient response of photoimpedance and the in situ sample temperature is studied for epitaxial YBa2Cu3O7−δ (YBCO) films at a wavelength of 810 nm using 100 fs laser pulses. The temperature dependences of the dc resistance and the amplitudes of the fast and slow photoresponse signals were measured simultaneously. For laser energy density of 20 μJ/cm2 per pulse (average power 22 mW), the average sample temperature is found to increase by about 1 K for 300 nm thick YBCO film with 0.5 mm thick LaAlO3 substrate as shown by the shift of resistance versus temperature curves. Calculations of time constant show that heat diffusion in LaAlO3 is the bottleneck for heat escape which causes the observed increase of the sample temperature. The amplitudes of both slow and fast signals show a peak in the temperature dependence curves near the superconducting transition temperature; and the peak temperature decreases, while the peak amplitude increases with laser power. At 82 K, the lase...

We have measured the angular dependence of the critical current density (J{sub c}) on magnetic field and temperature in untwinned a-axis-oriented YBa{sub 2}Cu{sub 3}O{sub 7{minus}x} films. The direction of magnetic field with respect to the crystallographic axes was found to be the dominant factor determining the behavior of J{sub c}. J{sub c}({theta}) measurements, for currents driven along the b direction, yielded a peak at 0{degree} corresponding to the magnetic field applied parallel to the CuO{sub 2} planes. For supercurrents flowing along the c direction, a crossover from grain-boundary pinning to surface and interface pinning was observed as temperatures approached T{sub c}. Lawrence-Doniach and Tinkham H{sub c2}({theta}) models were used to fit our J{sub c}({theta}) data by simply replacing H{sub c2}({theta}) with J{sub c}({theta}). These models fit our J{sub c}({theta}) data very well, at high and medium-to-low temperature ranges, respectively. {copyright} {ital 1997} {ital The American Physical Society}

In order to obtain an enhancement of low field magnetoresistance (MR) in Nd/sub 0.7/Sr/sub 0.3/MnO/sub 3/ (NSMO) films, two kinds of superconducting flux focusing devices made of YBa/sub 2/Cu/sub 3/O/sub 7/ (YBCO) have been fabricated. In the superconducting state, YBCO expels magnetic flux from its interior and focuses the magnetic flux on a bridge of NSMO film. Using such a magnetic "lens", at temperatures below 77 K, /spl sim/900% enhancement in MR was observed. This corresponds to more than 15% change in the MR of NSMO in the presence of a couple of hundred Gauss. In order to successfully integrate high-T/sub c/ superconductivity with the magnetoresistive effect, bilayers of YBCO/NSMO were in situ deposited on (100) LaAlO/sub 3/ substrates by pulsed laser deposition so that the peak resistance temperature (T/sub p/) of NSMO was below the superconducting transition temperature (T/sub c/) of YBCO. X-ray diffraction and Rutherford Backscattering Spectroscopy (RBS) measurements provide evidence of epitaxial growth of YBCO/NSMO heterostructures.

We studied the effects of Co doping on the intrinsic anisotropic properties of aligned a-axis YBa/sub 2/Cu/sub 3-x/Co/sub x/O/sub 7-/spl delta// films pulsed laser deposited on (100) LaSrGaO/sub 4/ substrates We used X-ray-absorption fine structure analysis and resistivity data to determine the quality of Co incorporation. Higher deposition pressures provided with better Co dopant incorporation but smaller grain size. However at lower pressures Co incorporation can still be achieved by down the cooling process. For transport along the c-direction, Co dopant causes reduction interlayer coupling as evidenced by an increase resistive anisotropy (/spl rho//sub c///spl rho//sub b/) with increasing level of Co incorporation, Co doping level of x=0.22 effectively doubles the resistive anisotropy of YBa/sub 2/Cu/sub 3/O/sub 7-/spl delta// films (from -18 to -40 at 100 K).

We have studied the role of pinning in the mixed-state thermomagnetic transport properties of $\mathrm{Y}{\mathrm{Ba}}_{2}{\mathrm{Cu}}_{3}{\mathrm{O}}_{7\ensuremath{-}\ensuremath{\delta}}$. We demonstrate the pinning independence of the transport entropy ${S}_{\ensuremath{\varphi}}$, and its consequent scaling within an anisotropic mass model. Due to the anisotropy of $\mathrm{Y}{\mathrm{Ba}}_{2}{\mathrm{Cu}}_{3}{\mathrm{O}}_{7\ensuremath{-}\ensuremath{\delta}}$ the extrinsic pinning strength effectively decreases as we rotate the magnetic field into the $\mathrm{ab}$ plane. The Nernst ($\frac{{E}_{y}}{{\ensuremath{\nabla}}_{x}T}$) and Seebeck ($\frac{{E}_{x}}{{\ensuremath{\nabla}}_{x}T}$) effects are enhanced as we reduce the effective pinning, yet the transport entropy ${S}_{\ensuremath{\varphi}}\ensuremath{\propto}\frac{(\frac{{E}_{y}}{{\ensuremath{\nabla}}_{x}T})}{{\ensuremath{\rho}}_{\mathrm{xx}}}$, the ratio of the Nernst and Seebeck signals, and the ratio of Seebeck and longitudinal resistivity ${\ensuremath{\rho}}_{\mathrm{xx}}$ are unchanged, similar to the pinning independence observed for the Hall conductivity ${\ensuremath{\sigma}}_{\mathrm{xy}}$. These results can be explained within a simple phenomenological model of vortex dynamics.

The normal state and transition edge optical response of epitaxial thin films of n-type superconductor Nd/sub 1.85/Ce/sub 0.15/CuO/sub 4-y/ has been measured. In contrast to the optical response of p-type superconductors such as YBa/sub 2/Cu/sub 3/O/sub 7-/spl delta// the normal state optical response of these films were not proportional to the temperature derivative of the resistance. The normal state optical response of films with different transition temperature (and, therefore, different oxygen content) were also remarkably different from each other. We attribute the observation of anomalous optical response to the possible presence of photoconductivity in Nd/sub 1.85/Ce/sub 0.15/CuO/sub 4-y/. We also discuss the feasibility of fabricating bolometers based on superconducting p-n bilayers. >

We have measured the microwave magnetoabsorption of both pristine and irradiated c-axis-oriented YBa/sub 2/Cu/sub 3/O/sub 7/ thin films. The irradiation was done using 270-MeV Ag ions and produces columnar defects along the film normal. The angular dependence of the absorption for pristine films can be described by sin/spl theta/; where /spl theta/ is the inclination of the field from the film plane. However, there is a minimum in the magnetoabsorption of the irradiated films when the applied field is parallel to the columns. This minimum is indicative of vortex localization as predicted by Nelson and Vinokur. We believe that this is the first high-frequency measurement of this phenomenon. >

Epitaxial c-axis-oriented thin films of Fe- or Zn-doped YBa 2 Cu 3 O 7-δ have been grown on (001) LaAlO 3 substrates by pulsed excimer laser ablation. Adequate substitutional incorporation of Fe atoms required optimal choice of oxygen pressure during deposition as well as a postsynthesis annealing treatment at 550 °C. Zn incorporation did not require such special processing conditions. The resistivity transitions for such high-quality well-characterized films were studied at different magnetic fields up to 5 T. Analysis of T c depression and change in dH c2 /dT at T c has been made in terms of the possible changes in the density of states at the Fermi level, contributions of the exchange field, magnetization field, and nonmagnetic scattering. Estimates of the activation energy [U 0 (H)] for vortex motion have also been made.

Automating the detection of lesions in liver CT scans requires a high performance and robust solution. With CT-scan start to become the norm in emergency department, the need for a fast and efficient liver lesions detection method is arising. In this paper, we propose a fast and evolvable method to profile the features of pre-segmented healthy liver and use it to detect the presence of liver lesions in emergency scenario. Our preliminary experiment with the MICCAI 2007 grand challenge datasets shows promising results of a fast training time, ability to evolve the produced healthy liver profiles, and accurate detection of the liver lesions. Lastly, the future work directions are also presented.

The far-infrared transmission of YBa2Cu3O7−δ films with columnar defects produced by high-energy ion irradiation has been measured from 20 to 150 cm-1 at 6 K in magnetic fields of 0–9 T. The change in transmission produced by irradiation can be understood by modeling the columnar defects as normal-metal or insulating cylinders in a superconducting background. Magnetic field induced spectral structure near 60 cm-1 in the pristine samples is suppressed by a defect density equal to the density of vortices at that field. However, the magneto-transmission above 60 cm-1 is nearly unaffected by the irradiation process. We discuss these results in terms of the current understanding of the nature of vortices and columnar defects in YBa2Cu3O 7−δ.

We report the angular magnetic-field dependence of the critical current density in epitaxial thin films of Nd 1.85 Ce 0.15 CuO 4-δ in the temperature range 1.4 K to 14 K. At low temperatures, the critical current anisotropy is well described by the 2D model of Josephson-coupled layers. Above 10 K we observe deviations from the 2D behavior which may be attributed to the temperature dependence of the coherence lenght and the influence of the anisotropy of the upper critical field. The field dependence of the critical current density for the field orientation parallel to the CuO 2 planes is consistent with the dimensionality indicated by the angular dependence.

The angular magnetic field dependence of the critical current density JC(θ) of epitaxial YBa2Cu3O7 thin films is presented in the temperature regime close to Tc. The high temperature behavior of Jc(θ) shows features that are significantly different from the earlier observations at lower temperatures. A comparison between the films on (100) LaAlO3 and (100) yttria stabilized zirconia (YSZ) indicates significant differences that may be attributed to the differences in the microstructure of the films on the two substrates. In particular, the observation of enhanced pinning in the films on YSZ may be due to the pinning effects of the low angle grain boundaries present in these films.

This paper investigates the effects of feature selection via dimensionality reduction techniques for the task of object class recognition. Two filter-based algorithms are considered namely Correlation-based Feature Selection (CFS) and Principal Components Analysis (PCA). A Support Vector Machine is used to compare these two techniques against classical feature concatenation, based on the Graz02 dataset. Experimental results show that the feature selection algorithms are able to retain the most relevant and discriminant features, while maintaining recognition accuracy and improving model building time.

This paper proposes a cyclic load balancing strategy to parallel Fuzzy C-Means cluster analysis algorithm. The problem is to minimize the total time cost and maximize the parallel processing efficiency when a subset of clusters is distributed over a set of processors cores on shared memory architecture. The parallel Fuzzy C - Means (FCM) cluster analysis algorithm is composed by two distinct parts. The two distinct parts are; first: the cluster analysis whereby using the FCM algorithm to calculate the cluster centers and second: the evaluation of the subset of clusters whereby using the cluster validity functions to produce the result of the optimal cluster. The experimental result shows that the cyclic load balanced parallel FCM cluster analysis algorithm presents good speed up especially when the size of clusters is large as compared to the parallel FCM cluster analysis algorithm.