Miracle-dz/UniFAR-FTUs huggingface dataset:
Almost sure convergence of a randomized algorithm for relative localization in sensor networks

This paper regards the relative localization problem in sensor networks. We study a randomized algorithm, which is based on input-driven consensus dynamics and involves pairwise “gossip” communications and updates. Due to the randomness of the updates, the state of this algorithm ergodically oscillates around a limit value. Exploiting the ergodicity of the dynamics, we show that the time-average of the state almost surely converges to the least-squares solution of the localization problem. Remarkably, the computation of the time-average does not require the sensors to share any common clock. Hence, the proposed algorithm is fully distributed and asynchronous.
Life Satisfaction and Death Anxiety in Elderly Nursing Home and Public Housing Residents

To compare life satisfaction and death anxiety in older adults, 30 elderly residents of a public housing apartment complex and 20 nursing home residents completed the Death Anxiety Scale, the Philadelphia Geriatric Center Morale Scale, and a structured interview. Nursing home residents more frequently reported that in five years they expected to be dead, whereas public housing residents more frequently reported that in five years they would be doing about the same thing or nothing. The two groups did not differ on their reported death anxiety or life satisfaction. However, across both groups, those reporting higher life satisfaction also reported lower death anxiety and a more positive attitude toward growing older. It appears that, for the elderly indivcduals in this study, place of residence was not related to their expression of life satisfaction or death anxiety.
Face recognition method based on two-directional and Modular Fuzzy 2DPCA

Feature extraction specific to face recognition, an improved version of two-dimensional principal component analysis (2DPCA) named Two-directional and Modular Fuzzy 2DPCA (MF(2D)2PCA) is proposed in this paper. First, Fuzzy K-Nearest Neighbor algorithm is used to get the fuzzy membership degree matrix of training samples. Then, modular processing is done to training images, combing with fuzzy membership degree to construct the total scatter matrix in row and column directions, respectively. And then obtain a projection matrix. Finally, lower dimensional local facial features are extracted after the transformation based on projection matrix and an improved minimum distance classifier is employed to implement classification. This method makes use of local characteristic of face effectively and the distribution information of overlapping samples is introduced into the scatter matrix in the form of weights allocation. Experimental results on ORL and AR face database show that the proposed approach outperforms other traditional methods and has better adaptability.
Maintaining Approximate Maximum Weighted Matching in Fully Dynamic Graphs

We present a fully dynamic algorithm for maintaining approximate maximum weight matching in general weighted graphs. The algorithm maintains a matching ${\cal M}$ whose weight is at least $1/8 M^{*}$ where $M^{*}$ is the weight of the maximum weight matching. The algorithm achieves an expected amortized $O(\log n \log \mathcal C)$ time per edge insertion or deletion, where $\mathcal C$ is the ratio of the weights of the highest weight edge to the smallest weight edge in the given graph. Using a simple randomized scaling technique, we are able to obtain a matching whith expected approximation ratio 4.9108.
Enhanced vascular strain imaging using arterial pressure equalization

Peripheral vascular strain imaging has limited strain dynamic range since arterial wall deformations only produce small strains under physiologic pressures. A non-invasive method has been developed to apply external force, comparable to the force generated in measuring a subject's blood pressure, to achieve higher strains by equalizing the internal arterial baseline pressure. When the applied pressure matched the internal baseline diastolic pressure of 80 mmHg, strain and strain rate increased by a factor of 10 over a cardiac cycle. The feasibility of this technique is validated through ex- and in-vivo measurements.
Use of Internal Transcribed Spacer Primers and Fungicide Treatments to Study the Anther‐Smut Disease, Microbotryum violaceum (=Ustilago violacea), of White Campion Silene alba (=Silene latifolia)

We report the construction and use of polymerase chain reaction (PCR) primers for detection of Microbotryum violaceum in Silene alba. Such primers show that the pathogen is present in the aboveground bud meristems, flower pedicels, and flower‐stem internodes but not in the flowering‐stem leaves and roots of flowering plants. Use of primers also showed that the pathogen was absent from plants that had been inoculated with the fungus but remained healthy. The fungicides Folicur and Bayleton cured plants of the disease, and the absence of the fungus from such cured plants was confirmed using the PCR primers.
The high efficiency transformer-less PV inverter topologies derived from NPC topology

The grid-connected photovoltaic (PV) systems are an important part of renewable energy sources and their integration is getting more and more widespread. In order to improve the efficiency, practicality and reliability of the PV systems, many kinds of new inverter topologies have been proposed to avoid using a grid isolation transformer. The NPC topology and two other derived topologies are presented and analyzed in this paper. Validated by experiments, it has been proven that they are very suitable for using in transformer-less PV applications due to high efficiency, low leakage current and EMI. Simulations using Simulink and the PLECS toolbox have been done for evaluating efficiency of different NPC topologies and some experimental results are presented in this paper to validate the operation of the different topologies.
Extracting More Object Usage Scenarios for API Protocol Mining

Automatic protocol mining is a promising approach to infer precise and complete API protocols. However, the effect of the approach largely depends upon the quality of input object usage scenarios, in terms of noise and diversity. This paper aims to extract as many object usage scenarios as possible from object-oriented programs for automatic protocol mining. A large corpus of object usage scenarios can help with eliminating noise accurately and is likely to be diverse. Therefore, precise and complete protocols may be achieved. Given an object-oriented program p, generally, object usage scenarios that can be collected from a run of p is not more than the number of instances used in p. Relying on the inheritance relationship among classes, our technique can extract a maximum of n times more object usage scenarios from p, where n is the average inheritance depth of all object usage scenarios in p. In order to investigate the effect of our technique on mining protocols, we implement it in our previous prototype tool ISpecMiner and use the tool to mine protocols from several real-world applications. The experimental results show that our technique is promising to achieve complete and precise API protocols. In addition, protocols of classes that have not been used in programs can be also achieved, which is helpful for program documentation and understanding.
Reconstructing Animated Meshes from Time‐Varying Point Clouds

In this paper, we describe a novel approach for the reconstruction of animated meshes from a series of time‐deforming point clouds. Given a set of unordered point clouds that have been captured by a fast 3‐D scanner, our algorithm is able to compute coherent meshes which approximate the input data at arbitrary time instances. Our method is based on the computation of an implicit function in ℝ4 that approximates the time‐space surface of the time‐varying point cloud. We then use the four‐dimensional implicit function to reconstruct a polygonal model for the first time‐step. By sliding this template mesh along the time‐space surface in an as‐rigid‐as‐possible manner, we obtain reconstructions for further time‐steps which have the same connectivity as the previously extracted mesh while recovering rigid motion exactly.
Experimental results of randomized clustering algorithm

This paper describes computational results for k-clustering algorithm using random sampling technique [2] to show its practical usefulness. By computational experiments, first, we show that small size of samples are actually enough for 2-clustering problem. Then, we apply this algorithm for kclustering problem in a recursive manner and use the output as the initial solution of the existing local improvement technique, called k-means. We compare the result with variancebased algorithm [1, 4] which is commonly used. 1 Randomized 2-clustering algorithm Clustering is the grouping of similar objects. A k-clustering of a set is a partition of its elements into k clusters that is chosen to minimize some dissimilarity cost in each cluster. It is very fundamental and used in various fields in computer science such as pattern recognition, learning theory, image processing, computer graphics, etc. Variance-based clustering problem for a set S of n points Xi is to find a k-clustering of S into Sj (j = 1, ., k) minimizing the clustering cost ~~=1 V(SJ ) where V(s, ) = ~ Ilz, – fi(sj)ll’, p,E s> II -II is they ~m , and Z(Sj ) is the centroid of points m SJ, I.e., ,s,, xi. For this problem, an optimal kP, c . 52 clustering is induced by the Voronoi Diagram generated by k centroids of the clusters. For this problem, we have proposed the following 2-clustering randomized algorithm in [2]. We implement this algorithm for the planar case and add a local improvement step for the inner loop.
Automated Multiple Related Documents Summarization via Jaccard’s Coefficient

Today, in the hasty advancement epoch of technology, allotting and gathering of information are imperative. Readers enthrall with an undersized edition of copious prolonged text documents. In this paper, we represent our approach which we used in our Automated Text Summarization System known as MDSS (Multiple Documents Summarization System). We elucidate a new fangled approach which is based on statistical (rather than semantic) factors. In contrast to single document summarization, the issues of compression, speediness, superfluous and passage opting are more decisive in multiple documents summarization. For sentence comparison, Jaccard‟s coefficient is used to improve the worth and quality of the summarization. Resemblance exists between our algorithms and dynamic time warping. Our experimental domino effects indicate that it is useful and effectual to enhance the quality of multiple documents summarization via Jaccard‟s coefficient. Our system MDSS is implemented in Java (jdk 1.6). General Terms: Text mining, text summarization
Separate domains of KAR1 mediate distinct functions in mitosis and nuclear fusion

The yeast KAR1 gene is essential for mitotic growth and important for nuclear fusion. Mutations in KAR1 prevent duplication of the spindle pole body (SPB), and affect functions associated with both the nuclear and cytoplasmic microtubules. The localization of hybrid Kar1-lacZ proteins, described elsewhere (Vallen, E. A., T. Y. Scherson, T. Roberts, K. van Zee, and M. D. Rose. 1992. Cell. In press), suggest that the protein is associated with the SPB. In this paper, we report a deletion analysis demonstrating that the mitotic and karyogamy functions of KAR1 are separate and independent, residing in discrete functional domains. One region, here shown to be essential for mitosis, coincided with a part of the protein that is both necessary and sufficient to target Karl-lacZ hybrid proteins to the SPB (Vallen, E. A., T. Y. Scherson, T. Roberts, K. van Zee, and M. D. Rose. 1992. Cell. In press). Complementation testing demonstrated that deletions in this interval did not affect nuclear fusion. A second region, required only for karyogamy, was necessary for the localization of a Kar3-lacZ hybrid protein to the SPB. These data suggest a model for the roles of Kar1p and Kar3p, a kinesin-like protein, in nuclear fusion. Finally, a third region of KAR1 was found to be important for both mitosis and karyogamy. This domain included the hydrophobic carboxy terminus and is sufficient to target a lacZ-Kar1 hybrid protein to the nuclear envelope (Vallen E. A., T. Y. Scherson, T. Roberts, K. van Zee, and M. D. Rose. 1992. Cell. In press). Altogether, the essential mitotic regions of KAR1 comprised 20% of the coding sequence. We propose a model for Kar1p in which the protein is composed of several protein-binding domains tethered to the nuclear envelope via its hydrophobic tail.
Parameterization of shortwave ice cloud optical properties for various particle habits

[1] The relative importance of ice clouds in the climate system is highly uncertain. Measurements of their microphysical properties are sparse, especially given their complex structure and large variability in particle size, shape, and density. To better understand the role of ice clouds in the climate system, parameterizations of their radiative properties are needed. The shortwave bulk optical properties of seven ice particle shapes, or ‘‘habits,’’ are parameterized as a function of the effective ‘‘radius’’ and ice water content by integrating the scattering properties over 30 in situ size distributions. The particle habits are solid and hollow hexagonal columns, hexagonal plates, two- and three-dimensional bullet rosettes, aggregates of columns, and dendrites. Parameterizations of the volume extinction coefficient, single-scattering albedo, and the asymmetry parameter are presented for 6, 24, and 56 band shortwave schemes from 0.2 to 5.0 mm. Applications to downwelling flux and upwelling radiance calculations indicate that differences in fluxes for various habits can be more than 15%, and differences in retrievals of cloud optical depth from satellite visible reflectances can be more than 50%. INDEX TERMS: 3359 Meteorology and Atmospheric Dynamics: Radiative processes; 0360 Atmospheric Composition and Structure: Transmission and scattering of radiation; 3360 Meteorology and Atmospheric Dynamics: Remote sensing;
Failure Site Transition During Drop Testing of Printed Wiring Assemblies

This paper is part of an ongoing effort to develop a test methodology to examine the durability of surface mount interconnects under impact loading conditions. Literature indicates that as the drop height is increased, there is a transition in the failure site from the ductile solder to the brittle intermetallic. Not much work has been done to understand this phenomenon. This study considers damage accumulated in the interconnects in terms of the local strain in the printed wiring assembly (PWA), local strain rate and component acceleration. The advantage is that the results are less dependant on structure and loading, because damage is quantified in terms of specimen response rather than the loading. A simple test specimen is fabricated to concentrate the study on interconnect failure mechanisms. An instrumented, repeatable test setup is developed to conduct high speed bend tests and drop tests on the specimen. All tests are replicated twice for proof of consistency of the test data. The paper presents the results of the high speed bend tests. As expected, the durability of the specimen decreases monotonically with PWA strain. On the other hand, the durability first increases and then decreases as the PWA strain rate increases. Failure analysis shows a transition in the failure site from solder to intermetallic. It is hypothesized that for a given package design, the rate dependent material properties determine the partitioning of the strain energy of deformation. Yield stress of the solder and fracture toughness of the intermetallic are identified as the key parameters. More tests are needed to understand this rate dependent strain energy partitioning. The end goal is to develop a consistent, accurate and generic methodology for ranking the impact durability of different surface mount interconnects technologies. © 2005 ASME
Insights from a Simple Expression for Linear Fisher Information in a Recurrently Connected Population of Spiking Neurons

A simple expression for a lower bound of Fisher information is derived for a network of recurrently connected spiking neurons that have been driven to a noise-perturbed steady state. We call this lower bound linear Fisher information, as it corresponds to the Fisher information that can be recovered by a locally optimal linear estimator. Unlike recent similar calculations, the approach used here includes the effects of nonlinear gain functions and correlated input noise and yields a surprisingly simple and intuitive expression that offers substantial insight into the sources of information degradation across successive layers of a neural network. Here, this expression is used to (1) compute the optimal (i.e., information-maximizing) firing rate of a neuron, (2) demonstrate why sharpening tuning curves by either thresholding or the action of recurrent connectivity is generally a bad idea, (3) show how a single cortical expansion is sufficient to instantiate a redundant population code that can propagate across multiple cortical layers with minimal information loss, and (4) show that optimal recurrent connectivity strongly depends on the covariance structure of the inputs to the network.
Imposed Hispanicity: How the Imposition of Racialized and Gendered Identities in Texas Affects Mexican Women in Romantic Relationships with White Men

Intimate, romantic spaces are important sites for the examination of self-identification and perceived identification, especially with regard to gender and racial power. In this article I examine how white men in romantic relationships or marriages with Mexican women and residing in Texas, impose “Hispanic” as a racial identity as a discursive tactic that reinforces the hegemonic power of being white and being a man in order to define the situation, impose ideals that distance Mexican partners from being “too ethnic” or “threatening” in order to achieve closer proximity to “honorary whiteness” and acceptability of racial others, and creates a romantic space that is coercive instead of loving and safe. This study thus finds that white men used their hegemony to not only employ imposed Hispanicity, which I define as an institutionally created but culturally and institutionally imposed label, and an action based on the use of direct and indirect coercion and force by others, in this case, white romantic partners, for the purpose of establishing power and determining the situation in which racial definitions are made. Therefore, “Hispanic” becomes an identity that is chosen by others and while participants of Mexican descent do employ agency, the socially imposed conditions and expectations associated with “Hispanic” serve to police the identities, bodies, lives, and actions of people of Latin American descent.
Identifying Wrong Links between Datasets by Multi-dimensional Outlier Detection

Links between datasets are an essential ingredient of Linked Open Data. Since the manual creation of links is expensive at large-scale, link sets are often created using heuristics, which may lead to errors. In this paper, we propose an unsupervised approach for finding erroneous links. We represent each link as a feature vector in a higher dimensional vector space, and find wrong links by means of different multidimensional outlier detection methods. We show how the approach can be implemented in the RapidMiner platform using only off-the-shelf components, and present a first evaluation with real-world datasets from the Linked Open Data cloud showing promising results, with an F-measure of up to 0.54, and an area under the ROC curve of up to 0.86.
Extremely Low Bit-Rate Nearest Neighbor Search Using a Set Compression Tree

The goal of this work is a data structure to support approximate nearest neighbor search on very large scale sets of vector descriptors. The criteria we wish to optimize are: (i) that the memory footprint of the representation should be very small (so that it fits into main memory); and (ii) that the approximation of the original vectors should be accurate. We introduce a novel encoding method, named a Set Compression Tree (SCT), that satisfies these criteria. It is able to accurately compress 1 million descriptors using only a few bits per descriptor. The large compression rate is achieved by not compressing on a per-descriptor basis, but instead by compressing the set of descriptors jointly. We describe the encoding, decoding and use for nearest neighbor search, all of which are quite straightforward to implement. The method, tested on standard benchmarks (SIFT1M and 80 Million Tiny Images), achieves superior performance to a number of state-of-the-art approaches, including Product Quantization, Locality Sensitive Hashing, Spectral Hashing, and Iterative Quantization. For example, SCT has a lower error using 5 bits than any of the other approaches, even when they use 16 or more bits per descriptor. We also include a comparison of all the above methods on the standard benchmarks.
Effizienzsteigerung in organischen Leuchtdioden

Diese Arbeit befasst sich mit verschiedenen nano- und mikrotechnologischen Konzepten zur Steigerung der Auskoppeleffizienz von OLEDs. Hierfur werden drei bottom-up-Ansatze, bei denen Nanopartikel wahrend der OLED-Herstellung in die OLED eingebracht werden, beschrieben und zwei top-down-Ansatze vorgestellt, bei denen vor der eigentlichen OLED-Herstellung die Substratoberflache durch Nano- und Mikrostrukturierung modifiziert wird.
Modeling the microstructure of sintered copper

Abstract. Microfocus computer tomography (μCT) is a promising tool for gaining insight into the microstructure of sintered materials. In this paper, we investigate volume images of sintered copper with spherical grains in the early stages of the sintering process. Methods from spatial statistics are used to analyze the microstructure of the copper samples. Starting from these observations, a model based on a random dense packing of spheres is proposed.
Arrays of Silicon P-i-N Nanowires for Antenna-enhanced and Polarisation Sensitive Detection of Light

Arrays of Silicon P-i-N Nanowires for Antenna-enhanced and Polarisation Sensitive Detection of Light Corey Stewart Master of Applied Science Graduate Department of Materials Science and Engineering University of Toronto 2013 A novel antenna effect is demonstrated in arrays of 500, 200 and 100 silicon nanowires embedded in silicon dioxide. The silicon nanowire gratings are analyzed using spectral and polarisation resolved photocurrent microscopy. Resonant enhancements in the electric field and thus photocurrent response are observed at multiple wavelengths corresponding to coupling of incident radiation into the grating’s multiple-scattering electromagnetic modes. The photoresponse retains the sinusoidal polarisation anisotropy expected in single nanowires. The resonances are modeled quantitatively using electromagnetic scattering theory and show excellent agreement with measurement. A experimental quality factor of Q ≈ 10 was measured for the gratings, exceeding that of a single wire, but lower than expected from theory which gives Q ≈ 70. The difference can be ascribed to the finite length of the wires and their termination at ohmic contacts. Strategies to improve Q are discussed, and a polarisation sensitive grating is presented to resonantly enhance light detection at red, green and blue wavelengths for application as a colour imaging sensor.